mergers and acquisitions of financial institutions fdic, arlington, va. 30 th november – 01 st...

Mergers and Acquisitions of Financial InstitutionsFDIC, Arlington, VA.

30th November – 01st December 2007

Steve MerciecaSteve Mercieca Klaus SchaeckKlaus Schaeck Simon Simon WolfeWolfeUniversity of SouthamptonUniversity of Southampton Cass Business SchoolCass Business School University University of Southamptonof Southampton

Bank market structure, competition, andSME financing relationships in European regions

What the paper does:

a) We investigate the determinants of multiple bank relationships based on SME firm, bank market, and financial system architecture characteristics.

b) How do changes in bank market structure and competition among banks affect the number of bank relationships that SMEs maintain?

First paper – to the best of our knowledge – that

a) investigates determinants of the number of bank relationships maintained by SMEs

b) disentangles the effects of concentration and competition on bank relationships

c) emphasizes regional perspective

Motivation/Rationale – Related literature – Definitions and Data - Method – Results - Conclusion

Bank market structure, competition, and SME financing relationships in European regions

Steve Mercieca, Klaus Schaeck, and Simon Wolfe

What do we mean by bank financing relationship?Any kind of financing activity, e.g. firm start up, product development, business acquisition, management buy-in/buy-out, stock purchase, tax payments.

Our definition excludes bank relationship based only on deposit accounts/cheque usage.


Why are these issues important?a) In Europe, SMEs account for 99% of all companies, employ around 75 million people and generate one in every two new jobs (European Commission, 2004).

b) Important benefits arise from interaction between borrowers and banks (e.g. Elyasiani and Goldberg, 2004)



Why are these issues important? (cont’d)c) The link between structure and competitive conduct is not clear-cut.

Many previous studies proxy competition by the degree of concentration, with the (implicit) assumption of an inverse relationship between the two!


This however gives rise to several issues:This however gives rise to several issues:

(1) Definition of a market affects measurement of concentration (Shaffer, 2004).

(2) Measures of market structure are not necessarily related to competition (Baumol et al., 1982).

(3) Empirical evidence that concentration and competition describe different characteristics of banking systems (Claessens and Laeven, 2004; Carbo et al., 2006).



One bank relationship vs > 1 one bank relationship

1. Superior information enables single bank to extract monopoly rents. Competition from additional informed bank eliminates ‘hold up’ costs (Sharpe, 1990; Rajan, 1992)

2. Legal setting and institutional environment (La Porta et al., 1997)

1. Easier access to credit (Petersen and Rajan, 1994)

2. Pre-existing relationship as source of financial services has effect on potential lender’s decision to extend credit (Cole, 1998)

3. Diversification (Detragiache et al., 2000)




Market structure vs. competitive conduct

Wave of consolidation across European banking systems due to increasing number of M&As (Goddard et al., 2007), de Guevara et al. (2005), and Amel et al. (2004).

Increasing degrees of competition in European banking systems (Staikouras and Koutsomanoli-Filipaki (2006), and Cihak and a 2nd author (2007)

Fears that consolidation decreases the number of banks specializing in relationship banking (e.g. community banks) with possibly detrimental welfare effects for local firms, especially SMEs, theseFirms’ access to credit, and ultimately, economic growth.

Extensively studied for the US (e.g. Craig and Hardee, 2006; Berger and Udell, 2002; Cole et al., 2004; Berger and Frame, 2005).

Beneficial effects arising from increased competition in banking for the provision of banking services may be offset by greater concentration in banking.

Market power hypothesis: competition enhances access to credit (e.g. Boot and Thakor, 2000)

Information hypothesis: less competition improves credit availability (e.g. Petersen and Rajan, 1995)




Overview on SMEs The EU defines SMEs as enterprises that employ fewer than 250 people, have an annual turnover not exceeding 50 million EUR, and/or annual balance sheet total not exceeding 43 million EUR.


Our dataTaken from the 2002 ESRC survey conducted by the Centre for Business Research of the University of Cambridge.

Survey focuses on funding of SMEs in three different regions in Europe (South east of England, Bavaria in Germany, and Emilia-Romagna in Italy).

Questionnaire contains 191 questions for Germany and the UK, and 188 for Italy. 247 responses for the UK, 161 for Italy, and 114 for Germany.

Questions from the survey include but are not limited to:

• the main markets served• the type of finance used• whether firms have used bank finance• the role played by banks• whether firms make use of providers of venture capital




Number of bank relationships by country

Bank relationships Italy Germany UK

Total observations 161 114 247

Number of relationships 0 1 >1 0 1 >1 0 1 >1

% of Total observations 12.4 16.1 71.4 55.3 20.2 24.6 54.3 42.9 2.8

Italian SMEs tend to maintain the highest number of bank relationships, followed by German and British SMEs.

The UK makes up 47% of the sample, followed by Italy (31%), and Germany (22%).

Source: Survey of the financing of small and medium sized enterprises in Western Europe.




Measuring competition – Panzar and Rosse H-Statistic

H-Statistic measures market power by the extent to which changes in factor input prices are reflected in equilibrium revenues of a bank.

This measure is considered to be analytically superior to (structural) measures of competition because it is derived from profit-maximizing equilibrium conditions (Shaffer, 2004).

The H-Statistic is calculated as follows:

)ln()ln()ln()ln()ln()ln()ln()ln( 44332211332211 YYYYWWWR

R total revenueW1 – W3 input prices (interest expenses + personnel expenses + other operating and admin expenses)Y1 – Y4 control variables

H-Statistic is the sum of the coefficients β1 + β2 + β3.



Estimation strategy

We regress the number of bank relationships on firm, market, and region-specific variables.

The dependend variable is coded as

0 – no bank relationship1 – one bank relationship2 – more than one bank relationship

Caveat: The survey does not provide details beyond more than one bank relationship.

We use both tobit and logit models (for the decision to have more than just one bank relationship) for the empirical setup.

All regressions control for SME characteristics, variables that describe SME-firm relationship, and distance. We also include environmental variables such as regional GDP growth, regionally active population, and concentration in the banking system.





Empirical results Table 2: Tobit model

(1) (2) (3) (4) (5) Firm Age 0.1575**

(0.0610) 0.1571** (0.0605)

0.1277** (0.0566)

0.1048* (0.0551)

0.1078* (0.0648)

Firm Type -0.3542*** (0.0582)

-0.3493*** (0.0580)

-0.1303** (0.0618)

0.0177 (0.0662)

0.0183 (0.0531)

Ownership Change -0.3037*** (0.0527)

-0.3001*** (0.0525)

-0.1595** (0.0526)

-0.0674 (0.0535)

-0.0534 (0.0520)

R&D investment -0.1183** (0.0527)

-0.1150** (0.0525)

-0.0936* (0.0491)

-0.0890* (0.0470)

-0.0639 (0.0521)

Turnover 0.0637** (0.0279)

0.0617** (0.0278)

0.0269 (0.0264)

0.0091 (0.0256)

0.0833 (0.0221)

Distance

0.1996*** (0.0506)

0.2037*** (0.0506)

0.2427*** (0.0478)

0.2464*** (0.0457)

0.2455*** (0.0415)

Bank Role 0.3084*** (0.0621)

0.3553*** (0.0694)

0.4010*** (0.0599)

0.2530*** (0.0628)

0.3012*** (0.0513)

Bank Terms

0.2165*** (0.0651)

0.2242*** (0.0652)

0.2085** (0.0605)

0.1618*** (0.0584)

0.2010*** (0.0602)

Amount of bank finance used 0.0450** (0.0225)

0.0427** (0.0225)

0.0507** (0.0210)

0.0652** (0.0203)

0.0783** (0.0304)

Regional bank

1.1774*** (0.0844)

1.1628*** (0.0845)

1.0929*** (0.0788)

1.0772*** (0.0756)

1.0885*** (0.0801)

National bank 0.9196*** (0.0852)

0.8535*** (0.0946)

0.7108*** (0.0827)

0.8399*** (0.0845)

0.8395*** (0.0851)

HHI

0.6357** (0.4152)

-2.818*** (0.5353)

-0.5148*** (0.0568)

H-Statistic

1.7312*** (0.2435)

2.9655*** (0.3302)

1.6779*** (0.0401)

HHI*H-Statistic

0.3175*** 0.0748

Pseudo R2 0.40 0.40 0.42 0.46 0.46 Observations 522 522 522 522 522




Empirical results (1) Competition and concentration both enter positively and signficiantly

when included in separate regressions.

(2) However, the sign of the coefficient for the HHI becomes negative when we account for the effect of competition as measured by the H-Statistic.

The negative effect of consolidation (or, better, concentrated markets) is aligned with the evidence in Craig and Hardee (2007).

These results imply

(1) Concentration and competition measure different characteristics of banking systems.

(2) The degree of competition should not be proxied with concentration measures.



Access to financial services 0.0080** (0.0037)

Regional GDP growth 0.0078*** (0.0018)

Regional population 0.5959*** (0.1405)

Regional patents 0.0001*** (0.3253)


Empirical results (cont’d)

The effects of competitive conduct and market structure appear to cancel outeach other.

Regional characteristics such as access to banking facilities, regional growth, regional population and regional degree of innovation all tend to be positively associated with the number of bank relationships.




Empirical results (cont’d)

Legal obstacles -1.1850*** (0.2794)

Financing obstacles -0.7608*** (0.1794)

Time to start business 0.0257*** (0.0066)

Cost to start business 0.3564*** (0.0846)

Banking Freedom 0.4141*** (0.0977)

Financing and legal obstacles are inversely related to bank soundness.

Time and cost to start a business motivate banks to set up multiple bank relationships.

SMEs operating in more open banking systems are more likely to have multiple bank relationships.

No effect on the significance/sign of H and HHI in these extensions.




Robustness checks

Our inferences are insensitive to

a) Alternatively computed H-Statistics (interest revenue as dependent variable)

b) Alternative measures of market structure (3 bank concentration ratio instead of HHI)

c) Using a logit model with marginal effects rather than a Tobit model




Economic significance of the effects of HHI and H-Statistics

We assess the affect of HHI and H-Statistics using marginal effects.

Increasing the HHI by one percent decreases the probability of having an additional bank relationship by 0.04 percent.

However, increasing the H-Statistic by one percent increases the probability of having an additional bank relationship by 0.05 percent.

The negative effect of concentration is offset by increasing competition.




Summary

(1) Competition and concentration appear to be different characteristics of banking systems.

Our results support the “market power” hypothesis according to which firms maintain more bank relationships in more competitive banking systems.

(2) We uncover contrasting independent effects arising from both concentration and competition.

(3) Regional characteristics also impact on the number of bank relationships.

(4) Firm size, bank role, and distance are also important determinants of the number of bank relationships.



Caveats/Qualifiers

The comparatively small sample size recommends that we exert some caution when interpreting the results.

However, our findings are aligned with a growing body of empirical work that disentangles the effects of concentration and competition.

We refrain from interpreting the results in a causal sense.





Concluding remarks

(1) To the best of our knowledge, our study is the first one that investigates the determinants of SME-bank financing relationships in Europe.

(2) We also focus on the effect of changes in bank market structure on on the number of bank relationships maintained by SMEs.

(3) Our results suggest that policies that promote competition among banks may have potential to facilitate access to finance for SMEs.

(4) Policymakers’ concerns about the adverse ramifications arising from consolidation in banking may be overstated.



mergers and acquisitions of financial institutions fdic, arlington, va. 30 th november – 01 st...

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