Presentation on theme: "SME-Bank financing relationships within regional European areas Steve MerciecaSimon Wolfe University of SouthamptonUniversity of Southampton."— Presentation transcript:
SME-Bank financing relationships within regional European areas Steve MerciecaSimon Wolfe University of SouthamptonUniversity of Southampton
Outline (I)Rationale/contributions (II)Related Research (III)Data (IV)Methodology and empirical analyses (V) Preview of results (VI)Conclusion and future research SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe
Motivation for this Research 1. 1.SME importance in Europe 2. 2.Focus on Regional areas of Europe 3. 3.Regional SME and Bank Interaction 4. 4.Bank Competition and Market Structure (I) – Research Rationale First paper, to best of our knowledge, that investigates: i) i) Determinants of regional SME bank relationships with a european cross-country sample; ii) ii) Regional growth characteristics; iii) iii) Impact of Competition / Concentration on SME-bank financing relationships We investigate the determinants of multiple bank relationships based on Regional SME firm, bank, market and financial system architecture characteristics. SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe How do observed changes in bank market structures affect the number of bank relationships maintained by SMEs?
For the purpose of our research ‘bank financing relationship’ refers to SME financing for the following purposes: For example: Firm start-up; Product development; Purchases of fixed assets; Cash flow; Other business/company acquisition; Bridge while raising next funding round; Seasonal production/trading; Research Excludes bank financing relationship that is based only on the deposit accounts and cheque usage. SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe (I) – Research Rationale
One Bank R’ship vs > 1 Bank R’ship Banks as investors devoted to reducing monitoring, screening, or renegotiation costs ( Diamond:1984, Bhattacharya and Thakor:1993 ) 1. Superior information enables single bank to extract monopoly rents. Competition from additional informed bank eliminates ‘hold-up’ costs Sharpe (1990), Rajan (1992) 2. Diversification (Detragiache 1999) 3. Refinancing of unprofitable projects (Dewatripont & Maskin 1995) 1. 1.Easier access to credit Petersen & Rajan (1994) 2. Pre-existing relationship as source of Financial services has effect on potential lender’s decision to extend credit (Cole, 1998) SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe
Study Main investigation SampleFindings Harhoff & Korting (1998) Investigate lending r’ships to explore the nature of firm-bank r’ships and their impact on the collateral requirements, cost, availability of external finance for SMEs. German survey data Number of r’ships increases with firm’s age, size, leverage and more R&D. Firms that experienced financial distress have more r’ships. Elsas & Krahnen (1998) Comparison between house-bank financing and normal bank financing German dataset View that house-banks are able to establish a distinct behavioural pattern consistent with idea of long-term commitment Elsas (2005) Which factors determine whether a particular bank lender is a r’ship lender. SME corporate borrowers Variables related to information access of banks and influence on borrower management are important determinants. Three potential determinants of r’ship financing are identified: borrower, bank & market characteristics. Ongena & Smith (2000) Analyse determinants of number of bank r’ships on European cross-country basis Large firm dataset Firms in countries with relatively stable and un-concentrated banking systems maintain more bank r’ships, whilst firms in countries with strong judicial systems and strong creditor protections maintain fewer bank r’ships. Angelini et al. (1998) Investigate the effects of firm-bank relationships on the cost and availability of credit focusing on possible differential effects related to the local and/or cooperative nature of lending banks. Small Italian firms sample They find that with banks other than cooperative banks, lending rates in Italy tend to increase in the duration of a relationship. SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe (II) – Related Research
Although most of these studies focus on developing/rural economies, analogous mechanisms may also be mirrored in regional communities of industrialised countries Study Main investigation SampleFindings Banerjee et al. (1994) Besley & Coate (1995) Present theory of ‘long-term interaction hypothesis’ Agents who take part in the life of community share information that would be available to an outsider only at a cost. Banks operating in small communities, may take advantage of such information in its financing activities. Degryse & Ongena (2003) “if local market conditions matter, they should matter the most for small firms, which have difficulty in raising funds at a distance, than for large firms” Affinito & Piazza (2005) Investigate characteristics of European regional banking systems through analysis of structural variables Presence of linguistic minorities and smaller non-financial firms favour a more local character of the regional banking system and reduces the average size of its banks. Ferri and Messori (2000) Analyse extent and impact of r’ship banking in Italy’s three sub-systems: North, Centre, South. Italian Dataset R’ship banking is more extensive in areas were small businesses prevail and suggest that relationship banking may be beneficial or detrimental depending on the socio-economic structure SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe (II) Related Research
Fears that consolidation decreases the number of banks specialising in relationship banking (e.g. community banks) with possibly detrimental welfare effects for local firms, especially SMEs, these firms’ 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)] SME bank financing within EU regional areas Increasing degrees of competition in European Banking Systems Staikouras and Koutsomanoli-Fillipaki (2006) and Schaeck and Cihak (2007) Wave of consolidation across European banking systems resulting from an increasing number of M&As. Goddard et al. (2007), de Guevara et al. (2005), and Amel et al. (2004) Mercieca and Wolfe Mercieca and Wolfe (II) Related Research
SME bank financing within EU regional areas Beneficial effects arising from increased competition in banking systems for the provision of banking services may be offset by higher degrees of concentration in banking systems. As part of our empirical investigation, we seek to answer this question as the extant literature on the effect of market structure and competition on SME financing offers two contrasting theories Mercieca and Wolfe Mercieca and Wolfe ‘MARKET POWER’ notion contends that competition enhances access to credit, ‘MARKET POWER’ notion contends that competition enhances access to credit, (Elsas, 2005; Boot, 2000; Boot and Thakor, 2000, Ongena and Smith, 2000) ‘INFORMATION HYPOTHESIS’ argue that less competition improves credit availability (Dell’Ariccia and Marquez, 2005; Petersen and Rajan, 1995) These contrasting findings may be due to the way competition is determined in empirical studies that frequently proxy competition with concentration measures. This assertion places our paper into a growing body of work by Beck et al. (2006), Claessens and Laeven (2004), Carbo et al. (2006), Schaeck et al. (2006), and de Guevara et al. (2005) indicating that concentration is a poor proxy for competition and that concentration and competition describe different characteristics of banking systems (II) Related Research
(III) - Data Definition of SMEs The European Union 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. Evolution of SME in Europe SME represent 99% of all companies in the EU. They are the biggest sector of the EU economy, with 23 million enterprises employing around 75 million people. Responsible for the creation of one in every two new jobs. SME produce considerably more than half the EU's GDP. SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe
2002 ESRC survey conducted by the Centre for Business Research of the University of Cambridge; Survey focuses on the funding of SMEs in three different regions of Europe between March and October 2001: South East of England, Bavaria in Southern Germany and Emilia-Romagna in Italy; 191 questions for Germany and the UK and 188 questions for Italy; Questionnaire yielded 247 responses for the UK, 161 for Italy and 114 for Germany; Questions from the survey cover a variety of topics including: the main markets serviced; the type of finance used and for what reasons; whether firms have used bank finance; the role that banks play; and whether firms have utilised Venture Capital. (III) - Data SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe
SME Survey Summary Statistics _________________________________________________________________________________________________________________________ ItalyGermany UK Bank Relationships01>101>10 1 >1 _________________________________________________________________________________________________________________________ Total Observations161114 247 Number of Observations2026115632328134 106 7 % of Total Observations12.416.171.455.320.224.654.3 42.9 2.8 Oldest Trading SMEs1932192719051900186816021926 1926 1959 Youngest SMEs199919992001200120012001 2001 2001 1998 Changed ownership8839461515119 95 6 TurnoverSum56653681335977200 214 15 Average22.214.171.124.112.572.751.49 2.02 2.14 Private Company4933482020131 106 7 Public Company16178215383 0 0 EmployeesSum40412561336287195 205 18 Average21.5126.96.36.1993.111.46 1.93 2.57 R&D Investment (1=yes)20126541121350 49 3 Distance (miles) Average01.121.1001.131.250 1.41 1.43 Favourable Terms (1=yes)02694020220 85 4 Regional Bank02310509240 104 6 National Bank0310015200 2 2 SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe (III) - Data
(IV) - Methodology We employ firm-level regressions of the number of bank relationships on firm, market and regional/country specific variables; The dependent variable used in econometric model is the multi-bank relationship variable; SMEs are categorised between those having no bank financing relationships, 1 bank financing relationship, and those have >1 bank financing relationships. Survey does not present precise number of bank relationships beyond 1; Because our dependent variable is discrete-valued, OLS is not suitable and we report estimates of the firm-level model using a Tobit specification. where yi denotes the number of bank relationships of SME i, is the constant term and denotes the coefficients to be estimated for the explanatory variables xi; ui is the error term SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe
(IV) - Methodology The Panzar and Rosse (1987) H-Statistic Measures market power by the extent to which changes in factor input prices translate into equilibrium revenues by bank i. H-Statistic is analytically superior to other measures for competition (used in the empirical banking literature) as it is derived from profit-maximising equilibrium conditions (Shaffer, 2004a). It is widely used in the banking literature (e.g. Shaffer, 1982; Molyneux et al., 1996; DeBandt and Davis, 2000; Bikker and Haaf, 2002; Claessens and Laeven, 2004; Carbo et al., 2006; Schaeck et al. (2006) SME bank financing within EU regional areas Mercieca and Wolfe Mercieca and Wolfe We adopt our H-Statistic variables from Schaeck and Cihak (2007) who include all savings, cooperative and commercial banks operating in Italy, Germany and the UK in 2001. The sample is split between large and small banks to highlight potential differences. The results are then averaged for the year since competition in the market is arising from both small and large banks.
(IV) – Methodology – Firm level Variables Variable Type (from ESRC survey) VariableDescription Firm-levelTurnover Measure of firm size and possibly indication of market power in financing negotiations R&D Measure for entrepreneurial innovation 1 = engage in R&D, 0 not Year Ranges between 1700-2001 and is the difference between 2001 and the year the SME began trading. Type of Company Whether the SME is public or private company (1=public, 0 otherwise). Employees Employees for year 2001. Variable takes value of 1 if between 1 – 9; value of 2 if between 10 - 19; value of 3 if between 20 - 49; value of 4 if between 50 – 99; value of 5 if >=100. Number of bank relationships used regularly as a variable in research (Elsas, 2005; Ongena and Smith, 2000; Cole, 1998; Harhoff and Korting, 1998; Petersen and Rajan, 1994; Houston and James, 1996). Apart from Ongena and Smith however, none examines the determinants of the number of bank relationships. SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe
(IV) – Methodology: Bank & Market Variables Variable Type VariableDescriptionSource Bank-SME Bank Role Takes value of 1 if Bank plays a role for SME being either a seat on the firm’s board; technical advice; management advice; marketing and sales advice; and other roles; 0 otherwise. ESRCsurvey Bank Terms Takes value of 1 if bank’s terms are reasonable, 0 otherwise. ESRCSurvey Distance Distance of main bank from firm. Variable takes value of 1 if = 50 miles. ESRCsurvey Market Structure Stock Markets Stock Market Capitalisation/GDP Stock Market Turnover Ratio Beck et al. (2000) Financial regulation & supervision Activity restrictions, Supervisory Power, Economic Freedom, Banking Freedom Barth et al. (2004) Barth et al. (2004) Financing, Legal, Corruption Obstacles Cost to start up business WBES (2005) Bank Concentration Assets of 3 largest banks as a share of all commercial banks Beck et al. (2005) Regional Regional GDP, Regionally economically active population, Regional Patents Regio Database SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe
(V) – Preview of Results SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe (1)(2) Firm Age 0.7013***0.1575** Firm Type -0.5558***-0.3542*** Ownership Change -0.4275***-0.3037*** R&D investment -0.2023*-0.1183** Turnover0.2963***0.0637** Distance (firm-bank) 0.1996*** Bank Role in Firm 0.3084*** Bank Terms 0.2165*** Amount of Bank Finance used 0.0450** Regional Bank 1.1774*** National Bank 0.9196*** Bank Concentration H-Statistic Observations522522 R-squared0.200.40(3)(4)(5)0.1571**0.1277**0.1048* -0.3493**-0.1303**0.0177 -0.3001***-0.1595**-0.0674 -0.1150**-0.0936*-0.0890* 0.0617**0.02690.0091 0.2037***0.2427***0.2464*** 0.3553***0.4010***0.2530*** 0.2242***0.2085**0.1618*** 0.0427**0.0507**0.0652** 1.1628***1.0929***1.0772*** 0.8535***0.7108***0.8399*** 0.6357**-2.8180*** 1.7312***2.9655*** 522522522 0.400.420.46 Results consistent when sample of SMEs is divided into micro SME sample
(V) – Preview of Results (1)(2)(3)(4)(5)(6)(7)(8) Concentration-0.4442***-1.5006***-0.6918***-0.2560*** -0.6934 *** -0.0278*-0.2796***-0.4929 H-Statistic1.6382**0.8170***0.4081***1.7352***0.7263***0.9785*** 0.2618 *** 1.7976 ** Branches/sq km 0.0080** Regional GDP growth 0.0078*** Reg. Patent Applications 0.0010*** Stock Market capitalisation -0.3130 *** Activity Restrictions -0.2120*** Financing Obstacles -0.7608*** Cost to start business 0.3564** Banking Freedom 0.4141*** Pseudo R 2 0.470.460.460.450.460.460.480.45 Observations522522522522522522522522 SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe
(VI) –Conclusions Conclusion: Precisely, the evidence suggests Firm/Bank/Access to Financial Services/Regional and Market Structure variables are important determinants of SME-bank financing; Regional growth variables are a determinant of SME financing; Competition (H-Statistic) and Concentration are different characteristics of banking systems since they produce contrasting independent results in our regressions; Such evidence suggests that policies that promote competition among banks may have potential to also strengthen the accessibility to bank financing for SMEs. SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe
(VI) –Conclusions Conclusion: This research extends previous work on SMEs by investigating the determinants of regional SME-bank financing relationships. We also investigate how observed changes in bank market structures affect the number of bank relationships maintained by SMEs. Using cross-country data for 3 European regional areas we employ regional variables and bank/firm specific variables to test for the determinants of bank financing relationships. We also employ the Panzar-Rosse H-Statistic and the 3- bank concentration ratio to highlight the difference between concentration and competition. We propose that the contrasting views on competition are due to differences between Competition and Concentration, which, as recent literature shows are different characteristics of the banking system. SME financing, competition and bank market structure Mercieca and Wolfe Mercieca and Wolfe
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