how did the crisis in international funding markets affect bank lending? balance sheet evidence from...

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How did the crisis in international funding markets affect bank lending? Balance sheet evidence from the UK

Shekhar AiyarInternational Monetary Fund and Bank of England.

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Motivation

How did problems originating in one asset class in one country propagate internationally and spark the Great Recession?

A standard stylized explanation relies on the globalization of the banking system and has two parts.

1.Stress in the US banking system (and others with direct exposure to US mortgages / structured products) spread internationally through bank funding markets.

2.This shock to banks’ external funding was transmitted domestically through a reduction in credit supply.

This paper seeks to identify step 2 above for the UK.

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Related Literature

• Older literature on impact of non-monetary shocks on bank lending: Bernanke (1983); Peek and Rosengren (1997)

• Khwaja and Mian (2008). Impact of external funding shock on domestic lending for Pakistani banks. Use 1998 nuclear test to identify equation.

• Schnabl (2011). Liquidity shock to global banks from Russian default in 1998 led to fall in lending to Peruvian banks.

• Cetorelli and Goldberg (2010). Liquidity shocks in developed country banking systems led to contraction in loan supply to EMEs.

• Amiti and Weinstein (2009), Chor and Manova (2009). Impact of bank health on trade volumes (via trade finance).

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•Between end-Q1 2008 and end-Q3 2009, the external liabilities of UK-resident banks fell by 22%.

•The previous largest 6-quarter fall was 9%, during the ERM crisis.

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Chart 1: An unprecedented shock to banks' external funding

UK-resident banks' external liabilities

UK-resident banks' external liabilities adjusted for exchange rate changes

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Empirical strategy: data• As a global financial center, UK has a large and heterogenous

sample of resident banks, HQ’d in several countries.

• Study uses detailed regulatory balance sheet data reported to BOE at quarterly frequency (CL, CE, BT, BE forms).

• Focus on period during which shock to external funding occurred (March 2008 through September 2009).

• Bank mergers dealt with by creating a synthetic merged series.

• Domestic lending constructed as sum of lending to Households, Businesses, Other Banks and OFIs. Each subseries constructed by summing relevant items in BT / BE reporting forms.

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Empirical strategy: estimation

We want to estimate

where i indexes banks∆DLi = change in (log) domestic lending

∆XLi = change in (log) external liabilities

where j indexes sector {Households, Businesses, Other Banks, OFIs}; denotes bank i’s claims on sector j as a ratio of its total domestic claims; and denotes the change in lending by all banks to sector j.

Jj

jiji TBLsDEM

iiiii ZDEMXLDL '21

ijs

jTBL

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Identification

• If is exogenous, no problem.

• But this needs to be established, not assumed.

• Potentially OLS is biased and inconsistent (omitted variables / reverse causality).

• Hence implement IV, using 3 instruments for

iXL

iXL

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First instrument• Share of repos in bank’s external liabilities at t=0.

• Measures ex-ante reliance on wholesale funding.

• Plenty of evidence that repo markets became very stressed, with a substantial increase in repo haircuts (Gorton and Metrick 2009). Bear Stearns collapse in March 2008 precipitated by loss of secured short-term funding, despite adequate capital (Acharya and Gale 2009).

• Funding shock was transmitted in part through repo market (Raddatz 2010).

• So higher reliance on external repo funding at the beginning of the shock period should be associated with bigger funding shock.

• Equally, external reliance on repo should not impact future domestic lending except through the funding shock.

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Second instrument

• Share of external liabilities to foreign affiliates at t=0.

• Measures the degree to which liabilities are “within firm”.

• In response to monetary shocks “internal capital markets” are activated to insulate against shock. Cetorelli and Goldberg (2010).

• In financial crises foreign subsidiaries rely on liquidity from parent banks: De Haas and Lelyveld (2010).

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Third instrument

• Banking system stress in country of ownership.

• Use data on nationality of bank HQ to divide all nations into 9 regions (USA, UK, EUR, CHE, CAN, JAP, NJA, OTH).

• For each region, use change in LIBOR-OIS spread as a measure of banking system stress.

• Wherever possible, use region-specific LIBOR equivalent (EURIBOR for EUR, SIBOR for SIN, BBSR for AUS etc.)

• Taylor and Williams (2008) emphasize that LIBOR-OIS spread measures counterparty risk not liquidity risk.

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LIBOR-OIS Spreads

USA UK EUR CHE JPY CAD SGP

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LIBOR-OIS Spreads

Pre-sample period (2006 - Q1 2008) Q1 2008 - Q3 2009

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1 2 3 4

Dependent variable: ∆DL 2SLS 2SLS 2SLS 2SLS

∆XL .55** 0.59** .65** .60**

0.27 0.25 0.28 0.28

DEMAND .035*** .032***

0.009 0.01

Size controls No No Yes Yes

N 141 141 141 141

Underidentification (H0: Not identified)

A-P chi-squared statistic 31.57 38.76 30.53 32.34p-value 0.00 0.00 0.00 0.00

Overidentifying restrictions (H0: Instruments uncorrelated with error process)

Sargan chi-squared statistic 0.35 0.17 0.12 0.071

p-value 0.84 0.92 0.94 0.96

Weak instruments (H0: Instruments are weak)

K-P Wald rank F-statistic 10.23 12.46 9.74 10.25

10% critical value (Stock and Yogo) 9.1 9.1 9.1 9.1

Table 1: Impact of change in external liabilities on change in domestic lending

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1 2

Dependent variable: ∆DL 2SLS OLS

∆XL .60** .51***

0.28 0.09

DEMAND .032*** .034***

0.01 0.01

Size controls Yes Yes

N 141 141

R-squared 0.27

Exogeneity of explanatory variable (H0: Variable is exogenous)

Difference-in-Sargan statistic 0.14

p-value 0.71

Table 2: 2SLS and OLS

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Conditional Quantile Functions

95% quantile confidence interval

Quantile regression estimate

OLS estimate

1 2Dependant variable: ∆DL OLS Median Regression

∆XL .51*** .55***0.09 0.1

DEMAND .034*** .031***0.01 0.01

Size controls Yes Yes

N 141 141R-squared 0.27 0.21

Table 4: Median impact on change in domestic lending

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1 2Dependant variable: ∆DL OLS OLS

∆XL .45*** .83***0.10 0.12

DEMAND .032*** .033***0.01 0.01

UOB 25.98***6.3

SUB -26.8***6.95

BRN -26.1***6.92

UOB*∆XL .38**0.17

SUB*∆XL -.52***0.17

BRN*∆XL -.32*0.19

Constant 3.02 29.6***4.56 6.66

Size controls Yes Yes

N 141 141R-squared 0.31 0.32

Table 5: The impact of bank type

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1 2Dependant variable: ∆DL OLS OLS

∆XL .54*** .45**0.15 0.19

DEMAND .024** .024**0.011 0.012

Fraction of DL in FX (t=0) -21.5* -16.7912.77 11.59

(Fraction of DL in FX)*∆XL -0.8 -0.010.32 0.31

UOB 23.46***7.78

UOB*∆XL .41**0.22

Constant 12.19* 7.684.84 5.20

Size controls Yes Yes

N 141 141R-squared 0.29 0.32

Table 6: Lending in FX

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1 2 3Dependant variable: ∆DL OLS OLS OLS

∆XL .56*** .49*** .39***0.15 0.10 0.12

DEMAND .033*** .033*** .031***0.01 0.01 0.01

Foreign assets / Total assets (t=0) -14.7210.74

(Foreign assets / Total assets)*∆XL -0.110.32

Foreign assets / Foreign liabilities (t=0) -6.56** -4.543.21 3.2

(Foreign assets / Foreign liabilities)*∆XL -0.003 0.040.06 0.06

UOB 24.18***6.44

UOB*∆XL .41**0.17

Constant 13.46** 11.98** 6.726.59 5.35 5.66

Size controls Yes Yes Yes

N 141 141 141R-squared 0.28 0.29 0.33

Table 7: Are foreign assets a significant buffer?

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Households Businesses Other Banks OFIs1 2 3 4

Full sample ∆XL -63.18 (54.86) -552 (554) 1.16 (.59)* .51 (.28)*% of total lending 100 100 100 100N 122 134 139 130

Lending > £100 m∆XL -.27 (.36) .58 (.16)*** .41 (.22)* .69 (.24)***% of total lending 99.8 99.8 99.8 99.9N 27 91 105 73

Lending > £500 m∆XL .08 (.27) .47 (.15)*** .56 (.27)** .92 (.31)***% of total lending 99.6 98.4 99.2 98.8N 19 60 70 47

Lending > £1000 m∆XL .32 (.19) .45 (.19)** .87 (.26)*** 1.01 (.32)***% of total lending 99.1 96.5 98.6 96.9N 15 47 48 40

Sample

Change in lending to:

Table: Sectoral regressions

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Change in lending to: 1 2 3 4 5 6 7 8 9

Businesses∆XL 0.53 .56** .66*** .62** .54*** .49*** .51*** .57*** .60**s.e. 0.54 0.22 0.22 0.24 0.17 0.1 0.09 0.18 0.29

Other Banks∆XL -0.02 0.31 .32* .51*** .39** .55*** .52** 0.58 0.14s.e. 0.25 0.19 0.17 0.19 0.18 0.16 0.23 0.43 1.28

OFIs∆XL -0.26 0.38 .54*** .84** .83* .93** .91** 1.08*** 1.11**s.e. 0.36 0.31 0.16 0.35 0.48 0.46 0.38 0.26 0.46

Decliles of conditional distribution

Table: Quantile regressions on components of domestic lending

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Conclusions• Large, well-identified and robust impact of external funding shock on

domestic bank lending.

• Relationship holds across the distribution.

• Corroborates standard view that bank lending was significant in transmitting international financial crisis to real economy.

• Foreign-owned banks (branches and subs) cut back domestic lending more, irrespective of size of funding shock. UK-owned backs calibrated pullback in lending more closely to size of funding shock.

• Evidence for pullback in domestic lending to 3 out of 4 sectors: businesses, OFIs and other banks. No evidence of pullback in HH lending (maybe because of unwinding securitization).