1. SME Credit Availability Around the World: Evidence from the World Bank’s Enterprise Survey World Finance Conference Venice, Italy July 3, Rebel A. Cole, Driehaus College of Business at DePaul University Andreas Dietrich, Lucerne University of Applied Sciences and Arts

2. Agenda 1 Introduction 2 Literature Overview 3
Model, Methodology and Data 4
Results 5
Summary and Conclusions
Andreas Dietrich

3. Background and Motivation
Lack of access to finance is a growth constraint for small and medium-sized firms; and has a negative impact on a country‘s economy
Research has shown that SMEs are very important for any economy, esp. for employment and GDP.
In the U.S., for example, small privately held firms account for about half of GDP growth and 2/3rd of employment growth.
Financing obstacles, besides crime and political instability, have been found to impact firm growth directly and significantly & therewith the overall economy in a country
also our research data confirms that access to finance is perceived as the biggest obstacle
it is crucial that governments and also financial institutions are aware of the determinants of access to finance in order to be able to tackle the issue, and to reduce barriers by implementing policies and regulations
Andreas Dietrich

4. Background and Motivation
The answers to the questions:
“Who needs credit?”
“Who applies for credit?” and
“Who gets credit?”
are of great importance not only to the firms themselves, but also to prospective lenders to these firms and to policymakers interested in the financial health of these firms.
Financing obstacles, besides crime and political instability, have been found to impact firm growth directly and significantly & therewith the overall economy in a country
also our research data confirms that access to finance is perceived as the biggest obstacle
it is crucial that governments and also financial institutions are aware of the determinants of access to finance in order to be able to tackle the issue, and to reduce barriers by implementing policies and regulations
Andreas Dietrich

5. Background and Motivation
In this study, we analyze data from a series of World Bank-sponsored surveys of small and medium-size enterprises (SMEs) located in 80 countries to provide new evidence on how to answer these three questions.
We document what firm, owner and market characteristics explain outcomes in the credit allocation process.
Financing obstacles, besides crime and political instability, have been found to impact firm growth directly and significantly & therewith the overall economy in a country
also our research data confirms that access to finance is perceived as the biggest obstacle
it is crucial that governments and also financial institutions are aware of the determinants of access to finance in order to be able to tackle the issue, and to reduce barriers by implementing policies and regulations
Andreas Dietrich

6. Credit Need/ Credit Discouragement/ Credit Availability
Research Question
What determines:
(i) the need for credit,
(ii) discouragement from applying for credit,
and, finally,
(iii) success in obtaining credit?
Firm characteristics?
Owner characteristics?
Market characteristics?
Credit Need/ Credit Discouragement/ Credit Availability
Market
characteristics
Owner characteristics
Firm characteristics
Andreas Dietrich

7. Methodology – Our Approach
(1)
Need Credit?
(2)
Apply for Credit?
(3)
Get Credit? No
Yes
No-Need Firm
Discouraged Firm
Denied
Firm
Approved Firm
Andreas Dietrich

8. Why is this study important?
Almost no studies analyze “No-Need” firms.
A few studies analyze “Discouraged” firms that need credit but don’t apply.
“Discouraged” firms are numerous
To improve availability of credit, it is critically important to better understand these firms
Most of these studies pool “discouraged” firms with “denied” firms to analyze credit allocation.
This can lead to faulty conclusions if the two groups differ systematically (which they do).
We provide new evidence on these issues, analyzing data from 80 countries.
However, many small firms indicate that they do not need credit (“no-need” firms) while others indicate that they needed credit but did not apply for credit (“discouraged” firms)
Most of the existing literature essentially has ignored “no-need” firms. “Discouraged” firms—those that do not apply for credit because they expect to be turned down—have received somewhat more attention in the literature than “no-need” firms, but not nearly as much as firms that actually apply for credit. Many of the studies that have analyzed “discouraged” firms pool them with firms that actually applied for, but were denied credit, even though Cole (2009) finds important and significant differences in the two groups.
Andreas Dietrich

9. Agenda 1 Introduction 2 Literature Overview 3
Model, Methodology and Data 4
Results 5
Summary and Conclusions
Andreas Dietrich

10. Existing Literature : Availability of Credit
The availability of credit is one of the most fundamental issues facing a small businesses.
It has received much attention in the academic literature
Petersen and Rajan, JF 1994;
Berger and Udell, JB 1995;
Cole, JBF 1998
Many, many more (x 100)
Cole (SBA 2009) first proposed this taxonomy of four types of firms.
Who needs credit: Need vs. No-Need
Who applies for credit: Discouraged vs. Applied
Who gets credit: Denied vs. Approved
, whereas we look at 80 countries around the world after, They find
Andreas Dietrich

11. Existing Literature: Studies using World Bank SME Surveys
Beck et al. (2008; 48 countries, 3,000 firms): finds that, in countries with poor institutions, firms (and especially small firms) use less finance.
Brown et al. (2011; 20 countries in E.-W. Europe, 8,000 firms): Finds that small and financially opaque firms are less likely to apply for credit. Most interestingly, they find that firms applying for credit rarely are denied credit.
Chakravarty and Xiang (2013; 10 countries; 8,000 firms): Finds that discouraged firms differ across developed and developing countries; and that larger firms, more transparent firms, and firms with stronger banking relationships are less likely to be discouraged.
, whereas we look at 80 countries around the world after, They find
Andreas Dietrich

12. Agenda 1 Introduction 2 Literature Overview 3
Model, Methodology and Data 4
Results 5
Summary and Conclusions
Andreas Dietrich

13. Methodology: Classification of Firms/Models
(1)
Need Credit?
(2)
Apply for Credit?
(3)
Get Credit? No
Yes
No-Need Firm
Discouraged Firm
Denied
Firm
Approved Firm
Andreas Dietrich

14. Methodology: Explanatory Variables
Need Credit, Apply for Credit, Get Credit
Firm Characteristics
Age
Size
Growth
Legal Form
External auditor
Industry Dummies
Owner Characteristics
Experience of Management
Domestic vs. Foreign Owned
Female vs. Male Owned
Important: say that we’ve added one market characteristic indicator as well as WGI and EFI for country-level governance characteristics
Auch auf Datenquellen eingehen:
World Bank’s Enterprise Sureys
Firm-level data der World Bank’s Enterprise Surveys
Worldwide Governance Indicator der Weltbank
Index of Economic Freedom der Heritage Foundation und des Wall Street Journals
Bankkonzentration aus Bankscope
Market Characteristics
City Size (Rural vs. Urban)
GDP growth
GDP per capita
Inflation
Year Dummies ( )
Andreas Dietrich

15. Methodology: Univariate and Multivariate Tests
Once we have classified each firm, we calculate univariate statistics for each group and test for significant differences in means across groups
We then run a series of three sequential probit regression models to explain each step of the credit approval process:
1. Need credit? (Yes or No?), then
2. Apply for credit? (Yes or No?), then
3. Get credit? (Approved or Denied?)
We further analyze whether the results differ between developing and developed countries
Andreas Dietrich

16. Data
Our data are taken from the World Bank’s (WB) Enterprise Surveys (WBES).
WB conducted these surveys in 99 countries between 2006 and 2011.
Since 2006: WB uses the “Global Methodology,” which attempts to make the surveys comparable across countries and years.
Our final sample includes 41,991 firm-year observations from 80 countries over the 2006 – 2011 period.
We delete data from two countries, as only one observation per country was available for our analysis
We delete data from 17 other countries because not all information necessary for our analysis was available from the survey.
Andreas Dietrich

17. Data Limitation of the WBES:
Much of data gathered are based on owner responses to a survey, which are vulnerable to the subjective perceptions of the respondents.
Some key information about firms that typically are required by banks when a company applies for credit (e.g., performance indicators, capital structure, margins, etc.) were not collected by the WBES.
No information on credit supply, only demand.
We delete data from two countries, as only one observation per country was available for our analysis
We delete data from 17 other countries because not all information necessary for our analysis was available from the survey.
Andreas Dietrich

18. Agenda 1 Introduction 2 Literature Overview 3
Model, Methodology and Data 4
Results 5
Summary and Conclusions
Andreas Dietrich

19. Descriptive Statistics: Need-Credit Firms vs. No-Need Firms
Need-credit firms are older, larger, growing faster; less likely to be organized as corps and to have an external auditor.

20. Descriptive Statistics: Need vs. No-Need Firms
Need-credit firms are more likely domestic, female owned, urban.

21. Descriptive Statistics: Discouraged vs. Applied Firms
Discouraged firms are younger, smaller, grow slower; less likely to be organized as corps, or to have an external auditor.

22. Descriptive Statistics: Discouraged vs. Applied Firms
Discouraged: Less managerial experience; more likely female, domestic owned.

23. Descriptive Statistics: Denied vs. Approved Firms
Denied: younger, smaller, grow faster, less likely corp, external auditor.

24. Descriptive Statistics: Denied vs. Approved Firms
Denied: less mgt experience; more likely female, domestic, rural.

25. Multivariate Results

26. Multivariate Results

27. Multivariate Results

28. Agenda 1 Introduction 2 Literature Overview 3
Model, Methodology and Data 4
Results 5
Summary and Conclusions
Andreas Dietrich

29. Summary and Conclusions
In this study, we use data on more than 41,000 SMEs in 80 countries surveyed by the World Bank to analyze the availability of credit around the world.
Following Cole (2009), we classify firms into one of four mutually exclusive groups:
no-need,
discouraged,
denied, and
approved.
We analyze differences in these groups using both univariate and multivariate tests.
Andreas Dietrich

30. Summary and Conclusions
Overall, we find that a “no-need” firm:
is older and smaller than a firm that needs credit;
is more likely to be organized as a corporation and to have an outside auditor;
is more likely to be owned by a male and by a foreigner; and
is more likely to be located in a small city and in a country with higher GDP per capita and GDP growth.
Andreas Dietrich

31. Summary and Conclusions
Among firms that need credit, we find that a “discouraged” firm:
is younger, smaller and growing slower than a firm that applied for credit;
is much less likely to be organized as a corporation or to have an external auditor;
is less likely to run by an experienced management team or to be owned by a foreigner or female; and
is more likely to located in a small city and in a country with higher inflation and lower GDP per capita but with higher GDP growth.
Andreas Dietrich

32. Summary and Conclusions
Among firms that apply for credit, we find that an approved firm:
is older, larger, and growing faster;
is less likely to be organized as corporations but more likely to have an external auditor;
is more likely to be run by more experienced management team and to be owned by foreigner and a male; and
is more likely to be located in a large city and in a country with lower inflation and GDP per capita but higher GDP growth.
Andreas Dietrich

33. Summary and Conclusions
As compared with results from Cole (2009) for U.S. SMEs, we find that firms around the world:
Are much more likely to need credit (67% vs. 55%)
Are much more likely to be discouraged from applying for credit (39% vs. 28%),
Are much more likely to be denied credit (50% vs. 20%) when they need, and apply, for credit.
In summary, credit is much less “available” around the world than in the U.S., so that policies to improve the availability of credit are even more important outside of the U.S.
Andreas Dietrich

34. Summary and Conclusions
Credit constraints might limit product development and innovation by some firms, possibly harming long-term economic growth.
Policies to increase information sharing and transparency (for example, by encouraging use of external auditors) may be an effective ways to improve credit availability.
Andreas Dietrich

35. Summary and Conclusions: Limitations
The reason why a firm is discouraged from applying for a loan is not clear, e.g., are borrowers discouraged because of high interest rates, large collateral requirements, etc.:
Non-economic reasons (such as discrimination) and thus true impediments of promising firms/projects?
Or financial difficulties of the firm?
Not clear whether the large fraction of discouraged and denied borrowers reflects missed growth opportunities or whether it is the result of a useful screening of weak applicants by lenders.
Interesting data, such as profitability, capital structure, etc. are not available from the World Bank Enterprise Surveys.
High interest rates/ large collateral requirements may reflect true impediments of promising firms and projects. On the other hand, high interest rates and large collateral requirement might also be due to financial difficulties of the discouraged firm. The subjective “feeling” of discouragement can be the result of the fact that a firm knows that the probability of success of the relevant project is low, or because of non-economic reasons such as discrimination.
Andreas Dietrich