J Financ Serv Res (2010) 37:83–98DOI 10.1007/s10693-009-0079-2

Liquidity, Bank Runs, and Bailouts: Spillover EffectsDuring the Northern Rock Episode

Paul Goldsmith-Pinkham · Tanju Yorulmazer

Received: 19 September 2008 / Revised: 3 November 2009 / Accepted: 17 November 2009 /Published online: 15 December 2009© Springer Science+Business Media, LLC 2009

Abstract In September 2007, Northern Rock—the fifth largest mortgage lender inthe United Kingdom—experienced an old-fashioned bank run, the first bank runin the U.K. since the collapse of City of Glasgow Bank in 1878. The run had beencontained by the government’s announcement that it would guarantee all depositsin Northern Rock. This paper analyzes spillover effects during the Northern Rockepisode and shows that both the bank run and the subsequent bailout announcementhad significant effects on the rest of the U.K. banking system, as measured byabnormal returns on the stock prices of banks. The paper also shows that the effectswere a rational response by investors to market news about the liability side of banks’balance sheets. In particular, banks that rely on funding from wholesale markets weresignificantly affected, a result consistent with the drying up of liquidity in wholesalemarkets and the record-high levels of the London Interbank Offered Rate (LIBOR)during the crisis.

Keywords Contagion · Banking crisis · Bank run · Liquidity · Event study ·Systemic risk · Bailout

JEL Classification G21 · G14 · G28 · E58 · D62

The views expressed in this paper are those of the authors and do not necessarily reflect theviews of the Federal Reserve Bank of New York or the Federal Reserve System. Part of thisproject was completed while Paul Goldsmith-Pinkham was at the Federal Reserve Bank ofNew York. We are grateful to Viral Acharya, Robert DeYoung (editor), Douglas Gale, BeverlyHirtle, Donald Morgan, Ihab Seblani, David Skeie, Til Schuermann, Hyun Shin, Haluk Unal(editor) and an anonymous referee for helpful suggestions.

P. Goldsmith-PinkhamOffice of the Doctoral Program, Harvard Business School,Wyss House, 102 Soldiers Field Road, Boston, MA 02163, USAe-mail: pgoldsm@fas.harvard.edu

T. Yorulmazer (B)Federal Reserve Bank of New York, 33 Liberty Street, New York, NY 10045, USAe-mail: Tanju.Yorulmazer@ny.frb.org

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1 Introduction

The financial turmoil that started in the summer of 2007 once again showed that crisesand bank runs are an important feature of our financial landscape.1 In September2007, Northern Rock experienced an old-fashioned bank run: Depositors formedlong queues in front of its branches to withdraw their money. This marked the firstbank run in the United Kingdom since the collapse of City of Glasgow Bank in 1878.Eventually, the run was contained by the government’s announcement that it wouldguarantee all deposits in Northern Rock.

Spillover of difficulties from one bank to the rest of the system is a prime concernfor authorities and is the main rationale for the regulation of the financial system.Losses and other difficulties can spill over to the rest of the system through variouschannels, such as direct exposures via interbank linkages (Allen and Gale 2000);information spillover, where difficulties of one bank can be interpreted as a badsignal for the soundness of other banks (Chen 1999); and illiquidity and asset prices(Diamond and Rajan 2001; Gorton and Huang 2004; Cifuentes et al. 2005).

This paper uses an event-study methodology to analyze the Northern Rock epi-sode and detect spillover effects on the rest of the U.K. banking system.2 We usestock price reactions to investigate the presence of spillover. Event studies in theliterature usually test spillover by comparing the “normal” return of a stock, aspredicted by a standard market equilibrium model such as the CAPM, estimatedusing historical data, with the actual returns on the day of the event or during awindow around the event date. Significant abnormal returns for other banks areregarded as evidence of spillover effects.

This paper shows that, during the Northern Rock episode, both the bank run andthe bailout announcement had spillover effects on the rest of the banking system,as measured by significant abnormal returns on the stock prices of banks. It alsoshows that the spillover effects were a rational response by investors to market newsand can be explained by the characteristics of affected banks: in particular, banksthat rely on wholesale markets for funding were affected severely. This finding isconsistent with developments in the financial markets prior to the run on NorthernRock, where liquidity dried up in debt and interbank markets, leading to record-highlevels of LIBOR (see Fig. 1). Hence, the spillover is associated with the liability sideof bank balance sheets rather than the asset side.

1Lindgren et al. (1996) show that, during the period 1980–96, of the 181 IMF member countries,133 experienced significant banking problems. Such problems have affected developed as well asdeveloping and transitional countries. Also see Dell’Ariccia et al. (2008) for an analysis of the realeffects of banking crises.2See MacKinlay (1997) and Chapter 4 in Campbell et al. (1997) for a detailed discussion of eventstudies in economics and finance.

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Fig. 1 Three-month libor in British pounds. Source: British Bankers Association

This paper is related to the literature on bank runs (Bryant 1980; Diamondand Dybvig 1983; Allen and Gale 1998; Calomiris and Kahn 1991; Chari andJagannathan 1988 and others) and their origins (Gorton 1988; Calomiris and Gorton1991) as well as runs in wholesale funding markets (Huang and Ratnovski 2008,2009). It is also related to event studies in the empirical banking literature thatanalyze spillover by testing whether bad news—such as a bank failure, the announce-ment of an unexpected increase in loan-loss reserves, bank seasoned stock issueannouncements, etc.—adversely affects other banks.3 These studies use a varietyof indicators such as intertemporal correlation of bank failures (Hasan and Dwyer1994; Schoenmaker 1996), bank debt risk premiums (Carron 1982; Saunders 1987;Cooperman et al. 1992; Jayanti and Whyte 1996; Morgan and Stiroh 2001), depositflows (Saunders 1987; Saunders and Wilson 1996; Schumacher 2000), survival times(Calomiris and Mason 1997, 2003), and stock price reactions (Aharony and Swary1983; Swary 1986; Slovin et al. 1992, 1999; Lang and Stulz 1992).

Section 2 provides a discussion of the Northern Rock episode. Section 3 discussesthe two events that are studied here, and the event-study methodology employed,prior to analyzing the abnormal returns and their relation to bank characteristics.Section 4 concludes.

3See De Bandt and Hartmann (2002) for an excellent survey of theoretical and empirical models ofsystemic risk and the references therein for further discussion.

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2 A summary of the Northern Rock crisis

Box 1 presents a timeline of the events during the Northern Rock episode.4

Box 1: Timeline for the Northern Rock crisis

25 July: Northern Rock issues trading results saying that the outlook is “very positive”. But, it notes that sharp increases in borrowing rates in money markets and changes in interest rates and credit risk environments will influence annual profits.

9 August: BNP Paribas’ decision to suspend three investment funds with exposure to subprime mortgage increases concerns in financial markets. ECB injects 94 billion into the European banking system.

13 August: Northern Rock informs FSA about its funding difficulties.

14 August: Bank of England has been alerted about the problems of Northern Rock.

4 September: Problems in money markets escalate and LIBOR rises to its highest level in nine years.

12 September: Bank of England says it would be prepared to provide emergency loans to any bank that ran into short-term difficulties but appears to rule out following the lead of the Federal Reserve and the ECB in injecting huge sums of liquidity.

13 September: At 20:30, BBC reveals that Northern Rock has asked for and been granted emergency support from the Bank of England.

14 September: The Bank of England, the Treasury and the FSA announced that the standby facility will enable Northern Rock to fund its operations during the period of turbulence in financial markets. Queues form outside Northern Rock branches.

17 September: After the stock market closes, the government announced it would guarantee all existing deposits in Northern Rock during the period of turbulence in financial markets.

19 September: Around noon, Bank of England announced an injection of liquidity into money markets and an extension of collateral to include mortgage debt.

20 September: The government guarantee has been extended to cover existing (and renewed) unsecured wholesale funding.

9 October: The scope of the guarantee was extended to cover new retail deposits such as those initially made after 19 September.

C

Since its conversion from a building society—a residential mortgage lender ownedby its savers and borrowers—to a stock-form U.K. bank in 1997, Northern Rockgrew remarkably to become Britain’s fifth biggest mortgage provider. NorthernRock’s success depended crucially on a particular business model that relied heavilyon securitization and funding from wholesale markets, rather than the traditionalbanking model of funding from retail deposits and holding the loans on the balancesheet until maturity.5 Even though retail deposits can be more costly, many banks still

4The timeline and the discussion here rely on the description of the Northern Rock episode inthe October 2007 Financial Stability Report of the Bank of England (2007); the articles “Downthe Drain” and “Lessons of the Fall” in the September 6, 2007 and October 18, 2007 issues ofThe Economist, respectively; and the BBC website: http://news.bbc.co.uk/2/hi/business/7007076.stm.5Northern Rock had only 76 branches in 2007 and retail deposits accounted for only 27 percent ofits liabilities, whereas wholesale funding accounted for 68 percent of its liabilities, according to itsinterim results in June 2007. In January and May 2007, Northern Rock raised £10.7 billion throughsecuritization, which made it the top securitizer among British banks.

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prefer them because they are a more stable source of funding, compared to wholesalefunding.6

The business model of Northern Rock made it vulnerable to adverse develop-ments in wholesale markets. In the summer of 2007, the ongoing increase inarrears on U.S. subprime mortgages led to a sharp increase in credit spreads onU.S. subprime securities. Information problems associated with complex financialstructures led to uncertainty about the nature and the source of losses and, fromJuly on, spreads on asset-backed securities rose in world markets. This led to adrying up of liquidity in short-term debt markets such as the asset-backed commercialpaper (ABCP) market, on which conduits and structured investment vehicles (SIV)rely. Conduits and SIVs were mainly set up by banks as off-balance-sheet entitiesthat allow banks to extend their lending without the pressure of regulatory capitalrequirements, and most conduits and SIVs had back-up liquidity facilities with banks.When the ABCP market ceased to provide the needed liquidity, conduits had nochoice but to tap their bank lines of credit. This resulted in many of the risks thatwere thought to be off banks’ balance sheets rushing back to those balance sheets,creating an enormous strain on bank liquidity. Uncertainty about liquidity needs ledbanks to hoard liquidity rather than lend it in markets, which resulted in a dryingup of liquidity in wholesale markets and the LIBOR reaching record-high levels(see Fig. 1).

The developments in financial markets adversely affected Northern Rock, whichrelied on securitization and wholesale markets for funding. On August 13, 2007,Northern Rock told the Financial Services Authority about its difficulties. Thisinformation had also been shared with the Bank of England and the Treasury.7

By mid-September, the longer-term funding markets were closed to Northern Rock.While the possibility of the Bank of England acting as a lender of last resort had beendiscussed among the authorities, the option of selling Northern Rock to another bankhad been tried first. Although Lloyds TSB emerged as a serious contender, the dealdid not go through because Lloyds’ demand for a loan from the Bank of Englandhad been rejected by the tripartite authorities on the grounds that it would not beappropriate to help finance a bid by one bank for another.8 On September 13, theauthorities agreed that the Bank of England should provide emergency assistanceto Northern Rock. On the same day, on its evening news, the BBC revealed thatNorthern Rock had asked for and been granted emergency support from the Bankof England. The government put out a public statement on Friday, September 14,confirming that the Bank of England would be ready to act as a lender of last resort.

6This can arise due to the costs associated with changing banks that unsophisticated depositors incur,such as switching and searching costs. For example, data collected on current account switchingbehavior from the Financial Research Survey of the National Opinion Poll for the UK imply thata representative current account holder would only change banks every 91 years (Gondat-Larraldeand Nier 2006).7According to the tripartite structure, the Bank of England, the Financial Services Authority, andthe Treasury are mandated to deal with financial crises.8Acharya and Yorulmazer (2008) analyze various policy options to resolve bank failures such asliquidation, bailouts, and sale of a failed bank to a healthy bank, with and without governmentassistance. They show that, from a social welfare point of view, the sale of a failed bank to a healthybank with government assistance can be preferable to bailing out the failed bank.

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These developments confirmed the extent of the bank’s difficulties and resultedin a depositor run on Northern Rock. On the evening of Monday, September 17,the government announced that it would guarantee all of Northern Rock’s existingdeposits during the current instability in the financial markets. On September 19, theBank of England announced that it would inject £10 billion into the money marketsto bring down the cost of borrowing in the interbank market. Furthermore, the assetsthat banks are allowed to use as collateral were extended to include mortgage debt.The government guarantee for Northern Rock deposits was extended on September20 to cover existing (and renewed) unsecured wholesale funding.9

3 Model and results

This section discusses the two events analyzed, the event-study methodologyemployed, and the abnormal returns and their relation to bank characteristics.

3.1 Data and events

The ten largest U.K.-owned banks we focus on, which accounted for around 90percent of U.K.-owned banks’ assets, are: Abbey National, Alliance & Leicester(A&L), Barclays, Bradford & Bingley (B&B), HBOS, HSBC, Lloyds TSB, NorthernRock (NR), Royal Bank of Scotland (RBS), and Standard Chartered (SC). Stockmarket data for these ten banks and the FTSE All-Share index, which are publiclyavailable, are used. This analysis concentrates on the following two events:

(1) On September 13, 2007, at 20:30, the BBC revealed that Northern Rock hadasked for and been granted emergency financial support from the Bank ofEngland. On September 14, the authorities announced a standby facility thatwould enable Northern Rock to fund its operations during the current periodof turbulence in financial markets. On the same day, queues started to formoutside Northern Rock branches. To analyze the impact of the bank run onother banks, this study uses stock market returns on Friday, September 14 andMonday, September 17.

(2) On September 17, at around 16:30 in the afternoon, the governmentannounced it would guarantee all existing deposits in Northern Rock. To ana-lyze the impact of the bailout, this study uses stock market returns on Tuesday,September 18.10

9An announcement on September 21 confirmed and clarified the guarantees announced onSeptember 20.10An important issue is whether there were other events, not directly related to the run on NorthernRock that might have confounded the effects. For example, Wall and Petersen (1990) extend Swary’s(1986) analysis of Continental Illinois and show that events related to U.S. banks’ holdings of claimson Latin America were confounding factors that needed to be included in the analysis. One such issuearises in our analysis for the effects of the bailout announcement. On September 19, at around noon,the Bank of England announced an injection of liquidity into the money markets and the extensionof collateral to include mortgage debt, in an attempt to ease the liquidity crunch in wholesalemarkets. Hence, the returns on September 19 can be jointly affected by the bailout announcementon September 17 and the Bank of England’s announcement on September 19. To focus solely on theeffect of the bailout announcement, we prefer to concentrate on returns for September 18.

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Table 1 Raw returns (%)

14 Sep 17 Sep 18 Sep

Abbey −0.7 −1.0 3.1A&L −6.9 −31.3 32.2Barclays −3.1 −2.5 4.5B&B −7.7 −15.4 6.0HBOS −3.6 −5.5 3.1HSBC 0.2 −0.7 1.6Lloyds −2.7 −1.3 1.3NR −31.5 −35.4 8.2RBS −0.7 −4.3 3.4SC −1.4 −1.7 4.2FTSE −1.3 −1.7 1.4

Table 1 shows the raw stock returns for the above dates.

3.2 Measurement of abnormal returns

We use the standard market model to estimate the daily expected firm returns asfollows:

Rit = αi + βi Rmt + εit, (1)

where Rit and Rmt are the rates of return of bank i and the FTSE All-Share indexat date t, respectively. The error term εit is assumed to have zero mean, to beindependent of Rmt, and to be uncorrellated across firms.

An OLS regression, with the Newey-West HAC adjustment to control for thepresence of autocorrelation and heteroskedasticity, is run to estimate α̂i and ̂βi.

Abnormal returns, ARit, are calculated as the difference between the realized returnand the estimated return from the OLS regression:

ARit = Rit − α̂i − ̂βi Rmt. (2)

The parameters of the market model are estimated using a T = 250 trading day(1 year) window, beginning 270 days before the event date (September 14, 2007).

To determine whether abnormal returns are significantly different from zero, wecalculate standardized abnormal returns as:

SARit = ARit

σ̂it∼ t(T − 2), (3)

where σ̂it is the sample standard deviation of the abnormal return.To determine the abnormal returns for a period of t1 � t � t2, we use cumulative

abnormal returns defined as

CARi(t1, t2) =t2

∑

t=t1

ARit, (4)

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Table 2 Abnormal returns (%)

14 Sep 17 Sep 14–17 Sep 18 Sep

Abbey 0.6 0.7 1.3 1.6∗(0.536) (0.616) (0.815) (1.386)

A&L −5.5∗ −29.3∗∗∗ −34.8∗∗∗ 30.7∗∗∗(−1.622) (−8.673) (−7.234) (9.114)

Barclays −1.1 −0.2 −1.3 2.6∗∗(−0.809) (−0.117) (−0.651) (1.911)

B&B −5.8∗∗∗ −13.0∗∗∗ −18.8∗∗∗ 4.3∗∗(−2.541) (−5.760) (−5.833) (1.894)

HBOS −2.1∗ −3.6∗∗∗ −5.7∗∗∗ 1.7(−1.512) (−2.553) (−2.856) (1.202)

HSBC 0.6 0.3 0.9 0.8(0.750) (0.321) (0.753) (0.970)

Lloyds −1.7∗ 0.1 −1.6 0.0(−1.553) (0.116) (−1.010) (−0.036)

NR −28.9∗∗∗ −32.7∗∗∗ −61.6∗∗∗ 6.5(−5.293) (−5.984) (−7.926) (1.199)

RBS 0.6 −2.6∗∗ −2.0 2.0∗∗(0.502) (−2.124) (−1.139) (1.669)

SC 0.7 0.8 1.5 2.1(0.457) (0.522) (0.689) (1.374)

t-statistics are in parenthesis∗Significant at the 10% level ∗∗Significant at the 5% level ∗∗∗Significant at the 1% level

where the standard deviation of the cumulative abnormal returns is given as

σ̂i(t1, t2) =(

t2∑

t=t1σ̂it

)1/2

. Hence, we have the standardized cumulative abnormal

returns given as:

SCARit = CARi(t1, t2)σ̂i(t1, t2)

∼ t(T − 2). (5)

3.3 Results on abnormal returns

Table 2 reports daily and cumulative abnormal returns.First, we analyze how the run on Northern Rock on September 14 and 17 affected

other banks. The results show that Bradford & Bingley (−5.8 percent) and NorthernRock (−28.9 percent) experienced strong negative abnormal returns (significant atthe 1 percent level) on September 14. On the same day, Alliance & Leicester, HBOSand Lloyds TSB also experienced negative abnormal returns (significant at the10 percent level). On September 17, the difficulties of Northern Rock had a strongspillover effect on the rest of the banking system, as confirmed by the negativeabnormal returns for Alliance & Leicester (−29.3 percent), Bradford & Bingley(−13.0 percent), HBOS (−3.6 percent) (all significant at the 1 percent level), andRBS (−2.6 percent, significant at the 5 percent level). Moreover, the results showsignificant negative abnormal returns for Alliance & Leicester (−34.8 percent),Bradford & Bingley (−18.8 percent) and HBOS (−5.7 percent) during the eventwindow of September 14–17. Overall, we find that, during the event window of

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September 14–17, the difficulties of Northern Rock had negative spillover effectson a significant portion of the U.K. banking system.11

Second, we analyze the effect of the bailout announcement on September 17.12

The results show significant positive abnormal returns for Alliance & Leicester(30.7 percent), Barclays (2.6 percent), Bradford & Bingley (4.3 percent), RBS(2.0 percent), and to some extent Abbey (1.6 percent, significant at the 10 percentlevel) on September 18.13 The announcement had a positive effect on the share priceof Northern Rock on September 18, but not a significant one. Also, Northern Rockexperienced significant negative abnormal returns (−19.5 percent) on September 19.Hence, the bailout announcement prevented the spillover effects, but at that pointthe market seemingly was convinced about the difficulties of Northern Rock, andthe announcement could not prevent further negative abnormal returns and theinstitution’s eventual failure.

3.4 Abnormal returns and bank characteristics

An important question is whether the effects were the result of a panic or whetherthey were a rational response by investors to market news and attributable to thecharacteristics of affected banks. To analyze whether the spillover from NorthernRock to other banks (and the effect of the bailout announcement) was the result ofsimilarities between Northern Rock and the affected banks, we looked at the relationbetween abnormal returns and various bank balance sheet features such as customerdeposits (deposit), wholesale funding (wholesale),14 shareholders’ equity (capital) onthe liability side, and total assets (size) and mortgage loans (mortgage) on the assetside. Table 3 shows balance sheet data for the ten banks.

11The total assets of the ten banks in the study are approximately £4441 billion, which is around317 percent of the U.K. GDP (£1401 billion) in 2007. The total assets of Alliance & Leicester,Bradford & Bingley and HBOS—the three banks on which we found significant spillover effects—are approximately £710 billion, which is around 51 percent of the U.K. GDP in 2007. Furthermore,spillover effects during September 14–17 wiped out 59, 32 and 14 percent of Tier 1 capital of Alliance& Leicester, Bradford & Bingley, and HBOS, respectively.12O’Hara and Shaw (1990) study the effect of the announcement of the too-big-to-fail guarantee bythe U.S. Office of the Comptroller of the Currency, and find a positive value effect for the largestbanks.13On September 19, at around noon, the Bank of England announced an injection of liquidity intothe money markets and the extension of collateral to include mortgage debt. As a result, we choseto focus only on September 18 to analyze the effect of the bailout announcement. However, onSeptember 19, Bradford & Bingley experienced a significant positive abnormal return (7.5 percent,significant at the 1 percent level). Hence, the cumulative abnormal return for Bradford & Bingley is11.8 percent for September 18–19, which would only make the results of the paper stronger. While thefailure of Northern Rock is clearly bad news for other banks that pursue the same business model, theannouncement on September 18 contains some uncertainty about the government’s future responseto difficulties in other banks. Even though the announcement on September 18 may imply that similarguarantees might be provided for other banks in the future, this potential guarantee is not explicit.Hence, the uncertainty about future government interventions still remains, which mitigates theeffect of the government intervention. However, one can interpret the announcement on September19 as indicative of the authorities’ willingness to intervene, which would have reduced the uncertaintyabout government interventions. Hence, the effects we find for the government intervention couldbe expected to serve as a lower bound for the effect of the bailout announcement.14Consistent with the October 2007 Financial Stability Report of the Bank of England, we definewholesale funding as the sum of debt securities in issue and the deposits from other banks.

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Table 3 Balance sheet data

Mortgage Deposits Debt Interbank Wholesale Equity

Abbey 53 34 19 2 21 1.7A&L 55 45 39 13 52 3.0Barclays 6 26 11 8 19 2.5B&B 62 51 41 3 44 3.2HBOS 37 38 30 6 36 3.6HSBC 4 48 11 6 17 6.2Lloyds 28 42 15 12 27 3.4NR 77 27 65 3 68 3.1RBS 8 43 10 14 24 4.8SC 17 58 10 10 20 7.1Average 34.7 41.2 25.1 7.7 32.8 3.86

Deposits represent customer deposits, Debt represents debt securities in issue, Interbank representsdeposits from other banks, Equity represents shareholders’ equity, all as a percentage of totalliabilities. Wholesale is the sum of Debt and Interbank, and represents funding from wholesalemarkets, as a percentage of total liabilities. Mortgage represents mortgage loans as a percentageof total assets. Data for mortgage loans is for the 2006 year end and is collected from the website ofCouncil of Mortgage Lenders (http://www.cml.org.uk/cml/statistics), except for Standard Chartered,which is from the interim results for 30 June, 2007. All other data is from interim results for 30 June,2007, except for Bradford & Bingley, which is from the annual report for 31 December, 2006

Northern Rock had a particular business model. On the asset side, mortgage loansconstituted 77 percent of the institution’s assets. On the liability side, Northern Rockhad a small depositor base (27 percent of liabilities came from customer deposits),whereas most of its liabilities came from wholesale funding (68 percent of liabilitiesfrom interbank deposits and debt securities in issue). Hence, if the spillover fromthe run on Northern Rock to other banks was a rational response by investors,one would expect mortgages and wholesale funding to negatively affect abnormalreturns, whereas customer deposits would positively affect abnormal returns. Onerole of capital is to act as a cushion for negative shocks. Thus, we would expectshareholders’ equity to have a positive effect on abnormal returns. One can thinkof big banks having easy access to markets and possibly enjoying implicit too-big-to-fail guarantees such that size would have a positive effect on abnormal returns. Also,banks that were affected negatively by the run on Northern Rock could have beenexpected to experience positive effects from the bailout announcement. In otherwords, one would expect the balance sheet characteristics to have opposite effectson abnormal returns as a result of the run on Northern Rock (September 14 and 17)and the bailout announcement (September 18).

To analyze the effect of bank characteristics on abnormal returns, we run a seriesof OLS regressions, in which Northern Rock is excluded from the sample.15 In theseregressions, the dependent variable is the abnormal return during the period of inter-est and the explanatory variables are the bank balance sheet characteristics discussedabove. Four sets of OLS regressions are run: one for each date of September 14, 17,and 18, and one for the period September 14–17. The regression results are presentedin Tables 4 and 5.

15Inclusion of Northern Rock makes the results stronger.

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Table 4 Abnormal returns and bank characteristics (simple regressions)

Sep 14Constant 0.0408∗∗∗ −0.0024 0.0089 −0.0341∗∗ −0.0399

(4.49) (−0.05) (0.80) (−2.68) (−1.86)Wholesale −0.1938∗∗∗

(−6.65)Deposit −0.0300

(−0.29)Mortgage −0.0802∗∗

(−2.66)Size 0.0039

(1.85)Capital 0.6251

(1.25)R2 0.8634 0.0121 0.5020 0.3272 0.1822Adjusted R2 0.8439 −0.1290 0.4309 0.2311 0.0653Akaike −55.29 −37.48 −43.65 −40.94 −39.18Schwarz −54.89 −37.09 −43.26 −40.55 −38.79

Sep 17Constant 0.1459∗∗∗ 0.0183 0.0119 −0.1416∗∗ −0.1327

(3.66) (0.11) (0.24) (−2.75) (−1.47)Wholesale −0.7500∗∗∗

(−5.85)Deposit −0.2083

(−0.52)Mortgage −0.2755∗

(−2.07)Size 0.0147

(1.70)Capital 1.5694

(0.75)R2 0.8304 0.0374 0.3795 0.2934 0.0737Adjusted R2 0.8061 −0.1001 0.2908 0.1924 −0.0586Akaike −28.63 −13.01 −16.96 −15.79 −13.36Schwarz −28.24 −12.62 −16.57 −15.40 −12.96

Sep 14–17Constant 0.2019∗∗∗ 0.0323 0.0377 −0.1548∗∗ −0.1528

(5.00) (0.15) (0.66) (−2.52) (−1.43)Wholesale −0.9317∗∗∗

(−7.19)Deposit −0.2326

(−0.48)Mortgage −0.3496∗

(−2.25)Size 0.0182

(1.77)Capital 2.1690

(0.87)R2 0.8808 0.0321 0.4202 0.3082 0.0968Adjusted R2 0.8638 −0.1062 0.3374 0.2094 −0.0322Akaike −28.43 −9.58 −14.20 −12.61 −10.21Schwarz −28.04 −9.19 −13.80 −12.21 −9.81

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Table 4 (continued)

Sep 18Constant −0.1026 0.0208 0.0074 0.1221∗ 0.1143

(−1.66) (0.12) (0.14) (2.34) (1.31)Wholesale 0.5836∗∗

(2.93)Deposit 0.1057

(0.27)Mortgage 0.1955

(1.36)Size −0.0116

(−1.33)Capital −1.2252

(−0.60)R2 0.5517 0.0106 0.2096 0.2019 0.0493Adjusted R2 0.4876 −0.1308 0.0967 0.0879 −0.0865Akaike −20.72 −13.60 −15.62 −15.53 −13.96Schwarz −20.33 −13.20 −15.22 −15.14 −13.56

∗Significant at the 10% level ∗∗Significant at the 5% level ∗∗∗Significant at the 1% levelThe dependent variables in the regressions are the abnormal returns

For each set of regressions, the tables report the results for three different modelspecifications. Table 4 presents the simple regression results, and Table 5 presentsthe results from multiple regressions. In particular, in Table 5, model (i) presents themodel with the most comprehensive set of explanatory variables, whereas model (ii)presents the specification selected by the Akaike and Schwarz information criteria.

The simple regression results in Table 4 show that wholesale is the only ex-planatory variable that is significant in explaining abnormal returns for all fourperiods of interest in this study.16 The results are very strong as wholesale issignificant at the 1 percent level in all regressions, except for September 18, where thep-value is 0.02. From the simple regression results, we also observe that mortgage hassome explanatory power for abnormal returns on September 14, September 17 andSeptember 14–17 (significant at the 5, 10, and 10 percent levels, respectively), whereasit is not significant at the 10 percent level for September 18.17 These results areconsistent with the main features of Northern Rock’s business model: On the assetside, mortgage loans represented a majority of Northern Rock’s assets, and the bankhad a small depositor base with most of its liabilities coming from wholesale funding.

The results from the multiple regressions in Table 5 confirm the importance ofthe explanatory variable wholesale in explaining the abnormal returns during theNorthern Rock episode. Model (i) is the model with all five explanatory variables.The results show that wholesale is the only variable that is significant in explainingthe abnormal returns.18 Furthermore, in all four periods analyzed, the model that has

16See Fig. 2 for an illustration of the relation between abnormal returns and wholesale funding. Notethat Northern Rock is excluded from Fig. 2.17The other three explanatory variables, deposit, size, and capital, mostly have the expected signs,but they are highly insignificant.18Wholesale is significant at the 5 percent level for September 14–17, significant at the 10 percentlevel for September 14 and September 17, whereas the p-value is 0.12 for September 18.

J Financ Serv Res (2010) 37:83–98 95

Tab

le5

Abn

orm

alre

turn

san

dba

nkch

arac

teri

stic

s(m

ulti

ple

regr

essi

ons)

Sep

14Se

p17

Sep

14–1

7Se

p18

(i)

(ii)

(i)

(ii)

(i)

(ii)

(i)

(ii)

Con

stan

t0.

0608

0.04

08∗∗

∗0.

0456

0.14

59∗∗

∗0.

1395

0.20

19∗∗

∗0.

3314

−0.1

026

(0.9

6)(4

.49)

(0.1

5)(3

.66)

(0.4

4)(5

.00)

(0.7

6)(−

1.66

)W

hole

sale

−0.1

812∗

−0.1

938∗

∗∗−0

.901

0∗−0

.750

0∗∗∗

−1.0

666∗

∗−0

.931

7∗∗∗

0.92

470.

5836

∗∗(−

2.87

)(−

6.65

)(−

2.89

)(−

5.85

)(−

3.41

)(−

7.19

)(2

.14)

(2.9

3)D

epos

it−.

2052

0.06

71−0

.177

2−1

.042

1(−

0.93

)(0

.06)

(−0.

16)

(−0.

69)

Mor

tgag

e0.

0476

0.22

130.

2595

−0.3

710

(0.6

1)(0

.57)

(0.6

7)(−

0.69

)Si

ze−0

.001

20.

0081

0.00

57−0

.027

7(−

0.29

)(0

.42)

(0.2

9)(−

1.03

)C

apit

al1.

4048

0.24

841.

8225

4.01

62(1

.10)

(0.0

4)(0

.29)

(0.4

6)R

20.

9063

0.86

340.

8537

0.83

040.

8987

0.88

080.

6917

0.55

17A

djus

ted

R2

0.75

010.

8439

0.60

980.

8061

0.72

990.

8638

0.17

800.

4876

Aka

ike

−50.

68−5

5.29

−21.

96−2

8.63

−21.

90−2

8.43

−16.

09−2

0.72

Schw

arz

−49.

50−5

4.89

−20.

78−2

8.24

−20.

72−2

8.04

−14.

91−2

0.33

∗ Sig

nific

anta

tthe

10%

leve

l∗∗ S

igni

fican

tatt

he5%

leve

l∗∗∗

Sign

ifica

ntat

the

1%le

vel

The

depe

nden

tvar

iabl

esin

the

regr

essi

ons

are

the

abno

rmal

retu

rns

96 J Financ Serv Res (2010) 37:83–98

-40.0%

-35.0%

-30.0%

-25.0%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55

Wholesale funding

Per

cen

tag

e ab

no

rmal

ret

urn

s

Fig. 2 Abnormal returns (September 14–17) and wholesale funding

been selected using the Akaike and Schwarz information criteria is the model withwholesale as the unique explanatory variable.

These results show unambiguously that reliance on wholesale markets for fundingis the most important bank characteristic explaining the spillover effects duringthe Northern Rock episode.19 Furthermore, the results show that the effects werea rational response by investors and a manifestation of the drying up of liquidityand the resulting funding difficulties in the wholesale markets. The R2 values showthat bank balance sheet characteristics, in many cases, were able to explain around90 percent of the variation in abnormal returns, which confirms that the spillovereffects were a rational response by investors rather than pure panic effects. While theproportion of mortgage loans has some explanatory power, the spillover is associatedmainly with the funding sources of banks, suggesting that the liability side andfunding characteristics of banks can also be a leading source of bank failures andspillover effects.

Furthermore, as a robustness check, all the regressions were run without includingAlliance & Leicester.20 Alliance & Leicester is the bank that most closely resemblesNorthern Rock in terms of its heavy reliance on wholesale markets and its involve-ment in mortgage origination. But even without including Alliance & Leicester, theresults hold. This shows that the results are robust, and are not driven by idiosyncraticfactors. Rather, they show systematically that the market participants’ response can

19This finding is consistent with Shin (2009), who argues that Northern Rock’s reliance on institu-tional investors for short-term funding made it extremely vulnerable to the drying up of liquidity incredit markets.20Results are available from the authors upon request.

J Financ Serv Res (2010) 37:83–98 97

be explained by the business model adopted by the affected banks—in particular,their heavy reliance on wholesale funding.21

4 Conclusion

In 2007, world financial markets experienced extraordinary events. An importantepisode was the depositor run on Northern Rock and the U.K. government’sannouncement that it would guarantee all deposits to contain the run. This papershows that both the run on Northern Rock and the subsequent bailout announce-ment had significant effects on the rest of the banking system. Furthermore, theeffects were a rational response by investors to market news and reflected the char-acteristics of affected banks. In particular, the spillover effects can be explained bybanks’ funding characteristics given that banks that rely on funding from wholesalemarkets were affected severely, a result consistent with the liquidity crunch in debtand interbank markets prior to the run on Northern Rock. Hence, this paper providesan interesting contribution to the literature on whether spillover effects are the resultof a panic or a rational response by investors to available information. Furthermore,the results contribute to the discussion on the origins of bank failures by providingevidence that the liability side and funding characteristics of banks can be a leadingsource of bank failures and spillover effects.

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