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
ℎ
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
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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
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
ℎ
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
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
ℎ
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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Arellano M and Bond S (1991) Some tests of specification for panel data Monte Carlo
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Arellano M and Bover O (1995) Another look at the instrumental variable estimation of
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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
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
ℎ
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
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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
ℎ
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
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
ℎ
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
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
ℎ
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
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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
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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
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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
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
ℎ
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
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
ℎ
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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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
ℎ
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
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
ℎ
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
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
ℎ
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
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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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
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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
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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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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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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Priced publications
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doi102760063349
ISBN 978-92-79-67444-0
KJ-A
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7-007-E
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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
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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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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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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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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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
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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
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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
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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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
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Arcand JL Berkes E and Panizza U (2015) Too much finance Journal of Economic
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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 Levine R and Loayza N (2000) Finance and the sources of growth Journal of
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Bezemer D Grydaki M and Zhang L (2014) Is financial development bad for growth
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14016-GEM)
Blundell R and Bond S (1998) Initial conditions and moment restrictions in dynamic panel
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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
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Cournegravede B and Denk O (2015) Finance and economic growth in OECD and G20
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Cournegravede B Denk O and Hoeller P (2015) Finance and inclusive growth OECD
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Demirguumlccedil-Kunt A Feyen E and Levine R (2013) The evolving importance of banks and
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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
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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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King RG and Levine R (1993) Finance and growth Schumpeter might be right Quarterly
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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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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
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
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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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
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
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
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
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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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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7-007-E
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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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doi102760063349
ISBN 978-92-79-67444-0
KJ-A
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7-007-E
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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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doi102760063349
ISBN 978-92-79-67444-0
KJ-A
E-1
7-007-E
N-N
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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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
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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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
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
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
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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bull more than one copy or postersmaps
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() 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
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7-007-E
N-N
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
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
doi102760063349
ISBN 978-92-79-67444-0
KJ-A
E-1
7-007-E
N-N