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The Impact of Credit Information on Firm Financing
August 2014
Miriam Bruhn, Sole Martinez Peria, Claudia Ruiz Ortega,
Sandeep Singh
January 5, 2015
Luis Domenech, IFC CDI Department, ldomenech@ifc.org
Shalini Sankaranarayan, Ssankar1@ifc.org
5
Without content’s modification. Minor typographicalcorrections
Name, Organization, email, Day, month, year

BackgroundFirms, especially small and medium enterprises (SMEs) state that access to credit is one of the main
constraints on their growth.
The theoretical literature on credit information emphasizes that information sharing schemes canimpact firm financing (see Pagano and Jappelli, 1993; Padilla and Pagano, 1997; Klein, 1992;
Vercammen, 1995; Padilla and Pagano, 2000).
But the existing evidence is limited and, with few exceptions, subject to identification problems.

ObjectivesThis paper explores the impact of credit information sharing reforms on firm financing.
The study analyzes the effect of the establishment of private credit bureaus (CBs) and public credit
registries (CRs) on five measures of firm financing:





Whether the firm has a loan.
The interest rate charged on the latest loan.
The maturity of the latest loan.
The share of working capital (WC) financed by bank lending.
The share of fixed (FA) assets financed by bank lending.

Analysis
DataPage 1 of 7The study combines data from the Doing Business, Enterprise Surveys, and World Development
Indicators databases.
Doing Business: From internal raw data for the Getting Credit module the study is able to establish
which countries have a credit bureau (CB) and/or credit registry (CR) and the year of their introduction.
The study also collects data on the scope and quality of the credit information databases by using thedepth of credit information index and the percentage coverage of CBs and CRs.
Enterprise surveys: The study uses firm-level data for over 75,000 firms from 63 countries across theperiod 2002-2013 where at least two surveys were conducted. The study focuses on five aspects offirms’ access to finance:

Whether they have a loan, line of credit or overdraft protection.
Interest rate paid on the most recent loan.
Maturity of the most recent loan.
Fraction of working capital financed by banks.
Fraction of fixed assets financed by banks

The study also obtains information on different firm characteristics including firm size, age, ownership
type, exporter status, and sector
World Development Indicators: The study used country-level data on inflation, GDP growth, and credit
to the private sector.
Methodology
The study’s identification strategy relies on the fact that there are countries in the sample that
introduced a CB/CR during the survey period and countries that never adopted such credit information
sharing schemes.
The study uses a quasi-difference-in-difference approach to estimate causal impact:Treatment group consists of countries where a CB/CR was introduced in between two or moreavailable survey years.
Control group consists of countries with two or more years of Enterprise Surveys, but whereCBs/CRs were never introduced.

The study includes country fixed effects to control for time-invariant country characteristics that couldexplain differences across countries in firms’ access to finance.
The study includes time fixed effects to control for common time effects that can explain differences infirm financing over time (e.g., global crisis).
111213

1

1Finance Indicator = Credit information reform + X + Z + +γ +εi,j,tj,tPage 2 of 7i,j,tj,tjt1i,j,t

Finance indicator refers to the five measures of firm financing
Credit information reform is a dummy variable that take value 1 for treatment countries after reformand 0 otherwise.
X is a matrix of firm-level characteristics including firm size, age, ownership type, exporter status, andsector (manufacturing versus services).
Z refers to a matrix of country-level variables that might influence firms’ access to finance (i.e., inflation
rate, GDP growth rate, private credit/GDP).
 are the country fixed effects.
γ are time effects.
The credit information reform dummy can be thought of as the interaction between a treatment
dummy (1 for treatment countries) and a post reform dummy (1 for years after reform).
The reform variables along with two way country and time fixed effects makes our empiricalmethodology akin to a difference-in-difference format, comparing countries with and without reform,
and years pre- and post-reform.
ε are robust standard errors clustered at country-year level.
SampleCreditBureaureform year
Country
Albania
AngolaArmenia
Azerbaijan
Bangladesh
Belarus
Benin
Bosnia-Herzegovina
Botswana
Bulgaria
Burkina Faso
Cameroon
Cape Verde
China
Colombia
CongoSurvey years
2002, 2005, 2007
2006, 2010
2002, 2005, 2009
2002, 2005, 2009, 2013
2002, 2007, 2013
2002, 2005, 2008, 2013
2004, 2009
2002, 2005, 2009, 20132006, 2010
2002, 2004, 2005, 2007, 2009, 20132006, 2009
2006, 2009
2006, 2009
2002, 2003, 2012
2006, 2010
2006, 2010

2007

CreditRegistry
reformyear

2003
2005
2007

Control
sample forCB
regressions

Control
sample forCR
regressions

xxxxxxxx

2007
x
2005

Page 3 of 7

2004

xxxxxxx

Croatia
Czech Republic
Ecuador
Eritrea
Estonia
Georgia
Guatemala
GuyanaHungary
Indonesia
JamaicaKazakhstan
Kenya
Kyrgyzstan
LatviaLebanonLesothoLithuania
Macedonia
Madagascar
MalawiMali
Mauritius
MexicoMoldova
Mongolia

Country
Nepal
Nicaragua
Niger
PanamaPhilippines
PolandRomania
RussiaRwandaSenegalSerbia-Montenegro
Slovakia
Slovenia
South Africa
Sri Lanka
Tajikistan
Tanzania

2002, 2005, 2007, 2009, 2013
2002, 2005, 2009
2003, 2006, 2010
2002, 2009
2002, 2005, 2009
2002, 2005, 2008, 2013
2003, 2006, 2010
2004, 2010
2002, 2005, 2009
2003, 20092005, 2010
2002, 2005, 2009, 2013
2003, 2007, 2013
2002, 2003, 2005
2002, 2005, 2009
2006, 2013
2003, 2009
2002, 2004, 2005, 2009
2002, 2005, 2009, 20132005, 20092005, 2009
2003, 2007, 2010
2005, 2009
2006, 2010
2002, 2003, 2005, 2009, 2013
2004, 2009

Survey years
2009, 2013
2003, 2006, 2010
2005, 2009
2006, 2010
2003, 2009
2002, 2003, 2005, 2009
2002, 2005, 2009
2002, 2005, 2009
2006, 2011
2003, 2007
2002, 2005, 2009, 2013
2002, 2005, 2009
2002, 2005, 2009, 2013
2003, 2007
2004, 2011
2002, 2003, 2005, 2008
2003, 2006, 2013

2007
2002
2005

x
2002
2008
xxxxxxx

2005
2004

xx
2006
2008
2003
2008

xxxxxxxxx

2011

2005

xxxxxxx

2011
CreditBureaureform year

CreditRegistry
reformyear

2005

2007

x
Control
sample forCB
regressions

Control
sample forCR
regressions

xxxxx
2004
2006
2010xx

2004
2004
2008

xxxPage 4 of 7xxxx

UgandaUkraineVietnam
Zambia2003, 2006, 2013
2002, 2005, 2008, 20132005, 2009
2002, 20072009
2007xxxxx

Note: For the Credit Registry/Bureau reform regressions, the treatment sample consists of countries with a Credit
Registry/Bureau reform in between two or more years of available Enterprise Survey data. The control sample
consists of countries with two or more years of Enterprise Surveys, but where Credit Registry/Bureau do not exist.

Results-Impact of CBs

Figure 1: Average trend of access variables for treatment and control countries in CBsample

Access to financeMaturity

Interest rate

WK by banks

FA by banks

TreatmenttControl

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-Impact of CRs

Page 6 of 7

Conclusions and Recommendations
CB reforms but not CR reforms have an effect on firm financing.
After the introduction of a CB:

A larger share of firms has access to finance.
Interest rates drop.
Maturity lengthens.
The share of working capital financed by banks increases.

Effects of CB reform are more pronounced the greater the coverage of the CB and the scope andaccessibility of the credit information sharing scheme.
Some evidence that CB reform effects are more pronounced for younger, smaller and more opaquefirms.

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