1. Default Rates in the Loan Market for SMEs: Evidence from Slovakia Small business banking and financing: a global perspective Cagliari, 25 May 2007 Christa Hainz University of Munich, CESifo, and WDI Jarko Fidrmuc University of Munich, CESifo, and Comenius University Bratislava Anton Malesich Comenius University Bratislava

2. SMEs in emerging markets face barriers in access to finance: -SMEs contribute significantly to growth and employment in the new EU member states (EBRD, 2005). -SMEs crucially depend on external financing provided by locally operating banks. The lending boom and concerns about future stability: -Markets are attractive for foreign banks (Claeys and Hainz, 2006). -Financial vulnerability increases during a lending boom (Coricelli et al., 2006, Duenwald et al., 2005, Honohan and Klingebiel, 2000). Motivation

3. Loans to Households and Domestic Firms

4. Research questions: -What are the typical default rates of loans to SMEs in Slovakia? -Which factors determine default? -What are the implications for financial vulnerability? Results: -On average, 6 per cent of the SMEs default on their loan. -We find large sectoral differences. -Indebtedness increases the probability of default only for firms with above average indebtedness. -Natural persons are less likely to default. This suggests effect of liability on incentives. This paper

5. Hypothesis 1: More highly indebted firms are more likely to default. -If firms are highly indebted, when successful they have to pay a higher proportion of their payoff to the bank. -Incentive to exert effort suffers. Hypothesis 2: Firms are more likely to default if they are less profitable and less liquid. -Probability that firm becomes bankrupt depends on profitability and liquidity (Altman, 1968). What determines defaults?

6. Hypothesis 3: The higher is the debtor’s liability, the less likely the firm is to default. -If the debtor is fully liable, he internalizes the effect of his investment decision on payoffs. -Debtor’s incentives are distorted if he is not (fully) liable (Bester, 1987, Holmström, 1996). What determines defaults?

7. Unique data of loans to 667 SMEs in Slovakia -provided by one of the major banks (foreign investor), -between 2000 and 2005, -1496 observations. Data on whether firms have become defaulted -Default: delay of repayment > 90 days. Financial data from the firm’s annual balance sheets -reported as shares on total assets or liabilities for the previous year, -total sales indicate the size of the SMEs (€ 1 to 10 million). Data Description

8. 90 SMEs (6 per cent) defaulted on their loan. International Comparison: Syndicated loans – five year period (Altman and Suggit, 2000) -4.6 per cent for companies with an original S&P rating B, -23.5 per cent for companies with an original S&P rating Caa. SMEs in the US -2.7 per cent (Agarwal and Hauswald, 2007). SMEs in Sweden -0.9 – 2.3 per cent (Jacobsen, Lindé, Roszbach, 2005). Defaults

9. Observations by Years

10. Data Structure by Legal Forms Default Companies Non-Default Companies

11. Descriptive Statistics

12. We estimate following probit (and marginal probability) models -Debt channel: Bank loans as a share of total liabilities (C t-1 ), -Liquidity channel: Cash and bank accounts as a share of total assets (Z 1,t-1 ), -Profitability channel: Earnings before taxation as a share of total assets (Z 2,t-1 ), -Further control variables: industry, time and legal form dummies. Determinants of Defaults

13. Basic Estimation

14. Control for possible selection bias by including industry, time, and legal form dummies. Highly indebted SMEs may have higher default probabi- lities. We split up the sample into companies with debt levels below/ above median level of credits (12% of total liabilities). Panel probit estimations reflect the possible effects of unobservable firm characteristics and the selection bias. Sensitivity Analysis

15. Loan Size  For firms with a high level of credits, indebtedness increases the probability of default significantly.

16. Panel Estimations  Effects are robust to inclusion of firm fixed effects.

17. Industry-Specific Effects  Default probabilities differ largely across industries.

18. Legal-Form Effects  Natural persons are much less likely to default than other legal forms.

19. Default rates of loans to SMEs in Slovakia were higher than in mature markets (already before lending boom started). Evidence that defaults depends on -Indebtedness (for those with indebtedness above average), -Legal form -Thus, incentives matter. Should we worry about the “lending boom”? -Possibly yes, if leverage of SMEs increases. -No, if new loans are made to SMEs. -The banks perform comparably well in this market. Conclusions