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 FidrmucUniversity of Munich, CESifo, and

Comenius University Bratislava

Anton MalesichComenius University Bratislava

• 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

Loans to Households and Domestic Firms

• 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

• 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?

• 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?

• 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

• 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

Observations by Years

0

50

100

150

200

250

300

350

Jan. 2000-June 2001 Jan. 2001-June 2002 Jan. 2002-June 2003 Jan. 2003-June 2004 Jan. 2004-June 2005

defaults non-defaults

Data Structure by Legal Forms

Default Companies Non-Default Companies

limited liability

company46%

joint stock company

29%

coope-rative24%

state enterpris

0.0%

natural person

1%

natural person

5%

limited liability

company51%

joint stock company

24%

state enterprise

0%

coope-rative20%

Descriptive Statistics

Total sales SKK mill.

Bank loans

Cash & bank accounts

Earnings before tax.

A: Non-default companies Mean 100319 0.152 0.298 0.033 Max 298431 0.853 27.727 0.488 Min. 30115 -0.190 -0.237 -0.321 Std. Dev. 65584 0.125 0.832 0.078 B: Default companies Mean 114200 0.177 0.100 -0.038 Max 291358 0.666 0.715 0.171 Min. 30142 0.006 -0.120 -0.617 Std. Dev. 71465 0.147 0.138 0.119 C: F-Test of equal mean and variance between the sub-samples Mean 3.747* 3.258* 5.082** 66.804*** p-value 0.053 0.071 0.024 0.000 Variance 1.187 1.381* 36.439*** 2.343*** p-value 0.300 0.052 0.000 0.000

• 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.

Determinants of Defaults

it

it

itt

it CqP 11211|1 Z

Basic Estimation

P1 P2

Bank loans 0.797* 1.195**

(0.409) (0.484)

Cash and bank accounts -1.675*** -1.804***

(0.392) (0.416)

Earnings before taxation -4.612*** -5.214***

(0.728) (0.815)

Constant -1.381*** -1.073***

(0.100) (0.237)

Industry, time, leg. form dummies No Yes

Number of observations 1496 1496

Pseudo-R2 0.134 0.183

• 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

Loan Size

P3a P3b

Bank loans -0.587 1.733***

(2.834) (0.659)

Cash and bank accounts -2.551*** -1.555***

(0.683) (0.554)

Earnings before taxation -7.691*** -3.561***

(1.421) (1.127)

Constant -1.761*** -1.720***

(0.533) (0.399)

Industry, time, leg. form dummies Yes Yes

Credit size Small Large

Number of observations 748 748

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

Panel Estimations

REP1 REP2 REP3

Bank loans 0.791 1.474* 2.948**

(0.619) (0.809) (1.325)

Cash and bank accounts -2.205*** -2.571*** -2.392***

(0.566) (0.673) (1.003)

Earnings before taxation -5.294*** -6.621*** -4.865***

(1.042) (1.351) (2.063)

Constant -1.848*** -1.475*** -2.762***

(0.217) (0.431) (0.906)

Industry, time, leg. form dummies No Yes Yes

Credit size All All Large

Number of observations 1496 1496 748

Effects are robust to inclusion of firm fixed effects.

Industry-Specific Effects

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Agriculture Construction Retail trade Other services

Probit Large Credits Panel-Probit Panel Probit for Large Credits

Default probabilities differ largely across industries.

Legal-Form Effects

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

Natural persons Limited liability company (s.r.o.) Joint stock company (a.s.)

Probit Large Credits Panel-Probit Panel Probit for Large Credits

Natural persons are much less likely to default than other legal forms.

• 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