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Credit market conditions and the impact of

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Keywords:Capital structureCredit ratingsBond market accessFinancial crisis

played by credit ratings in explaining corporate capital structure choice during a

International Review of Financial Analysis 25 (2012) 2863

Contents lists available at SciVerse ScienceDirect

International Review oThe seminal work of Modigliani and Miller (1958) assumes that inthe absence of market imperfections supply of capital is perfectlyelastic and capital structure decision of a rm depends entirely onits demand-side considerations (Lemmon & Roberts, 2007). The keyassumption is that rms can borrow as much as they wish at thesame cost of capital and a rm's capital structure is purely a function

real world market frictions, such as information asymmetry, implythat the supply of capital is inelastic and rms can be rationed bytheir lenders in terms of both pricing and debt availability. Most ofthe previous empirical literature concentrates on the demand-sidedeterminants of capital structure while paying little attention to thesupply of capital (see Frank & Goyal, 2007; Rajan & Zingales, 1995).Recently researchers have recognised the importance of the supply-side factors as a potential driver of the capital structure decision. Forexample, Faulkender and Petersen (2006) argue that in the presence

We are very grateful to Standard and Poor's and Fitch Ratings for providing us withcredit rating data. Thanks also to Ian Byrne, Bridget Gandy, John Grout, John Redwood

and Ian Stewart for useful comments and suggestions. Wat the University of Santiago de Compostella, UniverSchool, Standard and Poor's, Joint Seminar at the Deparand Skills and HM Treasury, GdRE Symposium onMoneying University, Money Macro and Finance Research GroConference at the University of Birmingham, Europeathe Economy at the University of Southampton, and Mcomments and suggestions. The usual disclaimer applie Corresponding author.

E-mail address: [email protected] (A. Ko

1057-5219/$ see front matter 2012 Elsevier Inc. Allhttp://dx.doi.org/10.1016/j.irfa.2012.09.003of rm's characteristics, such as, size, protability, asset tangibility,and growth opportunities, that inuence its demand for debt. In the1. Introductionare potentially as important as demand-side forces in determining corporate leverage. This is based on the pre-mise that debt markets are segmented and that those rms that have access to the private debt markets do notnecessarily have access to the public debt markets. The question of access to debt nance has become a majorissue for public policy makers in several developed economies during the 20072009 nancial crisis. The UKeconomy has been subjected to a period of severe tightening of creditmarket conditions resulting in a signicantreduction in the availability of bank credit to the corporate sector. An important question iswhether the contrac-tion in the ow of bank credit to rms has affected rms equally or whether rms with access to alternativesources of debt nance have been able to mitigate the effect of adverse changes to the cost and availability ofbank credit. To investigate this issue, this study employs data over a 20 year period that includes two recessionsand three noticeable periods of credit market tightening. Despite the fact that a severe recession has accompa-nied the 20072009 nancial crisis we argue that the underlying forces driving the weakness in bank lendingto the corporate sector are mainly supply side rather than demand side factors. In this study we use the posses-sion of a credit rating as an indicator of access to the public debt markets. Our results provide support for thenotion that having a rating is associatedwith higher leverage ratios, even after controlling for demand-side lever-age determinants andmacroeconomic conditions. More importantly, the study nds that the impact on leverageof having a credit rating varies over our sample period with the effect being greatest in those years when creditmarket conditions were tightest. The results are robust to the use of an alternative measure for public debtmarket access, different proxies for measuring the tightness of the credit markets, alternative econometricspecications and various sub-periods within our overall sample period.

2012 Elsevier Inc. All rights reserved.JEL classication:

period characterised by a major adverse loan supply shock. Recent literature has argued that supply-side factorsAvailable online 2 October 2012 This study examines the rolecorporate leverage

Amrit Judge, Anna Korzhenitskaya Economics and Statistics Department, Middlesex University Business School, The Burroughs

a b s t r a c ta r t i c l e i n f oe thank seminar participantssity of Porto, ISCTE Businesstment for Business, Innovation, Banking and Finance at Read-up 43rd Annual Internationaln Conference on Banking andiddlesex University for helpfuls.

rzhenitskaya).

rights reserved.access to the public debt market on

ndon, London NW4 4BT, UK

f Financial Analysisof information asymmetry rms that can access the public debt capitalmarkets face less nancial constraints and are able to borrow more.Conversely, they suggest that rms that desire to raise funds but areconstrained by lack of access to capital markets might be signicantlyunder-levered.

The importance of supply side factors has come to the fore since theonset of the current nancial crisis in the latter half of 2007. During thelast three years, banks have attempted to repair their balance sheets

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29A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863and consequently have signicantly cut back on their lending commit-ments to the corporate sector.1 The Bank of England's (BOE) creditconditions surveys have reported that between the fourth quarter of2007 through to the end of 2008 nancial market turbulence reducedsignicantly UK banks' capacity to extend credit to the corporatesector.2 The credit conditions surveys report that during this periodthere was a signicant tightening of price and non-price terms onloans to the corporate sector. Banks widened their spreads and raisedthe fees and commissions they charged on loans to rms. In additionbanks imposed stricter covenants, raised collateral requirements andreducedmaximum credit lines. This has made raising bank loan nanceextremely difcult for creditworthy rms since the fourth quarter of2007 and consequently has limited the availability of debt-basednance for rms that are heavily reliant on banks for their debt capital.Post the nancial crisis the future level of bank lending could be subjectto greater restrictions as the new Basel capital requirements, whichwillmore than double the core Tier 1 capital ratio from2% to 4.5%, come intoforce. Some have argued that the Basel guidelines do not go far enough.For example, David Miles, an external member of the Bank of Englandmonetary policy committee, has suggested a target capital ratio ofbetween 15 and 20% (Mallaby, 2011). Kernan, Wade, and Watters

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Fig. 1. Real GDP(2010) argue that the forthcoming Basel III requirements will increasethe amount of capital banks need to hold to support their corporatelending operationswhichwill hike lending costs and lead to a reductionin lending capacity within the banking system. They anticipate that thiswill be likely to result in a longer term structural impetus for rising bondissuance over bank loans (Kernan et al., 2010, page 9).

The drying up of the ow of bank credit could have serious conse-quences for the UK economy's ability to pull itself out of recession andtherefore prolonging the economic downturn slowing down economicrecovery. The problem is potentially more acute in the UK becausebanks have traditionally been the main source of capital for the privatesector with 76% of debt being currently provided by banks (Kernanet al., 2010). The situation is however likely to change according toKernan et al. (2010) who point out that since the events of September2008, corporate bond issuance by U.K. businesses with a credit ratinghad increased by 22.1 billion, while U.K. nancial institutions havereduced their net lending (both in sterling and foreign currencies) toU.K. companies by 59.1 billion. Kernan et al. (2010) suggest that thismakes corporate bond issuance the main provider of new debt

1 Balance sheet repairs may also take the form of injection of new equity capital andselling assets.

2 See Bank of England, 2007a,b and 2008a,b,c,d Credit Conditions Survey.nancing on a net basis since the third-quarter of 2008. Bacon, Grout,and O'Donovan (2009) survey chief nancial ofcers and treasurers ofUKrms and nd that the possession of a credit rating and the resultingaccess to public debt markets it offers has become especially importantduring the 20072009 nancial crisis. Recent trends in lending datafrom the Bank of England (2009d) points to rated rms raising capitalmarket debt to pay back bank loans and issuing bonds rather accessingnew bank loan facilities. The BOE suggest that access to the debt capitalmarkets has enabled ratedrms tomitigate the impact of a shortening inthematurity of bank lending available since the onset of the nancial crisis(Bank of England, 2009d). The BOE in its August 2009 Trends in Lendingreport suggested that while companies with bond market access hadturned to arm's length sources of nance, smaller businesses withoutaccess still remained severely nancially constrained. Bacon et al.(2009) report that many rms that did not have a rating during thecrisis were seeking to obtain one.

A credit rating by providing access to the public debt markets canoffer considerable benets to a rm. Not only does it widen the investorbase and improves debt pricing but also provides an opportunity toenter foreign bond markets and gain international visibility, therebyreducing the reliance on local banks. Faulkender and Petersen (2006),

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th 19622010.Mitto and Zhang (2008), Kisgen (2009) nd that companies with a rat-ing have access to broader sources of debt nance, and as a result havehigher leverage ratios compared to unratedrms. There is also evidencethat rated companies suffer less during adverse economic conditions.For example, Chava and Purnanandam (2009) nd that in the US,bank-dependent rms suffered larger valuation losses and greater sub-sequent decline in their capital expenditure during and after the Rus-sian crisis of 1998 as compared to their rated counterparts. Similarly,Campello, Giambona, Graham, and Harvey (2009a) nd that themajor-ity of US rms have been adversely affected by the 2008 credit supplyshock but the impact has been greatest for nancially constrained rms.

Adverse economic conditions and distortions in the supply of capitalcan severely affect rms' leverage and especially those rms that do nothave access to alternative sources of nance, such as the public debtmarkets. The last two decades provide periods when the macroeco-nomic environment was stable and turbulent together with periodsthat experienced signicant movements in credit market conditions.This study investigates the role played by access to public debt marketsover a twenty year period during which there were three episodes ofcredit market tightening with the most recent being the severest.Signicantly, the second of these periods (20002003) of tight creditwas not associated with an economic downturn whereas the rst(19911992) and the third period (20072009) were. Although we

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30 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863demonstrate that the recent weakness in bank lending is largely supplydriven this additional fact helps to further downplay any potentialeffects of credit demand on our results.

During the 20072009 crisis we have witnessed the largest reduc-tion of bank lending to the UK corporate sector in recent economic his-tory. At the peak of the nancial crisis several major banks experiencednancial distress resulting in a severe lack of liquidity in the bankingsystem forcing all banks to change considerably the terms of theirlending to the corporate sector. Commitment fees and interest spreadswent up, while debt maturities went down. The nancial crisis there-fore provides a very unique opportunity to investigate the role of accessto public debtmarkets in determining rms' leverage during a period ofreduced bank loan supply. To the best of our knowledge, this study isthe rst to investigate the impact of access to public bond markets oncorporate leverage during a period characterised by a major tighteningin credit market conditions in a UK context.

The remainder of the paper is organised as follows. Section 2 pre-sents an overview of the literature on credit market conditions andcapital structure. Section 3 presents an analysis of the conditions ofthe UK credit markets between 1998 and 2010. In this section we alsoexamine whether the weakness in bank lending during the nancial-20000

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Fig. 3. Net monthly ow ocrisis reects a reduction in the supply of credit or weaker demand forfunds from rms as their investment opportunities have dried upduring the recession. We present a robust analysis of the underlyingforces driving the reduction in the ow of credit to the corporate sector.Section 4 describes the rating characteristics of our sample. Sections 5and 6 present our empirical analysis and the results from robustnesstests, respectively. Finally, Section 7 concludes.

2. Access to public debt markets, credit market conditions andcapital structure: overview of the empirical literature

Following Modigliani and Miller (1958) theorem three competingtheories emerged that attempt to explain what determines capitalstructure choice (Cole, 2008): the trade-off theory, pecking order theory,andmarket timing theory. Under the trade-off theory of capital structure,a rm chooses its leverage ratio by balancing the costs and benets ofusing debt. The primary gains of debt are the tax-shields, which arisefrom the deductibility of interest on debt on the prot and loss account,whereas, the costs of debt are principally direct and indirect nancialdistress costs (Frydenberg, 2011). Cole (2008) points out that thetrade-off theory is often set up as a competitor theory to the pecking01-N

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31A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863order theory of capital structure (e.g. Frydenberg, 2011; Myers, 1984)Pecking order theory was introduced by Myers (1984) and Myers andMajluf (1984), which states that there is a nancing hierarchy ofretained earnings, debt and then equity. Myers (1984) and Myers andMajluf (1984) argue that due to the information asymmetry betweenmanagers and investors, rmswill use their retained earningwheneveris possible, then issue bonds for external capital, and raise equity only asa last resort. Another theory that has gained prominence in recentcapital structure literature is the market-timing theory. This theory,proposed by Baker and Wurgler (2002), argues that capital structureis the cumulative outcome of past attempts to time the market.3 Thetheory suggests that managers issue equity when they believe it isovervalued (as measured by market-to-book ratio) and repurchaseequity or issue debt when they believe it is undervalued, i.e. managerstime the market and make their nancing decisions according tofavourable conditions in the debt or equity markets (Baker & Wurgler,2002).

Each of these theories identies key factors in determining capitalstructure choice, such asrm size, tangibility, market-to-book and prof-itability, but according to Frank and Goyal (2007) neither of them canfully explain capital structure choice (Frank & Goyal, 2007). Frank andGoyal (2007) argue that currently there is no unied model of leverageavailable that can simultaneously account for all the stylised facts. Theyclaim that different theories apply to rms under different circum-stances. Frydenberg (2011) in his overview of capital structure theories

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Fig. 4. Growth rate of monetary nancial institdeclares that capital structure is a too complex fabric to t into a singlemodel.4 Factors suggested by the capital structure theories and widelyexamined in the previous literature largely represent demand-sidedeterminants of leverage. In the world with information asymmetryand loan supply frictions, rms can nd it difcult to raise the desiredamount of debt and can be signicantly under-levered (Faulkender &Petersen, 2006). This issue becomes especially relevant during theperiods when credit market conditions are tight and the supply of cap-ital becomes an important determinant of capital structure choice.

Recently there has been a move in the empirical literature towardsexamining the link between credit market conditions and rms' capitalstructure decisions. Lemmon and Roberts (2007) explore the relation-ship between the loan supply shock of 1989 and rms' nancing deci-sions. Their ndings underline that even large rms with access topublic debt market are affected by capital supply shocks. Chava andPurnanandam (2009) examine the shock to the US banking systemduring the Russian crisis of 1998 using full sample analysis andmatching sample techniques. They nd that bank-dependent rms lost

3 Baker and Wurgler (2002), p.23.4 Frydenberg (2011), p.25.disproportionally higher market value and suffered larger declines incapital investments and growth rates following the crisis as compared torms with access to the public debt market (Chava & Purnanandam,2009, p.30).

Leary (2009) in a study of the relevance of capital market supplyfrictions for corporate capital structure decisions following the 1966credit crunch in the United States nds that larger rms with accessto public debt market were less affected by contraction in bank loansupply due to their greater ability to substitute toward arm's lengthdebt nancing. Leary (2009) nds that the use of bond debt by rmswith access to public debt markets increased, relative to that of small,bank-dependent rms. As a result the leverage of bank-dependentrms signicantly declined compared to rms with access to publicbond markets. By using rm size as a proxy for debt market access, hends that following the 1966 loan supply contraction, leverage ratiosof small, bank-dependent rms signicantly decreased relative tolarge rms with bond market access. When Leary (2009) expandshis sample period to cover the 35 years from 1965 to 2000, he ndsthe leverage difference between rms with and without public debtmarket access becomes greater in periods of reduced loan supply andtighter credit markets. Voutsinas and Werner (2011) examine how -nancial constraints and uctuations in the supply of credit affect rmcapital structure. They investigate the impact of asset bubble in the1980s and the credit crunch of the late 1990s on corporate capital struc-ture decisions of publicly listed Japanese rms. They nd that both

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s' loans to private non-nancial corporations.eventsthe asset bubble burst of the 1980s and the credit crunch inthe 1990swere followed by severe reductions in leverage (total lever-age was reduced by 0.0239 when the bubble burst). Voutsinas andWerner (2011) conclude that uctuations in the supply of credit andchanges in monetary conditions have a serious impact on rms' capitalstructures. During the Japanese credit crunch all rms experienced asevere reduction in their leverage levels, but especially smaller sizedbank-dependent ones.

The question of access has become amajor issue since the latter halfof 2007, when the banking systems around the world experiencedmajor liquidity problems, resulting in a severe tightening of creditmarket conditions leading to signicant falls in lending to the corporatesector. Ivashina and Scharfstein (2009) indicate that in the US banklending dropped considerably across all loans types during the20072009 crisis. They nd that new bank loans fell by 47% duringthe peak of the nancial crisis (fourth quarter of 2008) relative to thethird quarter. When compared to the peak of the credit boom (secondquarter of 2007) they nd that bank loans dropped by 79% in the fourthquarter of 2008. The terms and conditions of bank lending have alsoworsened. Campello, Giambona, Graham, and Harvey (2009a) reportthat the tightening of US credit markets during the 20072009 nancial

Bougheas, Mizen, and Yalcin (2006) evaluate the inuence of rm-specic characteristics on the response of corporate nance to mone-

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32 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863crisis has manifested itself in the form of an increase of commitmentfees by 14 basis points, mark-ups over LIBOR/Prime rate by 69 basispoints and decline in maturity by 2.6 months from 30 months on aver-age. Empirical evidence suggests that debt market segmentation hasresulted in differential sensitivity to the recent credit market shock.For example, Campello, Graham, and Harvey (2009b) provide evidenceon how nancially constrained and unconstrained US rms managetheir investment expenditure during the 2007 nancial crisis. In partic-ular they nd that the nancial crisis has had a severe impact on creditconstrained rms, leading to deeper cuts in planned R&D (by 22%),employment (by 11%), and capital spending (by 9%). Furthermore, theinability of these rms to borrow externally has caused many rms tocancel or postpone attractive investment projects, with 86% of CFOs inthe US stating that they had to restrict investments in attractive projectsduring the credit crisis. Similarly, Kisgen (2007) suggests that havingaccess to alternative sources of debt capital can help rms raise fundsduring adverse economic conditions and prevent underinvestment inpositive-NPV projects. All rms have suffered from the credit supplyshock but the impact has been greatest on those rms heavily relianton the banking sector for their funding.

The UK's corporate sector has also been adversely affected by the re-

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Fig. 5. Contributions to growth in lending to UK businduction in the bank lending during the 20072009 crisis. Bacon et al.(2009) in their survey of chiefnancial ofcers and corporate treasurerson the impact of changing banking and credit market conditions oncorporate funding plans during the 20072009 nancial crisis, foundthat with increased borrowing margins and reduced maturity periods,the availability of funds from the banking sector fell signicantly. Inaddition, they point out that if banking market capacity is reduced inthe foreseeable future, bondmarkets are likely to become an alternativesource of capital.

Several studies have looked at the effect of macroeconomic condi-tions on rms' capital structure decisions. Cantillo and Wright (2000)suggest that macroeconomic conditions have a powerful effect onhow rms choose their lenders. They nd that less constrained compa-nies tend to issue more debt during favorable economic conditions(Cantillo & Wright, 2000; Korajczyk & Levy, 2003; Levy, 2000). Levy(2000) investigates how rms' capital structure choice varies withmacroeconomic conditions in the presence of agency problems. Hends counter-cyclical patterns for debt issues for rms that access pub-lic capital markets. This nding is supported in the later work ofKorajczyk and Levy (2003) who point out that capital structure choicevaries over time and acrossrms. By splitting their sample into nancialconstrained and nancial unconstrained rms, they also nd thatleverage of nancially unconstrained rms varies counter-cyclicallytary policy. They examine UK manufacturing rms over two periods:the rst, 19901992, a period of tight monetary policy that coincidedwith a recession and a harsh environment for existing and new corpo-rate borrowers. The second, 19931999, was a period of loosemonetarypolicya time of sustained economic growth, falling unemploymentand ination, relatively low interest rates, and less constrainedborrowing conditions. Their results show that there was a marked dif-ference in the response to rm specic characteristics when interactedwith monetary policy. In particular, they found that small, young andrisky rms were more noticeably affected by monetary tighteningthan large, old and secure rms.

3. Credit market conditions in the U.K. 19982010

In this section we present an analysis of the conditions of the UKcredit markets before, during and after the 20072009 nancial crisis.with macroeconomic conditions. In other words, unconstrained rmstime their issue choice to coincide with periods of favorable macroeco-nomic conditions, while constrained rms do not. In a similar manner,

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s (12 month growth rate (%) in the stock of lending).We are interested in establishing whether the period under study pro-vides a good setting for identifying the effect of supply frictions on thecapital structure of UK rms. Leary (2009), in the context of the 1966US credit crunch, suggests that there are three elements to this. Firstly,did the 20072009 nancial crisis and any earlier credit crisis representa change in credit supply? Secondly, if these periods were subject tocredit supply shocks were they bank-specic or shocks to total capitalsupply? And, thirdly, could the effects on capital structure be drivenby simultaneous changes in credit demand? To nd answers to thesequestions we investigate three aspects of the UK credit markets: theow and stock of bank lending to the corporate sector, capital marketissuance and the pricing of bank loans. We will utilise evidence fromthese areas to examine whether the observed weakening in bank lend-ing to the corporate sector is an indicator of a reduction in the supply ofcredit due to a tightening in bank's credit provision or weaker demandfor nance from rms as a result of the recession.

Fig. 1 shows that between 2008 and 2009 the UK has been miredin the deepest as well as longest postwar recession since the 1930swith seven quarters of negative growth.5 The recession began in thesecond quarter of 2008 and by the end of 2009 the annual rate of

5 A recession is dened as two or more consecutive quarters of falling real GDP.

Fig. 3 presents Bank of England (BOE) data on net monthly bank

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33A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863lending ows to the UK corporate sector for the period 1998 to 2011and includes lending in both sterling and foreign currency (expressedin sterling millions).8 The chart shows that from 1999 through to thedecline in GDP reached nearly 5.6%the biggest fall since recordsbegan in 1955.6

3.1. Bank lending to the UK corporate sector

Fig. 2 provides a historical perspective on the annual growth inbank sterling lending to UK rms over the period 19642010. The shad-ed areas indicate periodswhen the UK economywas in recession (1974to 1975, 1980 to 1981, 1990 to 1991 and 2008 to 2009). The gureshows that recessions are always associated with decreases in thegrowth of lending and that growth has become negative in real termsduring the last four recessions. The 20082009 recession has seen thedeepest real terms contraction in bank lending. For example, in July2009 sterling-only net lending to private non-nancial corporationswas 8.4 billion which was the weakest ow since the series beganin 1963.7 However, it is worth pointing out that a slowdown in banklending does not always take place in the midst of a recession. Fig. 2shows that there have been three occasions in the last fteen yearswhere lending has weakened during periods of positive economicgrowth, these being around 1994, 19971999 and 20022003. We be-lieve that this fact makes it less likely that any credit rating or access ef-fects on capital structure we observe will be due to simultaneouschanges in credit demand.

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Fig. 6. Net capital market and net bankend of 2003 net monthly lending ows made several forays into nega-tive territory indicating a net repayment of bank loans in thosemonths.Net monthly lending ows were negative in 17 out of 60 months (28%of months) during this period with an average ow of 1559 million. Instark contrast, during the four year period from 2004 to 2007 lendingows were negative in only 2 months out of 48 (4% of months) and theaverage net monthly lending ow had nearly tripled to 4634 million.Thiswas then followedby thenancial crisiswhich resulted in the biggestreduction in bank lending to corporates since the BOE started collectingthis data in 1998. For the three years between January 2008 and January2011 the net monthly bank lending ow was negative in 25 out of37 months (68% of months) with an average net monthly lending ow

6 Sourced from the Ofce For National Statistics website.7 See www.bankofengland.co.uk/statistics/fm4/2009/jul/FM4.pdf or see Bank of

England (2009f) Trends in lending, September, page 4.8 Monthly changes of monetary nancial institutions' sterling and all foreign curren-

cy loans (excluding securitisations) to private non-nancial corporations (in sterlingmillions) seasonally adjusted.equal to698 million.9 Over these 37 months the stock of bank lendingto non-nancial rms shrank by 25.8 billion.

Fig. 4 shows the twelve-month and three-month growth rates ofthe stock of lending over the period January 1999 to January 2011.10

There was a dip in both growth rates towards the end of 1999, duringthe rst half of 2002 and then again over the second half of 2003which is consistent with the tightening of credit markets experiencedduring these years. From the middle of 2004 to the middle of 2005 wesee a rapid increase in both growth rates. For a two year period thetwelve month growth rate of the stock of lending averages around15% and then it picks up again in the middle of 2007. Twelve monthlending growth peaks at 24% in April 2008 after which it commenceda rapid decline hitting negative growth in May 2009 for the rst timesince the monthly series began in 1999.11 The annual rate of contrac-tion (negative growth rate) of the stock of loans peaked in the rstquarter of 2010 and since then the rate of contraction has slowed.

The strong ow and growing stock of lending to the corporate sectorshown in Figs. 3 and 4 during the pre-crisis years of 2004 to 2007 is con-sistent with the notion that during this period the bankswere very pro-active in encouraging rms to take on higher levels of debt and mostborrowers could not resist the cheap nancing facilities available. TheBOE points out that during this period themacroeconomic environmentwas very favorable, asset prices were rising and interest rates aroundthe world were relatively low which facilitated an increase in theamount of lending to companies in the UK and the rest of the world.Furthermore, the BOE suggests that before the credit crisis borrowingmargins were on the whole at historically low levels and at the peakof the boom in the latter part of 2006 bankswere competing aggressive-

2006 H2

2007 H1

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2008 H1

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nds & CP Equity

funds raised by UK rms 20032010.ly to provide credit on favorable terms (Bank of England, 2009a).Fig. 5 presents a breakdown of the growth of UK lending by geo-

graphical source. During the pre-crisis years 2005 to 2007 there was anincreasing contribution by foreign lenders to the growth of UK lendingwith about half of the growth in lending to private non-nancial rmsin 2007 being attributed to the activities of foreign lenders. However,with the onset of the nancial crisis the balance sheets of banks globallycame under severe pressure during the latter part of 2007 and conse-quently the contribution of those foreign lenders began to fall. This de-cline gathered momentum in the second half of 2008, as foreign bankscut back on new lending abroad. Fig. 5 shows that the growth in lending

9 Bank of England data covering lending by all UK-resident banks and building societiesshowed that there was a net repayment of loans in 21 of the months over the period Jan-uary 2009 to January 2011.10 Monthly 12 and 3 month growth rate of monetary nancial institutions' sterlingand all foreign currency loans (excluding securitisations) to private non-nancial cor-porations (in percent) seasonally adjusted11 The three month growth rate peaked at 36.5% in October 2007.

Sep

Sep 09 (327bp)

Fig. 7. Average estimated spreads on in

34 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863100

ions0

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006

Dec

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6

Bas

is p

oint

s

Source: Bank of Englandby UK lenders has also decreased, but their relative contribution to over-all growth is now greater than in 2007.

3.2. Capital market issuance by UK rms 20032010

In this section we examine whether the credit supply shocksdescribed above affected the ow of credit from both the bank and cap-ital markets or were isolated to the banking sector. This is important forthis study for two reasons. Firstly, if the nancial crisis resulted in a re-duction in total capital supply then we would expect to observe a zeroimpact of access on leverage during these periods. Secondly, if rms re-duce their borrowing from banks during the nancial crisis but are ableto switch to another source of nance, such as capital market debt, thenwewould expect to observe a positive access effect. Furthermore, in thiscase the resulting weakness in bank lending is more likely to reecttighter credit supply than weaker demand.

Rated rms in the UK raise debt funds from public debt capital mar-kets as well as by borrowing from banks. This allows them to diversifytheir sources of debt nance though in the UK bank lending tends tobe the dominant source of debt funds for private non-nancial rms(Kernan et al. (2010)). The Bank of England (2009c) reported that theaverage maturity of new lending during the crisis fell relative to beforethe crisis. The BOE noted that before the crisis the term premium

-40

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98Q3

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Q2

Net

% in

dica

ting

tight

cre

dit c

ondi

t

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Source: US Federal Reserve Board, European Cen

Fig. 8. Credit market conditions in the US, Europe and the UK (PMay

200

7O

ct 2

007

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8

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1

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07 (42bp)

vestment-grade syndicated loans.associated with borrowing over longer periods had been relativelysmall, and so loan facilities were mainly arranged with maturities ofve to seven years. However during the crisis, banks found it very dif-cult and costly to raise longer-term funding and thiswas reected in theprices they charged for longer-term facilities. The BOE suggest that a re-luctance by companies to lock in those higher costs over a long period,given uncertainty about future demand contributed to a decline in thematurity of new bank lending to two to three years. The BOE suggestedthat large investment-grade companies requiring longer-term nanc-ing were able to borrow in the capital markets given improved publicdebt market conditions in early 2009. Bond issuance by investment-grade companies was relatively strong in the early months of 2009,allowing these companies to mitigate the impact of a shortening inthe maturity of bank lending available (see Bank of England, 2008c).There were indications that during the nancial crisis large rms wereissuing capital market debt and using the proceeds to repay bank debt.

Fig. 6 shows that during 2009 large non-nancial rms wereaccessing capital markets reected by higher public debt and equityissuance, with some using equity proceeds to repay bank debt inorder to reduce leverage.12 It is clear to see from Fig. 6 that there wasgreater equity issuance during the crisis years as rms were seeking

12 The BOE suggest that rms were also repaying bank debt from other forms offunding such as internally generated funds.

2000

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Q3UROPE UK

tral Bank and Bank of England

ositive net% implies tight credit conditions for corporates).

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%

03

35A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 286310 14 17 20 24 24 28 35 39 41

4% 5%6% 7%

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Fig. 9. Number and proportion of rms

42 47 44 36 35 4

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sto reduce their leverage given the severe economic conditions. Fig. 6also shows that non-nancial rms' net equity and bond issuance wasconsiderably higher in 2009 than its average over the 20032008 peri-od. Furthermore, the BOE reports that between January and October of2010 gross bond issuance in the UKwas greater than its annual averageover the 20002007 period which was partly the result of strong issu-ance by non-investment grade rms (Bank of England, 2010b, Quarter4, page 252). Survey evidence also points to a preference for capitalmarket issuance during this time. For example, Deloitte Chief FinancialOfcer (CFO) Survey, 2009a, reported that sentiment among chiefnancial ofcers (CFOs) about equity and corporate bond issuancerose in June 2009, to its highest level since the survey started in 2007and for the rst time there was a preference for bond and equity issu-ance over bank borrowing. The Deloitte Chief Financial Ofcer (CFO)Survey, 2009b reported that a net balance of CFOs perceived UK compa-nies to be overleveraged and expected a long-term shift in the corporatefunding mix towards capital market issuance and away from bankborrowing.

The proportion of UK rms issuing bonds for the rst time has beenincreasing since the second half of 2008.13 Bank of England, 2010b,suggests that the majority of the new issuers in the UK have used theproceeds to repay maturing bank loans which they argue is consistentwith ongoing disintermediation of banks by UK rms. Bank of England(2010a) points out that there is evidence that since 2010 a wide rangeof companies have been accessing the public debt markets instead ofborrowing from the banks. The report indicates that around 40% ofthose rms that have issued corporate bonds in 2010 did so for the

13 Bank of England (2010b), Quarter 4, page 252.

Fig. 10. Number and proportion of rms wit67 65 67 68 69 67 63 55 51

20%23%

25%25%27%28%

29%27%27%

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Percentage

h S&P rating between 1989 and 2008.

43 45 53 43 39

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2004 2005 2006 2007 2008

Percentagerst time and suggests the fall in the cost of bond nance (corporatebonds yields have fallen) might be the factor behind such issuance.

The Bank of England (2009h) provides a number of explanations forthe strength of capital market issuance, relative to bank lending duringthe nancial crisis years. Firstly, it is suggested that increased equity is-suancemay have reected a desire by some rms to reduce their lever-age in light of the weaker economic environment and the belief thatcorporate leverage had risen too far. Secondly, the reduced availabilityof bank lending, and its increased cost relative to reference rates suchas three-month Libor, particularly for loans of longer maturities, mighthave encouraged companies to raise funds from capital markets. Third-ly, it is suggested that bank debt is considered to have a greater adverseaffect on rms' credit ratings than capital market debt, due to a belief ofgreater renancing risk associated with shorter debt maturities. TheBOE suggest that this may have led some rms to prefer bond issuanceover bank borrowing.

In addition to BOE data and corporate surveys there has been a largevolume of anecdotal evidence pointing to increasing bond issuance bynon-nancial rms during the nancial crisis. For example,

In the US and even more so in Europe, it is the small to medium-sizedcompanies that will most drastically be affected by a signicant con-traction in bank lending because they do not have access to bond mar-kets. (Davies, 2008, FT.com)

Companies have been turning to the bondmarkets to renance debt asbank lending has become constrained. (Sakoui & Lee, 2009, FT.com)

With bankingmarket capacitymuch reduced for the foreseeable futurethe capital markets are seen as a replacement funding source even forthose that have traditionally not made use of bonds. Some unrated

h Fitch rating between 1998 and 2008.

Our analysis would seem to suggest that the UK provides a good

47

5%

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16%

ned

36 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863corporates are expecting to seek their rst rating in order to gain accessto new sources of funding. (Bacon et al., 2009, page 3).

New investment grade corporate bond issuance in Euros for the rst4 weeks of January 2009 reached the same level as the rst 15 weekslast year (Bacon et al., 2009, page 5)

Businesses, frozen out by the world's biggest banks, have ocked to thecorporate bond market to raise new funds, triggering a 160 per centsurge in debt issuance since the beginning of the year. About$331 billion (229 billion) has been raised through corporate bond is-sues since January in Europe, America and Britain, compared with$127 billion for the same period last year. Financiers say that the risehas happened because banks effectively stopped lending competitivelyto business after the collapse of Lehman Brothers, theWall Street invest-ment bank, last September. (Jagger & Power, 2009)

since the events of September 2008, U.K. nancial institutions havereduced their net lending (both in sterling and foreign currencies) toU.K. companies by 59.1 billion, while corporate bond issuance byU.K. businesses had increased by 22.1 billion, according to Bank ofEngland gures. (Kernan et al., 2010, page 7)

According to Dealogic, European bond issuance reached 557.2 billionin 2009 compared with 338.4 billion of loans, the rst time bondmar-ket volumes have exceeded loans. (Churchill, 2010, http://www.risk.net/credit/)

34 27 27 70 119 134 118 97 128

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Fig. 11. Frequency and proportion of rating grades assigBritish companies, including Cadbury, Vodafone, Tesco and NationalGrid, have issued a swath of bonds in recent months, dipping into a poolof pension fund money while the banks were closed for lending.(Mortished, 2009, page 41)

Bondmarkets virtually closed following Lehman Brothers' collapse lastSeptember but co-ordinated state bail-outs have since reassured debtinvestors, with the number of global issues recovering from 133 inOctober to 315 last month. The UK also enjoyed its best January in atleast three years, with pounds 15.7 bn placed across 15 issues. Bondissuance is vital if companies are to fund future investment and isparticularly critical now that the banks are making less credit avail-able. (Aldrick & Ebrahimi, 2009, page 3)

The Financial Times (31st August 2010) reports that The effect of thenancial crisis on bank lending is prompting companies to develop oth-er funding channels. In 2009 companies around the world withinvestment-grade ratings raised record volumes of debt in capitalmarkets, much of it to renance bank loans. In the US, investment-setting for identifying the effect of supply frictions on capital struc-ture. The preceding analysis has demonstrated that large UK corpo-rates have been reducing their borrowing from banks and switchingto alternative sources of nance such as capital market debt. It followsthat the resulting weakness in bank lending is more likely to reecttighter credit supply than weaker demand. The evidence we havepresented also indicates that the credit supply shocks that havetaken place during our sample period were specic to bank creditand not shocks to total debt capital supply.

3.3. Corporate loan pricing and interest rate spreads

In the sections above we have shown that there has been a signi-cant weakening in bank lending to the UK corporate sector during the20072009 nancial crisis. We have argued that an important questionis whether this weakening in lending is due to a reduction in the supplyof credit, as banks have restricted the ow of lending to rms, or sub-dued demand for funding from rms as growth prospects have declinedgrade bond issuance by non-nancial companies totalled $512bn(402bn, 330 bn). In Europewhich has a much smaller bond inves-tor baseit hit 218 bn and in the UK, 47 bn was raised, accordingto data from Citigroup. Peter Goves, credit strategist at Citi, says sub-investment grade bond issuance in the rst half of this year was alsoat a record, with companies seeking to renance the bank loans theyused for leveraged buy-outs. (Cohen & Goff, 2010, page 7).

20 15 25 7 10 6 1 2

2% 2%3%

1% 1% 1% 0% 0%0%

2%

4%

6%

8%

10%

12%

Percentage

by S&P amongst UK non-nancial rms (19892008).during the recession. The evidence we have presented so far points to adecrease in the supply of bank credit and hence a credit market tighten-ing. However, this analysis is incompletewithout an examination of thebehaviour of interest rate spreads during this period. If the lendingslowdown is largely driven by a fall in demand then, all else beingequal, we would expect spreads charged on lending to decrease. How-ever, if a tightening of supply is the dominant factor, spreads wouldbe expected to increase (Bank of England, 2009a). Therefore, in orderto more fully disentangle the demand and supply effects on banklending we need to look at the behaviour of interest rate spreads beforeand during the nancial crisis.

The cost of bank loan nance to a rm can be broken down into thefees charged by a bank to provide loan facilities, the spread over a givenreference rate14 at which loans are provided, and the prevailing level ofthat reference rate in the markets (Bank of England, 2009g). The BOE

14 Usually three-month Libor or the Bank Rate. The Bank Rate is the ofcial rate paidon commercial bank reserves by the Bank of England.

64%

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37A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863reported that the extra cost associated with borrowing over longer pe-riods had been relatively small in the years leading up to the crisis (Bankof England, 2009c). Furthermore, in communications with the BOE, UKbanks suggested that spreads and fees had fallen to unsustainably lowlevels by early 2007 (Bank of England, 2009a). The BOE Credit Condi-tions surveys in 2008 and early 2009 indicated that since onset of thecrisis spreads over reference rates increased substantially across alltypes of lending. Fig. 7 shows that the period from September 2007 toSeptember 2008witnessed a signicant increase in the cost of syndicat-ed bank credit as loan spreadswidened. Spreads over reference rates onnew-investment-grade syndicated lending jumped by 148 basis points(bp) during this 12 month period and peaked at 327 basis points a yearlater in September 2009. During this two year period syndicated loanspreads went up by nearly eight times (42 bp to 327 bp). The CreditCondition surveys also found that the net percentage balances oflenders were reporting increased fees on secured lending and thatfees or commissions on loans to rms also went up. As the weaknessin bank lending is associated with higher spreads this would suggestthat a tightening in credit supply is most probably the key driver forweak bank lending during the nancial crisis.

In order to shed further light on this issue we can examine the rea-sons put forward to explain why loan spreads increased during thenancial crisis. Firstly, UK banks reported to the BOE that spreads overreference rates had increased to better reect the higher costs oflonger-term funding. From the start of the crisis banks found it ex-tremely difcult and costly to raise longer-term funding and conse-

6 22 10 19 41 79 61%

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Fig. 12. Frequency and proportion of rating grades assigquently this was reected in the prices they charged for long-termloans. At this time UK banks were under pressure to lengthen theterm structure of wholesale funding to better match that of assets, asa result using Libor as a reference rate was no longer appropriatesince longer-term funding rates were a better reection of the banksmarginal cost of funding. Banks indicated that the spreads charged onlonger-term facilities had been increased to better account for therisks of funding over the lifetime of the loan (Bank of England,2009b). Secondly, the BOE reported that increases in spreads mightalso have reected in part a re-pricing of risk due to increased percep-tions of credit risk, following a lengthy period earlier in the decadewhen corporate credit risks were underpriced. Banks suggested thatdeteriorating credit quality of borrowers had led to higher capital re-quirements and costs, which had acted to fuel the hike in spreads(Bank of England, 2009c). Thirdly, higher capital requirements underthe new Basel II capital adequacy framework explained in part the in-creased charges for unused loan facilities (Bank of England, 2009a). Asthese reasons are strongly linked with credit supply factors this evi-dence also points to an independent tightening in the supply of creditduring the nancial crisis.3.4. Measuring credit market conditions: loan ofcer surveys

The US Federal Reserve Board, European Central Bank (ECB) and theBank of England (BOE) conduct a quarterly survey of commercial banksunder their jurisdiction to measure the extent to which banks are will-ing to provide loans to the corporate sector. Of the three surveys the USFederal Reserve's Senior Loan Ofcer Opinion Survey is the oldestestablished survey running since 1967, although it was suspendedfrom the rst quarter of 1984 through to the second quarter of 1990.15 The ECB survey started in 2003 and is conducted in each membercountry by the respective national central bank, and the results arethen collated and analysed at the aggregate level. The ECB credit condi-tions survey is sent to senior loan ofcers of a sample of euro area banks.The banks participating in the survey comprises around 90 banks fromall euro area countries and takes into account the characteristics of theirrespective national banking systems. The questionnaire examinesissues relating to both loan demand and loan supply. The loan supplyquestions address issues relating to credit standards and credit condi-tions and terms, as well as to the various factors that may be behindany loan supply changes.16

The BOE ran their survey for the rst time in the second quarter of2007.17 The BOE survey asks questions about both how bank lendingtrends have changed over the past three months (relative to the previ-ous three months), and how they are expected to change over the nextthree months (relative to the latest three months). The survey also asksabout changes in the amount of credit lenders are willing to supply

80 104 12 17 6 8

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10%

BBB+ BBB BBB- BB+ BB BB-

ntage

By Fitch amongst UK non-nancial rms (19982008).and about howbothprice and non-price terms are changing such as col-lateral requirements and loan covenants. The latter gives an indicationof whether the terms and conditions on which banks are willing tolend have improved or worsened. To calculate aggregate survey results,the BOE assigns to each lender a score based on their response. Lenderswho report that credit conditions have changed a lot are assignedtwice the score of those who report that conditions have changed alittle. These scores are then weighted by lenders' market shares. Theresults are analysed by calculating net percentage balancesthe differ-ence between the weighted balance of lenders reporting that, forexample, terms and conditions were looser/tighter. The net percentagebalances are scaled to lie between 100. Negative balances indicate

15 The US Federal Reserve LoanOfcer data is obtained fromhttp://www.federalreserve.gov/boarddocs/snloansurvey/.16 The ECB Lending Survey data is obtained from http://www.ecb.int/stats/money/surveys/lend/html/index.en.html.17 The BOE Credit Conditions Survey data is obtained from http://www.bankofengland.co.uk/publications/Pages/other/monetary/creditconditions.aspx.

that lenders, on balance, reported/expected credit availability to belower than over the previous/current three-month period, or that theterms and conditions on which credit was provided became expensiveor tighter respectively. This is opposite to the Federal Reserve and ECBsurveys where a positive net percentage balance indicates a creditmarket tightening. Therefore, in this studywemultiply the BOE net per-centage balances byminus 1 to make them consistent with those of theFederal Reserve and ECB. Thus, for all three surveys a positive (negative)net percentage balance indicates an overall tightening (loosening) inthe supply of credit.

In this study we use the net percentage balance of respondents tothe question How has the availability of credit provided to the corpo-rate sector overall changed? to get an overall assessment of the condi-tions of the UK credit markets. We use the results to the correspondingquestion in the Federal Reserve and ECB surveys to measure the condi-tions of the credit markets in the US and Europe, respectively. Fig. 8 pre-sents net percentage balance data for the US, European and UK creditcondition surveys for the period from 1990 to 2010.

Fig. 8 indicates that since the middle of 2005 there appears to be

access debt markets or they might simply not want to have access

All nancial data is sourced from DataStream. Credit rating data issourced directly from Standard and Poor's (S&P) and Fitch. For creditrating we use a company's long-term credit rating. Credit rating datafrom S&P covers the 20 years from 1989 to 2008 and Fitch credit rat-ings are available for the 11 years from 1998 to 2008. In our sample1010 or 15.4% of rm-year observations possess a rating (either S&Por Fitch). This percentage is similar to Mitto and Zhang's (2010) 15%for a sample of Canadian rms and to Faulkender and Petersen's(2006) 19% for US rms.

Fig. 9 illustrates the frequency of rms with a S&P credit rating forthe period from 1989 to 2008 and the proportion of rms in our samplethat possess a S&P rating. Fig. 9 shows that only 4% (10 rms) ofrms inour sample were rated by S&P in 1989. The percentage of S&P ratedrms peaked at 29% in 2006 and stood at 27% in 2008.

Fig. 10 shows the frequency and percentage of rms with a Fitchcredit rating for the period from 1998 to 2008. Twelve percent of oursample possessed a Fitch rating in 1998 and this had reached 20% in2008.

0%

38 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863and prefer to nance themselves with equity. If rms in this categoryqualify to have a rating but do not want to obtain it, they will bemisclassied as rms without access. There are 707 of rms (around10%) with zero debt in our sample. To avoid any misclassication biasin our analysis we follow Faulkender and Petersen (2006) and Chavaand Purnanandam (2009) and exclude all zero-debt rms from theanalysis. This leaves us with a panel of 6551 rm-year observations.

9%

4% 3% 2%

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0%

5%

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25%some degree of synchronicity in the state of the credit markets in theUS, Europe and the UK. Simple correlation analysis conrms that creditmarket conditions are highly correlated with a correlation coefcientaround+0.8, although credit markets in Europe and the UK are slightlymore closely aligned with each other than with the US. Fig. 8 also sug-gests that the severity of the tightening in credit conditions during thenancial crisis was greatest in the US.

4. Sample description

Our sample employs data for the top 500 UK listed non-nancialrms by market capitalization for the period from 1989 through to2008. Following previous studies on capital structure (Byoun, 2008;Faulkender & Petersen, 2006; Hovakimian, Kayhan, & Titman, 2008;Kisgen, 2006; Kisgen, 2009) we exclude all nancial rms fromthe sample, resulting in a panel of 7258 rm-year observations.According to Faulkender and Petersen (2006) and Chava andPurnanandam (2009) rms with no debt might either not be able toFig. 13. Proportion of European non-nancial rms with a S&P rating in9%

23%

11%

3%

11%10%

5%

8%

19%4.1. Rating categories

The ratings assigned to the rms in our sample range from thehighest AAA to the lowest CC, indicating each rm's individual creditquality (see Appendix, Table A). All ratings above and including BBB-fall into the category of investment grade ratings and ratings belowand including BB+ are considered to be non-investment or speculativegrade ratings. In our sample of 1010 rm-years with a rating, 909 pos-sess an investment grade rating and 101 have a non-investment graderating. Figs. 11 and 12 illustrate frequencies of the rating categoriesassigned by S&P and Fitch credit rating agencies to UK non-nancialrms. Fig. 11 presents frequencies of the rating grades assigned byS&P to UK rms.

Fig. 11 shows that the highest concentration of S&P rated rm-yearsis observed within the A+ to BBB rating interval with 596 out of 887rm-years observations (66% of S&P rated rm-year observations).The rating category with the highest frequency is A with 134rm-years observations (15% of the S&P rated rm-years). Fig. 12 pre-sents frequencies of the rating grades assigned by Fitch to UK non-nancial rms. Similar to the S&P ratings data Fig. 12 indicates thatmost of the Fitch rated rm-year observations are concentrated withinthe A to BBB credit rating interval with 70% of the rated rm-yearspossessing a Fitch rating between these grades (329 out of 470 of therm-year observations). The highest frequency is observed in the BBBcategory with 22% of the rm-years in this rating category (104 of therm-year observations).2010. (Source: Author's calculation using Standard and Poor's data).

Table 1Differences in leverage between rms with and without access to public bond market.The table reports tests for differences in the mean andmedian of rms' leverage ratios forrms with and without access to public bond market. The sample is based on listednon-nancial rms for the period between 1989 and 2008 and contains rm-year obser-vations with positive debt only. Access to the public debt markets is measured by: 1) thepossession of long-term corporate credit rating (Panel A); 2) rm size, where Top20% areclassied as having access and Remaining80% are classied as not having access (Panel B);3) rm size, where Top20% are classied as rms with access and Bottom20% as rmswithout access (Panel C); 4) rms with rating as having access and rms in the bottom20% as not having access (Panel D). Leverage is measured by debt-to-asset ratio. Therst two columnsmeasure leverage on amarket value of assets basis, the last two columnson a book value of assets basis. Columns I and III display results for gross value of leverageand columns II and IV for net leverage (total debt less cash and equivalents). ***, **, * indi-cate signicance at 1%, 5% and 10% level respectively.

I II III IV

Gross leverageMV

Net leverageMV

Gross leverageBV

Net leverageBV

Panel A: Access proxied by credit ratingFirms with accessN 1007 1007 999 999Mean 0.2794 0.1858 0.3047 0.2072Percentiles 25 0.1465 0.0554 0.1750 0.0729Median 0.2474 0.1670 0.2876 0.2075Percentiles 75 0.3896 0.2940 0.4083 0.3266

Firms without accessN 5455 5455 5470 5470Mean 0.2283 0.1272 0.2228 0.1057Percentiles 25 0.0708 0.0058 0.1007 0.0119Median 0.1724 0.0945 0.1990 0.1160Percentiles 75 0.3316 0.2493 0.3097 0.2430

Firms with access vs. rms without access (mean difference test)Mean difference 0.0511*** 0.0586*** 0.0818*** 0.1015***T-Stat 8.0039 8.6906 14.5352 14.2398Signicance 0.0000 0.0000 0.0000 0.0000

Firms with access vs. rms without access (median test)Mediandifference

0.0750*** 0.0725*** 0.0886*** 0.0915***

Chi-squared 124.254 99.616 151.007 108.796Signicance 0.0000 0.0000 0.0000 0.0000

Panel B: Access proxied by rm size (Top20Remaining 80)Firms with accessN 1361 1361 1359 1359Mean 0.2930 0.1947 0.2816 0.1886Percentiles 25 0.1540 0.0669 0.1709 0.0766Median 0.2533 0.1752 0.2622 0.1928Percentiles 75 0.3985 0.3101 0.3657 0.2924




0.0884 0.0877 0.0654 0.0822


Panel C: Access proxied by rm size (Top20Bottom20)Firms with accessN 1361 1361 1359 1359Mean 0.2930 0.1947 0.2816 0.1886Percentiles 25 0.1540 0.0669 0.1709 0.0766Median 0.2533 0.1752 0.2622 0.1928Percentiles 75 0.3985 0.3101 0.3657 0.2924


Table 1 (continued)

I II III IV

39A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863Gross leverageMV

Net leverageMV

Gross leverageBV

Net leverageBV

Panel C: Access proxied by rm size (Top20Bottom20)Firms with access vs. rms without access (mean difference test)Mean difference 0.1530*** 0.1703*** 0.1181*** 0.2176***T-Stat 19.3147 19.6379 17.5575 20.7819Signicance 0.0000 0.0000 0.0000 0.0000


0.1929*** 0.1761*** 0.1493*** 0.1955***


Panel D: Access proxied by the possession of credit rating and rm size (RatedSmall20)a

Firms with accessN 906 906 899 899Mean 0.2651 0.1787 0.2959 0.2008Percentiles 25 0.1430 0.0549 0.1740 0.0723Median 0.2413 0.1600 0.2800 0.2037Percentiles 75 0.3605 0.2794 0.3933 0.3146




0.1804*** 0.1601*** 0.1667*** 0.2044***4.2. Credit ratings in Europe

Fig. 13 shows the percentage of non-nancial rms in Europeancountries that possess a long-term S&P credit rating in 2010. For thethree largest European economies Germany, France and the UK we re-strict our sample to around the largest 300 non-nancial listed rms.On this basis, the UK has the highest proportion of rated rms with19% of listed non-nancial rms possessing a rating followed by Francewith 15% and Germany with 13%. This suggests that the UK is a goodsetting to examine the role of ratings in determining capital structuredecisions.18

5. Empirical analysis

5.1. Methodology

The empirical analysis that follows presents results from univariateandmultivariate analyses. Bondmarket access is proxied by the posses-sion of a credit rating (Faulkender & Petersen, 2006; Mitto & Zhang,2008). Following Faulkender and Petersen (2006) and Leary (2009)leverage is measured as a ratio of gross total debt to market value of as-sets. The univariate analysis examines differences in leverage and otherrm characteristics between rms with and without a rating in oursample and other alternative measures of debt capital market access.The multivariate analysis shows the impact of credit rating on leveragewhile controlling for other rm characteristics and macroeconomicconditions. Following Chava and Purnanandam (2009) all variables

18 In our sample Luxembourg has a small number of listed rms (26 rms) which ex-plains the relatively large percentage of rated rms.


a Note that some rms that have a rating fall into the bottom 20% of rms by size dis-tribution. This may be due to the fact that our sample consists of the top 500 UK rmsby market capitalisation, and therefore, while these rms are considered to be small,in our sample they are large enough to have a rating.

ble presents the results from Univariate independent sample t-tests for the sample of UKd from 1989 to 2008 and contains rm-year observations with positive debt only. Accesscredit rating (Panel A); 2) rm size, where Top20% are classied as having access and

% are classied as rms with access and Bottom20% as rms without access (Panel C); 4)el D*a

47381554445488965541

40 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863Table 2Mean differences in rm characteristics between rms with and without access. The talisted non-nancial rms with and without access to public bond market for the perioto the public debt markets is measured by: 1) the possession of long-term corporateRemaining80% are classied as not having access (Panel B); 3) rm size, where Top20rms with rating as having access and rms the bottom 20% as not having access (Panwith and without access. *** indicates statistical signicance at 1% level, **at 5% level,

Access N No access N

Panel A: Access is measured by credit ratingSize 15.5565 1003 12.8937 54Age 3.5237 1007 3.2751 54Protability 0.1269 1002 0.1017 54Asset tangibility 0.6543 1007 0.5347 54Market-to-book 1.4841 999 1.6349 54R&D expenditure 0.0112 1007 0.0149 54Asset volatility 0.2275 993 0.2442 52Equity return 0.0106 997 0.0071 52Short-term debt 0.2529 1007 0.3713 54Tax paid 0.2494 1000 0.2520 54are winsorised at 1% level to eliminate outliers that could inuence theresults.

The rst stage of our analysis employs univariate tests to identify ifrated rms possess different characteristics compared to those withouta rating. We begin by comparing the leverage of rated and non-ratedrms. We then compare rm characteristics of rated and non-ratedrms that capital structure theories predict to have an impact onrms' leverage. We follow the prior literature in our choice of variables(Faulkender & Petersen, 2006; Leary, 2009). These characteristicsinclude: rm size, rm age, protability, asset tangibility, market-to-book ratio, R&D expenditure, asset volatility, equity return, a portionof short-term debt and tax paid.

To verify that our results are not driven by the way we dene access(possession of a credit rating), we follow Leary (2009) and Voutsinasand Werner (2011) and create alternative measures of access based onrm size. Leary (2009) indicates that while this may not be a perfectproxy, size is clearly highly correlated with public debt market access(Leary, 2009, page 1160). In addition, Leary (2009) points out

Panel B: Access is measured by rm size (Top20Remaining80)Size 15.6249 1361 12.6831 5080Age 3.5127 1356 3.2637 5076Protability 0.1016 1351 0.1066 5054Asset tangibility 0.6898 1361 0.5171 5088Market-to-book 1.1872 1361 1.7255 5078R&D expenditure 0.0093 1361 0.0156 5088Asset volatility 0.2070 1348 0.2505 4924Equity return 0.0117 1348 0.0068 4932Short-term debt 0.2498 1361 0.3801 5088Tax paid 0.2666 1361 0.2477 5074

Panel C: Access is measured by rm size (Top20Bottom20)Size 15.6249 1361 11.0939 1105Age 3.5127 1356 2.8152 1109Protability 0.1016 1351 0.0883 1102Asset tangibility 0.6898 1361 0.4059 1109Market-to-book 1.1872 1361 2.8684 1107R&D expenditure 0.0093 1361 0.0347 1109Asset volatility 0.2070 1348 0.3110 1023Equity return 0.0117 1348 0.0607 1027Short-term debt 0.2498 1361 0.5526 1109Tax paid 0.2666 1361 0.2041 1106

Panel D: Access is measured by the possession of credit rating and rm size (RatedSmall20)Size 15.6774 905 11.0919 1093Age 3.5524 906 2.8287 1097Protability 0.1386 902 0.0867 1090Asset tangibility 0.6606 906 0.4065 1097Market-to-book 1.5044 898 2.8619 1095R&D expenditure 0.0112 906 0.0345 1097Asset volatility 0.2228 895 0.3094 1015Equity return 0.0245 896 0.0619 1019Short-term debt 0.2614 906 0.5554 1097Tax paid 0.2615 899 0.2037 1094). Mean values are reported. Fifth column reports mean differences between the rmst 10% level.

Mean difference t-stat P-value R vs. NR

2.6628 61.5640 0.0000 R>NR0.2486 7.5004 0.0000 R>NR0.0252 3.6673 0.0002 R>NR0.1196 16.0639 0.0000 R>NR

0.1508 2.9988 0.0028 RbNR0.0038 3.8371 0.0001 RbNR0.0167 4.0735 0.0000 RbNR0.0036 0.2514 0.8015 R>NR

0.1184 14.4944 0.0000 RbNR0.0027 0.2649 0.7911 RbNRthat according to Johnson (1997), and Krishnaswami, Spindt, andSubramaniam (1999), the proportion of outstanding debt from publicsources is strongly correlated with rm size. He denes rms with ac-cess based on the upper two (three) deciles of book assets, while thosewithout access are those in the lower two (three) deciles. In Leary's sam-ple the upper two deciles contain large rms with assets greater than$100 million, whilst the lower two deciles contain small rms with as-sets between $1 million and $10 million (Leary, 2009, page 1161).19

Following Leary's (2009) and Voutsinas and Werner's (2011) ap-proach, we create three sized-based measures of access:

1. Firms with access are dened as being in the top 20% (30%) of thedistribution by book value of assets, and rms without access are

19 The exception could be large multinational companies. According to Aggarwal andKyaw (2010) multinational companies, while being large and diversied, have signi-cantly lower debt ratios compared to domestic companies, with such debt ratios de-creasing with the degree of multinationality.

2.9418 96.1117 0.0000 R>NR0.2491 8.5686 0.0000 R>NR

0.0050 1.1583 0.2468 RbNR0.1727 25.8194 0.0000 R>NR

0.5383 15.6919 0.0000 RbNR0.0064 7.6340 0.0000 RbNR0.0435 12.8165 0.0000 RbNR0.0049 0.4020 0.6877 R>NR

0.1302 17.8304 0.0000 RbNR0.0189 2.1258 0.0336 R>NR

4.5310 105.1458 0.0000 R>NR0.6975 18.0569 0.0000 R>NR0.0133 1.2721 0.2036 R>NR0.2839 31.5714 0.0000 R>NR

1.6811 18.3599 0.0000 RbNR0.0254 12.3439 0.0000 RbNR0.1040 15.7111 0.0000 RbNR0.0490 2.1932 0.0284 RbNR0.3028 26.5421 0.0000 RbNR0.0625 5.4052 0.0000 R>NR

4.5855 87.8429 0.0000 R>NR0.7238 16.8188 0.0000 R>NR0.0519 4.5496 0.0000 R>NR0.2541 26.0053 0.0000 R>NR

1.3575 13.5655 0.0000 RbNR0.0233 10.7972 0.0000 RbNR0.0867 12.3808 0.0000 RbNR0.0374 1.6205 0.1053 RbNR0.2940 24.1281 0.0000 RbNR0.0578 4.3555 0.0000 R>NR

Table 3Access and capital structure, access is measured by the possession of a credit rating: Pooled OLS. The table presents estimates of Eq. (1) using annual data of UK listed non-nancialrms for the period from 1989 to 2008. The dependent variable is the ratio of total debt to the market value (MV) of assets. Total debt incorporates short-term debt and long-termdebt. MV of assets is the sum of MV of equity and BV of total debt. Public bond market access is proxied by the possession of a credit rating. Credit rating is interacted with the yeardummies to measure the variation in the effect of credit rating over time. Firm size is the natural logarithm of MV of assets. Age is the natural log of rm age plus one. Protability ismeasured as return on invested capital (ROIC) which calculated as the sum of pre-tax prots and total interest charges divided by invested capital. Asset tangibility is calculated asthe difference of total assets minus current assets divided by total assets. Market-to-book ratio of assets is MV of assets over BV of assets. Firm's spending on R&D is expressed asnatural logarithm of the ratio of one plus R&D expenditure scaled by total assets. Riskiness of operations is calculated as equity volatility multiplied by the equity-to-asset ratio.Equity volatility is expressed as square root of number of trading days multiplied by standard deviation of natural log of the daily price growth rate. Past equity returns are calcu-lated as natural log of share price at the end of the year over share price at the beginning of the year. Portion of short-term debt is calculated as the sum of short-term debt andcurrent portion of long-term debt due to within one year divided by total debt. Average tax paid is calculated as income taxes over pre-tax income (taxable income). All variables arewinzorised at 1% level in order to prevent potential outliers driving the results. All specications include annual stock market return and annual GDP growth rate to control for macro-economic conditions. Annual stockmarket return is calculated as natural logarithmof FTSE at the end of the year over FTSE at the beginning of the year. Annual GDP growth rate is sourcedfrom the IMF ofcial website.a Industry dummies are included across all specications to control for industry-specic effects. Variables denitions are presented in Appendix, Table B.Standard errors (in parenthesis) are adjusted for heteroskedasticity and clustering by rms. ***, **, * indicate statistical signicance at 1%, 5%, and 10% levels respectively.

Variables (1) (2) (3) (4) (5) (6)

Credit rating 0.0524* 0.0534** 0.0537** 0.0467* 0.0548** 0.0537**(0.027) (0.026) (0.026) (0.026) (0.025) (0.025)

Size 0.0028 0.0008 0.0000(0.004) (0.004) (0.004)

Age 0.0073 0.0085 0.0086 0.0080 0.0083* 0.0086*(0.005) (0.005) (0.005) (0.005) (0.005) (0.005)

Protability 0.2338*** 0.2284*** 0.2211*** 0.2316*** 0.2290*** 0.2211***(0.019) (0.018) (0.018) (0.018) (0.017) (0.017)

Asset tangibility 0.1119*** 0.0834*** 0.0823*** 0.1165*** 0.0824*** 0.0823***(0.024) (0.024) (0.024) (0.024) (0.024) (0.024)

Market-to-book 0.0114*** 0.0103*** 0.0105*** 0.0112*** 0.0104*** 0.0105***(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)

R&D spending 0.2108* 0.2573** 0.2636** 0.2083* 0.2576** 0.2636**(0.116) (0.111) (0.111) (0.115) (0.111) (0.111)

Asset volatility 0.4458*** 0.4295*** 0.4338*** 0.4477*** 0.4291*** 0.4338***(0.033) (0.033) (0.033) (0.034) (0.033) (0.033)

Equity return 0.1159*** 0.1162*** 0.1151*** 0.1149*** 0.1165*** 0.1151***(0.006) (0.006) (0.006) (0.006) (0.006) (0.006)

Short-term debt 0.0925*** 0.0908*** 0.0920*** 0.0908***(0.011) (0.011) (0.010) (0.010)

Tax paid 0.0405*** 0.0405***(0.009) (0.009)

Rating_1989 0.0494 0.0570* 0.0569* 0.0498 0.0568* 0.0569*(0.032) (0.029) (0.029) (0.032) (0.029) (0.029)

Rating_1991 0.0173 0.0105 0.0091 0.0186 0.0103 0.0091(0.012) (0.012) (0.012) (0.012) (0.012) (0.012)

Rating_1992 0.0758*** 0.0742*** 0.0689*** 0.0770*** 0.0739*** 0.0689***(0.025) (0.024) (0.024) (0.025) (0.024) (0.024)

Rating_1993 0.0267 0.0312 0.0298 0.0274 0.0310 0.0298(0.024) (0.023) (0.023) (0.024) (0.023) (0.023)

Rating_1994 0.0100 0.0231 0.0219 0.0095 0.0231 0.0219(0.024) (0.023) (0.022) (0.024) (0.023) (0.022)

Rating_1995 0.0425* 0.0490** 0.0482** 0.0428* 0.0489** 0.0482**(0.025) (0.025) (0.024) (0.025) (0.025) (0.024)

Rating_1996 0.0230 0.0310 0.0306 0.0232 0.0309 0.0306(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_1997 0.0726** 0.0771** 0.0759** 0.0730** 0.0770** 0.0759**(0.031) (0.031) (0.030) (0.031) (0.031) (0.030)

Rating_1998 0.0877*** 0.0883*** 0.0876*** 0.0871*** 0.0884*** 0.0876***(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_1999 0.1021*** 0.1052*** 0.1047*** 0.1018*** 0.1052*** 0.1047***(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_2000 0.1271*** 0.1340*** 0.1331*** 0.1266*** 0.1341*** 0.1331***(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_2001 0.1109*** 0.1169*** 0.1123*** 0.1111*** 0.1168*** 0.1123***(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_2002 0.1013*** 0.1051*** 0.1051*** 0.1013*** 0.1051*** 0.1051***(0.029) (0.028) (0.028) (0.029) (0.028) (0.028)

Rating_2003 0.1456*** 0.1444*** 0.1462*** 0.1457*** 0.1444*** 0.1462***(0.029) (0.028) (0.027) (0.029) (0.028) (0.027)

Rating_2004 0.0894*** 0.0874*** 0.0833*** 0.0895*** 0.0874*** 0.0833***(0.030) (0.029) (0.029) (0.030) (0.029) (0.029)

Rating_2005 0.0842*** 0.0786*** 0.0755*** 0.0848*** 0.0784*** 0.0755***(0.030) (0.029) (0.029) (0.030) (0.029) (0.029)

Rating_2006 0.0665** 0.0666** 0.0654** 0.0673** 0.0664** 0.0654**(0.029) (0.027) (0.027) (0.029) (0.027) (0.027)

Rating_2007 0.0785*** 0.0785*** 0.0760*** 0.0796*** 0.0782*** 0.0760***(0.030) (0.029) (0.029) (0.030) (0.029) (0.029)

Rating_2008 0.1372*** 0.1390*** 0.1393*** 0.1388*** 0.1385*** 0.1393***(0.032) (0.031) (0.031) (0.032) (0.031) (0.031)

Stock market return 0.0592*** 0.0501*** 0.0507*** 0.0608*** 0.0498*** 0.0507***

(continued on next page)

41A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863

(3)

(0.00.(0.00.33(0.06210.5046.10.00

10/

42 A. Judge, A. Korzhenitskaya / International Review of Financial Analysis 25 (2012) 2863those in the remaining 80% (70%) of the size distributionreferred toas Top20% Remaining80% (Top30%Remaining70%) thereafter.This classication includes all rms in the sample.

2. Firms with access are dened as those in the top 20% (30%) of thedistribution by book value of assets, and rms without access aredened as those in the bottom 20% (30%) of the size distributionreferred to as Top20%Bottom20% (Top30%Bottom30%)thereafter.In this classication we drop the middle 60% (40%) of rms in thesize distribution, thus keeping 40% (60%) of rms in the sample.

3. Firms with access are those with a credit rating and rms withoutaccess are those in the bottom 20% (30%) of the size distributionreferred to as RatedBottom20% (RatedBottom30%) thereafter.In this case we exclude all unrated rms that are not included inthe bottom 20% (30%) of rms by book value of assets.

5.2. Univariate analysis: differences between rms with and without acredit rating

5.2.1. Differences in leverage ratiosIn this section we examine if leverage of rms possessing a credit

rating is different to those without a rating. Leverage is measured bydebt-to-asset ratio, which is dened as book value of total debt(long-term debt plus short-term debt) divided by market value ofassets (MV), where market value of assets is dened as total assetsminus book value of equity plus market value of equity. FollowingFaulkender and Petersen (2006) and Voutsinas and Werner (2011)we also employ book value (BV) of assets in the denominator to mea-sure leverage. Finally, we use net debt (total debt minus cash) as analternative to total debt to measure net leverage (for full details seevariable denitions in Appendix, Table B). Table 1 reports the resultsof tests for differences in the mean and median leverage betweenrms with and without a credit rating.

Panel A of Table 1 shows that rms with a rating are clearly morehighly levered than their unrated counterparts whether we measureleverage by MV or BV of assets or by total or net debt. When we employMVmeasures of gross and net leverage (columns I and II), the univariatet-test shows that companies with rating have on average 56% more le-verage. This difference increases to between 8 and 10% when weemploy BV measures of gross and net leverage (columns III and IV)(p-valueb0.01). These results imply that the possession of a credit rating

Table 3 (continued)

Variables (1) (2)

(0.013) (0.013)GDP growth 0.0079*** 0.0090***

(0.002) (0.002)Constant 0.2466*** 0.3364***

(0.046) (0.047)Observations 6214 6214R-squared 0.4851 0.5031F test 45.1230 47.9731Prob>F 0.0000 0.0000

a Available at the ofcial IMF website at http://www.imf.org/external/pubs/ft/weo/20increases rm's leverage by between 22% [5.11/22.83] and 46% [5.86/12.72] when we compare MV leverage ratios and by between 37% and96% when we compare BV leverage ratios. The results are robustthroughout the whole distribution.Whether we look at differences in le-verage at the 25th, 50th or 75th percentiles of the distribution, we ob-serve that rms possessing a credit rating are more highly levered. Forthe median rm, credit rating increases market gross leverage by 7.5%and book gross leverage by almost 9%. Our result is slightly lower thanthat of Faulkender and Petersen (2006) results who nd that having adebt rating raises MV debt ratio by 13.7% and BV ratio by 15.7%. The re-sults are similar when we use the alternative measures of public debtmarket access in panels B, C and D. The univariate test shows that rmswith a rating have higher leverage ratios than those without a rating.5.2.2. Differences in rm characteristics between rated and non-rated rmsThe previous analysis shows that rms perceived to have access to

the debt capitalmarkets have higher leverage ratios than thosewithout.In this section we examine whether rated rms exhibit the characteris-tics normally associatedwith highly leveredrms. Capital structure the-ories predict that rm characteristics such as size, age, protability,asset tangibility, growth opportunities, business risk, and tax shieldsare related to the level of a rm's indebtedness. Here we test whetherthese characteristics are related in a similar fashion to rmswith accessto the capital markets.

The results in panel A of Table 2 show that rated rms are consider-ably larger thannon-rated rms (about 266% on averagedifferences innatural logarithms). This result is consistent with the notion that sincethe average size of issues of bonds is higher than borrowing from theprivate sources and public bonds issues are associated with higherxed costs hence it is only large rms that borrow from public debtmarket (Faulkender & Petersen, 2006). The difference is statistically sig-nicant at 1% level. We nd that rms with a rating are signicantlyolder (the difference is 25%) andmore protable. These results are sim-ilar to Faulkender and Petersen (2006).

Consistent with Faulkender and Petersen (2006) we nd thatrms with and without a rating differ in the type of assets they pos-sess: rms wi

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Documents

rms capital structure

capital structure decision

thesupply of capital

debt availability

rms characteristics

thesame cost of capital

public debt markets

credit market conditions