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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

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LIBOR-OIS Spreads

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

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1 2 3 4Dependent 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 2Dependent variable: ∆DL 2SLS OLS

∆XL .60** .51***0.28 0.09

DEMAND .032*** .034***0.01 0.01

Size controls Yes Yes

N 141 141R-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).