Abstract
Loans to small firms are associated with relationship lending technologies that may be better supported by smaller banks. Whether competition helps or hinders small firm access to finance may depend on the size distribution of banks and the ways in which banks compete. Using cross-country data from surveys of firms and banks and a measure of contestability evidence is produced for a non-linear relationship between competition and the use of bank financing by small firms. While at very low levels of contestability an increase in contestability increases small firm use of bank finance, for most observations of contestability in the sample, an increase in contestability produces the opposite result. This also holds for medium size firms outside of manufacturing. Medium size firms in manufacturing exhibit a non-linear relationship between competition and use of bank credit, but in an opposing direction. Small firms are also more likely to use bank financing the higher is the small bank market share. However, neither the size distribution of banks nor the level of profitability of lending is shown to further influence the effect of contestability on small firm use of bank lending.
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Notes
Berger et al. (2004b) look at the effect of small banks on economic growth in both developed and emerging market economies.
“[I]n low-income markets…[s]mall local banks are the best entities for providing financial services to the enterprises and households that are most important in terms of comparative advantage—be they asparagus farmers in Peru, cut-flower companies in Kenya or garment factories in Bangladesh..” The Economist, Economic Focus, “Walk, Don’t Run,” 9 July 2009.
Berger et al. (2010) provide evidence that small (community) banks in the US commonly use consumer credit scoring models to assess owners when lending to small businesses. However, this technology is relatively recent and is unlikely to have been in widespread use in emerging market banking systems at the time the data used in this study was collected.
Hsieh and Lee (2010), looking more generally at bank profitability, find that the relationship between competition and return on equity is affected by such factors as bank market structure, restrictions on non-bank activities and efficiency in the judicial system.
A number of approaches to measure access to finance at the firm level have been used in the literature. All have problems either conceptually or operationally. Scott and Dunkelberg (2003) in their study of rural US markets utilize firm survey responses to a direct question about bank competition. Without data on such a direct question, Petersen and Rajan (1995) look at small firm use of trade credit. They assume that since trade credit is a relatively expensive form of finance, small firms which use it must have less access to bank financing. However, recent research has cast doubt on this measure’s reliability, challenging the assumption that trade credit is relatively expensive (Giannetti et al. 2010) and, given its ubiquity, questioning its interpretation as indicating financial constraints (Miwa and Ramseyer 2005). Carbo-Valverde et al. (2009) use a disequilibrium approach in their study of banks across different regions in Spain. They construct separate demand and supply equations for credit at the firm level and then assess the difference between the predicted and actual level of bank borrowing employing a switching model to assess whether a firm is financially constrained. Their methodology is data intensive, using longitudinal observations on Spanish firms and utilizing regional variation in the banking and macroeconomic environments.
When firms responded to the survey, financing was included among a list of twelve potential obstacles which they were to rate individually on a 4-point Likert-type scale (“no obstacle” – 1; “major obstacle” – 4). However, as Ergungor points out, the survey question required that no more than four of the possible choices be designated as “major” obstacles. This may have biased answers if financing is in fact a major obstacle, but it was the fifth major obstacle and thus downgraded to a lower designation because of the maximum of four that could be identified as major.
Eight additional sources of financing could also be selected: internal funds/retained earnings, equity, investment funds/special development finance, family/friends, moneylenders, supplier credit, leasing arrangement and other.
Carbo-Valverde et al. (2009) use a Lerner index to measure bank market power and show that it is actually a function of concentration ratios and contestability. In their Spanish regional data set, the Lerner index and a contestability measure (using the same Panzar and Rosse methodology) have a correlation of 0.81.
As pointed out by an anonymous referee, using total assets as the denominator of interest rate margin may be problematic and create measurement error. There is great variation in the types of activities in which banks may engage across countries and the share of loans in total assets may also vary. A better measure of interest rate margin would use total loans in the denominator.
In early specifications additional variables that could impact demand for loans were included. These were reported expected growth in sales and whether family or friends were a major source of financing. The latter was expected to indicate alternative sources of financing for small firms. However, these variables did not produce significant coefficients in any of the specifications and were dropped.
Beck et al. (2004) include service as an additional sectoral variable. However, some unresolved inconsistency in the coding of the two separate sectoral variables in the data set led to use of the simplest indicator, manufacturing.
The level of GDP per capita has been associated with financial development. However, because of strong multicollinearity of GDP per capita with several other variables in the empirical model we tried two alternatives, the log of GDP per capita and a dummy variable for high income countries. The log of GDP per capita had inconsistent results and did not improve the overall ability to explain the variation in lending. The dummy variable produced no significant coefficients. Both were dropped from the empirical models.
Beck et al. (2004) include GDP per capita as a measure of economic development. However, this variable is highly correlated with other, more specific measures of development, such as institutional development (property rights) and private credit. Regressions were run with alternative specifications of economic development, such as the log of GDP per capita. The inclusion of the regional dummy variables leaves OECD countries as the omitted region and no additional indicators of economic development are included. The high correlations among private credit, property rights and stock market capitalization introduce problems of multicollinearity. A principal components analysis indicates two distinct factors that account for 95 % of the variation. As the first component is equally weighted, it is consistent with an interpretation of economic development. The second weights property rights more heavily and an interpretation of institutional development would seem appropriate. However, for ease of exposition, we have left all three of the original variables in. Significant coefficients are then due to the additional influence of the variable beyond its common variation with general economic development.
When a quadratic term for concentration is added to the specification in column 3, neither the coefficient on the quadratic term nor the coefficient on concentration itself are significant.
Restricting the small firm sample to only manufacturing firms reduced the sample size by 2/3 and to less than three hundred observations. Not surprisingly, none of the banking sector variables produced significant coefficients. The restriction of the large firm sample to only manufacturing firms had no appreciable difference on the results, reducing the sample size by about 10 %.
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Acknowledgment
The author would like to thank an anonymous referee, participants of the Macroeconomic Research in the Liberal Arts Workshop, the Tri-College Summer Economics Seminar at Swarthmore and the Southern Economic Association Meetings. Cynthia Bansak and Biswajit Banerjee provided important contributions at early and late stages, respectively. Valuable research assistance was provided by Li Xiang Poncz. The responsibility for any errors that remain is solely my own. Ursinus College supported the work of this paper through its early leave program.
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Mudd, S. Bank Structure, Relationship Lending and Small Firm Access to Finance: A Cross-Country Investigation. J Financ Serv Res 44, 149–174 (2013). https://doi.org/10.1007/s10693-012-0140-4
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DOI: https://doi.org/10.1007/s10693-012-0140-4
Keywords
- Access to credit
- Small and medium-sized enterprises
- Bank regulation
- Relationship lending
- Bank structure
- Contestability