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Finance and economic growth Financing structure and non-linear impact Benczúr, P., Karagiannis, S., and Kvedaras, V. September 2017 JRC Working Papers in Economics and Finance, 2017/7
Transcript
Page 1: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

Finance and economic growth

Financing structure

and non-linear impact

Benczuacuter P Karagiannis S and

Kvedaras V

September 2017

JRC Working Papers in Economics and Finance 20177

2

This publication is a Technical report by the Joint Research Centre (JRC) the European Commissionrsquos science

and knowledge service It aims to provide evidence-based scientific support to the European policymaking

process The scientific output expressed does not imply a policy position of the European Commission Neither

the European Commission nor any person acting on behalf of the Commission is responsible for the use that

might be made of this publication

Contact information

Name Peacuteter Benczuacuter

Address Via E Fermi 2749 I-21027 Ispra (VA) ITALY

Email peterbenczureceuropaeu

Tel +39 0332 785772

JRC Science Hub

httpseceuropaeujrc

JRC107909

PDF ISBN 978-92-79-67444-0 ISSN 2467-2203 doi102760063349

Luxembourg Publications Office of the European Union 2017

copy European Union 2017

The reuse of the document is authorised provided the source is acknowledged and the original meaning or

message of the texts are not distorted The European Commission shall not be held liable for any consequences

stemming from the reuse

How to cite this report Benczuacuter P Karagiannis S and Kvedaras V (2017) Finance and economic growth

financing structure and non-linear impact JRC Working Papers in Economics and Finance 20177

doi102760063349

All images copy European Union 2017

3

Finance and economic growth financing structure and non-linear impact

Peacuteter Benczuacuter

Stylianos Karagiannis

Virmantas Kvedaras

European Commission Joint Research Centre Via Fermi I-10 Ispra (VA) Italy

October 2017

Abstract

There is growing evidence that the impact of financial development on economic growth might be non-linear and

hump-shaped exhibiting a turning point However such findings are typically established using total finances

(mostly credit) and the apparent non-linear impact of totals can stem from a substantial structural change in the

composition of finances that has been taking place during the recent decades Though there are some studies

going beyond total finances they usually look at the impact of certain financing components separately or using

ratios which may bias the estimation and lead to incorrect conclusions Finally the findings are typically based

on a global pool of countries and may be driven by a developing versus developed country differential

Focusing on groups of high-income countries (from the OECD EU and EMU) this study shows that the finding

of a non-linear hump-shaped impact of financing on economic growth is robust to controlling for financing

composition in terms of the sources (bank credit debt securities stock market) and the recipients of finances

(households non-financial and financial corporations) or both In particular we obtain the following results (1)

The non-linear impact of total bank credit is more pronounced than that of either household credit alone or the

sum of bank credit debt securities and stock market financing (2) Credit to non-financial corporations tends to

have a positive while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4) The estimated turning

point of the non-linear relationship is close to that found by Cournegravede and Denk (2015) for the OECD countries

and lower than that established by Arcand et al (2015) for a broad set of countries

Keywords financial development economic growth finance-growth nexus non-linearity bank credit debt

securities stock markets

JEL numbers E44 G2 O4

The authors thank Michael Thiel and Plamen Nikolov for helpful comments and suggestions The opinions expressed are

those of the authors only and should not be considered as representative of the European Commissionrsquos official position

Contact information European Commission DG Joint Research Centre Via Fermi 2749 I-21027 Ispra (VA) Italy Emails

are peterbenczureceuropaeu stylianoskaragianniseceuropa and virmantaskvedaraseceuropaeu

4

1 Introduction

The relation between financial development and economic growth is much debated As was

hypothesized by Schumpeter (1934) and supported by King and Levine (1993) with numerous

papers thereafter differences in the level of the development of financial systems affect

economic growth differentials among countries The impact channels vary from additional

financial funds available to finance investment projects due to larger volumes of savings to

more efficient reallocation of funds thus reaching the right entrepreneurs and leading to higher

productivity (see eg Beck et al 2000 Levine 2005)

The early empirical literature (see overviews ibidem or Panizza 2014) suggested a positive

association between financial development and economic growth the former measured by eg

the amount of domestic private credit or stock market capitalization relative to gross domestic

product (GDP) The dominant positive attitude towards financial expansion encouraged a sharp

increase in financial penetration and the median level of private bank credit (in higher income

countries with data reported by the Bank for International Settlements BIS hereafter)

constituted around 90 percent of GDP in 2014 In a number of countries it has reached levels

much greater than their GDP Such high levels of financial penetration together with recent

and contemporary financial crises started casting doubt on the benefits of such a degree of

financial deepening (see eg Beck 2012)

The corresponding more recent empirical work provides evidence of either a vanishing positive

impact (as eg in Rousseau and Wachtel 2011) or a potentially non-linear (often an inverse

U-shaped) relationship as documented in numerous contemporary studies1 Although this

relationship can be complex and may vary among others with a countryrsquos level of economic

development and quality of financial institutions (Cecchetti and Kharroubi 2012 Demirguumlccedil-

Kunt et al 2013 Masten et al 2008 Rioja and Valev 2015) the particular functions

performed by the financial sector (Beck et al 2014) the speed of expansion of financial sector

(Cecchetti and Kharroubi 2012 Ductor and Grechyna 2015) the lsquonormalityrsquo of the period

under investigation (Balta and Nikolov 2013 Breitenlechner et al 2015 Gambacorta et al

2014) the high current levels of financial penetration and the recent findings of a non-linear

impact of financial development on economic growth point to a potential of lsquotoo much financersquo

in many countries thus questioning the desirability of large financial sectors

1 Examples include Arcand et al 2015 Cournegravede and Denk 2015 Cecchetti and Kharroubi 2012 Law and

Singh 2014 and Sahay et al 2015

5

These findings have been mainly obtained using aggregate credit data of financial institutions

leaving it open whether and how much the structure of financial systems affects such results

First different sources of finance (bank-based versus market-based financing) can have an

uneven impact (see eg Beck and Levine 2004 Cournegravede and Denk 2015 Demirguumlccedil-Kunt et

al 2013 Gambacorta et al 2014 Langfield and Pagano 2016 Mishra and Narayan 2015)

Next fund recipients (users of finance) might matter nontrivially for the outcome For instance

Beck et al (2012) stress that a substantial household credit expansion might be hurting

economic growth In parallel Bezemer et al (2014) point out that the share of credit to

nonfinancial business decreased sharply while it had a significantly positive effect on growth

Among these lines although warning for a small sample size Arcand et al (2015) indeed find

that the non-linearity of household credit is more significant than that of firm credit

Nevertheless the analysis of the importance of financial structure is currently quite limited

First the impact of different components of financing are mostly analyzed individually or

looking only at a few of them (see eg Cournegravede and Denk 2015) thus creating potentially an

omitted variable bias Second even when the analysis is performed including several

subcomponents together (see eg Gambacorta et al 2014) the difference between their

individual and joint impact (eg that of total financing) is not investigated Third though the

dependence of economic growth rates on bank credit financing and stock market financing is

often analyzed the influence of debt securities is rarely considered Moreover when it is like

in Langfield and Pagano (2016) the stock market and debt securities financing is often merged

which might impose an incorrect restriction and lead to biased inference Fourth to our

knowledge there is no study that jointly and not individually investigates the impact of both

the sources (bank financing debt securities financing and stock market financing) and the

recipients of finance (households non-financial corporations and financial corporations) not

to mention also the non-linearity Last but not the least the changing structure of financing

can lie behind the vanishing or non-linear impact of finance on economic growth2 therefore

it is crucial to investigate if the impact remains non-linear after controlling for the detailed

structure of finance that accounts for potential changes3 As far as data limitations allow us we

aim at considering all these aspects in our investigation

2 For instance if large finansing of households has a negative impact on growth while that of firms has a positive one either the vanishing or

the non-linear impact on growth of total financing can be created as the share of credit for households increases 3 And the other way round it is of interest to establish if the impact of structural components remains robust after taking into account the

nonlinear influence of financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 2: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

2

This publication is a Technical report by the Joint Research Centre (JRC) the European Commissionrsquos science

and knowledge service It aims to provide evidence-based scientific support to the European policymaking

process The scientific output expressed does not imply a policy position of the European Commission Neither

the European Commission nor any person acting on behalf of the Commission is responsible for the use that

might be made of this publication

Contact information

Name Peacuteter Benczuacuter

Address Via E Fermi 2749 I-21027 Ispra (VA) ITALY

Email peterbenczureceuropaeu

Tel +39 0332 785772

JRC Science Hub

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JRC107909

PDF ISBN 978-92-79-67444-0 ISSN 2467-2203 doi102760063349

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copy European Union 2017

The reuse of the document is authorised provided the source is acknowledged and the original meaning or

message of the texts are not distorted The European Commission shall not be held liable for any consequences

stemming from the reuse

How to cite this report Benczuacuter P Karagiannis S and Kvedaras V (2017) Finance and economic growth

financing structure and non-linear impact JRC Working Papers in Economics and Finance 20177

doi102760063349

All images copy European Union 2017

3

Finance and economic growth financing structure and non-linear impact

Peacuteter Benczuacuter

Stylianos Karagiannis

Virmantas Kvedaras

European Commission Joint Research Centre Via Fermi I-10 Ispra (VA) Italy

October 2017

Abstract

There is growing evidence that the impact of financial development on economic growth might be non-linear and

hump-shaped exhibiting a turning point However such findings are typically established using total finances

(mostly credit) and the apparent non-linear impact of totals can stem from a substantial structural change in the

composition of finances that has been taking place during the recent decades Though there are some studies

going beyond total finances they usually look at the impact of certain financing components separately or using

ratios which may bias the estimation and lead to incorrect conclusions Finally the findings are typically based

on a global pool of countries and may be driven by a developing versus developed country differential

Focusing on groups of high-income countries (from the OECD EU and EMU) this study shows that the finding

of a non-linear hump-shaped impact of financing on economic growth is robust to controlling for financing

composition in terms of the sources (bank credit debt securities stock market) and the recipients of finances

(households non-financial and financial corporations) or both In particular we obtain the following results (1)

The non-linear impact of total bank credit is more pronounced than that of either household credit alone or the

sum of bank credit debt securities and stock market financing (2) Credit to non-financial corporations tends to

have a positive while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4) The estimated turning

point of the non-linear relationship is close to that found by Cournegravede and Denk (2015) for the OECD countries

and lower than that established by Arcand et al (2015) for a broad set of countries

Keywords financial development economic growth finance-growth nexus non-linearity bank credit debt

securities stock markets

JEL numbers E44 G2 O4

The authors thank Michael Thiel and Plamen Nikolov for helpful comments and suggestions The opinions expressed are

those of the authors only and should not be considered as representative of the European Commissionrsquos official position

Contact information European Commission DG Joint Research Centre Via Fermi 2749 I-21027 Ispra (VA) Italy Emails

are peterbenczureceuropaeu stylianoskaragianniseceuropa and virmantaskvedaraseceuropaeu

4

1 Introduction

The relation between financial development and economic growth is much debated As was

hypothesized by Schumpeter (1934) and supported by King and Levine (1993) with numerous

papers thereafter differences in the level of the development of financial systems affect

economic growth differentials among countries The impact channels vary from additional

financial funds available to finance investment projects due to larger volumes of savings to

more efficient reallocation of funds thus reaching the right entrepreneurs and leading to higher

productivity (see eg Beck et al 2000 Levine 2005)

The early empirical literature (see overviews ibidem or Panizza 2014) suggested a positive

association between financial development and economic growth the former measured by eg

the amount of domestic private credit or stock market capitalization relative to gross domestic

product (GDP) The dominant positive attitude towards financial expansion encouraged a sharp

increase in financial penetration and the median level of private bank credit (in higher income

countries with data reported by the Bank for International Settlements BIS hereafter)

constituted around 90 percent of GDP in 2014 In a number of countries it has reached levels

much greater than their GDP Such high levels of financial penetration together with recent

and contemporary financial crises started casting doubt on the benefits of such a degree of

financial deepening (see eg Beck 2012)

The corresponding more recent empirical work provides evidence of either a vanishing positive

impact (as eg in Rousseau and Wachtel 2011) or a potentially non-linear (often an inverse

U-shaped) relationship as documented in numerous contemporary studies1 Although this

relationship can be complex and may vary among others with a countryrsquos level of economic

development and quality of financial institutions (Cecchetti and Kharroubi 2012 Demirguumlccedil-

Kunt et al 2013 Masten et al 2008 Rioja and Valev 2015) the particular functions

performed by the financial sector (Beck et al 2014) the speed of expansion of financial sector

(Cecchetti and Kharroubi 2012 Ductor and Grechyna 2015) the lsquonormalityrsquo of the period

under investigation (Balta and Nikolov 2013 Breitenlechner et al 2015 Gambacorta et al

2014) the high current levels of financial penetration and the recent findings of a non-linear

impact of financial development on economic growth point to a potential of lsquotoo much financersquo

in many countries thus questioning the desirability of large financial sectors

1 Examples include Arcand et al 2015 Cournegravede and Denk 2015 Cecchetti and Kharroubi 2012 Law and

Singh 2014 and Sahay et al 2015

5

These findings have been mainly obtained using aggregate credit data of financial institutions

leaving it open whether and how much the structure of financial systems affects such results

First different sources of finance (bank-based versus market-based financing) can have an

uneven impact (see eg Beck and Levine 2004 Cournegravede and Denk 2015 Demirguumlccedil-Kunt et

al 2013 Gambacorta et al 2014 Langfield and Pagano 2016 Mishra and Narayan 2015)

Next fund recipients (users of finance) might matter nontrivially for the outcome For instance

Beck et al (2012) stress that a substantial household credit expansion might be hurting

economic growth In parallel Bezemer et al (2014) point out that the share of credit to

nonfinancial business decreased sharply while it had a significantly positive effect on growth

Among these lines although warning for a small sample size Arcand et al (2015) indeed find

that the non-linearity of household credit is more significant than that of firm credit

Nevertheless the analysis of the importance of financial structure is currently quite limited

First the impact of different components of financing are mostly analyzed individually or

looking only at a few of them (see eg Cournegravede and Denk 2015) thus creating potentially an

omitted variable bias Second even when the analysis is performed including several

subcomponents together (see eg Gambacorta et al 2014) the difference between their

individual and joint impact (eg that of total financing) is not investigated Third though the

dependence of economic growth rates on bank credit financing and stock market financing is

often analyzed the influence of debt securities is rarely considered Moreover when it is like

in Langfield and Pagano (2016) the stock market and debt securities financing is often merged

which might impose an incorrect restriction and lead to biased inference Fourth to our

knowledge there is no study that jointly and not individually investigates the impact of both

the sources (bank financing debt securities financing and stock market financing) and the

recipients of finance (households non-financial corporations and financial corporations) not

to mention also the non-linearity Last but not the least the changing structure of financing

can lie behind the vanishing or non-linear impact of finance on economic growth2 therefore

it is crucial to investigate if the impact remains non-linear after controlling for the detailed

structure of finance that accounts for potential changes3 As far as data limitations allow us we

aim at considering all these aspects in our investigation

2 For instance if large finansing of households has a negative impact on growth while that of firms has a positive one either the vanishing or

the non-linear impact on growth of total financing can be created as the share of credit for households increases 3 And the other way round it is of interest to establish if the impact of structural components remains robust after taking into account the

nonlinear influence of financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

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Page 3: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

3

Finance and economic growth financing structure and non-linear impact

Peacuteter Benczuacuter

Stylianos Karagiannis

Virmantas Kvedaras

European Commission Joint Research Centre Via Fermi I-10 Ispra (VA) Italy

October 2017

Abstract

There is growing evidence that the impact of financial development on economic growth might be non-linear and

hump-shaped exhibiting a turning point However such findings are typically established using total finances

(mostly credit) and the apparent non-linear impact of totals can stem from a substantial structural change in the

composition of finances that has been taking place during the recent decades Though there are some studies

going beyond total finances they usually look at the impact of certain financing components separately or using

ratios which may bias the estimation and lead to incorrect conclusions Finally the findings are typically based

on a global pool of countries and may be driven by a developing versus developed country differential

Focusing on groups of high-income countries (from the OECD EU and EMU) this study shows that the finding

of a non-linear hump-shaped impact of financing on economic growth is robust to controlling for financing

composition in terms of the sources (bank credit debt securities stock market) and the recipients of finances

(households non-financial and financial corporations) or both In particular we obtain the following results (1)

The non-linear impact of total bank credit is more pronounced than that of either household credit alone or the

sum of bank credit debt securities and stock market financing (2) Credit to non-financial corporations tends to

have a positive while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4) The estimated turning

point of the non-linear relationship is close to that found by Cournegravede and Denk (2015) for the OECD countries

and lower than that established by Arcand et al (2015) for a broad set of countries

Keywords financial development economic growth finance-growth nexus non-linearity bank credit debt

securities stock markets

JEL numbers E44 G2 O4

The authors thank Michael Thiel and Plamen Nikolov for helpful comments and suggestions The opinions expressed are

those of the authors only and should not be considered as representative of the European Commissionrsquos official position

Contact information European Commission DG Joint Research Centre Via Fermi 2749 I-21027 Ispra (VA) Italy Emails

are peterbenczureceuropaeu stylianoskaragianniseceuropa and virmantaskvedaraseceuropaeu

4

1 Introduction

The relation between financial development and economic growth is much debated As was

hypothesized by Schumpeter (1934) and supported by King and Levine (1993) with numerous

papers thereafter differences in the level of the development of financial systems affect

economic growth differentials among countries The impact channels vary from additional

financial funds available to finance investment projects due to larger volumes of savings to

more efficient reallocation of funds thus reaching the right entrepreneurs and leading to higher

productivity (see eg Beck et al 2000 Levine 2005)

The early empirical literature (see overviews ibidem or Panizza 2014) suggested a positive

association between financial development and economic growth the former measured by eg

the amount of domestic private credit or stock market capitalization relative to gross domestic

product (GDP) The dominant positive attitude towards financial expansion encouraged a sharp

increase in financial penetration and the median level of private bank credit (in higher income

countries with data reported by the Bank for International Settlements BIS hereafter)

constituted around 90 percent of GDP in 2014 In a number of countries it has reached levels

much greater than their GDP Such high levels of financial penetration together with recent

and contemporary financial crises started casting doubt on the benefits of such a degree of

financial deepening (see eg Beck 2012)

The corresponding more recent empirical work provides evidence of either a vanishing positive

impact (as eg in Rousseau and Wachtel 2011) or a potentially non-linear (often an inverse

U-shaped) relationship as documented in numerous contemporary studies1 Although this

relationship can be complex and may vary among others with a countryrsquos level of economic

development and quality of financial institutions (Cecchetti and Kharroubi 2012 Demirguumlccedil-

Kunt et al 2013 Masten et al 2008 Rioja and Valev 2015) the particular functions

performed by the financial sector (Beck et al 2014) the speed of expansion of financial sector

(Cecchetti and Kharroubi 2012 Ductor and Grechyna 2015) the lsquonormalityrsquo of the period

under investigation (Balta and Nikolov 2013 Breitenlechner et al 2015 Gambacorta et al

2014) the high current levels of financial penetration and the recent findings of a non-linear

impact of financial development on economic growth point to a potential of lsquotoo much financersquo

in many countries thus questioning the desirability of large financial sectors

1 Examples include Arcand et al 2015 Cournegravede and Denk 2015 Cecchetti and Kharroubi 2012 Law and

Singh 2014 and Sahay et al 2015

5

These findings have been mainly obtained using aggregate credit data of financial institutions

leaving it open whether and how much the structure of financial systems affects such results

First different sources of finance (bank-based versus market-based financing) can have an

uneven impact (see eg Beck and Levine 2004 Cournegravede and Denk 2015 Demirguumlccedil-Kunt et

al 2013 Gambacorta et al 2014 Langfield and Pagano 2016 Mishra and Narayan 2015)

Next fund recipients (users of finance) might matter nontrivially for the outcome For instance

Beck et al (2012) stress that a substantial household credit expansion might be hurting

economic growth In parallel Bezemer et al (2014) point out that the share of credit to

nonfinancial business decreased sharply while it had a significantly positive effect on growth

Among these lines although warning for a small sample size Arcand et al (2015) indeed find

that the non-linearity of household credit is more significant than that of firm credit

Nevertheless the analysis of the importance of financial structure is currently quite limited

First the impact of different components of financing are mostly analyzed individually or

looking only at a few of them (see eg Cournegravede and Denk 2015) thus creating potentially an

omitted variable bias Second even when the analysis is performed including several

subcomponents together (see eg Gambacorta et al 2014) the difference between their

individual and joint impact (eg that of total financing) is not investigated Third though the

dependence of economic growth rates on bank credit financing and stock market financing is

often analyzed the influence of debt securities is rarely considered Moreover when it is like

in Langfield and Pagano (2016) the stock market and debt securities financing is often merged

which might impose an incorrect restriction and lead to biased inference Fourth to our

knowledge there is no study that jointly and not individually investigates the impact of both

the sources (bank financing debt securities financing and stock market financing) and the

recipients of finance (households non-financial corporations and financial corporations) not

to mention also the non-linearity Last but not the least the changing structure of financing

can lie behind the vanishing or non-linear impact of finance on economic growth2 therefore

it is crucial to investigate if the impact remains non-linear after controlling for the detailed

structure of finance that accounts for potential changes3 As far as data limitations allow us we

aim at considering all these aspects in our investigation

2 For instance if large finansing of households has a negative impact on growth while that of firms has a positive one either the vanishing or

the non-linear impact on growth of total financing can be created as the share of credit for households increases 3 And the other way round it is of interest to establish if the impact of structural components remains robust after taking into account the

nonlinear influence of financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 4: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

4

1 Introduction

The relation between financial development and economic growth is much debated As was

hypothesized by Schumpeter (1934) and supported by King and Levine (1993) with numerous

papers thereafter differences in the level of the development of financial systems affect

economic growth differentials among countries The impact channels vary from additional

financial funds available to finance investment projects due to larger volumes of savings to

more efficient reallocation of funds thus reaching the right entrepreneurs and leading to higher

productivity (see eg Beck et al 2000 Levine 2005)

The early empirical literature (see overviews ibidem or Panizza 2014) suggested a positive

association between financial development and economic growth the former measured by eg

the amount of domestic private credit or stock market capitalization relative to gross domestic

product (GDP) The dominant positive attitude towards financial expansion encouraged a sharp

increase in financial penetration and the median level of private bank credit (in higher income

countries with data reported by the Bank for International Settlements BIS hereafter)

constituted around 90 percent of GDP in 2014 In a number of countries it has reached levels

much greater than their GDP Such high levels of financial penetration together with recent

and contemporary financial crises started casting doubt on the benefits of such a degree of

financial deepening (see eg Beck 2012)

The corresponding more recent empirical work provides evidence of either a vanishing positive

impact (as eg in Rousseau and Wachtel 2011) or a potentially non-linear (often an inverse

U-shaped) relationship as documented in numerous contemporary studies1 Although this

relationship can be complex and may vary among others with a countryrsquos level of economic

development and quality of financial institutions (Cecchetti and Kharroubi 2012 Demirguumlccedil-

Kunt et al 2013 Masten et al 2008 Rioja and Valev 2015) the particular functions

performed by the financial sector (Beck et al 2014) the speed of expansion of financial sector

(Cecchetti and Kharroubi 2012 Ductor and Grechyna 2015) the lsquonormalityrsquo of the period

under investigation (Balta and Nikolov 2013 Breitenlechner et al 2015 Gambacorta et al

2014) the high current levels of financial penetration and the recent findings of a non-linear

impact of financial development on economic growth point to a potential of lsquotoo much financersquo

in many countries thus questioning the desirability of large financial sectors

1 Examples include Arcand et al 2015 Cournegravede and Denk 2015 Cecchetti and Kharroubi 2012 Law and

Singh 2014 and Sahay et al 2015

5

These findings have been mainly obtained using aggregate credit data of financial institutions

leaving it open whether and how much the structure of financial systems affects such results

First different sources of finance (bank-based versus market-based financing) can have an

uneven impact (see eg Beck and Levine 2004 Cournegravede and Denk 2015 Demirguumlccedil-Kunt et

al 2013 Gambacorta et al 2014 Langfield and Pagano 2016 Mishra and Narayan 2015)

Next fund recipients (users of finance) might matter nontrivially for the outcome For instance

Beck et al (2012) stress that a substantial household credit expansion might be hurting

economic growth In parallel Bezemer et al (2014) point out that the share of credit to

nonfinancial business decreased sharply while it had a significantly positive effect on growth

Among these lines although warning for a small sample size Arcand et al (2015) indeed find

that the non-linearity of household credit is more significant than that of firm credit

Nevertheless the analysis of the importance of financial structure is currently quite limited

First the impact of different components of financing are mostly analyzed individually or

looking only at a few of them (see eg Cournegravede and Denk 2015) thus creating potentially an

omitted variable bias Second even when the analysis is performed including several

subcomponents together (see eg Gambacorta et al 2014) the difference between their

individual and joint impact (eg that of total financing) is not investigated Third though the

dependence of economic growth rates on bank credit financing and stock market financing is

often analyzed the influence of debt securities is rarely considered Moreover when it is like

in Langfield and Pagano (2016) the stock market and debt securities financing is often merged

which might impose an incorrect restriction and lead to biased inference Fourth to our

knowledge there is no study that jointly and not individually investigates the impact of both

the sources (bank financing debt securities financing and stock market financing) and the

recipients of finance (households non-financial corporations and financial corporations) not

to mention also the non-linearity Last but not the least the changing structure of financing

can lie behind the vanishing or non-linear impact of finance on economic growth2 therefore

it is crucial to investigate if the impact remains non-linear after controlling for the detailed

structure of finance that accounts for potential changes3 As far as data limitations allow us we

aim at considering all these aspects in our investigation

2 For instance if large finansing of households has a negative impact on growth while that of firms has a positive one either the vanishing or

the non-linear impact on growth of total financing can be created as the share of credit for households increases 3 And the other way round it is of interest to establish if the impact of structural components remains robust after taking into account the

nonlinear influence of financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

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Page 5: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

5

These findings have been mainly obtained using aggregate credit data of financial institutions

leaving it open whether and how much the structure of financial systems affects such results

First different sources of finance (bank-based versus market-based financing) can have an

uneven impact (see eg Beck and Levine 2004 Cournegravede and Denk 2015 Demirguumlccedil-Kunt et

al 2013 Gambacorta et al 2014 Langfield and Pagano 2016 Mishra and Narayan 2015)

Next fund recipients (users of finance) might matter nontrivially for the outcome For instance

Beck et al (2012) stress that a substantial household credit expansion might be hurting

economic growth In parallel Bezemer et al (2014) point out that the share of credit to

nonfinancial business decreased sharply while it had a significantly positive effect on growth

Among these lines although warning for a small sample size Arcand et al (2015) indeed find

that the non-linearity of household credit is more significant than that of firm credit

Nevertheless the analysis of the importance of financial structure is currently quite limited

First the impact of different components of financing are mostly analyzed individually or

looking only at a few of them (see eg Cournegravede and Denk 2015) thus creating potentially an

omitted variable bias Second even when the analysis is performed including several

subcomponents together (see eg Gambacorta et al 2014) the difference between their

individual and joint impact (eg that of total financing) is not investigated Third though the

dependence of economic growth rates on bank credit financing and stock market financing is

often analyzed the influence of debt securities is rarely considered Moreover when it is like

in Langfield and Pagano (2016) the stock market and debt securities financing is often merged

which might impose an incorrect restriction and lead to biased inference Fourth to our

knowledge there is no study that jointly and not individually investigates the impact of both

the sources (bank financing debt securities financing and stock market financing) and the

recipients of finance (households non-financial corporations and financial corporations) not

to mention also the non-linearity Last but not the least the changing structure of financing

can lie behind the vanishing or non-linear impact of finance on economic growth2 therefore

it is crucial to investigate if the impact remains non-linear after controlling for the detailed

structure of finance that accounts for potential changes3 As far as data limitations allow us we

aim at considering all these aspects in our investigation

2 For instance if large finansing of households has a negative impact on growth while that of firms has a positive one either the vanishing or

the non-linear impact on growth of total financing can be created as the share of credit for households increases 3 And the other way round it is of interest to establish if the impact of structural components remains robust after taking into account the

nonlinear influence of financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

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Page 6: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

6

Next given the previously mentioned evidence that countries of different development benefit

from different types of financing and financial penetration in a different way it is also unclear

whether the empirically identified non-linearity is not an artefact of mixing different groups of

countries For instance Karagiannis and Kvedaras (2016) show4 using the original Arcand et

al (2015) data set that their non-linearity finding vanishes when considering more

homogeneous sets of countries (such as that of the Organization for the Economic Co-operation

and Development OECD or the European Union EU members)5 Nevertheless some other

recent research (see eg Cournegravede and Denk 2015 Cournegravede et al 2015 and Samargandi et

al 2015) has also concentrated on smaller sets of more homogeneous countries like the OECD

members or middle-income developing countries and found significant non-linearity It is of

further interest therefore to investigate whether similar results hold for the EU countries andor

the founding member states of the European Monetary Union (EMU1999) These groups are

interesting also because they are quite homogeneous in general as well as in terms of financing

structure in particular namely they have strongly bank-biased financing (Langfield and

Pagano 2016)

The usage of a smaller number of more homogeneous countries and the need of detailed

financial series limit the number of observations and influence the choice of the econometric

methodology that can be properly employed in our case However in order to be more

confident in the obtained empirical results we do not restrict ourselves only to the EU and

EMU1999 samples but also provide the results for a broader set of countries namely the

OECD countries where the required data are available This not only enables us to compare our

findings obtained using a different methodology with the already available ones (namely

Cournegravede and Denk 2015 and Cournegravede et al 2015) but also allows us to be more confident

in the results obtained for the EU and EMU member states given that the established patterns

are fairly robust across all investigated groups of countries

Focusing on groups of high-income countries (from the OECD EU and EMU1999) we show

that the finding of a non-linear hump-shaped impact of financing on economic growth is robust

to controlling for financing composition in terms of the sources (bank credit debt securities

stock market) and the users of finances (households non-financial and financial corporations)

or both In particular we obtain the following results which prove to be quite stable in our

extensive robustness analysis (1) The non-linear impact of total bank credit is more

4 Karagiannis and Kvedaras (2016) contains preliminary research connected with this paper 5 And this cannot be explained solely by larger penetration of finance in more developed countries because in the beginning of their sample

the credit-to-GDP ratio was below even 20 in a number of such countries

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 7: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

7

pronounced than that of either household credit alone or the sum of bank credit debt securities

and stock market financing (2) Credit to non-financial corporations tends to have a positive

while credit to households a negative impact on growth even after allowing for non-linearities

(3) Debt-securities and stock market-based financing have a different impact on growth (4)

The estimated turning point of the non-linear relationship is close to that found by Cournegravede

and Denk (2015) for the OECD countries and lower than that established by Arcand et al

(2015) for a broad set of countries

The paper is structured as follows Section 2 states the specific research questions Section 3

discusses data sources and variables Section 4 presents the econometric modelling approach

Section 5 presents and discusses the main empirical findings and Section 6 concludes Finally

some further details and robustness checks are delegated to the Appendix

2 Specific research questions

The joint consideration of financial structure with a potential non-linear impact of finance on

economic growth allows answering a number of questions Some of them have already been

analyzed previously in the literature but some emerge due to the richer analysis framework

employed here The sequencing of the nine specific questions under investigation that will be

listed shortly is determined by the gradual increase of the number of determinants included in

the econometric specifications Whereas from a conceptual point of view they can be

structured as follows

Apart from the central general question if there is too much finance leading to potentially

relatively slower economic growth (question Q1) we separate three broad sets of other

questions The first one comprises questions of the robustness of non-linearity to taking the

financial structure into account or in parallel the robustness of the impact of financing

components when non-linearity is included (questions Q3 and Q6)

The second group of questions analyses the significance of non-linearity at different

aggregation levels going from the total sum of financing components to separate ones

(questions Q7Q9) This also covers the question whether the non-linear impact of bank credit

emerges due to the specificity of bank credit to households (see eg Beck et al 2012) as

investigated in the heterogeneity analysis by Arcand et al (2015)

8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

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Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

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Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

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Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

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Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

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Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

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Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

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Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

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Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

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Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

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Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

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Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

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Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

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Mishra S and Narayan PK (2015) A nonparametric model of financial system and

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Panizza U (2014) Financial development and economic growth known knowns known

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Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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8

The third set of questions investigates the homogeneity of the impact of different components

of financing or the homogeneity of the absolute impact (questions Q2 Q4 and Q5) This allows

evaluating if various subcomponents of financing (credit to household and firms debt securities

issued by financial and non-financial corporations etc) have a different impact Moreover it

also evaluates whether it is sufficient to use various ratios (like bank credit to stock market or

bank credit to the sum of stock market and debt securities as eg in Demirguumlccedil-Kunt et al

2013 or Langfield and Pagano 2016) or additional disaggregation is required due to the non-

homogeneity of the impact (for such evidence see eg Kaserer and Rapp 2014) Looking from

the policy perspective the (non-) homogeneity of impacts reveals if all components of market-

based andor bank credit-based financing should be treated equally eg if it is beneficial to

promote all types of market-based financing in the same way

Consequently we will investigate the following specific questions

Q1 During the analyzed period are there signs of too much of finance overall ie did all the

different types of sources (bank credit debt securities and stock market financing) affect

growth negatively

Q2 Is the impact of bank-based financing and market-based financing (stock market and debt

securities) homogeneous (at least in absolute terms) Furthermore is the impact of market-

based financing components also homogeneous

Q3 Does the impact of bank credit remain non-linear even after the financing structure is taken

into account in terms of different types of sources (bank credit debt securities and stock market

financing)

Q4 Does economic growth benefit more from an increase of credit to firms than from that of

credit to households

Q5 Does economic growth benefit more from non-financial firms issuing more debt securities

than from financial corporations doing so

Q6 Does the impact of bank credit remain non-linear even after taking into account the

recipients of bank credit (households or non-financial corporations) and that of debt securities

(financial or non-financial corporations)

Q7 Does the impact of bank credit remain non-linear even after taking the non-linear impact

of total financing (ie sum of bank debt securities and stock market financing) into account

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 9: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

9

Ie is the non-linearity of bank influence not dominated by the non-linear impact of total

financing

Q8 Does the impact of bank credit remain non-linear even after taking into account the non-

linear impact of total financing as in Q7 as well as the financing structure in terms of recipients

of financing Ie does the non-linear impact of total financing on growth not dominate the

non-linearity of bank influence even after a detailed conditioning on the composition of

finance

Q9 Is credit to households mostly responsible for the hump-shaped non-linear impact of bank

credit on growth

3 Data and variables

In order to evaluate the effects of the composition of domestic private finance on economic

growth and their potential role in the non-linear impact of finance on growth we need

disaggregated data on the split of financing by the source (bank debt securities and stock

market financing) as well as the recipient (households non-financial firms and financial

corporations) For this our most important source is the Bank for International Settlements

(BIS) database of private non-financial sector credit and debt securities as it provides a fairly

detailed split of these series by the sources and users of finance Appendix A contains a detailed

description of the sources of all the variables that we use

All the employed financial variables are expressed in relative terms to GDP and used after the

logarithmic transformation (Table 1 describes the actual transformations of variables) This is

first of all prompted by a better fit we obtained and also suggested by the marginal impact of

credit on growth rates estimated and presented by Cournegravede and Denk (2015) in their Figure 5

using the logarithmic transformation we obtain the same shape of the marginal impact (see

Figure 1 in Section 51 below) Whenever the original BIS data is quarterly we use the last

quarter to align the frequency with the annual periodicity of other data The BIS credit database

contains directly the ratio of credit to nominal GDP series (with a split by credit to households

and credit to non-financial corporations) For the outstanding debt securities (with a split into

issued by non-financial corporations and financial corporations) we calculate these ratios to

GDP using the BIS debt securities data and the GDP data from the World Bankrsquos (WB) World

Development Indicators (WDI) database It should be pointed out that private bank credit data

at the aggregate level (without splitting into household and firm credit) are also available from

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 10: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

10

the WB Global Financial Development Database (GFDD) However the GFDD credit series

have a number of structural breaks whereas the BIS credit data are adjusted for breaks Figure

A1 in Appendix A presents several comparisons between data from the two sources and those

from the GFDD contain obvious structural breaks This motivated us to use the BIS data in the

econometric analysis

To represent the stock market financing of listed domestic companies we use the market

capitalization (in percentage of GDP) indicator from the WDI database It should be pointed

out that the usage of turnover ratio of domestic shares from the same database yields

qualitatively similar results but loses the significance which is consistent with the analogous

finding by Mishra and Narayan (2015) Another reason for preferring the market capitalization

series is that its ratio to GDP is more natural and therefore aligns better with the other employed

series that are also ratios to GDP

All the mentioned databases were downloaded in June 2016 and the respective extract of series

is available upon request from the authors The data period and number of observations to be

used in further estimations varies depending on the particular questionspecification at hand

and the availability of data The typical estimation period is from 1990 to 2014 whereas the

number of actually available countries varies from 9 to 27 depending on the particular group

of countries under investigation (OECD EU EMU1999) and data availability The number of

countries is always displayed in the tables containing the results

In addition to the discussed financial series a set of usual control variables is included

comprising GDP per capita enrolment in secondary education government final consumption

expenditure to GDP trade openness to GDP and inflation of consumer prices These indicators

come from the WB WDI database and are also annual The additional transformations of these

original data are described in Table 1 and the specific choices ensure comparability with Arcand

et al (2015)

11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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11

Short notation Description of the series used for the econometric exercise

INC logarithm of GDP per capita

INF the inverse hyperbolic sign transform6 (IHST) of inflation

EDU logarithm of gross enrolment ratio in secondary education7

GOV logarithm of government consumption to GDP

OPN logarithm of trade openness (exports and imports to GDP)

CREDIT logarithm of private bank credit to GDP

CREDIT2 square of CREDIT

DEBT_SEC logarithm of outstanding domestic debt securities issued by financial and

non-financial corporations to GDP

STOCKS logarithm of domestic stock market capitalization to GDP

CREDIT-HSH logarithm of credit to households to GDP (from banks and non-banks)

CREDIT-HSH2 square of CREDIT-HSH

CREDIT-NFC logarithm of credit to non-financial corporations to GDP (from banks and

non-banks)

DEBT_SEC-NFC IHST of outstanding debt securities issued by non-financial corporations

to GDP (see also footnote 6)

DEBT_SEC-FCO IHST of outstanding debt securities issued by financial corporations to

GDP (see also footnote 6)

TOTAL logarithm of the sum of private bank credit to GDP outstanding domestic

debt securities to GDP and domestic stock market capitalization to GDP

TOTAL2 square of TOTAL

Table 1 Notation and transformations of employed explanatory variables

4 Econometric modelling approach

41 Modelling strategy employed model and parameter estimation

Our econometric research strategy is to start from simple log-linear specifications with only

few financial variables and then to introduce richer specifications with more detailed structure

andor non-linearity Namely we first consider the impact of bank credit debt securities and

stock market on growth ie the impact of different sources of financing Afterwards we

further decompose finances not only by sources but also by fund users Finally we merge both

specifications discussed above with non-linear components While presenting the whole

6 Given a variable x the following transformation is applied log(x+(1+x2)05) Throughout our analysis we use it instead of the natural

logarithm in the cases where the values take also zero andor negative values 7 Here we follow Gambacorta et al (2014) using yearly data on education

12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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12

picture this gradual approach thus reveals also the sensitivity of different specifications

without falling into potential problems connected with relatively low degrees of freedom and

possible overfitting if only the richest specification were reported

Now let us turn to the model Let i 12N and t 12T stand for country and

period indices correspondingly For a fixed value of future horizon h we consider the

following econometric model with country and period fixed effects (ih and th respectively)

119894119905+1(ℎ)

= 119894ℎ + 119905ℎ

+ ℎ119910119894119905 + 119945prime119961119946119957 + 119894119905+1

(ℎ) (1)

where 119894119905+1ℎ stands for the average GDP per capita growth rate over the h 1 periods ahead8

119910119894119905 denotes the logarithm of income per capita 119961119946119957 includes explanatory variables to be

discussed shortly ℎ and 119945 are the corresponding real-valued parameter and the vector of

parameters whereas 119894119905+1(ℎ)

stands for the usual zero mean error term It should be pointed out

that the model is dynamic because future values 119910119894119905+119895 119895 gt 0 enter 119894119905+1(ℎ)

Furthermore since

119894119905+1(ℎ)

contains only future values both 119910119894119905 and 119961119946119957 are predetermined thus avoiding at least

contemporaneous endogeneity in equation (1)

The vector of explanatory variables 119961119946119957 can contain various linear and non-linear terms

(logarithms their squares interactions etc) of economic series The two main groups comprise

the control variables and financial series that were summarized in Table 1

Let us turn to the parameter estimation When the number of periods T grows to infinity ℎ in

equation (1) can be consistently estimated by eg the fixed effects estimator However when

T is fixed due to the problem of incidental parameters consistent estimation of ℎ cannot be

directly obtained from equation (1) and the instrumental variable-based estimators of Anderson

and Hsiao (1982 AH hereafter) or generalized method of moments (GMM) of Arelano and

Bond (1991) or Arellano and Bover (1995) and Blundell and Bond (1998) are usually applied

In larger samples the GMM estimator is known to be more efficient when T is small and N is

large but it has large biases when T is relatively large On the other hand the AH estimator is

consistent under both N and T asymptotics (see eg Phillips and Han 2014) This last property

is very convenient in our case because we want to estimate the impact of financial deepening

on economic growth in the sample of EMU countries which has a very limited number of

8 Namely 119894119905+1

(ℎ)= 100

1

ℎsum 119910119894119905+119895

119895=1 where for all i and t the first difference is yit = yit - yit-1 It should be pointed out that very similar

results appear when the geometric mean of gross growth rates is used instead (the gross rates are here needed as straightforward growth

rates may also be negative)

13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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13

countries thus forcing us to rely more on the increase in T rather than N Because of this and

in order to increase the number of observations we do not aggregate the initial data into eg 5

or 10 years periods (as in the baseline estimations of Arcand et al 2015) That would not only

substantially reduce the number of effective periods to a few but also might induce pre-

aggregation bias while the removal of business cycle effects by such a simple aggregation is

also questionable because the length of business cycles might vary both in time and among

different countries

Consequently the AH instrumental variable estimator will be used hereafter In all the cases

the robust inference is based on standard errors adjusted for clustering by countries

42 Caveats

The presented results should be considered with some caution due to several reasons

First given our focus on a homogenous set of developed countries (most importantly the EU

and EMU1999) the sample size is quite limited whereas the number of parameters is large

due to the consideration of a detailed structure of financing To tackle this we use yearly data

and not multi-year averages as that would further shrink the number of observations In

addition to increase the number of observations we consider also a larger group of countries

(the OECD countries) and given consistent results among various country groups we are more

confident in the findings established for the EU and the EMU1999 Note that a larger group

can also cover potentially less homogenous countries where the impact of financial deepening

andor its structure therefore might also differ

Second estimations that rely on the employed period (typically 1990-2014 or part of it) are

informative about processes that took place during these years but might be less indicative for

other periods (either past or future) It is particularly true if there were substantial changes in

the conditions for example if there were important alterations of the financial structure or the

inter-dependence between the structural components In order to account for this we try to

control as much as possible for all relevant aspects and include all components of interest

which however limits the degrees of freedom Consequently there is a tradeoff between weak

inferences versus potential biases due to omitted variables

Third in order to avoid endogeneity stemming from simultaneous relationships we use lagged

explanatory variables in equation (1) ie it is always the future growth rates that are under

prediction However this does not completely eliminate endogeneity as expectations about

future growth conditions can affect the choice of current levels of financial penetration which

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

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Page 14: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

14

may lead to a correlation between the financial series and the error term It is however difficult

to find the necessary (large number of) proper instruments needed in our case due to the

detailed analysis of the structure Therefore we present our results without taking into account

this aspect

Fourth the consideration of totals together with various levels of subcomponents (even though

in a non-linear model) might lead to multicollinearity and thus weaken the statistical inference

Therefore it is possible that some estimates would turn significant when adding more data

once they become available in the future

Fifth the complete disaggregation of finances is not available for example credit to

households or financial corporations are reported from all sectors and not only from banks

data coverage on private domestic or total outstanding debt securities varies across countries

5 Empirical results

This section presents and discusses the main empirical findings relying on equation (1) with

h = 5 ie we assess the impact of financial deepening and financing structure on the average

five year future growth rate of GDP per capita The results are presented in the following

arrangement First we consider interactions between the composition of finance and bank

credit (Subsection 51) Then we investigate whether the non-linearity of the effect of finance

on growth is sufficiently captured by the non-linear term of bank credit alone (Subsection 52)

Further robustness checks are summarized in Subsection 53 with the associated empirical

results presented in Appendix B

The results correspond to the questions stated in Section 2 The second line in all of the

tables identifies the relevant question connected with that particular estimation (column) The

dependent variable is always the average five-year future growth rate of GDP per capita

51 Financing composition and non-linearity in bank credit

Table 2 presents estimation results for the impact of composition with and without the non-

linear term for bank credit (questions Q1Q6) In general there are always consecutive triplets

of columns using the same specification but for the different country groups (OECD EU and

EMU1999) In particular columns (1)(3) present a basic specification with financing split

only by its source (bank credit debt securities and stock market) These results answer the

question whether all the different types of sources affected growth negatively (question Q1)

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 15: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

15

and whether these impacts are homogenous (question Q2) Columns (4)(6) check how much

these results change if one adds the non-linear component of bank credit (question Q3)

Columns (7)(9) refine the analysis of columns (1)-(3) by further splitting bank and security

based financing by its user and thus refer to the question whether the different types of users

affected growth negatively (question Q4 for bank credit and question Q5 for debt securities)

Finally columns (10)(12) augment further this financing split with the non-linear component

of bank credit (question Q6)

As can be seen from columns (1)(3) of Table 2 the answers to questions Q1 and Q2 are

(strongly) negative Even using the log-linear approximation of the impact of finance on

growth the impact varies substantially (even in terms of its sign) for different types of

financing bank credit and debt security have a significantly negative impact on growth

whereas stock market financing tends to have a significantly positive influence In terms of

bank and stock market financing we find that the latter is more beneficial for growth at least

in high-income economies This is consistent with the evidence found in many previous papers

(see eg overviews by Valickova et al 2015) In short it is not all types of financing that affect

growth negatively (question Q1)

The results also reveal that the impact of the different types of sources is not homogenous

(question Q2) In particular the absolute values of the coefficients of bank credit and stock

market capitalization are significantly different therefore the data does not support the use of

their ratio Next the finding that outstanding debt securities have a negative while stock market

capitalization has a positive effect (see eg Kaserer and Rapp 2014 for a similar finding for

the EU countries) reveals that mergingpooling all sources of market-based financing (as eg

in Langfield and Pagano 2016) is not supported Consequently the equal promotion of

different types of market-based financing can be suboptimal from an economic policy point of

view

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

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Page 16: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

16

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1Q2 Q1Q2 Q1Q2 Q3 Q3 Q3 Q4Q5 Q4Q5 Q4Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1627 -1428 -1097 9709 1368 8355 1336 1850 1360

(0578) (0496) (0577) (5990) (8097) (4224) (5155) (6525) (4894)

DEBT_SEC -0256 -0474 -0386 -0212 -0305 -0284

(0131) (0151) (00992) (00957) (0105) (0102) STOCKS 00622 00447 00315 00649 00467 00307 00673 00573 00331 00725 00594 00348

(00346) (00322) (00171) (00334) (00308) (00162) (00349) (00314) (00203) (00337) (00290) (00202)

CREDIT2 -1340 -1819 -1097 -1621 -2258 -1594

(0729) (0995) (0493) (0603) (0790) (0573)

CREDIT-HSH -2035 -1508 -1733 -1956 -1559 -1838

(0662) (0593) (0627) (0605) (0627) (0674)

CREDIT-NFC 0980 0471 0754 0720 0145 0919

(0507) (0481) (0417) (0445) (0592) (0349)

DEBT_SEC-FCO -0290 -0304 -0295 -0102 -00465 -0161

(0188) (0157) (00950) (0130) (0110) (00879)

DEBT_SEC-NFC -0260 -0280 -0136 -0244 -0272 -0161

(0200) (0201) (00892) (0185) (0184) (00976)

INC -9196 -1322 -7157 -1529 -2025 -9414 -8029 -1215 -7381 -1414 -1919 -1033

(4967) (4026) (4815) (7169) (7949) (5880) (4309) (3363) (4149) (5457) (5972) (4977)

EDU -0141 -0144 0118 -0178 -0350 00381 -0290 -0132 -144e-05 -0275 -0282 -0113

(0432) (0495) (0680) (0455) (0541) (0668) (0370) (0477) (0583) (0393) (0519) (0567)

GOV 1299 -0124 4317 -00744 -1700 3690 1513 0382 4312 0414 -0666 3534

(1563) (2529) (1887) (2044) (3192) (1812) (1324) (2129) (1527) (1495) (2234) (1371)

OPN -0189 0675 2972 -0283 0182 2707 -0159 0957 2767 -0307 0339 2298

(0817) (1140) (0861) (0658) (1055) (0844) (0741) (1084) (0596) (0587) (0932) (0604)

INF -3305 -1162 -6441 -2964 -0703 -5525 -2854 -0447 -5189 -2557 0262 -4144

(1813) (1880) (3300) (1915) (2884) (3347) (1818) (2144) (2824) (2262) (3572) (2923)

Constant 0489 0694 0705 0366 0479 0652 0645 0798 0751 0474 0540 0664

(0158) (0190) (0285) (0155) (0256) (0287) (0174) (0200) (0265) (0131) (0231) (0256)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0779 0811 0883 0813 0831 0894 0783 0808 0888 0819 0836 0903

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 2 Financing structure and non-linearity of bank credit

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 17: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

17

As columns (4)(6) show the same conclusions are robust to the introduction of the non-

linear impact of bank credit (CREDIT2) The only difference is that the linear term is positive

for bank credit while the quadratic term is negative Thus consistent with question Q3 the

non-linear impact of bank credit remains significant (at least at the 10 level) after taking into

account the split by the source of financing The finding that the linear term is positive while

the quadratic term is negative implies that there is a turning point in the impact of bank credit

on growth (see the end of this subsection for a detailed analysis of this) It should be pointed

out that CREDIT and CREDIT2 are highly correlated by construction which is partly

responsible for the moderate significance of CREDIT and CREDIT2 observed in the OECD

and the EU

Turning to the impact of an even more refined financing structure (both by sources and

users of finance) presented in columns (7)(9) we confirm earlier findings that bank credit to

households is a drag on economic growth whereas bank credit to firms tends to promote

economic growth rates significantly (question Q4)

A similar though somewhat weaker conclusion can be drawn about the importance of the

structure of outstanding debt securities (question Q5) Namely the coefficient of debt securities

issued by financial corporations tends to be significantly negative whereas that of debt

securities issued by non-financial corporations is insignificant Hence the positive answer to

question Q5 is softly supported during the analyzed period economic growth would have been

higher if outstanding debt securities were issued more by non-financial corporations than by

financial corporations Nevertheless the coefficient of debt securities of non-financial

corporations is still negative Although it is insignificant this negative sign contrasts sharply

with the positive coefficient of stock market capitalization which also tends to be significant

The further inclusion of the non-linear bank credit term in columns (10)(12) reveals again

that the non-linear relationship of bank credit remains robust to taking into account a finer

decomposition of financing structure Consequently the positive answer to Q6 is supported

We again find a positive linear and a negative quadratic term indicating a turning point (to be

further discussed shortly)

Looking the other way round ie at the stability of results about the role of financial

structure to the inclusion of the non-linear term a few changes emerge First the findings about

the relative benefits of promoting stock markets become even stronger as the coefficients of

stock market capitalization become larger and more significant Next the differentiation

18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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18

between the influence of different types of debt securities becomes more blurred Similarly the

positive impact of bank credit to non-financial corporations becomes significant only in the

EMU1999 case (although there it becomes more significant than without the non-linear term)

Nevertheless the relative inferiority of credit to households remains strongly valid

The main findings of Table 2 can be summarized as follows

- The impact of finance on economic growth differs substantially among the different types

and these findings are robust to presence or absence of the non-linear bank credit term

- During the analyzed period bank credit was on average a drag on economic growth rates

but the bulk of this stems from the negative impact of household credit

- Nevertheless the non-linear impact of bank credit is robust to controlling for the main

structural composition of financing both in terms of its source and its user Therefore a

part of reduced growth can also come from the non-linear impact of lsquotoo much creditrsquo

given that most countries in our sample have already reached credit levels higher than the

turning point (peak of maximum contribution of credit to growth to be characterized

shortly)

- Higher stock market capitalization seems to be robustly connected with higher economic

growth whereas larger outstanding debt securities to GDP have a negative impact (and

significantly so for financial corporations when the non-linear credit term is absent)

Although these conclusions might be specific to the period under investigation they are quite

robust despite substantial changes in model specifications

Finally let us discuss the estimated turning points of the non-linear impact of bank credit on

growth rates Figure 1 plots the marginal impact of bank credit on growth with the turning

point estimate identified where the marginal impact equals zero

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 19: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

19

Figure 1 The marginal impact of private bank credit to GDP on economic growth

Notes The figures use the estimated marginal impact of private bank credit to GDP (in ) on economic growth

rates in the OECD EU and EMU1999 groups The figures on the left (blue lines) correspond to estimates provided

in columns (4)(6) of Table 2 using only the sources of finance The figures on the right (red lines) use columns

(10)(12) where both the source and user of finance are incorporated The dashed lines indicate the 95

confidence bounds To ensure visibility of the turning points all lines start from a level of 25 of private bank

credit

First it can be seen that the estimated turning point is smaller when finance is split only in

terms of sources In this case it is below 50 of GDP and varies from 37 to 46 depending

on a group of countries Furthermore considering the confidence bounds the marginal

20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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20

impact of financing here is never found to be significantly positive On the other hand the

positive contribution becomes significant when a more detailed split of financing is employed

(also by the user of finance) In this case the turning point also increases and ranges from 61

to 72 in the different country groups It is interesting to note that these point estimates (in

particular 62 of GDP for the OECD) compare well with that obtained by Cournegravede and Denk

(2015) for the OECD countries using a longer intermediate credit series (their estimated

turning point is about 60 of GDP) However these point estimates are in general lower than

those established by Arcand et al (2015) using their global sample of countries Nevertheless

the mentioned difference is less evident once looking at the confidence bands for some

specifications provided in Arcand et al (2015) the difference is statistically significant

whereas for others it is not

52 Financing structure and other non-linearity questions

In this subsection we explore whether the non-linearity of the effect of finance on growth

is sufficiently captured by the non-linear term of bank credit alone Maybe the total amount of

financing from all the different sources is more relevant than bank credit alone in generating

the non-linearity conditionally either only on the sources of financing (question Q7) or the

sources and users of financing (question Q8) Alternatively maybe household credit is solely

responsible for the non-linear impact of bank credit9 thus after taking it into account the non-

linearity of total bank credit vanishes (question Q9)

In order to answer these questions we investigate the statistical significance of the respective

non-linear terms Table 3 presents the corresponding empirical findings Columns (1)(3)

include both the non-linear term of bank credit and that of the total financing conditioning on

the sources of financing Columns (4)(6) also condition on the users of finance Finally

columns (7)(9) compare the relative significance of the non-linear terms of total bank credit

and of household credit only

9 Since Arcand et al (2015) find that the non-linearity of household credit is more prevalent than that of firm

credit we present here only the results for household credit

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 21: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

21

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q7 Q7 Q7 Q8 Q8 Q8 Q9 Q9 Q9

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9013 1291 7473 1350 1771 1309 1306 1418 2067

(6329) (8151) (4699) (5913) (6838) (4980) (6070) (5546) (4921)

DEBT_SEC -0217 -0328 -0314

(0120) (0127) (0106) STOCKS 00818 00360 -00126 00902 00424 0000559 00722 00534 00395

(00425) (00386) (00390) (00320) (00463) (00417) (00320) (00276) (00194)

CREDIT-HSH -1967 -1517 -1815 -1751 1705 -1170

(0650) (0659) (0641) (3454) (4813) (3708)

CREDIT-NFC 0713 0140 0881 0716 0132 0933

(0409) (0617) (0383) (0482) (0584) (0260)

DEBT_SEC-FCO -00863 -00829 -0176 -0103 -00530 -0174

(0133) (0131) (00829) (0127) (0116) (00716)

DEBT_SEC-NFC -0242 -0273 -0154 -0243 -0259 -0175

(0188) (0188) (0103) (0185) (0175) (00984)

CREDIT2 -1251 -1716 -1005 -1635 -2160 -1543 -1584 -1722 -2442

(0769) (0999) (0538) (0683) (0825) (0584) (0693) (0657) (0574)

TOTAL 0569 2761 1818 -0367 2278 1048

(2087) (3787) (2342) (2147) (3762) (1563) TOTAL2 -00662 -0268 -0152 00269 -0216 -00823

(0187) (0344) (0209) (0199) (0345) (0137) CREDIT-HSQ2 -00294 -0494 1327

(0473) (0703) (0498)

INC -1498 -2123 -9907 -1397 -2002 -1070 -1415 -1893 -1205

(6988) (7254) (6181) (5272) (5539) (5222) (5446) (5702) (3233)

EDU -0182 -0363 00498 -0290 -0295 -0102 -0276 -0317 -0120

(0456) (0548) (0664) (0394) (0517) (0558) (0393) (0524) (0598)

GOV -00535 -1888 3729 0464 -0811 3573 0427 -0347 2789

(2007) (3130) (1979) (1415) (2183) (1516) (1505) (1986) (1090)

OPN -0268 -00111 2715 -0295 0186 2321 -0306 0319 2192

(0655) (1027) (0926) (0595) (0902) (0678) (0587) (0922) (0500)

INF -3047 -0956 -5081 -2604 00418 -3836 -2541 0376 -4327

(1908) (3008) (3310) (2257) (3549) (2970) (2473) (3591) (2972)

Constant 0388 0433 0644 0483 0500 0653 0475 0551 0601

(0148) (0193) (0306) (0131) (0185) (0270) (0136) (0227) (0231)

Observations 267 195 150 260 188 143 260 188 143

R-squared 0812 0832 0897 0819 0838 0904 0819 0837 0910

Number of countries 21 15 9 21 15 9 21 15 9

Notes Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over five years ahead (h = 5) The abbreviations of variables are explained in Table 1

Table 3 Financing structure and non-linearity of financing

Comparing the significance of the linear and non-linear terms of bank credit (CREDIT

CREDIT2) and total financing (TOTAL TOTAL2) in columns (1)(6) of Table 3 one can see

that the impact of bank credit is consistently more significant than that of the total financing

Although the difference is moderate in columns (1)(3) where we control only for the sources

of finance (in connection with question Q7) there is little doubt about the substantial difference

in significance when a detailed financing structure is taken into account (columns (4)(6) in

relation to question Q8) Therefore we can infer that bank credit seems to dominate in the

hump-shaped finance-growth relationship

One can draw similar conclusions from columns (7)(9) regarding the relative significance of

the non-linearity of household credit and (total) bank credit (question Q9) Bank credit retains

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 22: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

22

uniformly not only the sign of both its linear and non-linear terms but also the significance

whereas the non-linearity connected with household credit does not only change signs

irregularly but also becomes insignificant in the OECD and EU samples In the EMU1999

case the terms of household credit are significant but it is more likely to occur due to the small

number of observations potentially coupled with multicollinearity of bank credit and

household credit terms (and their squares)

We therefore can infer that even after controlling for a quite detailed structure of financing

the hump-shaped non-linear impact of finance on growth seems to be most strongly connected

with (total) bank credit

53 Robustness checks

In this subsection we summarize the implications of some robustness checks We look at the

impact of varying the length of future horizons (h) excluding outlier observations including

dummy-interaction variables for the latest after-crisis period reducing the number of variables

(dropping period effects dropping controls leaving only the most significant principal

component of controls) using ratios to represent the composition of financing instead of an

unconstrained estimation additional modeling of dynamics (by including the changes of

explanatory variables or including autoregressive terms of the dependent variable) and

including an additional indicator for accelerating real housing prices Appendix B describes the

implementation details

In order to save space we mostly concentrate on the sensitivity analysis of the main results

provided in Table 2 either the whole table whenever possible or a part of it namely the

specification connected with question Q6 (which has the most detailed split of financing

composition) Due to the same reason all tables associated with the empirical estimation results

are delegated to Appendix B

The results of the performed robustness analysis can be summarized as follows In general the

previously discussed main findings are quite robust to the considered deviations from the

baseline specifications considered in Table 2 The least robust one is about the impact of the

composition of outstanding debt securities although the negative sign of debt securities issued

by both the financial and non-financial corporations is dominant the ranking of its

subcomponents becomes less obvious in many of the performed investigations

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 23: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

23

Some additional interesting aspects are worth singling out First the negative impact of

household financing seems to emerge more over longer periods and is much smaller in shorter

horizons as revealed both by tables B1 and B8 Next the positive impact of stock market

financing seems to be mostly observed during periods of accelerating real housing prices as

illustrated in table B10 after which economic growth is significantly lower but less so in

countries that relied more on capital markets during the associated housing market spur The

analogous impact of debt securities was not observed and even had a negative sign which can

be connected also with the bank strategies to finance housing loans by issuing debt securities

6 Conclusions

This paper contributed to the analysis of the impact of finances on economic growth by

incorporating the structure of financing and allowing for the non-linearity of the impact of

finances in homogeneous groups of high-income countries Our results reveal that the

significance of the non-linear impact of bank credit is robust to controlling for a fairly detailed

composition of private finances Furthermore results are very similar in all the three high-

income groups of countries considered (member states from the OECD EU and EMU1999)

Besides its robustness we find the following additional features of this non-linearity The non-

linear impact of total bank credit is more pronounced than that of either only household credit

or the joint sum of bank credit debt securities and stock market financing The estimated

turning pointthreshold of the identified non-linear relationship is smaller than that established

eg in Arcand et al (2015) using a global panel while it is in line with that estimated for the

OECD countries by Cournegravede and Denk (2015) Therefore a large bank credit penetration

relative to GDP (especially with heavy financing of households) might be more harmful to

economic growth in high-income countries than thought previously At the same time due to

the dominance of bank-biased financing in the EU even a simple reduction of bank credit

relative to GDP could result in improved economic growth rates in a number of EU countries

We also find andor confirm many important aspects of the role of financing composition even

after controlling for the non-linearity discussed above First the impact of bank credit to

households and non-financial corporations qualitatively differ in our sample the former had a

strongly negative whereas the latter tended to have a positive impact on economic growth

Consequently if a reduction of bank credit were beneficial for a particular economy in general

the strongest promotion to growth could be achieved by shrinking household credit

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 24: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

24

This established empirical finding seems to support the hypothesis that in the long run

household credit diverts funds of limited supply from firms that could generate longer-lasting

positive development This can become especially acute during housing market booms periods

that facilitate expansion of credit to households by creating larger values of collateral

acceptable to banks and larger returns in this market We indeed find that during periods of

significantly positive real housing inflation growth was further reduced besides what has

already been captured by the amounts of credit to households directly Thus either housing

credit has a further negative impact on long-term growth relative to total household credit (eg

it may create a drag on householdsrsquo willingness to work productively) or the actually realized

amounts of household credit do not reveal its whole negative influence (eg banks shrank firm

financing more by foreseeing the need of additional household borrowing in the future)

Next the growth impact of stock market and debt security financing are qualitatively different

stock market financing has a positive whereas debt securities tend to have a negative influence

on growth Looking from both the methodological and policy perspectives this would suggest

that the use of financing aggregates and the equal promotion of all types of market-based modes

of financing might be just as misleading as cutting all types of bank credit

Although statistically less clear-cut we have found some evidence that shifting currently

outstanding debt securities from financial corporations towards the non-financial ones could

be beneficial for growth This can be due to several factors at play First a substantial part of

debt securities issued by financial institutions is connected to the financing of housing which

we find to have a negative impact on growth Furthermore international financial markets are

highly integrated and financial institutions issuing debt securities can outsource domestic

savings from high-income economies to other countries easily thus reducing the local funding

of investments On the other hand given the increased total globalization of corporate

activities it can be a potential explanation also for the negative sign (though smaller absolute

value) of the impact of non-financial corporations

Finally from the policy perspective our results point to several alternatives connected with the

financial deepness and its structure that would promote economic growth Regarding the

banking sector growth would be increased both by directing more credit towards non-financial

corporations and by reducing the bank credit to GDP levels in a number of European countries

(especially from the EMU) The reduction of household credit which simultaneously

diminishes the total amount of credit and favorably changes its composition can have the

largest economic impact However the effect of a reduction of the total amount of bank credit

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 25: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

25

also depends nontrivially on the initial conditions of a particular economy (namely the actual

distance from the peak impact of credit the level of penetration of all modes of finance etc)

Therefore for economies that are close to the turning point of the non-linear impact a balanced

compositional shift towards firm financing without affecting the total amount of credit might

be best suited The further development of market-based financing seems to be mostly

beneficial through the fostering of stock markets

References

Anderson T W and Hsiao C (1981) Estimation of dynamic models with error components

Journal of the American Statistical Association 76 598ndash606

Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic

Growth 20 105ndash148

Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo

evidence and an application to employment equations Review of Economic Studies 58 277ndash

297

Arellano M and Bover O (1995) Another look at the instrumental variable estimation of

error-components models Journal of Econometrics 68 29ndash51

Balta N and Nikolov P (2013) Financial dependence and growth since the crisis Quarterly

Report on the Euro Area 2013 12 7ndash18

Beck T (2012) Finance and Growth Lessons from the literature and the recent crisis July

2012 Prepared for the LSE Growth Commission

Beck T Buyukkarabacak B Rioja F and Valev N (2012) Who gets the credit And does

it matter Household vs firm lending across countries BE Journal of Macroeconomicsrdquo

Contributions 12 1ndash44

Beck T Degryse H and Kneer C (2014) Is more finance better Disentangling

intermediation and size effects of financial systems Journal of Financial Stability 10 50ndash64

Beck T and Levine R (2004) Stock markets banks and growth panel evidence Journal of

Banking and Finance 28 423ndash442

Beck T Levine R and Loayza N (2000) Finance and the sources of growth Journal of

Financial Economics 58 261ndash300

Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth

Groningen University of Groningen SOM research school (SOM Research Reports vol

14016-GEM)

Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel

data models Journal of Econometrics 87 115ndash143

Breitenlechner M Gaumlchter M and Sindermann F (2015) The finance-growth nexus in

crisis Economics Letters 132 31ndash33

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 26: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

26

Cecchetti SG and Kharroubi E (2012) Reassessing the impact of finance on growth BIS

Working Papers No 381

Contessi S Li L and Russ K (2013) Bank vs bond financing over the business cycle

Federal Reserve Bank of St Louis Economic Synopses 2013 No31

Coricelli F Driffield N Pal S and Roland I (2012) When does leverage hurt productivity

growth A firm-level analysis Journal of International Money and Finance 31 1674ndash1694

Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20

countries OECD Economics Department Working Papers No 1223 OECD Publishing Paris

Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD

Economic Policy Papers No 14 OECD Publishing Paris

Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and

securities markets World Bank Economic Review 27 476ndash490

Ductor L Grechyna D (2015) Financial development real sector and economic growth

International Review of Economics and Finance 37 393ndash405

Gambacorta L Yang J and Tsatsaronis K (2014) Financial structure and growth BIS

Quarterly Review March 21ndash35

Karagiannis A and Kvedaras V (2016) Financial development and economic growth A

European perspective JRC Science-for-policy reports (JRC103421)

Kaserer C and Rapp MS (2014) Capital markets and economic growth long-term trends

and policy challenges AIMA research report

King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly

Journal of Economics 108 717ndash738

Langfield S and Pagano M (2016) Bank bias in Europe effects on systemic risk and growth

Economic Policy 31 51ndash106

Law SH and Singh N (2014) Does too much finance harm economic growth Journal of

Banking amp Finance 41 36ndash44

Levine R (2005) Finance and growth theory and evidence in Handbook of Economic

Growth ed Philippe Aghion and Steve N Durlauf 865-934 Amsterdam Elsevier

Masten A Coricelli F and Masten I (2008) Non-linear growth effects of financial

development Does financial integration matter Journal of International Money and Finance

27 295ndash313

Mishra S and Narayan PK (2015) A nonparametric model of financial system and

economic growth International Review of Economics and Finance 39 175ndash191

Panizza U (2014) Financial development and economic growth known knowns known

unknowns and unknown unknowns Revue drsquoegraveconomie du degraveveloppement 22 35ndash65

Phillips CB and Han C (2014) True limit distribution of the Anderson-Hsiao IV estimators

in panel autoregression Cowles Foundation Discussion Paper No 1963

Rioja F and Valev N (2014) Stock markets banks and the sources of economic growth in

low and high income countries Journal of Economics and Finance 38 302ndash320

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 27: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

27

Rousseau PL and Wachtel P (2011) What is happening to the impact of financial deepening

on economic growth Economic Inquiry 49 276ndash288

Sahay R Cihak M NrsquoDiaye P Barajas A Bi R Ayala D Gao Y Kyobe A Nguyen

L Saborowski C Svirydzenka K and Yousefi SR (2015) Rethinking financial

deepening stability and growth in emerging markets Staff Discussion Notes SDN1508

Samargandi N Fidrmuc J and Ghosh S (2015) Is the relationship between financial

development and economic growth monotonic for middle income countries World

Development 68 66ndash81

Schumpeter JA (1934) The theory of economic development an Inquiry into profits capital

credit interest and the business cycle Translated from German by Redvers Opie New

Brunswick (USA) and London (UK) Transaction Publishers 2008

Valickova P Havranek T and Horvath R (2015) Financial development and economic

growth A meta-analysis Journal of Economic Surveys 29 506ndash526

28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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28

APPENDIX A Data

Table A1 Sources of Original Data

Variable

(notation of related series after transformations

defined in Table 1 of main text)

Source (all downloaded in June 2016)

Total credit by banks to the private non-financial

sector adjusted for structural breaks (CREDIT)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities (DEBT_SEC) Bank for International Settlements (BIS) Debt

Securities Statistics

Market capitalization of listed domestic

companies as a percentage of GDP (STOCKS)

World Bank World Development Indicators

(WDI)

Private credit received by households (CREDIT-

HSH)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Private credit received by non-financial

corporations (CREDIT-NFC)

Bank for International Settlements (BIS) Credit

to the Non-financial Sector

Outstanding debt securities issued by financial

corporations (DEBT_SEC-FCO)

Bank for International Settlements (BIS) Debt

Securities Statistics

Outstanding debt securities issued by non-

financial corporations (DEBT_SEC-NFC)

Bank for International Settlements (BIS) Debt

Securities Statistics

GDP per capita constant LCU (INC) World Bank World Development Indicators

(WDI)

Inflation of consumer prices annual (INF) World Bank World Development Indicators

(WDI)

Gross enrolment ratio secondary both sexes in

of the corresponding age group (EDU)

World Bank World Development Indicators

(WDI)

General government final consumption

expenditure as a percentage of GDP (GOV)

World Bank World Development Indicators

(WDI)

Trade openness calculated as exports plus

imports divided by GDP (OPN)

World Bank World Development Indicators

(WDI)

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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ISBN 978-92-79-67444-0

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Page 29: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

29

Figure A1 Bank credit to GDP (in ) from the Bank for International Settlements (BIS) credit

database and the Global Financial Development Database (GFDD) of the World Bank Selected

sample of countries having structural breaks Belgium (BEL) Canada (CAN) Denmark

(DNK) France (FRA) Japan (JPN) Sweden (SWE)

30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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30

APPENDIX B Robustness checks

We perform the following robustness checks

Varying the future horizon h (Table B1) In addition to the main five-year horizon considered

in the previous tables we present the estimation results for a broader range of future horizon

values namely h 34567 for the specification connected with question Q6 However it

should be kept in mind that higher horizons used for calculation of average yearly economic

growth rates reduce further the degrees of freedom

Excluding outlier observations (Table B2) This table presents the results of the re-estimation

of the specifications of Table 2 after removing observations (separately in each specification)

that result in residuals being greater than three standard errors On average such an operation

reduces the number of observations by 30 as compared to those in Table 2

Including dummy-interaction variables of the latest after-crisis period (Table B3) To

investigate the stability of parameter estimates we include the interaction terms of financing

sources (of bank debt securities and stock market financing) with the crisis period dummies

in the specification connected with question Q6 Because in the main estimations we

considered five-year ahead periods of growth rates as defined in equation (1) the included

interaction terms start from 2003 Hence starting from 2003 the five-year average growth rate

includes only the 2008 crisis period starting from 2004 it includes 2008 and 2009 and so on

In such a way it is possible to allow for a time varying impact of the crisis It should be also

pointed out that there is no need to include additional dummies without interaction since our

specifications already have period fixed effects It should be again kept in mind that this

increases further the number of estimated parameters

Reducing the number of variables dropping period effects (Table B4) dropping potentially

insignificant controls10 (Table B5) or leaving only the most significant principal component of

controls (Table B6) The main concern regarding the basic estimation is the low degree of

freedom Therefore we present several sensitivity evaluations of Table 2 by reducing the

number of parameters under estimation First we drop period dummies as in Table B4 Next

we keep only the initial income variable that is always significant and drop the remaining ones

that in many specifications were insignificant (Table B5) Finally since omitted variables can

10 See the last paragraph of Section 3 for the set of control variables

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

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Page 31: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

31

create estimation bias we also use the most significant principal component from previously

omitted variables to reduce it (Table B6)

Using ratios to represent the composition of financing (Table B7) The main findings reveal

that the estimates using ratios are likely to be biased Nevertheless the use of ratios allows

reducing the number of estimated parameters and the variability of the estimates Hence we

also study if the results are similar to those presented in Table 2 whenever ratios of proper

variables are employed instead of the unconstrained estimation Namely we use a) the

logarithm of the ratio of outstanding debt securities to bank credit (DEBT_SEC CREDIT)

and the logarithm of the ratio of stock market capitalization to bank credit (STOCKS

CREDIT) to represent the composition of financing by type of instrument b) the logarithm of

the ratio of credit to household and non-financial corporations (CREDIT-HSH CREDIT-

NFC) to represent the credit structure and c) the logarithm of the ratio of outstanding debt

securities issued by financial and non-financial corporations (DEBT_SEC-FCO DEBT_SEC-

NFC) to represent the composition of debt securities

Additional modelling of dynamics included first differences of explanatory variables (Table

B8) or included lagged left hand side variable (Table B9) Despite that further terms in the

equations increase the number of parameters we also investigate the sensitivity of the results

of Table 2 to the inclusion of additional dynamic terms the first difference of explanatory

variables as in Table B8 and the lagged left hand side variable as in Table B9

Including a dummy variable for accelerating real housing prices (Table B10) The expansion

of household credit was influenced by an increasing credit for housing needs which in turn

interacts strongly with housing price developments The recent crisis and housing price bubbles

suggest that this aspect could have been behind the negative impact of bank credit to

households Although we do not have the respective split of household credit we investigate

the significance of a dummy variable (and its interactions) of an accelerated increase in housing

prices (as motivated by the studies of Langfield and Pagano 2016 and Karagiannis and

Kvedaras 2016) In particular the dummy takes a value of one if the real growth rate of housing

prices exceeds one percentage point and zero otherwise

The respective tables are presented below preceded by a list of tables provided for

convenience

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Page 32: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

32

List of tables

1 Table B1 Varying the future horizon h

2 Table B2 Excluded outlier observations

3 Table B3 Included dummy-interaction variables of the latest after-crisis period

4 Table B4 Reduced number of variables dropping period effects

5 Table B5 Reduced number of variables dropping potentially insignificant

controls

6 Table B6 Reduced number of variables leaving only the most significant principal

component of controls

7 Table B7 Using ratios to represent the composition of financing

8 Table B8 Additional modelling of dynamics included changes of explanatory

variables

9 Table B9 Additional modelling of dynamics included autoregressive term

10 Table B10 Included a dummy to represent an accelerated growth of real housing

prices

33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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33

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Future horizon (h=3) (h=3) (h=3) (h=4) (h=4) (h=4) (h=5) (h=5) (h=5) (h=6) (h=6) (h=6) (h=7) (h=7) (h=7)

VARIABLES Group

of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 1955 2087 2564 1928 2403 2537 1336 1850 1360 1250 1952 1041 3506 7592 -1168

(5101) (6506) (4864) (4705) (7176) (3970) (5155) (6525) (4894) (5937) (6213) (3153) (4472) (4248) (3430)

CREDIT2 -2377 -2458 -2970 -2376 -2814 -2942 -1621 -2258 -1594 -1449 -2263 -1230 -0374 -0793 0120

(0531) (0719) (0529) (0550) (0827) (0451) (0603) (0790) (0573) (0671) (0737) (0378) (0504) (0492) (0422)

STOCKS 00315 00304 00824 00438 -000599 -000765 00725 00594 00348 000881 -000314 000252 00498 00227 00129

(00564) (00658) (00590) (00427) (00292) (00167) (00337) (00290) (00202) (00478) (00458) (00308) (00314) (00334) (00176)

CREDIT-HSH -0645 -1326 -1338 -1914 -2625 -1949 -1956 -1559 -1838 -2371 -2702 -2355 -2063 -2900 -1490

(1178) (1347) (1379) (0872) (0957) (0862) (0605) (0627) (0674) (0486) (0352) (0732) (0744) (0852) (0780)

CREDIT-NFC -0178 -0254 1172 0185 -0306 0828 0720 0145 0919 0361 0324 0794 0514 0405 0561

(0912) (0776) (0753) (0629) (0692) (0720) (0445) (0592) (0349) (0411) (0510) (0422) (0330) (0434) (0369)

DEBT_SEC-FCO -0317 00349 -0127 -00771 0188 -0125 -0102 -00465 -0161 00549 0176 0205 -0191 -0102 -000232

(0273) (0238) (0183) (0246) (0218) (0160) (0130) (0110) (00879) (0119) (00997) (0211) (0209) (0263) (0240)

DEBT_SEC-NFC 0118 0120 -0328 -00964 -0102 -0156 -0244 -0272 -0161 -0253 -0276 -0151 -0171 -0176 000349

(0149) (0149) (0186) (0134) (0115) (00924) (0185) (0184) (00976) (0197) (0193) (00989) (0119) (0130) (0102)

INC -1802 -2177 -1657 -1426 -1848 -1278 -1414 -1919 -1033 -1082 -1589 -5819 -6199 -6411 -00721

(1300) (8127) (1075) (8529) (5163) (7448) (5457) (5972) (4977) (7033) (8051) (5900) (6660) (6677) (1031)

EDU -1449 -0325 -00877 0155 0690 0730 -0275 -0282 -0113 -0531 -0664 0201 -0198 -00582 0600

(1109) (0606) (0753) (0442) (0376) (0298) (0393) (0519) (0567) (0476) (0605) (0318) (0438) (0498) (0474)

GOV 1761 -1150 1961 1321 -0549 2241 0414 -0666 3534 0857 -0754 3667 1307 2622 4116

(2798) (2696) (2764) (2309) (1917) (1348) (1495) (2234) (1371) (1878) (2569) (1163) (1059) (1163) (1699)

OPN -1215 -00818 2551 -0846 -0162 2922 -0307 0339 2298 -0173 -0474 1489 0207 0768 2320

(0836) (1286) (1389) (0968) (1342) (0635) (0587) (0932) (0604) (0414) (0614) (0741) (0394) (0670) (1271)

INF -1972 -4311 3521 4123 4612 0804 -2557 0262 -4144 -1332 -0801 -6896 4362 7010 -2932

(3199) (3258) (8374) (2920) (2401) (3364) (2262) (3572) (2923) (1521) (2311) (2828) (1855) (2363) (3620)

Constant 0487 0464 0000352 0101 0189 -0291 0474 0540 0664 0247 0331 00723 0131 0150 -0224

(0149) (0185) (0249) (0162) (0186) (0218) (0131) (0231) (0256) (00980) (0160) (00880) (0194) (0242) (0288)

Observations 296 212 162 277 199 152 260 188 143 244 178 135 226 166 127

R-squared 0780 0811 0861 0763 0794 0890 0819 0836 0903 0776 0830 0842 0726 0753 0765

Number of countries 23 17 11 22 16 10 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B1 Robustness checks future horizon in years for calculating the average yearly growth rate (h 34567)

34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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34

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1877 -1462 -1446 5064 1234 8556 2092 2795 1112

(0554) (0649) (0617) (7824) (6993) (7181) (8574) (8278) (9104)

DEBT_SEC -0746 -0969 -0549 -0650 -0725 -0347

(0424) (0429) (0117) (0474) (0491) (0176) STOCKS 00438 00256 00427 00484 00315 00438 00912 00872 00435 0123 0120 00553

(00299) (00218) (00157) (00274) (00207) (00166) (00589) (00525) (00277) (00590) (00527) (00288)

CREDIT2 -0805 -1634 -1142 -2482 -3357 -1379

(0883) (0839) (0801) (0977) (0954) (1025)

CREDIT-HSH -3131 -2260 -1782 -2961 -2523 -1324

(1011) (0891) (1042) (1011) (1032) (0971)

CREDIT-NFC 1941 1530 -00174 1616 1497 0461

(0777) (0773) (0756) (0517) (0593) (0661)

DEBT_SEC-FCO -0396 -0636 -0403 000945 00233 -0229

(0230) (0231) (0164) (0227) (0219) (0203)

DEBT_SEC-NFC -0641 -0702 -0160 -0655 -0720 -0167

(0255) (0254) (0113) (0261) (0274) (0102)

INC -7263 -1325 -7902 -1030 -1834 -1001 -3512 -1035 -9102 -1171 -1831 -1009

(5391) (4397) (2364) (6952) (5728) (3655) (5290) (2693) (2127) (6622) (5618) (3101)

EDU 0199 00589 0243 0121 -0122 0156 0286 0286 0157 0107 00255 0186

(0547) (0583) (0707) (0564) (0626) (0740) (0532) (0617) (0659) (0596) (0724) (0740)

GOV -0303 -2505 2434 -0587 -3027 2299 1240 -1392 2853 0740 -1357 2708

(1644) (2468) (0845) (1785) (2597) (0885) (1511) (1797) (1147) (1412) (1584) (1047)

OPN -0985 -0445 1478 -0893 -0505 1566 -0821 -0171 1912 -0772 -0523 1677

(0785) (1409) (0824) (0797) (1191) (0772) (0679) (1412) (0769) (0525) (0980) (0679)

INF -3369 -1296 -3347 -4161 -2672 -3154 -3955 -3135 -2517 -6425 -6010 -3242

(1963) (1426) (3063) (1702) (2240) (3236) (1791) (2341) (3325) (1902) (3136) (3443)

Constant 0642 0804 0711 0541 0580 0638 0798 0877 0787 0448 0367 0671

(0212) (0276) (0262) (0123) (0203) (0268) (0246) (0279) (0290) (0158) (0225) (0279)

Observations 188 143 115 188 143 115 181 136 108 181 136 108

R-squared 0772 0821 0901 0789 0837 0905 0771 0820 0900 0821 0858 0906

Number of countries 19 14 9 19 14 9 19 14 9 19 14 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B2 Robustness checks exclusion of outlying observations

35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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35

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Related questions Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6 Q6

Interaction term CREDIT CREDIT CREDIT DEBT_SEC DEBT_SEC DEBT_SEC STOCKS STOCKS STOCKS

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT 9892 1576 1188 1638 2190 1611 1550 1892 1260

(5987) (8521) (5388) (6971) (7915) (4229) (5557) (6503) (4521)

CREDIT2 -1093 -1777 -1387 -1943 -2566 -1875 -1879 -2277 -1450

(0704) (0984) (0666) (0804) (0905) (0477) (0642) (0788) (0537)

STOCKS 00674 00549 00355 00746 00515 00360 00627 00671 00442

(00261) (00241) (00188) (00365) (00304) (00215) (00293) (00260) (00176)

CREDIT-HSH -2373 -2216 -1971 -2040 -2027 -1963 -1751 -1799 -2083

(0521) (0423) (0675) (0515) (0507) (0746) (0675) (0730) (0800)

CREDIT-NFC 0521 00745 0911 0634 0254 1030 0747 0306 1087

(0414) (0593) (0344) (0363) (0553) (0359) (0445) (0577) (0367)

DEBT_SEC-FCO -00839 -00950 -0182 -00999 -00922 -0191 -00867 -00253 -0114

(0122) (0102) (00839) (0194) (0172) (00952) (0115) (00884) (00678)

DEBT_SEC-NFC -0241 -0282 -0109 -0204 -0230 -0174 -0246 -0294 -0221

(0183) (0181) (0114) (0149) (0152) (0110) (0188) (0186) (0101)

INC -1691 -2238 -9545 -1413 -1949 -1005 -1513 -1914 -8816

(5195) (6592) (3919) (4177) (5265) (4910) (5273) (6203) (4746)

EDU -00623 00156 -0452 00932 -00117 -0286 -0251 -0302 -0159

(0455) (0593) (0501) (0434) (0558) (0506) (0391) (0491) (0502)

GOV 0249 -0921 3976 0474 -0364 3722 -00892 -0548 3674

(1483) (2318) (1421) (1215) (1654) (1632) (1555) (2263) (1525)

OPN -0265 0173 2348 -0228 0605 2239 -0377 0403 2377

(0525) (0901) (0437) (0609) (0802) (0544) (0638) (0842) (0554)

INF -3608 -1876 -3093 -3466 -1026 -3364 -2051 0486 -5241

(1897) (3325) (3144) (1533) (2176) (3701) (2098) (2905) (2435)

Interactterm I(yeargt=2003) -00908 -0228 0381 -000178 -00311 0181 00851 00793 00432

(0226) (0239) (0174) (00422) (00575) (00687) (0125) (0146) (00936)

Interactterm I(yeargt=2004) -0460 -0555 0688 -0162 -0230 00923 -00795 -0253 -0257

(0366) (0416) (0509) (0111) (0138) (0191) (0256) (0278) (0303)

Interactterm I(yeargt=2005) -00730 -0126 -0148 00925 00620 -00969 -00927 -0210 -0264

(0144) (0130) (0215) (00811) (0103) (00700) (0117) (00932) (00917)

Interactterm I(yeargt=2006) -0365 -0366 -0512 0237 0244 -00546 -00357 -00948 -00663

(0148) (0184) (0198) (0215) (0231) (0146) (0108) (0108) (0152)

Interactterm I(yeargt=2007) -0262 -0306 -0544 0121 0155 000550 0295 0129 000201

(0127) (0176) (0163) (0142) (0153) (0118) (00982) (0120) (0251)

Interactterm I(yeargt=2008) -0385 -0372 00823 -00938 -00893 -0107 00192 -00211 0221

(0137) (0280) (0205) (00490) (00976) (00705) (0141) (0214) (0173)

Interactterm I(yeargt=2009) -0121 -0183 0145 -00103 -0136 -00929 -00348 -00754 -00153

(0104) (0197) (0135) (00246) (00956) (0154) (0141) (0219) (0190)

Constant 0394 0433 0692 0423 0560 0662 0377 0717 0829

(0115) (0230) (0221) (0118) (0188) (0242) (0222) (0259) (0326)

Observations 260 188 143 260 188 143 260 188 143

R-squared 0833 0845 0911 0834 0856 0905 0825 0842 0903

Number of countries 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B3 Robustness checks crisis period dummy interaction terms (an interaction term

used in each case is specified in the third line which is bolded)

36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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36

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -3359 -3595 -2722 4357 3034 7066 1541 1990 1292

(0895) (0799) (0585) (7252) (7805) (4637) (6033) (7039) (4188)

DEBT_SEC -0539 -0688 -0715 -0518 -0649 -0666

(0171) (0216) (0115) (0156) (0205) (0123)

STOCKS 00345 00201 00161 00396 00250 00198 00620 00511 00590 00727 00692 00666

(00281) (00315) (00274) (00277) (00310) (00282) (00299) (00286) (00173) (00304) (00320) (00201)

CREDIT2 -0911 -0792 -1118 -1858 -2393 -1616

(0859) (0921) (0511) (0700) (0821) (0521)

CREDIT-HSH -4120 -4168 -3591 -4270 -4557 -2755

(1017) (0942) (0527) (0874) (0929) (0948)

CREDIT-NFC 0910 1051 0300 0880 1014 0583

(0778) (0847) (0347) (0686) (0716) (0322)

DEBT_SEC-FCO -0417 -0338 -0357 -0297 -0201 -0293

(0233) (0221) (0169) (0200) (0203) (0166)

DEBT_SEC-NFC -0183 -0214 -0354 -0168 -0209 -0407

(0267) (0282) (0118) (0244) (0257) (0127)

INC -1133 -3579 -4378 -4054 -5663 -5957 -1558 -2870 -4891 -5979 -7477 -6516

(8882) (7645) (7264) (9561) (9295) (7864) (8253) (7628) (6326) (8105) (7514) (6719)

EDU 3277 3601 3603 3183 3499 3555 2842 3313 3353 2714 3054 3314

(0942) (1180) (1284) (0942) (1149) (1270) (0829) (1076) (1219) (0821) (1028) (1190)

GOV 6157 5411 6313 5060 4729 5767 6972 6553 7045 5407 5330 6109

(2896) (2523) (1398) (3139) (3112) (1904) (2545) (2418) (0916) (2495) (2582) (1451)

OPN -1836 -2038 -0702 -1665 -1840 -0554 -2046 -2121 -0748 -1764 -1671 -0636

(1460) (1763) (1935) (1386) (1758) (1859) (1485) (1832) (1885) (1299) (1556) (1726)

INF -7024 -8057 -1388 -6587 -7620 -1312 -6831 -7960 -1367 -6108 -6611 -1308

(2200) (2643) (3612) (1947) (2496) (3493) (2025) (2630) (3589) (1873) (2713) (3119)

Constant 00438 00811 00547 00938 0119 00839 00993 00888 00903 0180 0191 0120

(0131) (0121) (00968) (0149) (0157) (0119) (0109) (0114) (00701) (0122) (0128) (00945)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0438 0505 0564 0487 0533 0580 0469 0512 0579 0544 0582 0601

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B4 Robustness checks reducing the number of variables (exclusion of period dummies)

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

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doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 37: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

37

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1472 -1533 -1515 1109 1620 8781 1393 1933 1479

(0594) (0573) (0542) (6396) (9930) (3326) (5722) (7458) (3786)

DEBT_SEC -0227 -0482 -0412 -0181 -0259 -0310 (0133) (0133) (00956) (00857) (0141) (0111)

STOCKS 00405 00352 00156 00422 00454 00164 00571 00565 00263 00567 00583 00295

(00337) (00228) (00152) (00298) (00303) (00180) (00346) (00255) (00130) (00305) (00257) (00163)

CREDIT2 -1491 -2135 -1195 -1706 -2381 -1801

(0777) (1205) (0390) (0654) (0852) (0469)

CREDIT-HSH -1662 -1480 -1923 -1666 -1544 -1588

(0626) (0664) (0602) (0647) (0737) (0689)

CREDIT-NFC 0865 0608 1012 0604 0252 1095

(0462) (0431) (0611) (0432) (0609) (0598)

DEBT_SEC-FCO -0250 -0309 -0285 -00435 -000705 -0109

(0156) (0116) (0108) (0114) (0117) (00847)

DEBT_SEC-NFC -0219 -0255 -0116 -0210 -0250 -0154

(0192) (0201) (0116) (0179) (0188) (0116)

INC -1020 -1404 -1437 -1742 -2230 -1749 -1005 -1314 -1305 -1565 -1925 -1522

(6026) (5607) (1045) (9106) (1084) (1090) (4643) (4462) (6192) (5923) (6475) (6860)

Constant 0700 0628 0521 0419 0278 0384 0791 0702 0618 0568 0457 0523

(0232) (0227) (0473) (0341) (0453) (0471) (0214) (0188) (0269) (0210) (0232) (0266)

Observations 294 205 158 294 205 158 287 198 151 287 198 151

R-squared 0782 0818 0889 0824 0834 0901 0787 0811 0885 0826 0842 0901

Number of countries 22 16 10 22 16 10 22 16 10 22 16 10

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B5 Robustness checks reducing the number of variables (exclusion of potentially insignificant controls)

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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doi102760063349

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7-007-E

N-N

Page 38: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

38

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1414 -1407 -1328 1029 1542 8394 1319 1963 1385

(0544) (0563) (0549) (5786) (8931) (3649) (5663) (7408) (3661)

DEBT_SEC -0234 -0477 -0429 -0199 -0271 -0324 (0140) (0136) (0121) (00946) (0129) (0129)

STOCKS 00480 00531 00296 00593 00656 00311 00542 00648 00227 00627 00688 00270

(00267) (00237) (00147) (00257) (00295) (00168) (00304) (00303) (00203) (00292) (00308) (00213)

CREDIT2 -1397 -2039 -1129 -1597 -2386 -1632

(0719) (1107) (0433) (0652) (0869) (0444)

CREDIT-HSH -1711 -1430 -1970 -1803 -1672 -1975

(0615) (0657) (0619) (0655) (0693) (0626)

CREDIT-NFC 0921 0404 0684 0639 00646 0864

(0457) (0433) (0472) (0413) (0588) (0388)

DEBT_SEC-FCO -0306 -0311 -0293 -0106 -00206 -0153

(0176) (0140) (0116) (0136) (0135) (0106)

DEBT_SEC-NFC -0263 -0285 -0121 -0246 -0277 -0151

(0192) (0204) (00961) (0182) (0193) (0111)

INC -1060 -1450 -1523 -1665 -2160 -1713 -9686 -1349 -1361 -1502 -1956 -1538

(4924) (4915) (4697) (7493) (9196) (6055) (4158) (3914) (3296) (5494) (6274) (4390)

PC 0169 0228 0612 -000659 0122 0577 0241 0324 0666 00835 0203 0621

(0315) (0331) (0223) (0362) (0445) (0276) (0278) (0289) (0209) (0304) (0369) (0250)

Constant 0654 0580 0466 0428 0304 0391 0795 0663 0590 0585 0438 0528

(0183) (0197) (0207) (0271) (0366) (0249) (0197) (0158) (0166) (0196) (0230) (0189)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0783 0814 0896 0814 0827 0902 0789 0811 0896 0819 0836 0906

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B6 Robustness checks reducing the number of variables (keeping the most significant principal component (PC) of potentially insignificant

controls)

39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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39

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6

VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

DEBT_SEC CREDIT -0204 -0436 -0390 -0212 -0305 -0284 (0110) (0131) (0133) (00957) (0105) (0102)

STOCKS CREDIT 00874 00810 00529 00649 00467 00307 00796 00775 00296 00708 00611 00274

(00402) (00344) (00208) (00334) (00308) (00162) (00345) (00295) (00235) (00316) (00285) (00212)

CREDIT 9562 1342 8101 1390 1865 1459

(5979) (8098) (4259) (5568) (7237) (4981)

CREDIT2 -1340 -1819 -1097 -1792 -2416 -1786

(0729) (0995) (0493) (0695) (0921) (0576)

CREDIT-HSH CREDIT-NFC -0930 -0568 -1055 -0802 -0300 -1076

(0444) (0537) (0524) (0457) (0630) (0419)

DEBT_SEC-FCO DEBT_SEC-NFC 0123 0129 -0116 0159 0189 000620

(0150) (0144) (00923) (0143) (0142) (00579)

INC -1583 -1864 -1011 -1529 -2025 -9414 -1468 -1733 -8640 -1810 -2227 -1065

(5022) (5316) (5967) (7169) (7949) (5880) (4927) (5526) (5256) (6604) (7466) (5440)

EDU -0212 -0316 000444 -0178 -0350 00381 -0331 -0289 -00887 -0309 -0387 -0137

(0464) (0524) (0644) (0455) (0541) (0668) (0429) (0540) (0540) (0434) (0547) (0579)

GOV -0368 -1813 3514 -00744 -1700 3690 -00708 -1218 3515 -0652 -1796 3083

(1686) (2965) (1946) (2044) (3192) (1812) (1557) (2652) (1386) (1846) (2593) (1226)

OPN 00984 0747 3146 -0283 0182 2707 0121 0936 2997 -0209 0186 2367

(0689) (1012) (0917) (0658) (1055) (0844) (0612) (0940) (0622) (0491) (0868) (0610)

INF -2909 -0614 -4416 -2964 -0703 -5525 -2907 -0178 -4318 -2749 -00219 -4273

(1718) (2352) (2989) (1915) (2884) (3347) (2083) (2907) (3191) (2542) (4010) (3092)

Constant 0354 0566 0692 0366 0479 0652 0383 0524 0696 0304 0355 0609

(0156) (0217) (0314) (0155) (0256) (0287) (0161) (0216) (0319) (0170) (0267) (0284)

Observations 267 195 150 267 195 150 260 188 143 260 188 143

R-squared 0797 0809 0886 0813 0831 0894 0796 0802 0885 0819 0830 0900

Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B7 Robustness checks the usage of ratios to reduce the number of parameters under estimation The respective ratios are represented using

the notation A B

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

Europe Direct is a service to help you find answers

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More information on the European Union is available on the internet (httpeuropaeu)

HOW TO OBTAIN EU PUBLICATIONS

Free publications

bull one copy

via EU Bookshop (httpbookshopeuropaeu)

bull more than one copy or postersmaps

from the European Unionrsquos representations (httpeceuropaeurepresent_enhtm)from the delegations in non-EU countries (httpeeaseuropaeudelegationsindex_enhtm)

by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

bull via EU Bookshop (httpbookshopeuropaeu)

doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 40: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

40

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1509 -1453 -1387 9168 1695 8108 1822 2577 1377

(0635) (0656) (0609) (4975) (7313) (4366) (4924) (5822) (5684) DEBT_SEC -0621 -0630 -0377 -0490 -0425 -0219

(0224) (0183) (0117) (0211) (0132) (0103) STOCKS -00343 -00159 00731 -00213 -000968 00716 -000574 -000385 00365 00133 -000176 00421

(0117) (0105) (00806) (00942) (00819) (00748) (0103) (00941) (00961) (00781) (00748) (00833) CREDIT2 -1256 -2176 -1098 -2132 -3019 -1611

(0603) (0901) (0490) (0574) (0675) (0667) CREDIT-HSH -2506 -2180 -2189 -2712 -2785 -2350

(0770) (0637) (0704) (0723) (0652) (0816) CREDIT-NFC 1877 1520 0858 1453 0914 0911

(0850) (0930) (1063) (0668) (0593) (0803) DEBT_SEC-FCO -0284 -0205 -0228 00125 0268 00321

(0258) (0251) (0190) (0192) (0195) (0193) DEBT_SEC-NFC -0661 -0680 -0126 -0660 -0714 -0211

(0328) (0329) (0193) (0300) (0288) (0191) INC -1014 -1391 -1016 -1492 -2161 -1183 -7656 -1090 -1194 -1467 -1973 -1399

(4705) (3743) (4074) (6224) (5798) (4561) (4211) (2898) (4382) (4667) (4773) (4765) EDU -00444 00185 00684 -00428 -0222 -00328 -0139 00506 00676 -0133 -0298 -0141

(0437) (0552) (0661) (0472) (0596) (0667) (0426) (0541) (0671) (0463) (0635) (0673) GOV 0177 -0777 3555 -0686 -2285 3048 0601 -0514 3224 -0343 -1090 2865

(1556) (2409) (1824) (1849) (2701) (1722) (1290) (1959) (1479) (1326) (1855) (1455) OPN -0176 0950 2846 -0219 0367 2601 -0270 1089 2669 -0364 0350 2194

(0913) (1258) (0914) (0763) (0968) (0855) (0840) (1295) (0761) (0660) (0993) (0791) INF -4779 -3607 -5695 -4939 -4259 -4845 -5493 -2479 -5995 -5438 -2163 -4330

(1869) (1647) (3382) (1536) (1752) (3466) (1847) (1727) (2896) (1662) (2238) (3253)

CREDIT 0786 1239 0857 0670 0590 0673 (0606) (0677) (0415) (0540) (0514) (0410)

DEBT_SEC 00858 0274 0118 00830 0200 000191 (0138) (0178) (0162) (0131) (0134) (0162)

STOCKS 00409 00149 -00393 00347 00175 -00348 00325 00258 -00229 00265 00294 -00235

(00698) (00540) (00544) (00569) (00421) (00511) (00602) (00512) (00607) (00439) (00374) (00523)

CREDIT-HSH 1399 2276 2418 1278 1468 2122

(0883) (0847) (1084) (0730) (0641) (1164)

CREDIT-NFC -0366 -0492 -0299 -0304 -0391 -0242

(0574) (0605) (0695) (0400) (0348) (0576)

DEBT_SEC-FCO 00915 -00203 -000479 -0000550 -0224 -0173

(0185) (0205) (0201) (0142) (0123) (0171)

DEBT_SEC-NFC 0215 0220 -00377 0237 0258 00353

(0212) (0221) (0124) (0196) (0195) (0125) Constant 0544 0723 0659 0411 0418 0617 0614 0879 0562 0412 0495 0499

(0182) (0256) (0247) (0133) (0200) (0246) (0195) (0261) (0210) (0105) (0227) (0211)

Observations 251 182 143 251 182 143 244 175 136 244 175 136 R-squared 0808 0837 0897 0833 0859 0904 0813 0847 0908 0857 0887 0916 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses plt001 plt005 plt01 Financial series are bold faced Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B8 Robustness checks additional modelling of dynamics with changes of explanatory variables ()

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

Europe Direct is a service to help you find answers

to your questions about the European Union

Freephone number ()

00 800 6 7 8 9 10 11 () The information given is free as are most calls (though some operators phone boxes or hotels may

charge you)

More information on the European Union is available on the internet (httpeuropaeu)

HOW TO OBTAIN EU PUBLICATIONS

Free publications

bull one copy

via EU Bookshop (httpbookshopeuropaeu)

bull more than one copy or postersmaps

from the European Unionrsquos representations (httpeceuropaeurepresent_enhtm)from the delegations in non-EU countries (httpeeaseuropaeudelegationsindex_enhtm)

by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

bull via EU Bookshop (httpbookshopeuropaeu)

doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 41: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -0987 -0553 -0646 -2287 1916 6538 3328 7063 1116

(0506) (0389) (0547) (6184) (5707) (3173) (6987) (7907) (3874) DEBT_SEC -0355 -0384 -0321 -0362 -0357 -0244

(0133) (0161) (00806) (0138) (0162) (00741) STOCKS 00540 00608 00432 00536 00610 00424 00504 00729 00482 00510 00728 00488

(00407) (00307) (00194) (00402) (00299) (00193) (00429) (00374) (00220) (00423) (00363) (00238) CREDIT2 0155 -0298 -0834 -0352 -0822 -1304

(0698) (0671) (0374) (0802) (0891) (0450) CREDIT-HSH -2072 -1141 -1051 -2299 -1383 -1195

(0720) (0333) (0650) (0830) (0662) (0675) CREDIT-NFC 1817 1168 0902 1672 0992 1029

(0563) (0501) (0401) (0514) (0380) (0359) DEBT_SEC-FCO -0167 -0157 -0269 -0132 -00720 -0160

(0177) (0131) (00937) (0182) (0133) (00808) DEBT_SEC-NFC -0160 -0185 -0106 -0160 -0188 -0128

(0135) (0142) (0103) (0132) (0140) (0107) INC 2535 -2799 -1771 3423 -4068 -3548 4227 -0807 -1930 2410 -3867 -4627

(4718) (2129) (3670) (7054) (4248) (4789) (4630) (1692) (3928) (7174) (4304) (4977) EDU 0114 0103 0237 0123 00669 0174 -0127 00546 0112 -0122 -000579 00127

(0508) (0585) (0710) (0502) (0578) (0708) (0472) (0542) (0603) (0467) (0546) (0607) GOV 3588 4136 5774 3782 3831 5281 3711 4671 5510 3448 4165 4818

(1457) (1534) (1702) (1899) (1823) (1682) (1378) (1369) (1377) (1695) (1522) (1348) OPN -0747 -00220 1308 -0745 -00953 1125 -0718 000329 0909 -0710 -0159 0613

(0809) (0845) (1245) (0826) (0710) (1152) (0711) (0984) (1243) (0680) (0836) (1145) INF -2028 0785 -4560 -2048 0838 -3884 -1915 1100 -3481 -1776 1429 -2668

(2254) (2111) (4366) (2300) (2145) (4379) (2027) (2290) (4042) (1993) (2404) (4178) Lagged LHS 0499 0600 0386 0507 0593 0382 0565 0648 0425 0553 0624 0405

(0121) (0108) (0248) (0126) (0115) (0252) (00930) (0105) (0277) (0111) (0119) (0279) Constant 0741 0854 0688 0759 0817 0648 0861 0895 0700 0824 0806 0632

(0227) (0236) (0272) (0225) (0193) (0269) (0220) (0220) (0263) (0216) (0186) (0245)

Observations 267 195 150 267 195 150 260 188 143 260 188 143 R-squared 0763 0836 0880 0755 0843 0890 0762 0827 0884 0778 0844 0899 Number of countries 21 15 9 21 15 9 21 15 9 21 15 9

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B9 Robustness checks additional modelling of dynamics with the lagged left hand side (LHS) variable

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

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Free publications

bull one copy

via EU Bookshop (httpbookshopeuropaeu)

bull more than one copy or postersmaps

from the European Unionrsquos representations (httpeceuropaeurepresent_enhtm)from the delegations in non-EU countries (httpeeaseuropaeudelegationsindex_enhtm)

by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

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doi102760063349

ISBN 978-92-79-67444-0

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Page 42: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Related questions Q1-Q2 Q1-Q2 Q1-Q2 Q3 Q3 Q3 Q4-Q5 Q4-Q5 Q4-Q5 Q6 Q6 Q6 VARIABLES Group of cntrs OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999 OECD EU EMU1999

CREDIT -1098 -1210 -0921 6359 9048 8016 8136 1310 1370 (0635) (0678) (0616) (5571) (4875) (5368) (5459) (5135) (6789)

DEBT_SEC -0313 -0296 -0448 -0242 -0191 -0327 (0200) (0135) (00798) (0175) (0114) (00992)

STOCKS 00330 00144 00571 00385 00188 00530 00293 000475 00444 00378 00129 00403 (00553) (00518) (00290) (00502) (00454) (00249) (00486) (00568) (00346) (00415) (00450) (00253)

CREDIT2 -0865 -1195 -1046 -0972 -1533 -1591 (0671) (0586) (0640) (0673) (0616) (0809)

CREDIT-HSH -1922 -2003 -1743 -1754 -2112 -2088 (0678) (0824) (0882) (0841) (0837) (0953)

CREDIT-NFC 0620 0459 0265 0713 0661 0597 (0237) (0268) (0337) (0289) (0287) (0340)

DEBT_SEC-FCO -0312 -0256 -0247 -0244 -0126 -00903 (0201) (0145) (00995) (0154) (00948) (00661)

DEBT_SEC-NFC 00540 00111 -00550 00424 -00209 -0142 (0108) (0115) (0177) (0109) (0108) (0208)

INC -5714 -1082 -8970 -7165 -1300 -1033 -8146 -1182 -7965 -9440 -1437 -9935 (6780) (4479) (4863) (7095) (5489) (5568) (5032) (4079) (4253) (5790) (4879) (4670)

EDU 00164 -00562 00373 -000823 -0112 -00234 -0149 -0220 -00101 -0174 -0297 -0119 (0397) (0528) (0569) (0405) (0543) (0572) (0340) (0507) (0535) (0348) (0514) (0538)

GOV 2257 2404 3476 1937 1892 3126 2352 2532 4127 1949 1835 3485 (1011) (1148) (1379) (1058) (1451) (1491) (1009) (1467) (1565) (1061) (1611) (1441)

OPN -0723 0831 2409 -0720 0712 2268 -0660 0609 2372 -0684 0413 2004 (0848) (0979) (0507) (0817) (0927) (0574) (0667) (1130) (0465) (0662) (1019) (0455)

INF -4722 -2841 -4904 -4851 -2296 -4003 -4670 -2128 -4591 -4906 -1300 -3269 (2351) (2709) (1875) (2236) (2625) (2254) (2133) (2263) (1850) (2032) (2009) (2088)

D_HOUS -1085 -0865 -0517 -1039 -0779 -0490 -0977 -0753 -0527 -0939 -0638 -0471 (0331) (0289) (0142) (0322) (0288) (0144) (0261) (0209) (0143) (0269) (0206) (0123)

STOCKS D_HOUS 0213 0182 00769 0204 0164 00744 0190 0147 00729 0183 0122 00649 (00714) (00709) (00240) (00690) (00703) (00236) (00558) (00478) (00323) (00568) (00476) (00272)

Constant 0276 0393 0608 0251 0343 0583 0264 0399 0657 0240 0353 0636 (0199) (0256) (0280) (0175) (0226) (0266) (0169) (0279) (0273) (0140) (0236) (0232)

Observations 211 142 118 211 142 118 210 141 117 210 141 117 R-squared 0816 0871 0895 0829 0883 0901 0842 0882 0895 0851 0895 0906 Number of countries 15 10 8 15 10 8 15 10 8 15 10 8

Robust standard errors in parentheses

plt001 plt005 plt01

Financial series are bold faced

Dependent variable average GDP per capita growth rate over various periods ahead The abbreviations of variables are explained in Table 1

Table B10 Robustness checks including dummy series for acceleration of housing prices (D_HOUS)

Europe Direct is a service to help you find answers

to your questions about the European Union

Freephone number ()

00 800 6 7 8 9 10 11 () The information given is free as are most calls (though some operators phone boxes or hotels may

charge you)

More information on the European Union is available on the internet (httpeuropaeu)

HOW TO OBTAIN EU PUBLICATIONS

Free publications

bull one copy

via EU Bookshop (httpbookshopeuropaeu)

bull more than one copy or postersmaps

from the European Unionrsquos representations (httpeceuropaeurepresent_enhtm)from the delegations in non-EU countries (httpeeaseuropaeudelegationsindex_enhtm)

by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

bull via EU Bookshop (httpbookshopeuropaeu)

doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 43: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

Europe Direct is a service to help you find answers

to your questions about the European Union

Freephone number ()

00 800 6 7 8 9 10 11 () The information given is free as are most calls (though some operators phone boxes or hotels may

charge you)

More information on the European Union is available on the internet (httpeuropaeu)

HOW TO OBTAIN EU PUBLICATIONS

Free publications

bull one copy

via EU Bookshop (httpbookshopeuropaeu)

bull more than one copy or postersmaps

from the European Unionrsquos representations (httpeceuropaeurepresent_enhtm)from the delegations in non-EU countries (httpeeaseuropaeudelegationsindex_enhtm)

by contacting the Europe Direct service (httpeuropaeueuropedirectindex_enhtm) orcalling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) ()

() The information given is free as are most calls (though some operators phone boxes or hotels may charge you)

Priced publications

bull via EU Bookshop (httpbookshopeuropaeu)

doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N

Page 44: Finance and economic growth - Europapublications.jrc.ec.europa.eu/...finance_growth_bkk... · dependence of economic growth rates on bank credit financing and stock market financing

doi102760063349

ISBN 978-92-79-67444-0

KJ-A

E-1

7-007-E

N-N


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