Comments on “Assessing Policies to Revive Credit Markets”

Comments on “Assessing Policies to Revive Credit Markets” Chapter 2 of Global Financial Stability Report, IMF, October, 2013

Rafael Doménech Madrid, October 18, 2013

Comments on “Assessing Policies to Revive Credit Markets” October 2013

Main results

•  Chapter 2 of the GFSR offers a timely and comprehensive empirical analysis of the factors that underlie the weakness in credit

•  Three different approaches to identify the constraints to credit:

•  Lending surveys

•  Structural determinants of the supply and demand of bank lending to firms

•  Firm-level regressions of changes in debt-to-asset ratio for manufacturing firms

•  Results:

•  Constraints in credit markets differ by country and evolve over time

•  Importance of careful country-by-country assessments and

•  Need for better data on new lending (production sectors, firms, etc.)

Page 2


Main results

•  Two main economic policy implications

•  Policymakers should also recognize that there are limits to credit policies and not attempt to do too much

•  Policymakers need to continually weigh the near-term benefits against the longer-run costs of policies aimed to boost credit

•  This chapter

•  finds very interesting results,

•  makes original empirical contributions to the literature, and

•  offers sound economic policy recommendations on a very relevant issue in the economic recovery of countries with high levels of credit to GDP ratios

Page 3


Main comments

•  The analysis focuses on the stock of credit and not on flows (new loans), due to the lack of data

•  Alternative approaches to identify supply and demand factors: estimation of a DSGE model with a banking sector

•  Policy implications

•  Some additional comments

Page 4


1. Flows vs the stock of credit

•  Assume a very simple model in which:

•  the economy was in steady state (real growth 2% yoy, credit stock/GDP=100%),

•  a (positive) financial shock occurred (credit growth from 2% to 10%), and

•  the economy returns to its steady state

•  Also assume that:

•  in steady state, new loans represent a fraction of GDP (10%)

•  repayments represent a constant fraction of the credit stock (10%)

•  Main result: for an extended period of time the stock of credit is falling (deleveraging) but the economy is in steady state

•  Weak growth of the stock of credit is not the appropriate measure

Page 5


Simulation of the stock of credit and GDP growth Source: BBVA Research


Page 6

-0.14 -0.12 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Gro

wth

of c

redi

t sto

ck

GD

P gr

owth

Quarters

Credit stock (right)

GDP (left)

20 quarters

0.05

0.1

0.15

0.2

0.25

0.3

0.35

-0.4

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

New

loan

s an

d re

paym

ents

ove

r GD

P

Gro

wth

of c

redi

t sto

ck

Quarters

Credit stock (left)

New loans (right)

Repayments (right)

Simulation of new loans and repayments (% GDP) Source: BBVA Research


Spain: stock of credit and nominal GDP growth Source: BBVA Research


Page 7

Spain: new loans and repayments (sa, % GDP) Source: BBVA Research

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1.10

1.20

1.30

1.40

mar

-03

sep-

03

mar

-04

sep-

04

mar

-05

sep-

05

mar

-06

sep-

06

mar

-07

sep-

07

mar

-08

sep-

08

mar

-09

sep-

09

mar

-10

sep-

10

mar

-11

sep-

11

mar

-12

sep-

12

mar

-13

sep-

13

mar

-14

sep-

14

New

loan

s an

d re

paym

ents

ove

r GD

P New loans

Repayments (right)

New loans include refinancing operations The growth of the credit stock is affected by SAREB

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

jun-

03

dic-

03

jun-

04

dic-

04

jun-

05

dic-

05

jun-

06

dic-

06

jun-

07

dic-

07

jun-

08

dic-

08

jun-

09

dic-

09

jun-

10

dic-

10

jun-

11

dic-

11

jun-

12

dic-

12

jun-

13

dic-

13

jun-

14

dic-

14

Gro

wth

of C

redi

t sto

ck

Nom

inal

GD

P gr

owth

Crédit stock (right)

Nominal GDP (left)


2. DSGE model for EMU with a banking sector

•  Alternative decompositions of supply and demand shocks can be obtained with other approaches, for example, with estimated DSGE models

•  Loans to firms and households could have been affected by supply and demand shocks in different ways

•  Results for EMU using an estimated DSGE model with a banking sector indicate that differences across sectors are relevant

Page 8



Production sector

External sector

Patient households

Impatient households

Banks

Central Bank

Retail

Wholesale

Deposits

Loans

Loans

Financial shocks Macroeconomic shocks

Monetary shock

Households

Public sector

Entrepreneurs

Retail sector Capital goods Labour market

Extended version of Gerali, Neri, Sessa and Signoretti (2010), with public and external sector.


Historical decomposition of EMU households loans growth (% y/y) Source: BBVA Research


Page 10

Historical decomposition of EMU corporate loans growth (% y/y) Source: BBVA Research

-8

-6

-4

-2

0

2

4

6

8

10

1998

Q1

1998

Q3

1999

Q1

1999

Q3

200

0Q

1 20

00

Q3

200

1Q1

200

1Q3

200

2Q1

200

2Q3

200

3Q1

200

3Q3

200

4Q1

200

4Q3

200

5Q1

200

5Q3

200

6Q1

200

6Q3

200

7Q1

200

7Q3

200

8Q1

200

8Q3

200

9Q1

200

9Q3

2010

Q1

2010

Q3

2011

Q1

2011

Q3

2012

Q1

2012

Q3

2013

Q1

2013

Q3

(f)

FISCAL MONETARY MACRO FINANCIAL Loans to households pc growh rate

-8

-6

-4

-2

0

2

4

6

8

10

1998

Q1

1998

Q3

1999

Q1

1999

Q3

200

0Q

1 20

00

Q3

200

1Q1

200

1Q3

200

2Q1

200

2Q3

200

3Q1

200

3Q3

200

4Q1

200

4Q3

200

5Q1

200

5Q3

200

6Q1

200

6Q3

200

7Q1

200

7Q3

200

8Q1

200

8Q3

200

9Q1

200

9Q3

2010

Q1

2010

Q3

2011

Q1

2011

Q3

2012

Q1

2012

Q3

2013

Q1

2013

Q3

(f)

FISCAL MONETARY MACRO FINANCIAL


3. Policy implications

Page 11

Changes in rejection rates of new loans Source: BBVA Research

It is di!icult to know without uncertainty when policy interventions are justi"ied (R)

or not (NR’)

In NR’ there is no change in risk evaluation rules but the rejection rate increases because more

applications are non-pro"itable

In R there is an additional increase in rejection rates (higher risk aversion, less liquidity,

regulatory uncertainty, etc.)


4. Additional comments

•  Lending survey analysis: consider the inclusion of credit over GDP (in t-1) as an additional regressor

Page 12

Credit growtht =α+βCredit growtht +

γiDemand factorst−i +δiSupply factorst−i +

φCreditt−1

GDPt−1

+εt



•  Firm-Level regressions of changes in debt-to-asset ratio for manufacturing firms:

•  Include the real interest rate from 1991 to 2012

•  The estimated effects for bank capital are not clear, given the increase in capital ratios from 2007 to 2012

Page 13


Capital and reserves over banks’ assets Source: BBVA Research


Page 14

Decomposition of change in Debt-to-Asset ratios for firms Source: IMF (2013)

6.9%

11.3%

2007 2012


Concluding remarks

Page 15

•  A timely and comprehensive empirical analysis of the factors behind the weakness in credit

•  A relevant issue in the economic recovery of countries with high levels of credit to GDP ratios (e.g., Spain)

•  Very interesting results

•  Original empirical contributions

•  Sound economic policy recommendations

Comments on “Assessing Policies to Revive Credit Markets” Chapter 2 of Global Financial Stability Report, IMF, October, 2013

Rafael Doménech Madrid, October 18, 2013

Date post:	19-Oct-2014
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