Do small business still prefer community banks?
q不碍事
Allen N.Berger a ,b ,c ,⇑,William Goulding d ,Tara Rice e
a
University of South Carolina,United States
网络销售员
b
Wharton Financial Institutions Center,United States c
European Banking Center,Netherlands d
Massachutts Institute of Technology,Sloan School of Management,United States e
描写童年的诗句Board of Governors of the Federal Rerve System,United States
a r t i c l e i n f o Article history:
Received 19June 2013Accepted 10March 2014
Available online 26March 2014JEL classification:G21G28G34
Keywords:Banks
Relationships Small business
Government policy
万圣节的手抄报
a b s t r a c t
We formulate and test hypothes about the role of bank type –small versus large,single-market versus multimarket,and local versus nonlocal banks –in banking relationships.The conventional paradigm sug-gests that ‘‘community banks’’–small,single-market,local institutions –are better able to form strong relationships with informationally opaque small business,while ‘‘megabanks’’–large,multimarket,nonlocal institutions –tend to rve more transparent firms.Using the 2003Survey of Small Business Finance (SSBF),we conduct two ts of tests.First,we test for the type of bank rving as the ‘‘main’’rela-tionship bank for small business with different firm and owner characteristics.Second,we test for the strength of the main relationships by examining the probability of an exclusive relationship and main bank relationship length as functions of main bank type and financial fragility,as well as firm and owner characteristics.The results are often not consistent with the conventional paradigm,perhaps becau of changes in lending technologies and deregulation of the banking industry.
Ó2014Elvier B.V.All rights rerved.
1.Introduction三月份星座
Banks are critical sources of funding for small firms,providing about 60%of debt financing to small business (Survey of Small Business Finance,2003).Small business lending is also important to banks.Both small and large banks extend significant amounts of small business loans.Despite the importance of the banks to small business and vice versa,surprisingly little is known about the characteristics of banks and small business and their rela-tionships with each other.In this paper,we examine bank types and their relationships with small business.
Banks often extract proprietary information from strong relationships and u this information to t contract terms and make credit underwriting decisions.The extant rearch suggests that small business benefit from relationships in terms of credit availability,credit terms,and firm performance.Yet strong relationships,particularly when they are exclusive,may also
involve costs associated with a hold up problem –extraction of rents from a captured firm –or with the potential for premature withdrawal of rvices if the bank becomes financially distresd or fails.Exclusive relationships with certain types of banks may also be inherently more fragile if the types are more likely to ver small business relationships or withdraw credit than other types.Firms often bear the duplicative costs of multiple banking relationships to mitigate the problems.
Arguments in the literature suggest that small banks are better able to form strong relationships with informationally opaque small business,while large banks tend to rve more transparent firms becau dealing with opaque firms requires the u of soft information and such information is difficult to quantify and trans-mit through the communication channels and layers of manage-ment of large organizations (e.g.,Berger and Udell,2002;Stein,2002).Much of the early empirical literature provides support for this conventional paradigm (e.g.,Haynes et al.,1999;Cole et al.,2004;Scott,2004;Berger et al.,2005b ).1By extension,the argu-ments about the difficulties of large banks in dealing with the soft information of opaque small firms may apply to multimarket and
dx.doi/10.1016/j.jbankfin.2014.03.0160378-4266/Ó2014Elvier B.V.All rights rerved.
q
The views expresd in this paper are tho of the authors only,and should not be interpreted as reflecting the views of the Federal Rerve Board of Governors,its staff,or the Federal Rerve System.
⇑Corresponding author at:University of South Carolina,United States.
E-mail address:aberger@moore.sc.edu (A.N.Berger),ulding@sloan.mit.edu (W.Goulding),tara.v (T.Rice).1
Also consistent with the conventional paradigm,Gilje (2012)finds that a higher local market share for small banks increas the number of establishments in industries most dependent on external finance when local deposits increa.
nonlocal banks as well.Thus,it is expected under the conventional paradigm in the literature that opaque small business would be best rved by small,single-market,local banks,while large,multi-market,nonlocal institutions would tend to rve more transparent firms.
If this conventional paradigm is correct,banking industry consolidation may have significant conquences for the effective-ness of banking relationships with small business.Small banks, single-market banks,and local banks may more often function as ‘‘community banks’’that u soft information gathered from rela-tionships with thefirm,its owner,and local community,while large banks,multimarket banks,nonlocal banks may act more as ‘‘megabanks’’with weaker community ties that ba their relation-ships primarily on hard information about thefirm.Bank consoli-dation may also affect the competitiveness of local banking markets,which may alter the strength of relationships and the benefits and costs of the relationships to small business.
The large banks,multimarket banks,and nonlocal banks created by consolidation may be disadvantaged in relationships bad on soft information and may be more likely to ver relationships or withdraw credit than the small,single-market,and local institu-tions they replace.During thefinancial crisis of2007–2009,small business saw their bank borrowing contract precipitously. Numerous reports cite small business owners’difficulty in obtain-ing access to credit over the crisis period,particularly from large banks.2
Recently,however,a number of articles challenge the conven-tional paradigm and allow for the possibility that technological progress and deregulation has made it easier for large,multimar-ket,and nonlocal banks to rve small,opaquefirms.Berger and Udell(2006)suggest that large banks may be able to rve opaque firms well using hard-information technologies,such as credit scoring and lending againstfixed ast collateral(real estate,motor vehicles,or equipment)with values that are relatively easy to asss.A number of empirical articles suggest that very large banks are able to increa their lending to opaque small business using credit scoring ,Frame et al.,2001,2004;Berger et al.,2005a)and two studies suggest that small business credit scoring is responsible for an increa in lending distance over time (Frame et al.,2004;DeYoung et al.,2011).Empirical results in Berger et al.(2007)do not suggest a significant net advantage or disadv
antage for large banks in small business lending overall,or in lending to informationally opaque small business in particu-lar.Rather,the relative convenience of large banks,reprented by their local market share of deposits,appears to be most impor-tant variable in determining lender size.Berger and Black(2011)find that large banks tend to lend more to both the smallest and the largest small business,with small banks specializing in lend-ing to medium-sized smallfirms.Canales and Nanda(2012)find that large banks with decentralized decision making lend more to small business and respond more to local market competition, consistent with behavior typically associated with small banks that make relationship loans.Berger and Black(2011)and Berger et al. (2011)find that small banks also u hard-information technolo-gies,fixed ast lending and credit scoring,respectively,in addition to relationship lending.de la Torre et al.(2010)find that both large and small banks cater to smallfirms.Finally,one paperfinds that the conventional paradigm held for recent startups in the mid-2000s–in that a higher local market share of offices owned by small banks resulted in more bank credit to startups–but did not hold for thefirms in the recentfinancial crisis(Berger et al.,2014).3
Despite the important issues and the recent controversy over the conventional paradigm,surprisingly little empirical effort has been devoted to investigating the type of bank that te
nds to rve as the main relationship bank with opaque small business and which types of main banks tend to be associated with stronger relationships with thefirms.The objective of this paper is to expand the literature along the lines.For our purpos,we define afirm’s‘‘main’’relationship bank as the‘‘primary’’financial institution identified by thefirm.We test hypothes about the role of main bank type–small versus large,single-market versus multimarket,and local versus nonlocal banks–in banking rela-tionships.In effect,we expand the conventional paradigm about the roles of small banks to single-market and local banks and the roles of large banks to multimarket and nonlocal banks,and test the conventional paradigm.Specifically,we test whether ‘‘megabanks’’(large,multimarket,nonlocal)less often rve as the main relationship bank than‘‘community banks’’(small,sin-gle-market,local)for opaque small business,and whether the main bank relationships of megabanks are weaker than tho of ‘‘community banks.’’Our application matches U.S.small business data from the2003Survey of Small Business Finance(SSBF)to the Consolidated Reports of Condition and Income for U.S.Banks (Call Reports)on the banks that provide them with credit and other rvices,and the Summary of Deposits data on the conditions in their local banking markets.
We conduct two ts of tests.First,we test for the type of bank rving as the main relationship bank i
dentified by small busi-ness.Prior analys of U.S.data typically do not focus on main banking relationships–they usually examine the relationship for a single loan at a time,and often do not match the loan to the bank type.4We include exogenous variables measuringfirm ,firm size and age,ownership type,and industry),principal owner ,if owner is also manager,has majority share,has had personalfinancial problems),and local banking mar-ket ,concentration,market shares of large and multi-market banks,bank offices per capita,state banking restrictions).We test the hypothesis from the conventional paradigm that relatively opaquefirms–measured byfirm size,age,owner involvement, and veral other characteristics–tend to have their main banking relationship with small,single-market,and local banks.Under the paradigm,the banks are expected to have advantages in soft-infor-mation-bad relationships relative to large,multimarket,and non-local banks,respectively.More transparent small business that rely more on hard-information-bad relationships are expected to have their main relationships more frequently at large,multimarket, and nonlocal banks.In contrast,bad on the recent literature,it could be the ca technological progress and deregulation have made it easier for large,multimarket,and nonlocal banks to rve small,opaquefirms,and small,single-market,local banks no longer have a comparative advantage in rving as the main banks for the firms.
Second,we test for the strength of the main relationships by examining the probability of an exclusive relationship versus multiple banking relationships and the length of a relationship as functions of the main bank type and itsfinancial fragility,as well
2Testimony of Governor Elizabeth A.Duke before the Committee on Financial Services and Committee on Small Business,U.S.Hou of Reprentatives,Washing-ton,DC,February26,2010(v/newvents/testimony/ duke20100226a.htm)and National Federation of Independent Business,Small Credit in a Deep Recession,February2010.
3In a related paper,Durguner(2012)shows that the importance of small business lending relationships in determining loan contract terms has diminished over time. Consistent with this,van Ewijk and Arnold(2013)find that U.S.banks have shifted from relationship-oriented models towards transactions-oriented models over time. 4Studies of German hausbanks are exceptions in which main banking relationships are examined.Hausbanks are found to provide liquidity insurance to their customers (e.g.,Elsas and Krahnen,1998).Hausbanks are also found to have better access to information,more influence on borrower management,and to provide relatively high shares of borrower debt(Elsas2005).
A.N.Berger et al./Journal of Banking&Finance44(2014)264–278265
asfirm,owner,and market characteristics.Under the conventional paradigm,relatively small,youngfirms with more‘‘important’’principal ,owner–managers with large stakes in their firms)and otherwi opaque small business tend to have stronger,more exclusive relationships to deal with their soft infor-mation problems,whereas larger,more mature,firms with less ‘‘important’’principal owners may more often engage in multiple banking to reduce hold up andfinancial distress concerns.Larger firms may also more often have multiple banks becau a single bank cannot provide all thefinancial rvices they need.In addi-tion,under the conventional paradigm,it is expected that–even after conditioning onfirm and owner characteristics–relation-ships with small,single-market,and local banks or‘‘community banks’’are likely to be stronger and more exclusive than tho with large,multimarket,and nonlocal banks or‘‘megabanks’’becau the former relationships are more likely to be bad significantly on soft information.In addition,firms may avoid single relation-ships with‘‘megabanks’’becau of the fragility of the relation-ships.The banks may have weaker ties to the local community and may be more likely to ver small business relationships or withdraw soft-information-bad credit than‘‘community banks.’’However,some of the recent literature suggests to the contrary that‘‘megabanks’’may be able to u hard information to have stronger and less fragile relationships with small,opaque business.
By way of preview,our empirical results are often not consis-tent with the predictions of the conventional paradigm.In thefirst test,wefind that opaque small business are not more likely to have a community bank as their main bank.In the cond test, wefind mixed evidence on whether opaque small business have stronger relationships with their main banks,but the evidence is clearer that strength does not depend on the type of bank.
We conjecture that the conventional paradigm may not hold becau of two important changes in the banking industry over time:(1)changes in lending technology,specifically the introduc-tion of credit scoring in small business lending,and(2)changes in bank regulation(such as the Riegle Neal Interstate Banking and Branching Efficiency Act of1994(IBBEA))that allows large,multi-market,and nonlocal banks to integrate offices across state lines.
The remainder of the paper is organized as follows.Section2 briefly reviews the relevant literature on banking relationship strength and associated rearch and policy issues.Section3dis-cuss the data t and provides summary statistics.Section4pre-nts the empirical methodology.Section5prents the empirical results,and Section6concludes.
2.Brief review of the relationship strength literature and associated issues
2.1.Relationship strength
Relationship strength is generally measured by the length or breadth of the relationship,or whether the bank is the exclusive provider offinancial rvices.Strong relationships may often be needed to extract proprietary soft information and to lend to small firms without sufficient hard information on which to ba credit decisions.Firms of all types may also benefit from strong banking relationships in which the bank is able to‘‘reu’’hard and soft information garnered over the cour of the relationship from loans,deposits,or other rvices to t contract terms or make credit underwriting decisions.As will become clear,the literature suggests that different types of banks–small versus large,sin-gle-market versus multimarket,and local versus nonlocal–may have different abilities to maintain strong relationships with small business.2.2.Benefits from strong relationships
Most empirical studiesfind benefits to borrowers from strong relationships.The rearch oftenfinds that stronger relationships are associated with better credit availability,as measured by a higher loan application acceptance rate,less dependence on expen-sive trade credit,or fewer collateral ,Petern and Rajan,1994,1995;Berger and Udell,1995;Cole,1998;Elsas and Krahnen,1998;Harhoff and Korting,1998;Machauer and Weber,2000;Moro and Fink,2013).Studies of U.S.small busi-ness typically alsofind lower loan interest rates when relation-ships are stronger(e.
g.,Berger and Udell,1995;Bharath et al., 2011),although European studies often yield no significant effects of relationship strength on ,Elsas and Krahnen,1998; Harhoff and Korting,1998;Machauer and Weber,2000;Degry and Van Cayele,2000).Some studies also discover favorable effects of strong relationships onfirm performance.Specifically, one study of publicly traded paniesfinds that strong rela-tionships increa the likelihood of success of moderatelyfinan-cially distresdfirms(Ronfeld,2011),another studyfinds that relationships aid in resolution of Chapter11bankruptcy proceed-ings(Dahiya et al.,2003),and a study of Italian manufacturers yields a positive association between relationship strength and innovation by borrowingfirms(Herrera and Minetti,2007).5
2.3.Costs to strong relationships that may result in multiple banking
Strong relationships–particularly when they are exclusive–may also involve costs.The private information generated by an exclusive banking relationship may give the bank market power over thefirm,yielding a hold up problem and extraction of rents from thefi,Sharpe,1990;Rajan,1992).Firms may bear additional costs to engage in multiple relationships to mitigate the rent ,Von Thadden,1992;Boot,2000;Farinha and Santos,2002;Elsas et al.,2004).6
Firms may also bear the duplicative costs of multiple banking instead of a single strong banking relationship to protect them-lves from premature withdrawal of rvices if their main bank becomesfinancially distresd or fails.Thus,firms may be more likely to have multiple banking relationships when their main bank isfinancially fragile and likely to become distresd or fail.The empirical literature on this topic is mixed,with studies in some casfinding positive,negative,and/or no consistent effect of bank fragility on the probability of multiple ,Detragiache et al.,2000;Ongena and Smith,2000;Berger et al.,2001,2008).7 The concept of relationship fragility may also be extended to apply to bank type if some types of banks are more likely to ver relationships or withdraw critical rvices,independent of the bank’sfinancial condition.In this regard,there is no literature on small versus large,single-market versus multimarket,or local ver-sus nonlocal banks on relationship verance.However,there are related studies on the effects of domestic versus foreign banks–an extreme form of local versus nonlocal banks.One study of Indian banking suggests that foreign banks have weaker ties to the country and may be more likely to ver relationships with localfirms than state-owned banks with mandates to rve localfirms(Berger et al., 2008).A related literaturefinds that foreign banks generally 5One study also documents some of the benefits to lenders from relationships in terms of incread future profitable lending opportunities(Bharath et al.,2007).
6The extraction of rents may also make it profitable for banks to lend to some additionalfirms with marginal credit quality,improving the credit availability of the marginalfi,Petern and Rajan,1995).
7A possible issue with the studies is that they typically do not measure the fragility of the main bank,but rather the fragility of one lending bank or all of the firm’s banks.We argue that the fragility of the main bank is the most logical choice, bad on the assumption that the main bank is determinedfirst.
266 A.N.Berger et al./Journal of Banking&Finance44(2014)264–278
reduced lending more than domestic banks during crisis periods (Klein et al.,2002;Claesns and Van Horen,2011;de Haas and Van Lelyveld,2011;Popov and Udell,2012;Ongena et al.,2012).8 In the prent context,it may be analogously expected that large, multimarket,and nonlocal banks have weaker ties to the local com-munity and may be more likely to ver small business relationships or cut off credit than small,single-market,and local institutions, respectively.
Finally,firms may more often bear the duplicative costs of mul-tiple banking when one bank cannot provide all of theirfinancial rvice needs.This is likely to occur for some of the largest of the small bu
siness studied here,which may be geographically dis-perd,requiring rvices in more markets than are rved by thefirm’s main bank.Multiple banks may similarly be needed if thefirm requires international rvices or specialized investment products not provided by thefirm’s main bank.Empirical rearch typicallyfinds that largerfirms are associated with multiple ,Houston and James,1996;Machauer and Weber,2000; Ongena and Smith,2000;Berger et al.,2001,b;Berger et al.,2008).9 2.4.Strong relationships and bank consolidation issues
Some rearch and policy issues concern the effects of bank con-solidation on relationships.Much of the relationship lending litera-ture focus on the effects of bank size,hypothesizing that larger banks are disadvantaged in relationships to smallfirms bad on soft information due to difficulties in processing and transmitting soft information through the communication channels of large ,Stein,2002),agency problems within large organizations with more layers of management becau the loan officer is the main repository of soft ,Berger and Udell,2002),and/or organizational diconomies of dealing with using hard-information-bad technologies for somefirms along with soft-information-bad technologies for otherfi, Williamson,1988).Large banks may have a comparative advantage in relationships with largerfirms due to economies of scale in pro-cessing and transmitting hard information.
Some empirical rearch is consistent with the expectations that large banks are less likely than small banks to lend to or have strong relationships with small,youngfirms with little hard infor-mation available and converly for relationships with large, maturefirms with more hard information ,Haynes et al.,1999;Cole et al.,2004;Scott,2004;Berger et al.,2005b). Thus,bank consolidation may have unfavorable implications for firms relying on relationships that make primary u of soft infor-mation and converly forfirms relying on relationships bad pri-marily on hard information.10
Presumably,arguments similar to tho bad on bank size apply to the geography of banks–single-market and local banks are more likely to have a comparative advantage in relationships bad on soft information,and multimarket and nonlocal banks are more likely to have a comparative advantage in hard-information-bad relationships.Some industrial organization rearch on banking focus on differences in competitive behavior and efficiencies of multimarket versus single-market banks and their effects on small business and consumers,but does not examine the role of ,Hannan and Prager,2006;Berger et al.,2007; Cohen and Mazzeo,2007;Berger and Ostromogolsky,2009).Simi-larly,there has been rearch showing that lending distances have incread over time,with more small business borrowing from nonlocal ,Petern and
Rajan,2002;Hannan,2003; Brevoort and Hannan,2006).This literature also usually does not focus on relationships,despite the likely role of soft information in local relationships and hard information in nonlocal relation-ships.Thus,the consolidation of the banking industry may be expected to shift resources from small,single-market,and local banks to large,multimarket,nonlocal institutions,with potentially significant conquences for banking relationships and their bene-fits to small business.
Consolidation may also affect the competitiveness of local banking markets.Mergers and acquisitions(M&As)within markets likely reduces competitiveness and M&As across markets likely increa competitiveness.Relationship strength and its con-quences may be greater when banking markets are less competi-tive,becaufirms have fewer potential alternatives in the future event that their main bank tightens contract terms dramatically. Empirical studies of the effects of concentration and other restric-tions on competitiveness on measures of credit availability,activ-ity,and general economic performancefind both favorable ,Petern and Rajan,1995;Cetorelli and Gambera, 2001;Bonaccorsi di Patti and Dell’Ariccia,2004;Cetorelli,2004) and unfavorable ,Black and Strahan,2002;Berger et al.,2004c;Karceski et al.,2005;Cetorelli and Strahan,2006; Chong et al.,2013).
3.Data and summary statistics
We combine data from the SSBF with the Call Reports.The SSBF is a survey by the Federal Rerve of thefinancial condition offirms with fewer than500full-time-equivalent employees.The survey wasfirst conducted in1987and repeated in1993,1998,and 2003.It contains details on small business’income,expens, asts,liabilities,and characteristics of thefirm,firm owners,and the small business’financial relationships withfinancial rvice suppliers for a broad t of products and rvices.The sample is randomly drawn but stratified to ensure geographical reprenta-tion across all regions of the United States.The SSBF also oversam-ples relatively largefirms(conditional on having fewer than500 workers).Given the above data,we can measure asts,liabilities, profits,firm age,and the length of timefirms have established rela-tionships with banks and other lenders.We also know the location offirms,so we can control for local market conditions.
Petern and Rajan(1994)and Berger and Udell(1995)are among thefirst to u the data from the1987survey.The papers bothfind that banking relationships expand credit availability for smallfirms.Other authors also u later waves of the data to study whether bank size affects credit allocation , Cole,1998;Jayaratne and Wolken,1999;Cole et al.,2004;Berger et al.,2005b;Berger and Black,2011).Our paper is thefirst to u the data to test role of bank type–sm
all versus large,sin-gle-market versus multimarket,and local versus nonlocal banks –in banking relationships.
The SSBF data contain information on up to20financial rvices firms with which a small business may have a relationship, including thefirm’s‘‘primary’’or main bank.11We match the small
裤子最小码是多少8However,it is possible that the major reason for the obrved decrea in lending during the crisis is the decrea infirms’demand for credit.For example,Kremp and Sevestre(2013)find that despite the stronger standards ud by banks when granting credit,small business in France do not appear to have been strongly affected by credit rationing since2008.
9Other motives for multiple banking relationships are discusd in Berger et al. (2008).
10However,some rearchfinds that market reactions may offt some of the conquences.Some studies of bank mergers and acquisitionsfind that small business lending appears to decline at consolidating institutions,but may be offt by incread lending supplies by other banks in the market or through incread market
entry of newly chartered ,Berger et al.,1998;Avery and Samolyk2004; Berger et al.,2004a).
11Unfortunately,it is not possible to identify a‘‘Second Main Bank Type,’’as no priority is given to the other institutions that providefinancial rvices.
A.N.Berger et al./Journal of Banking&Finance44(2014)264–278267
business’main banks with the Call Reports,which containfinan-cial statement and structure data on all cial banks.We exclude a number offirms from the sample.Of the4240firms in the SSBF,3350are in metropolitan markets.We restrict our study to metropolitan markets becau lending practices vary greatly between metropolitan and rural markets,and the sample of rural banks would be too small to analyze.DeYoung et al.,2012find fun-damental differences between small rural and metropolitan business borrowers and conclude that divergent lending practices made necessary by the differences may result in a greater number of small rural commercial banks than would be expected.
Of the3350metropolitanfirms,2846identified a commercial bank as their primary institution.We drop the other504firms from the sample that either did not have a commercial bank as a primary institution or provided an incomplete respon to the question, leaving the identity of the main institution uncertain.Another 232firms could not be matched to the Summary of Deposits data to gath
家长会er information on their local market conditions,and another 4firms were eliminated becau their industry perfectly predicted whether it had its main bank relationship with a multimarket insti-tution,leaving2610obrvations that could be ud in our regres-sions of main bank type(described below).We lo another27 obrvations,leaving a total of2583,for our regressions of relation-ship strength becau we did not have the requisite8quarters of prior data to compute one of our bank risk measures,the Z-score.
Table1Panel A reports the definitions of the variables ud in the analys taken from the2003SSBF matched with the Call Reports.Thefirm characteristics include measures offirm size, minority ownership,age,risk,and industry,and if thefirm has a bank loan.Forfirm size,we specify dummies for small,medium, and largefirms,with total asts6$100,000,$100,000–$1mil-lion,and over$1million,respectively,with smallfirms excluded as the ba ca in the regressions.Note that the are relative sizes within the broader category of small business that are in the SSBF,and do not include the largestfirms in the nation.Prior rearchfinds significant differences across the three size class in the comparative advantages of large and small banks in using different lending technologies(Berger and Black,2011).Forfirm age,we simply specify the natural log of age.Age is a measure of opacity and has been found to affect the likelihood of borrowing from large banks in prior
,Berger et al.,2005b, 2007).Forfirm risk,we include a measure of credit score,leverage, and a dummy that equals1if the business has been delinquent in the past three years.We also control for industry type with a t of dummies for one-digit SIC codes(not shown in tables for brevity).
The owner characteristics include measures of organizational form and the involvement or‘‘importance’’of the principal owner in the life of thefirm.Organizational form includes dummies for whether thefirm is a corporation,partnership,or proprietorship, as the forms offer thefirm different protections of asts in the event that they do not repay their bank credit and may also reflect the need for soft information in their banking relationships.We include variables measuring whether the principal owner of the firm is also the manager,and whether thefirm is owned exclu-sively by a single family.When the owner is also the manager and/or has a large stake in thefirm,it is more likely that the main relationship with thefirm will require significant collection of soft information about the owner.Thus,when the owner is more ‘‘important,’’thefirm may be more likely to have a main relation-ship with a small,single-market,or local bank to deal with the soft information under the conventional paradigm.Alternatively,when the owner is more‘‘important,’’large,multimarket,or nonlocal banks may be more likely to have the main relationship becau credit scoring is mostly bad on the consumer information on the owner,which may be more important when the owner is more important to thefirm.
Turning to main bank characteristics,we u a size cutoff of $1billion in gross total asts(GTA)to distinguish between small and large banks following prior rearch on the empirical definition of‘‘community banks’’(e.g.,DeYoung et al.,2004).Also following prior rearch and anti-trust guidelines,we define a sin-gle-market bank as one in a single metropolitan market–a Metro-politan Statistical Area(MSA)or New England County Metropolitan Areas(NECMA)in which the small business is located.All banks with branch offices in two or more metropolitan or rural markets are defined as multimarket banks.Main banks that do not have a banking office in thefirm’s local market are designated as nonlocal. In some specifications,we replace the main bank size dummy with the log of bank asts and the multimarket dummy with the num-ber or log of the number of markets in which the main bank has offices.In some specifications,we also account for thefinancial fra-gility of the main bank by including its equity to gross total asts (GTA)ratio,its ratio of nonperforming loans to total loans,a mea-sure of its illiquidity(liquidity creation to GTA ratio,taken from Berger and Bouwman,2009),its ratio of fee income from deposits to total revenues as an inver measure of nontraditional activities (similar to Lozano-Vivas and Pasiouras,2010and DeYoung and Torna,2013),and its Z-score computed over the prior12quarters (or8–11quarters if12quarters are unavailable),similar to Laeven and Levine(2009)and Mercieca et al.(2007).
Banking relationship variables include a dummy for an exclu-sive bank-firm relationship.We also u a measure of length of the relationship with the main bank.
Turning to local market characteristics,in the small bank versus large main bank estimation(described more in Section4),we also include a variable to measure the share of local market offices owned by large banks.This is included as a proxy for the relative convenience of large banks.It is expected thatfirms are more likely to have their main relationship at a large bank if the market pres-ence of this bank type is greater,all el equal.12Similarly,we include multimarket bank share of local market offices in the sin-gle-market versus multimarket bank equation to account for the rel-ative convenience of multimarket banks.In the local versus nonlocal bank equation,we include local bank offices per capita as an indica-tor of the relative convenience of local banks.In all the regressions, we include a control for the Herfindahl–Hirschman Index of local banking market concentration(HHI),which may or may not be an inver indicator of competition(Berger et al.,2004b).We also include an interstate branching index to control for regulatory and competitive conditions(Rice and Strahan,2010).
Summary statistics on the variables are shown in Table1 Panel B.We briefly discuss some of the here.On average,firms in our sample are about17years old,and69%are organized as cor-porati
ons.The leverage ratio debt-to-ast ratio of the averagefirm is33%,and about half of thefirms have a bank loan.Less than one percent offirms in our sample have declared bankruptcy in the past7years.Thefirms are largely family owned and operated –81.5%offirms are family owned and88%are owner-managed.
Over three-quarters of thefirms in our sample have large banks as their main banks,and over60%have multimarket or nonlocal banks as their main banks.13The majority offirms(57%)in the sam-ple state that they have only one bank and the average main bank relationship is11years.The high proportion offirms that have large, 12Prior rearchfinds that the local market share of large banks is a powerful predictor of lending bank ,Berger et al.,2005b;Berger et al.,2007).
牛血13The mean size of the main bank is quite large–over$140billion in gross total asts–much larger than the mean bank in the nation.This is becau the obrvations are by the small business relationships rather than by banks,and the largest banks tend to have many more small business relationships than the smallest banks.Similarly,mean number of markets of the main bank is very large at129 becau the banks with the most markets tend to have many more small business relationships than the banks with the fewest markets.
268 A.N.Berger et al./Journal of Banking&Finance44(2014)264–278
