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Default Rates in the Loan Market for SMEs: Evidence from Slovakia

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

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Default Rates in the Loan Market for SMEs: Evidence from Slovakia

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

  2. Motivation • 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).

  3. Loans to Households and Domestic Firms

  4. This paper • 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.

  5. What determines defaults? • 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).

  6. What determines defaults? • 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).

  7. Data Description • 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).

  8. Defaults • 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).

  9. Observations by Years

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

  11. Descriptive Statistics

  12. Determinants of Defaults • We estimate following probit (and marginal probability) models • Debt channel: Bank loans as a share of total liabilities (Ct-1), • Liquidity channel: Cash and bank accounts as a share of total assets (Z1,t-1), • Profitability channel: Earnings before taxation as a share of total assets (Z2,t-1), • Further control variables: industry, time and legal form dummies.

  13. Basic Estimation

  14. Sensitivity Analysis • 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.

  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. Conclusions • 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.

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