Banking supervision and nonperforming loans a cross country analysis

Description
The purpose of this paper is to empirically analyse the cross-countries determinants of
nonperforming loans (NPLs), the potential impact of supervisory devices, and institutional
environment on credit risk exposure

Journal of Financial Economic Policy
Banking supervision and nonperforming loans: a cross-country analysis
Abdelkader Boudriga Neila Boulila Taktak Sana J ellouli
Article information:
To cite this document:
Abdelkader Boudriga Neila Boulila Taktak Sana J ellouli, (2009),"Banking supervision and nonperforming
loans: a cross-country analysis", J ournal of Financial Economic Policy, Vol. 1 Iss 4 pp. 286 - 318
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Banking supervision and
nonperforming loans:
a cross-country analysis
Abdelkader Boudriga, Neila Boulila Taktak and Sana Jellouli
DEFI, University of Tunis, Mont?eury, Tunisia
Abstract
Purpose – The purpose of this paper is to empirically analyse the cross-countries determinants of
nonperforming loans (NPLs), the potential impact of supervisory devices, and institutional
environment on credit risk exposure.
Design/methodology/approach – The paper employs aggregate banking, ?nancial, economic, and
legal environment data for a panel of 59 countries over the period 2002-2006. It develops a
comprehensive model to explain differences in the level of NPLs between countries. To assess the role
of regulatory supervision on credit risk, the paper uses several interactions between institutional
features and regulatory devices.
Findings – The empirical results indicate that higher capital adequacy ratio (CAR) and prudent
provisioning policy seems to reduce the level of problem loans. The paper also reports a desirable
impact of private ownership, foreign participation, and bank concentration. However, the ?ndings do
not support the view that market discipline leads to better economic outcomes. All regulatory devices
do not signi?cantly reduce problem loans for countries with weak institutions, corrupt environment,
and little democracy. Finally, the paper shows that the effective way to reduce bad loans is through
strengthening the legal system and increasing transparency and democracy, rather than focusing on
regulatory and supervisory issues.
Practical implications – First, higher CARs results in less credit exposures. Second, international
regulators should continue their efforts to enhance ?nancial development. The results suggest that
foreign participation plays an important role in reducing credit exposure of ?nancial institutions.
However, in developed countries, foreign entry led to more problem loans. Finally, to reduce credit risk
exposure in countries with weak institutions, the effective way to do it is through enhancing the legal
system, strengthening institutions, and increasing transparency and democracy.
Originality/value – The paper contributes to the literature on banking regulation and supervision.
It examines aggregated data which best re?ect the level of NPL of the banks in a country as opposed to
individual data included in databases that suffer from the problem of representativeness. It considers
the impact of regulatory variables after controlling for bank industry factors that alter primarily
problem loans. Finally, the paper examines the effectiveness of regulation through the inclusion of
institutional factors.
Keywords Banking, Loans, Credit, Risk assessment, Regulation
Paper type Research paper
1. Introduction
After a relatively calm decade, the international banking industry suffered during
the last three years an unprecedented meltdown. Several banks throughout the world,
including in developed and developing countries, experienced severe losses on their
credit portfolios leading to banks failures and to a global fear of a systemic crisis.
This crisis raised further concerns about ?nancial systems stability and the need for
a closer control and supervision on lending activities and institutions. In particular,
international regulators (IMF, World Bank, and the BIS) engaged, over the last decade,
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
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Journal of Financial Economic Policy
Vol. 1 No. 4, 2009
pp. 286-318
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576380911050043
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several reforms, and programs aiming to strengthen banking and ?nancial systems in
different countries. Various assessments are periodically made to timely predict any
undesirable exposure. Speci?cally, the aggregate rate of nonperforming loans (NPLs) is
commonly used as a soundness indicator.
Despite ongoing efforts to control bank lending activities, NPLs are still a major
concern for both international and local regulators. According to the IMF (2007), the
aggregate rate of NPLs exhibits large disparities in a cross-country basis, particularly
between developed and developing countries. While some countries suffer severely
from bad loans, such as Egypt, Nigeria, Philippines, Morocco, Algeria, and Tunisia
(more than 15 percent), other countries do not seem to be exposed to deteriorated assets
quality, such as Sweden, Norway, Finland, Australia, and Spain (less than 1 percent).
Besides, over the last several years, a signi?cant strand of research stressed out the
central role of assets quality as a predictor of bank failures (Demirguc-Kunt, 1989;
Whalen, 1991; Barr and Siems, 1994; Berger and DeYoung, 1997).
Two strands of research have attempted to explain these disparities. In the ?rst
strand, NPLs are explained either by bank speci?c or by macroeconomic factors.
Problem loans are often used as an exogenous variable to explain other banking
outcomes such as bank performance, failures, and bank crisis. However, a limited
number of studies investigate problem loans as an endogenous variable (Sinkey and
Greenawalt, 1991; Kwan and Eisenbeis, 1997; Salas and Saurina, 2002). Recently, the
interest on the determinants of NPLs has been reconsidered by various authors, as data
on problem loans became available. For instance, Breuer (2006), using Bankscope data,
analyses the impact of legal, political, sociological, economic, and banking institutions
on problem bank loans. Nevertheless, her study suffers from a representativeness bias
due to the fact that Bankscope data on NPLs are only available for a very limited
number of countries and for a few numbers of banks. Babihuga (2007), in an IMF
working paper, explores the relationship between several macroeconomic variables
and ?nancial soundness indicators (capital adequacy, pro?tability, and asset quality)
based on country aggregate data. She explained the cross-country heterogeneity by
differences in interest rates, in?ation, and other macroeconomic factors. However, the
study does not consider the impact of industry speci?c drivers of problem loans.
A second growing strand of research, pioneered by Barth et al. (2004), investigates
the impact of banking regulation and supervision factors on various banking
outcomes, such as NPLs. The seminal works of Barth et al. (2004, 2006) highlighted the
superiority of the private interest view over the public interest view in governing
banking systems. According to the authors, market imperfections are preferred to
political imperfections in regard to economic and ?nancial outcomes. The debate over
which of the two points of view is preferred is yet unresolved. Some continue to argue
that empowering government regulation is the unique mean to overcome undesirable
market imperfections. Others, stress out that powerful governments and control
agencies are associated with inef?cient economic outcomes.
The aim of this study is ?rst to investigate the impact of bank industry factors
on the aggregate rate of NPLs. Based on an extensive literature review, we propose
a model relating NPLs to banking industry features. Particularly, it serves to capture
differences between banking systems in terms of capitalization, provisions policy,
pro?tability and ownership structure, and industry concentration. Second, the
study examines the impact of the regulatory environment on reducing problem loans.
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This is captured through public and private supervision, independence of supervision
authorities and the level of regulatory capital requirements. Finally, it addresses the
issue of the impact of the legal and political environment of the effectiveness of
supervisory regulations.
Our study contributes to the literature on problem loans in several ways. First, we
use aggregated data which best re?ect the level of NPLs of the banks in the country
level. Previous research used individual data provided by Bankscope which suffer
from the problem of representativeness. Second, we examine a period of time when the
IMF was conducting several ?nancial systems assessment programs and when local
regulators started to be aware of the necessary reduction of problem loans. We
therefore expect information disclosure on credit exposure to be more accurate and to
better re?ect the soundness (or not) of ?nancial systems.
Our study also contributes to the literature on how supervisory effectiveness
impacts accumulated problem loans. To the best of our knowledge, no research has
analyzed the impact of regulatory variables after controlling for bank industry factors
that primarily alter problem loans. Speci?cally, the work by Barth et al. (2004, 2006) do
not control for non regulatory determinants of problem loans among other banking
outcomes. We also control the differences in the political and the legal environment
between countries to assess the extent to which effectiveness of supervisory regulation
leads to a well-functioning ?nancial system, as suggested by a number of authors
(Barth et al., 2006; Kaufmann et al., 2008).
Using data from a sample of 59 countries for which bank industry and regulatory
information are available, the empirical results show that a high level of capitalization,
a prudent provisioning policy, the concentration of the banking industry, and the
presence of foreign capital are the main factors that reduce the level of NPLs. However,
we ?nd that state participation in banks increases problem loans. Regarding banking
surveillance, the results indicate that bank regulatory, and supervisory variables do
not systematically affect the level of NPLs. It is only in a healthy legal and democratic
environment that of?cial supervision and regulation contribute to promote a sound and
stable ?nancial system. Along these lines, it would be necessary to encourage
information disclosure, transparency and sharing alongside with implementing
supervisory devices.
The remainder of the paper is organized as follows. Section 2 reviews the existing
literature on bank industry and regulatory determinants of NPLs. Section 3 describes
the data and the methodology. Sections 4 and 5, respectively, present and discuss the
empirical results. Finally, Section 6 concludes the paper.
2. Bank industry factors, supervision and NPLs: literature review and
hypothesis development
2.1 Bank industry factors of NPLs
The empirical literature on NPLs explains banks problem loans using bank speci?c or
internal variables. These bank-speci?c factors are related to bank management and
?rm-level features which include proxies of bank capitalization, provisioning policy,
pro?tability, ownership status, and industry concentration.
2.1.1 Bank capitalization. Theoretically, the capital adequacy ratio (CAR) might
serve as a tool to control excessive risk taking by banks and to prevent them from
being insolvent through recapitalization (Basel accord). Banks with CAR less than
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the regulatory minimum are forced to adjust their balance sheet to comply with the
regulatory requirements either by raising more capital (holding assets constant) or
reducing risk-weighted assets (holding capital constant). In fact, raising the level of
capital relative to risky assets by either means could have a bene?cial impact on the
bank performance and soundness (Fries et al., 2002). Indeed, Koehn and Santomero
(1980) show theoretically that the portfolio risk increases with the increase of the
minimum capital ratio. They state that banks under pressure to increase capital will
reach the desired level by increasing the risk of assets.
Empirically, there is no consensus on the relation between capital adequacy and
NPLs. On one hand, Sinkey and Greenawalt (1991) show that banks with adequate
capital ratio experience lower rates of NPLs. On the other hand, banks with high levels
of CARs might be encouraged to embark in riskier activities leading to riskier credit
portfolios. Rime (2001) corroborates this argument. He observed a positive relationship
between bank risk and capital ratio for a panel of Swiss banks during the period
1989-1995:
H1. Capital adequacy ratio is negatively associated with NPLs.
2.1.2 Provisioning policy. Loan loss provisions are regarded as a controlling
mechanism over expected loan losses. Under backward-looking provisioning practices,
where provisions are triggered by default incidents on loans, higher levels of NPLs are
associated with high rates of pro-visioning (Hasan and Wall, 2004). At the same time,
banks anticipating high levels of capital losses might create higher provisions to
decrease earnings volatility and to reinforce medium term bank solvency. In this case,
managers can also use loan loss provisions to signal the ?nancial strength of their
banks. The willingness of a bank to provision for loan losses is regarded as a strong
belief in the future performance of the bank (Ahmad et al., 1999). The overall rate of
provisioning re?ects the general attitude of the banking system toward risk control:
H2. Loan loss provisions are positively associated with NPLs.
2.1.3 Bank pro?tability. Bank pro?tability may also determine the risk taking
behaviour of managers. Banks with high pro?tability are less pressured to revenue
creation and thus less constrained to engage in risky credit offerings. At the same time,
inef?cient banks are more likely to experience high levels of problem loans. Poor
management can imply weak monitoring for both operating costs and credit quality of
customers, which will induce high levels of capital losses. Under this bad management
hypothesis advanced by Berger and DeYoung (1997), managers lack competencies to
effectively assess and control risks incurred when lending to new customers.
Godlewski (2004), using the adjusted return on assets ratio (ROA) as a proxy for
performance, shows that banks pro?tability negatively impacts the level of NPLs ratio.
However, using a panel of 129 Spain banks during 1993-2000, Garcia-Marco and
Robles-Fernandez (2007) ?nd that higher levels of return on equity are followed by
greater risk in the subsequent periods. They argue that pro?t-maximizing policies will
be accompanied by higher levels of risk:
H3. Bank pro?tability is negatively associated with NPLs.
2.1.4 Ownership status. The ownership status of the bank is associated with NPLs.
Several studies document that State ownership may explain the behaviour of risk
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taking of bankers and consequently the level of NPLs. For instance, Salas and Saurina
(2002) argue that to enhance the economic development of the country, state-owned
banks have more incentives to fund riskier projects and to allocate more favourable
credits for small and medium ?rms. This inadequate risk taking behaviour (compared
to the return pro?le) will lead to a higher level of NPLs. In the same vein, Micco et al.
(2004) report that state-owned banks tend to have higher levels of NPLs, due to their
weak credit recovery capacity compared to privately owned banks. Others suggest that
the interaction between private and state shareholding in the same bank could
determine the risk level taken by banks. Hu et al. (2004) argue that unjusti?ed risky
behaviour is lower when the two groups check and balance each other. In the opposite,
when private and state shareholders collude, especially in societies with little civil
disciplines, problem loans will be higher due to risky credit offering. Tian (2000)
suggests that under conditions of market imperfection, due to a balancing mechanism
between management incentives and bureaucracy forces, a mixed enterprise ( joint
shareholding of private and state owners) will maximize social surplus.
Empirically, Novaes and Werlang (1995) report lower performance for state
controlled banks in Brazil and Argentina due to high proportion of problem loans given
to government. Micco et al. (2004), analyze 50,000 ?nancial institutions with different
ownership types covering 119 countries. They conclude that NPLs tend to be higher for
banks with state ownership than for other groups. This is explained by the development
mandate given to state-owned banks in developing economies. Hu et al. (2004) use a
panel of Taiwanese banks and ?nd a positive correlation between capital share owned
by the state and the level of NPLs. Finally, Garcia-Marco and Robles-Fernandez (2007)
investigate the relationship between risk taking and ownership structure. They
document that commercial banks (mainly private owned) are more exposed to risk than
deposit banks (mainly state owned):
H4. State ownership is positively associated with NPLs.
Foreignownershiphas a positive impact onbanks’ soundness. Levine (1996) suggests that
foreign shareholding improves the supply and the quality of ?nancial services, enhances
the overall supervisory environment and eases the access to international ?nancial
markets. Accordingly, Brealey and Kaplanis (1996) report that the presence of foreign
banks may enhance foreign direct investment in the non ?nancial sector. Besides, foreign
ownershipimproves humancapital throughthe presence of foreignmanagers whichbring
better skills and technologies, in particular in developing countries (Lensink and Hermes,
2004). This international expertise will also lead to improve local competencies through
training and knowledge transfer. Empirically, Barth et al. (2002) ?nd a negative effect of
foreign ownership on NPLs on a cross countries analysis. They highlight that foreign
banks raise loan quality in a country and may lead to improve domestic banks credit
quality. At the same time, Boubakri et al. (2005) showthat foreignparticipationreduces the
level of risk taking amongst banks on a sample of 81 banks from22 developing countries.
Finally, Micco et al. (2004) ?nd that foreign controlled banks are more performant than
domestic ones for a panel of emerging countries:
H5. Foreign ownership is negatively associated with NPLs.
2.1.5 Industry concentration. The banking industry concentration can also affect
the credit risk taking among banks (Fernandez de Lis et al., 2000). Two strands
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of literature are opposed: the competition-fragility view and the alternative
competition-stability view.
Under the traditional view, increased bank competition erodes market power,
reduces pro?t margins, and leads to low franchise value that encourages bank risk
taking and thus to increase the level of NPLs (Marcus, 1984; Keeley, 1990; Demsetz
et al., 1996). Banks tend to relax restrictions on loans to capture the additional market
share. Bad borrowers would get then loans, generating high levels of NPLs. For
example, Petersen and Rajan (1995) ?nd that in concentrated banking systems,
younger ?rms (supposed to be of lower quality) are ?nanced by banks in comparison to
more competitive markets, where ?rms use other instruments, leading thus to a higher
level of problem loans. At the same time, Breuer (2006) ?nds a small but a signi?cant
positive association between banking industry concentration and NPLs.
Under the alternative competition-stability view, banks increased market power
may lead to higher risk exposures. In monopolistic banking markets, lending
institutions charge higher interest rates to recover incurred losses on past loans. This
will make it harder for low quality ?rms to repay loans, and results in more moral
hazard and adverse selection problems. For instance, Keeley (1990), based on a sample
of American banks over the period 1970-1986, ?nd that Banks with more market power
hold more capital relative to assets and they have a lower default risk. Recently, using
data from the Central and Eastern European banking sectors over the period
1998-2005, Agoraki et al. (2009), suggest that banks with market power tend to take on
lower credit risk and have a lower probability of default. Besides, Fungacova and Weill
(2009) analyze the role of bank competition on the occurrence of bank failures, based on
a large sample of Russian banks for the period 2001-2007. They suggest that greater
bank competition is detrimental for ?nancial stability:
H6. Industry concentration is associated with NPLs.
2.2 Bank supervision and NPLs
By its nature, the banking sector should be regulated and supervised to ensure the
stability of the whole ?nancial system. During the recent decades, the banking
regulatory framework has experienced sharp changes. Several reforms regarding
banking supervision have been initiated since 1988 (Basel I) and reviewed since then
until 2004 (Basel II). The question of how regulation in?uences the banking stability
and soundness remains a source of debate. In previous studies, there is no consensus
on what type of regulations and supervisory practices promote bank development,
enhance ?nancial stability, and facilitate ef?cient corporate ?nance (Barth et al., 2004;
Beck et al., 2006b; Shaffer, 2008). In the remainder of this section, we examine the
impact of the regulatory framework on problem loans. We use four variables related to
the level of capital requirement, the of?cial supervisory power, the market discipline,
and the independence of supervisory authority.
2.2.1 Capital stringency. Regulatory and supervisory bodies emphasize the positive
role of capital stringency as a buffer against losses and hence failures (Dewatripont
and Tirole, 1994). However, empirical evidence suggests that this is not always the
case. Barth et al. (2004) study the relationship between speci?c regulatory and
supervisory practices and banking-sector development, ef?ciency and fragility. They
?nd that stringent capital requirements are associated with fewer NPLs but are not
robustly linked to other banking outcomes. Pasiouras (2008) reports a positive
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association between technical ef?ciency and capital requirements, albeit not
statistically signi?cant in all cases. Other studies indicate that capital requirements
increase, on the contrary, risk-taking behaviour (Besanko and Kanatas, 1996; Blum,
1999). For instance, Godlewski (2004), reports that capital regulation in the banking
industry is positively related to excess risk taking. This increased credit risk leads to
an increase in the ratio of NPLs. He explains that stringent constraints on capital imply
additional pressure on assets returns, which could be done through higher risk taking.
Pasiouras et al. (2006) ?nd a negative relation-ship between capital requirements and
banks’ soundness as measured by Fitch ratings. Finally, Delis et al. (2008) examining a
panel of transition countries, argue that capital requirements do not have a statistically
signi?cant impact on productivity:
H7. Capital stringency is negatively associated with NPLs.
2.2.2 Of?cial supervisory power. Granting broad power to supervisors remains a
subject of controversial debates. From a theoretical point of view, increased of?cial
supervisory power is bene?cial for the development and the stability of the ?nancial
system. Barth et al. (2004) argue that, due to market imperfections, of?cial supervision
may constitute a better substitute to market failure and contribute to further stabilize
the ?nancial system. However, under speci?c circumstances, such as corrupt
environment or lack of democracy and civil discipline, powerful supervision will hinder
the performance and the ef?ciency of the ?nancial system (Shleifer and Vishny, 1998;
Levine, 2003). Barth et al. (2004) show that broader supervisory power is associated
with higher problem loans and may hamper bank development, especially inside
closed political systems. Pasiouras et al. (2006) also ?nd evidence for the negative
impact of supervisory power and credit ratings:
H8. Of?cial supervisory power is negatively associated with NPLs.
2.2.3 Private monitoring. Market discipline function, proxied by the private monitoring
index, has not received suf?cient interest from researchers, although it is one of the
pillars of the Basel II accord. Private monitoring promotion is considered to lead to
more ef?cient banking sector, owing to accurate information disclosure (Hay and
Shleifer, 1998) and to less corruption of bank of?cials (Beck et al., 2006b). Empirically,
Barth et al. (2004) report no evidence of a relationship between enhanced information
disclosure and other regulatory incentives and banking fragility. Recently, Barth et al.
(2006) revisiting the market discipline function, indicate that the positive impact of
private monitoring on bank lending relies on the quality and the development of the
legal system and the governmental institutions effectiveness. On the other hand,
Demirguc-Kunt et al. (2008) ?nd that sounder banks are located in countries where
?nancial data on banks have to be reported regularly and accurately to regulators and
market participants:
H9. Private monitoring is negatively associated with NPLs.
2.2.4 Supervisory bodies’ independence. Finally, the independence of supervisory
authorities is deemed to have an impact on problem loans. Theoretically, the
independence of supervisory authorities is supposed to lead to healthier ?nancial
systems, as political interference in monetary policies is shown to have various
undesirable consequences. Barth et al. (2006) suggest that the extent to which bank
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supervisors are politically and economically pressured or in?uenced, may condition
disciplinary actions enforcement on banks. However, many policy makers are still
opposed to such independency. They fear that this will lead to create states into states,
particularly in developing economies. Hu¨pkes et al. (2006) advocate the need to draw up
accountability on supervision agencies to promote their performance and enhance
their legitimacy. Abrams and Taylor (2001), among others, stress the need to entrust
bank supervision to central banks, which are considered to be more independent than
banks supervision bodies, especially in emerging countries. Empirically, Donze´ (2006)
?nds supervision independence to be positively associated to sounder banking systems.
Klomp and de Haan (2008) considering data for 70 countries, report a negative
relationship between central bank independence and ?nancial instability:
H10. Supervisory authorities’ independence is negatively associated with NPLs.
3. Data and methodology
3.1 Data
This paper considers aggregated data on NPLs. This choice is motivated by the fact that
data on NPLs for individual banks are available only for a very limited number of
countries. As noted byHasan andWall (2004), only US banks provide full information on
their ?nancial outcomes and particularly on problem loans. They emphasize the
challenges that face researchers dealing with NPLs data on other countries. For instance,
the Bankscope database, which provides the widest coverage of countries and banking
organizations, suffers from representativeness bias. For instance, the data used by
Breuer (2006) do not represent the aggregate level of bad loans as published by the IMF,
albeit considering only countries providing NPLs data for at least four banks. To our
knowledge, except the study by Babihuga (2007), our paper pioneers the research work
investigating the determinants of NPLs at the aggregate level.
We use aggregate Financial Soundness Indicators (FSI) data drawn from the IMF
(2007), which provides a unique information set for 95 countries during the period
2002-2006. We started our sample selection by considering all the countries available in
the IMF (2007). We then excluded 19 countries for which information on NPLs, CAR,
return on asset and provisions are missing. We further excluded four countries for
which data on ?nancial development are missing in the ?nancial development report.
Finally, we excluded 12 countries not included in The World Bank database on
regulations and supervisions (Barth et al., 2001, 2006) or for which regulatory variables
were not available. Table I illustrates these different treatments. The ?nal data set
includes 59 countries for which data are available for all variables. This resulted in a
data set of 295 country-year observations.
3.2 Variables de?nition
We employ a sample of 59 countries over the period 2002-2006 to investigate bank
industry determinants of NPLs and the role of the supervisory framework. The bank
industry factors include the one year lagged bank regulatory capital to risk-weighted
assets minus the required minimum capital (Difcar
t21
). We think that this measure is
more appropriate than using the absolute level of the regulatory capital because it
controls for the differences in the regulatory minimum solvency ratio between
countries. This category is composed also of the one year lagged loan loss reserves
to total loans ratio (Prov
t21
), the one year lagged return on assets ratio (ROA
t21
),
Banking
supervision and
NPLs
293
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(
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)
the percentage of state-owned banks (State); the percentage of foreign ownership (Forg)
and the percentage of assets held by the ?ve largest banks (Conc) as a measure of
banking industry concentration. Finally, we use two control variables. First, the lagged
real gross domestic product (GDP) growth (GDPgr
t21
) is introduced to control for the
possible impact of economic conditions on problem loans (Sinkey and Greenawalt,
1991; Anandarajan et al., 2007). Second, to account for differences in the level of
?nancial development we use a dummy variable (Fin_Dev). Based on the work of
Rajan and Zingales (1998), it is deemed that ?nancial development helps institutions to
resolve moral hazard and adverse selection problems and hence contributes to reduce
?nancing costs and to enhance other banking outcomes. Table II provides further
details on variables calculations and sources of information.
To study the supervisory and regulatory environment, we use an assortment of
indicators from the Barth, Caprio, and Levine database developed on three versions
(Surveys I, II, and III established in 1999, 2001, and 2006 and published in 2001, 2003,
and 2007, respectively). Since this database is available at only three points in time, we
used information from Version 2 for the period 2002-2004, and from Version 3 for the
period 2005-2006[1]. A growing number of papers use the information contained in this
data set to study the impact of bank supervision and regulatory policies on bank
performance, stability, and corporate ?nance (Beck et al., 2003; Demirguc-Kunt et al.,
2003).
To test the effect of the regulatory and supervisory factors on problem loans, we
include four variables. First, to account for both initial and overall capital stringency,
we introduce the Capital regulatory index (Car_index), which is supposed to capture
both the overall stringency (amount of capital) and the initial capital stringency
(veri?able sources of capital), with higher values indicating higher capital stringency.
The second variable is the supervisory power (Pow_sup), which indicates the ability of
supervisors to exercise their power and to get involved in banking decisions. Then, to
capture the impact of private monitoring on problem loans we use the (Priv_mon),
which indicates the degree of information that is released to of?cials and to the public,
the auditing related requirements and whether credit ratings are required. Higher
values indicate more private oversight. These ?rst three variables may be seen as
re?ecting the three pillars of Basel II accord. Finally, the impact of the independence
Missing variables Countries
Nonperforming loans Albania, Montenegro, Romania, Austria, Malta,
Lesotho, Rwanda, and Sierra Leone
Capital adequacy ratio Argentina, Albania, Montenegro, Ireland, China,
Lesotho, Rwanda, and Sierra Leone
Return on asset Montenegro, The Netherlands, China, Gabon,
Lesotho, Rwanda, Senegal, and Sierra Leone
Loan loss reserves to total loans Guatemala, Albania, Bosnia and Herzegovina,
Macedonia, Serbia, Malta, The Netherlands, Ireland,
and Luxembourg
Financial development Belarus, Dominican, Lebanon, and Mozambique
Regulatory and supervisory variables Namibia, Ukraine, UAE, Swaziland, Chile, Ecuador,
Uruguay, Bangladesh, Hong Kong, Singapore
Armenia, and Georgia
Table I.
Data construction
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Table II.
Variables de?nition
Banking
supervision and
NPLs
295
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of the supervision authority on NPLs is captured through the variable (Indep), which
indicates the level of independence of supervisory authority. Higher values signify
greater independence.
3.3 Descriptive statistics
Summary descriptive statistics for the variables used in the empirical analysis are
presented in Table III (descriptive statistics by country are presented in Appendix 1,
Table AI). We note particularly that NPLs rate presents a higher disparity between
countries with a minimum of 0.2 percent and a maximum of 26.5 percent. A similar
pattern is observed for the provisions variable ranging between 18.6 and 276.9 percent.
Furthermore, we notice that some countries have a negative GDP growth rate and
negative banking performance with minimum values of 28.86 and 28.9 percent,
respectively. With regard to the ownership structure, foreign bank participation is
higher than state property with, respectively, mean values of 33 and 14 percent. Finally,
banking systems tend to be strongly concentrated with an average of 66 percent.
The correlation matrix of the bank industry variables (Appendix 2, Table AII) shows
statistically signi?cant correlations between NPLs and all of the explanatory variables
except for the one year lagged ROAand Foreign ownership. The coef?cients indicate no
signi?cant correlations between the independent variables included. Descriptive
statistics for regulatory variables are presented in Table IV (for more details, see
Appendix 3, Table AIII for summary statistics of regulatory and supervisory variables
by country).
Variables Mean Median Min Max SD
NPLs 6.52 3.7 0.2 26.5 6.77
Difcar
t21
5.33 4.70 23.50 21.50 3.44
Prov
t21
82.63 70.40 18.60 276.90 43.33
Roa
t21
1.38 1.10 26.10 8.70 1.27
State 0.14 0.04 0 0.92 0.21
Forg 0.33 0.21 0 0.99 0.30
Conc 0.66 0.67 0.14 1 0.19
GDPgr
t21
4.08 3.91 28.86 21.18 3.17
Notes: Where NPLs is the aggregate rate of nonperforming loans; Difcar is the difference between the
CAR and the minimum required; Prov is the bank provisions to NPLs; ROA is bank return on assets;
State is government-owned bank assets divided by total bank asset; Forg is foreign-owned bank assets
divided by total bank; Conc is percentage of assets held by the ?ve largest banks; and GDPgr is the
annual real growth rate of GDP
Table III.
Descriptive statistics for
NPLs and bank industry
variables
Variables Mean Median Min Max SD
Pow_sup 11.24 11.5 5 15.5 2.55
Priv_mon 8.27 8 4 11 1.34
Indep 1.68 2 0 3 0.93
Car_index 5.52 6 2 9 1.72
Notes: Where Pow_sup is the of?cial supervisory power; Priv_mon is the private monitoring index;
Indep is the independence of supervisory authority; and Car_index is the capital regulatory index
Table IV.
Descriptive statistics
for regulatory and
supervisory variables
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3.4 Methodology
We use two speci?cations to investigate the bank industry determinants of the
aggregate NPLs and the impact of supervisory environment. The baseline model
regress the bank industry variables on NPLs. Lagged GDP growth rate and ?nancial
development are used as control variables. The second speci?cation investigates the
impact of bank supervision factors by re-estimating the baseline model including each
of the four regulatory variables. The baseline model is expressed as follows:
NPL
it
¼ a
0
þa
1
Difcar
it21
þa
2
Prov
it21
þa
3
ROA
it21
þa
4
State
it
þa
5
Forg
it
þa
6
Conc
it
þa
7
GDPgr
it21
þa
8
Fin_Dev
it
þ1
where NPL is the aggregated NPLs to total loans ratio; Difcar
t21
, is the one year lagged
bank regulatory capital to risk-weighted assets minus the required minimum capital;
Prov
t21
is the one year lagged loan loss reserves to total loans ratio; ROA
t21
is the one
year lagged ROA; State is the percentage of state-owned banks; Forg is the percentage
of foreign ownership; Conc is the percentage of assets held by the ?ve largest banks;
GDPgr
t21
is the one year lagged real GDP growth rate, and Fin_Dev is a measure of
the level of country ?nancial development. CAR, loans loss provisions, return on
assets, and GDP growth rate are introduced in the model lagged one period to avoid
endogeneity.
We use a pooled regression approach. Panel data combines both time series and
cross-section data. First, it has the advantage to increase the number of observations,
degrees of freedom and reduce collinearity among explanatory variables especially
when the number of years is low. Second, pooling enables to control for exogenous
shocks common to all banks (time effects) and reducing the omitted variable bias (unit
effects). However, simple pooled regression may not be well designed to capture
relationships between the dependent variable and explanatory variables. This is due to
the fact that pooled regression assumes homogenous behavior of endogenous variable
for all individuals in the sample (same intercept and same slopes). This is not obviously
the case for the variable NPLs, as it varies considerably between countries and over
years. Several alternative estimation methods are more suitable for panel data (?xed
and random effects). Using the Hausman test, the ?xed effect speci?cation is preferred.
However, the use of ?xed effects speci?cation raises two concerns. First, as noted by
Haas and Lelyveld (2006), unit dummies are known to eliminate too much
cross-sectional variance. Second, the inclusion of units dummies eliminates de facto
time invariant exogenous variables and does not properly capture the impact of quasi
time invariant variables (Beck, 2005). With regard to error structure, the ?xed effects
speci?cation assumes that the error terms have a constant variance over time and are
serially uncorrelated. Another possible solution would have been to include
country-speci?c dummies to capture the ?xed effects. This would have considerably
reduced the degrees of freedom (Haas and Lelyveld, 2006). Moreover, the
country-speci?c effect is captured through the inclusion of macroeconomic and
structural variables related to the ?nancial sector. To further control for possible
differences between countries, we introduced a dummy variable for the level of
?nancial development. Besides, we are rather interested in making inferences with
respect to population characteristics than in estimating the country-speci?c effect.
We also turned to test the heteroskedasticity and the autocorrelation problems.
Contemporaneous correlations (i.e. the errors across cross-sectional units are correlated
Banking
supervision and
NPLs
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due to common shocks in a given time period), panel heteroskedasticity (i.e. the error
variance differs across cross-sectional units due to characteristics unique to the units),
and serial correlation (i.e. the errors within units are temporally correlated) characterize
our data structure. Feasible generalized last squares (FGLS) speci?cation can be used
after controlling for the heteroskedasticity and the autocorrelation problems. However,
Beck and Katz (1995, 1996), advocate the use of the panel corrected standard errors
(PCSE) method to improve inferences by taking into account the complexity of the error
process. Based on Monte Carlo studies, Beck and Katz (1995, 1996) demonstrate that
PCSE produces more reliable standard errors than FGLS method. Given the features of
our data we use the PCSE method to estimate our models.
4. Empirical results
Table V shows the empirical results of our regressions. Model 1 presents results for the
baseline model. Models 2 to 5 exhibit results for the supervision factors. The estimated
coef?cients on the banking industry variables appears to be robust to the speci?cation
used. The regressions show evidence for a negative impact of the variable (DifCar) on
the credit risk exposure. This indicates that the regulatory capital serves as an
indicator of the ?nancial risk exposure of the whole banking system. These results
suggest that the CAR might be used as a regulatory device to mitigate banks excessive
risk taking (Fries et al., 2002; Sinkey and Greenawalt, 1991). In conclusion, it appears
that the ?rst pillar of Basel II does not have any statistically signi?cant impact on
NPLs.
We ?nd also a signi?cant and negative relationship between NPLs and lagged loan
loss provisions rate (Prov). Countries with higher rates of problem loans exhibit lower
level of provisions rates and vice versa. This contradicts the theoretical assertion,
which predicts the use of provisions as a risk control tool and therefore to be positively
related to problem loans. On the other hand, countries with low rates of NPLs adopt a
better provisioning policy (higher loan loss provisions). This may re?ect the general
attitude toward risk in the banking industry of each country. In countries where risk
control is more effective and considered as an essential component of banks strategy,
loan loss provisions are used, among other means, to hedge future exposures to credit
risk. From a regulatory body point view, it is thus necessary to promote strong
incentives which aim to improve banks provisioning efforts.
However, we do not ?nd any evidence for the association between NPLs and lagged
ROA. We give the following explanations to this surprising result. First, it is possible
that the relation between performance and risk taking do not hold at the aggregate
level while it holds at the bank ?rm level. In fact, the overall performance of the
banking system may hide severe variations in the individual performance of banks,
while the aggregate level of NPLs exhibit lesser variation. Second, the absence of any
relation between performance and NPLs could be due to the inclusion in the sample of
countries with different level of performance. In fact, while in developing economies,
revenue creations pressures play a central role in shaping lending activities of banks,
those experiencing such pressures in developed countries do not necessarily embark in
riskier lending offerings (in an aggregate level), as they may turn to other non credit
revenues to respond to the revenue creation pressures.
The estimate coef?cients on state property (State) are positive and signi?cant,
which indicates that state-ownership rises the level of problem loans. This could
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Table V.
Panel data regression
of NPLs
Banking
supervision and
NPLs
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be explained either by the development mandate given to state-owned banks,
especially in developing countries, or by their weaker credit recovery capacities. These
combined effects lead to higher credit risk taking and to increased defaults. This result
corroborates those of Micco et al. (2004) who conclude that NPLs tend to be higher for
state-owned banks on a panel of emerging countries.
Foreign participation (Forg) is found to have a positive effect on reducing the degree
of bank problem loans. This result corroborates the ?ndings of Levine (1996) and Barth
et al. (2002) who highlight the positive impact of foreign shareholding on ?nancial
outcomes. Another plausible explanation for this result is that banks with foreign
participation are subject to more stringent control due to a more restrictive regulatory
framework (from their home regulatory authorities) than domestic banks, which are
supposed to have weaker institutions (especially when foreign ownership is directed
fromdeveloped to developing or emerging countries). Furthermore, as noted by Lensink
and Hermes (2004), foreign ownership contributes to improve human capital and
management ef?ciency as it brings better skills, technologies, and risk management
practices, in particular in developing countries. For policy makers, our ?ndings suggest
that increased participation by foreign banks improves ?nancial stability, and hence the
ef?ciency of the banking sector. However, the recent banking crisis raised concerns
about the harmful side effects of such entry.
Finally, we ?nd a negative relationship between bank concentration and NPLs. This
result suggests that in a concentrated banking market, risky borrowers cannot easily
access to credit from large banks which monopolize the banking sector (Fernandez de
Lis et al., 2000). On the other hand, in a non-concentrated market, increased competition
among lenders leads banks to relax the credit constraints which thus rises loans defaults
occurrence. Our ?ndings give hence evidence to the “competition-fragility” view, which
highlights the bene?ts of bank concentration (Allen and Gale, 2004). We then contribute
to the controversial debate over the impact of banking concentration on ?nancial
stability.
The estimated coef?cient for the lagged growth rate is not signi?cant, indicating that
economic conditions is not related to problem loans. This result is contradictory to both
theoretical prediction and common wisdom, which relate economic cycle to credit
quality of borrowers (Sinkey and Greenawalt, 1991; Salas and Saurina, 2002). However,
we document that the level of problem loans is higher in less ?nancially developed
economies.
We now turn to the investigation of the impact of the regulatory environment on
problem loans (Table V). For all the speci?cations used, the main relations remain the
same for all the variables of the basic model, indicating the robustness of our previous
results. However, all regulatory variables introduced are not signi?cant. These ?ndings
suggest that he regulatory channel is not the optimal device to reduce risk taking and
hence problem loans. The ineffectiveness of all the statutory powers reported in our
study corroborates the growing literature on the absence of any relationship between
supervisory regulation and banking outcomes.
To further investigate the extent of our results, we divide the sample into two groups:
developed and developing countries. Despite the fact that we control for differences
across countries and across time, countries which are more developed are likely to have
mature markets and institutions which can in?uence NPLs. We re-estimate the different
models for the two subsamples. The results are reported in Table VI.
JFEP
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Table VI.
Panel data regression
of NPLs
Banking
supervision and
NPLs
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The results are different for the two subsamples regarding foreign participation. In
developing countries, foreign ownership contributes to the reduction of NPLs. This
result corroborates our previous ?ndings. On the contrary, foreign participation
worsens the credit quality of banks in developed countries. Owing to similarities
in human capital ef?ciency and to a more homogenous regulatory framework, foreign
and domestic banks do not exhibit substantial differences in the assessment of credit
quality of borrowers. However, foreign banks as they seek to conquest local market
shares may engage in riskier activities and thus are exposed to greater risk compared
to domestic ?rms. With regard to bank performance, the estimated coef?cient entered
signi?cantly only for developed countries panel. This indicates that risk taking is
increased in banking systems exhibiting high levels of performance. Our results
corroborates those of Garcia-Marco and Robles-Fernandez (2007) who argue that
pro?t-maximizing policies are usually accompanied by higher levels of risk.
Regarding economic conditions, the estimated coef?cient for the lagged growth rate
enters negatively and signi?cantly indicating that economic conditions contribute to
explain problem loans. Economic booms improve borrowers credit quality and
facilitate repayments particularly in developing countries.
On the other hand, differences are found between countries as regard to the effect of
supervisory variables on ?nancial system stability when we split the sample into
developing and developed countries. In referring to the group of developing countries,
regulatory variables do not serve to control credit risk. Moreover, public supervision
power is reported to increase problem loans. This indicates that in developing
countries granting more power to supervisory bodies is counterproductive. We
contend that in immature markets, where civil discipline is low, corruption is high, and
institutions are weak, the regulatory channel is not the optimal device to reduce risk
taking and hence problem loans. For the developed countries panel, only capital
adequacy stringency and independence of supervisory authority enters signi?cantly.
In contrast, market discipline (private monitoring) shows no signi?cant association
with the level of problem loans. This may be explained by the fact that in developed
countries the variable Priv_mon exhibits no signi?cant variability across countries
and thus does not contribute to discriminate differences in NPLs.
However, as noted by several authors, the inef?cacy of regulatory devices may be
due to the fact that the measures used for regulatory variables only “relate to statutory
powers” and not to the effective power. Second, the ef?cacy of regulatory reforms
depends mainly on the quality and the effectiveness of the political and social
institutions. The next section seeks to expose and to explain the different aspects
related to this issue.
5. Discussion: explaining the ineffectiveness of regulatory devices
Hafeez (2003) stresses out that political institutions, corruption, rule of law and
protection of property rights play a central role in the ef?cacy of regulatory
reforms. As noted by Barth et al. (2006), strengthening of?cial supervision will enhance
the overall ?nancial development. The previous studies dealing with banking
regulation do not, however, consider whether the effective implementation of those
regulations play any role in the ef?cacy of such policies. To further investigate the
impact of regulatory and supervisory framework on problem loans, we introduced
three interactions to account for possible effect of the political and legal environment
JFEP
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(
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on the effectiveness of regulation. We hence consider three factors: the level of
corruption, the degree of democracy, and the rule of law.
Barth et al. (2006) highlight that conventional of?cial regulation and supervision
does not improve banking outcomes, especially in countries with weak political
institutions. They emphasize that empowering of?cial supervision and regulation will
lead to an increase in corrupt bank lending. Anderson (2004) supports this view. He
?nds that conventional government regulation is more likely to be counterproductive
as regulators are less competent than bankers and are exposed to corruption and to
political pressure. They end up by serving the interest of the banking industry and
pressure groups either than serving the public interest. Corruption could also be present
in privately owned banks especially in societies with little democratic traditions and
civil discipline (Finkel et al., 2000; Johnson and Wilson, 2000). In such societies, decision
makers are exposed to informal connections and other pressures from groups seeking
for unjusti?ed or illegal economic rents. The level of corruption is accounted for by the
corruption perception index (CPI) which ranges from ten (squeaky clean) to zero
(highly corrupt). To introduce the interactions terms, we constructed a dummy variable
taking 1 for countries with CPI value less than 5 and 0 otherwise.
On the other hand, Barth et al. (2004) stress out that of?cial supervision may be
harmful to the development of the banking sector in countries with less political
openness. Barth et al. (2006) suggest taking into account the level of democracy in the
country when evaluating the impact of supervisory independence on banking sector
outcomes. According to Sobel (2003), the level of democracy which depends on the
extent of political and civil freedom, will shape regulatory vulnerability to political and
other groups pressures. In fact, democratic governments through countervailing forces
and institutions are constrained to pursue public interest (Tsebelis, 1995; Eichengreen,
1998). However, the extent to which democracy and political participation shape
economic outcomes is somewhat controversial. Wittman (1995), Pastor and Sung (1995)
and Leblang (1997) argument that enhanced democracy precludes economic growth.
Helliwell (1994) and Alesina and Rodrik (1994) suggest that democracy is negatively
linked to economic outcomes. Finally, Keech (1995) and Clague et al. (1996) ?nd mixed
results. The level of democracy is accounted for by the democracy index which ranges
between 0 (authoritarian regime) and 10 (full democracy). For the purpose of our study,
we constructed a dummy variable taking 1 for countries with democracy index value
superior to 6 (democratic countries) and 0 otherwise (The Economist Intelligence Unit’s
Index of Democracy, 2007).
Finally, the extent to which contracts and laws are enforced in the country may
impact the ef?cacy of the implementation of both existing and newly implemented
regulations. This is particularly true as the global economy is moving toward
market-based systems. To this extent, Carothers (1998) notes that the rule of law is
central to both economic development and democracy. Besides, international
institutions are devoting considerable resources to strengthen legal institutions in
several countries. To account for the level of law enforcement, we use the rule of
law index developed by Kaufmann et al. (2008). It ranges between 22.5 (worst
execution of laws) and 2.5 (best enforcement). We introduce a dummy variable that
takes 1 for countries with values of rule of law index superior to the median and
0 otherwise.
Banking
supervision and
NPLs
303
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(
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In contrast with Barth et al. (2006), who consider only the impact of these variables
to examine their impact on bank crisis and other ?nancial outcomes, we investigate
this channel through the inclusion of interaction terms between the three political and
business environment variables and each of the regulatory and supervision variables.
Results for the full model including each of the supervisory and regulatory variables
together with the interaction terms are reported in Tables VII-IX. The main relations
remain the same for all the variables of the basic model (bank industry variables),
indicating the robustness of our previous results.
Table VII presents regression results after controlling for the level of corruption. In
countries with little corruption, only the level of independence of the supervision
authority is reported to reduce the level of NPLs. The other three regulatory devices
considered in our study have no signi?cant impact on the level of problem loans. In this
regard, we consider our results contradictory to those of Barth et al. (2004, 2006). In
fact, they conclude for the superiority of the self-regulated systems (private interest
view) based on the signi?cance of the relationship between banking outcomes and the
market discipline after controlling for the degree of corruption. Our results add
inconsistency to this point of view which is yet con?rmed by the 2008 crisis. At the
opposite, in corrupt systems the strength and the empowerment of regulation and
of?cial supervision seem to be counterproductive. All the interaction terms are
signi?cantly positive. Again, we argue that in corrupt banking markets, where civil
discipline is low and institutions are weak, the regulatory channel is not the optimal
device to reduce risk taking and hence problem loans.
Table VIII exhibits the results of regressions after taking into account the level of
democracy of a country. First, we ?nd that the stringency of regulatory capital, of?cial
supervisory power and the independence of supervisory authority positively impact
lending activities and hence reduces the level of problem loans in politically opened
countries. In contrast, there is no support for the view that private monitoring boosts
?nancial stability. We consider our ?ndings as an evidence (albeit not strong) against
the superiority of the private interest view over the public interest view. Second, for
countries with little democratic roots, the results show no signi?cant impact of
regulatory traits on the level of problem loans.
Table IX reports the results for the regression using the interaction between
regulatory variables and the rule of law. The results show clearly that in countries
where laws are better enforced, regulatory devices seem to have a positive impact on
the quality of loans. In contrast, in countries with weak rule of law, the stringency of
regulatory capital and private monitoring have an adverse impact on problem loans
and lending activities. There is however no support for any impact of the other two
regulatory traits.
Our empirical results broadly corroborates the growing number of studies which
suggest that there is no consensus as to what constitutes good regulation and supervision,
or how speci?c regulations in?uence the performance and the stability of the banking
sector (Barth et al., 2004; Beck et al., 2006b; Demirguc-Kunt et al., 2008; Shaffer, 2008). Our
results stress further the inef?cacy of regulations based on market discipline and indirect
monitoring, especially in immature markets. The ?ndings highlight that prior to
regulation reforms, international institutions have to focus on enhancing market
transparency, law enforcement, promoting healthy political institutions, and increasing
transparency and accountability.
JFEP
1,4
304
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Table VII.
Panel data regression
of NPLs (interaction CPI)
Banking
supervision and
NPLs
305
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(
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0
2
7
0
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0
0
0
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*
*
C
a
r
_
i
n
d
e
x
0
.
3
2
0
0
.
0
0
9
*
*
*
C
a
r
_
i
n
d
e
x
*
D
e
m
o
c
2
0
.
3
6
9
0
.
0
1
8
*
*
P
o
w
_
s
u
p
0
.
0
9
4
0
.
3
2
9
P
o
w
_
s
u
p
*
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e
m
o
c
2
0
.
1
9
3
0
.
0
4
0
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*
P
r
i
v
_
m
o
n
0
.
2
6
9
0
.
0
7
9
*
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r
i
v
_
m
o
n
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e
m
o
c
2
0
.
2
1
6
0
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0
7
0
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n
d
e
p
0
.
6
4
7
0
.
1
3
5
I
n
d
e
p
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e
m
o
c
2
1
.
1
2
5
0
.
0
2
7
*
*
I
n
t
e
r
c
e
p
t
1
7
.
4
7
1
0
.
0
0
0
*
*
*
1
9
.
1
5
2
0
.
0
0
0
*
*
*
1
7
.
7
5
6
0
.
0
0
0
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*
*
1
8
.
8
4
6
0
.
0
0
0
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*
*
R
2
0
.
5
8
6
3
0
.
5
9
1
0
0
.
5
8
5
8
0
.
5
7
5
1
N
b
.
G
r
o
u
p
s
(
O
b
s
.
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
*
1
0
,
*
*
5
,
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
m
e
t
h
o
d
e
s
t
i
m
a
t
i
o
n
i
s
p
a
n
e
l
c
o
r
r
e
c
t
e
d
s
t
a
n
d
a
r
d
e
r
r
o
r
s
;
w
h
e
r
e
D
i
f
c
a
r
i
s
t
h
e
d
i
f
f
e
r
e
n
c
e
b
e
t
w
e
e
n
t
h
e
C
A
R
a
n
d
t
h
e
m
i
n
i
m
u
m
r
e
q
u
i
r
e
d
;
P
r
o
v
i
s
t
h
e
b
a
n
k
p
r
o
v
i
s
i
o
n
s
t
o
N
P
L
s
;
R
O
A
i
s
b
a
n
k
r
e
t
u
r
n
o
n
a
s
s
e
t
s
;
S
t
a
t
e
i
s
g
o
v
e
r
n
m
e
n
t
-
o
w
n
e
d
b
a
n
k
a
s
s
e
t
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
b
a
n
k
a
s
s
e
t
;
F
o
r
g
i
s
f
o
r
e
i
g
n
-
o
w
n
e
d
b
a
n
k
a
s
s
e
t
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
b
a
n
k
a
s
s
e
t
;
C
o
n
e
i
s
p
e
r
c
e
n
t
a
g
e
o
f
a
s
s
e
t
s
h
e
l
d
b
y
t
h
e
?
v
e
l
a
r
g
e
s
t
b
a
n
k
s
;
G
D
P
g
r
i
s
t
h
e
a
n
n
u
a
l
r
e
a
l
g
r
o
w
t
h
r
a
t
e
o
f
G
D
P
;
D
e
v
?
n
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
t
h
a
t
t
a
k
e
s
1
f
o
r
?
n
a
n
c
i
a
l
d
e
v
e
l
o
p
e
d
c
o
u
n
t
r
i
e
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
D
e
m
o
c
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
t
h
a
t
t
a
k
e
s
1
f
o
r
d
e
m
o
c
r
a
t
i
c
c
o
u
n
t
r
i
e
s
a
n
d
0
o
t
h
e
r
w
i
s
e
,
P
o
w
_
s
u
p
i
s
t
h
e
o
f
?
c
i
a
l
s
u
p
e
r
v
i
s
o
r
y
p
o
w
e
r
;
P
r
i
v
_
m
o
n
i
s
t
h
e
p
r
i
v
a
t
e
m
o
n
i
t
o
r
i
n
g
i
n
d
e
x
;
I
n
d
e
p
i
s
t
h
e
I
n
d
e
p
e
n
d
e
n
c
e
o
f
s
u
p
e
r
v
i
s
o
r
y
a
u
t
h
o
r
i
t
y
;
a
n
d
C
a
r
_
i
n
d
e
x
i
s
t
h
e
c
a
p
i
t
a
l
r
e
g
u
l
a
t
o
r
y
i
n
d
e
x
Table VIII.
Panel data regression
of NPLs (interaction
democracy)
JFEP
1,4
306
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
3
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
M
o
d
e
l
1
M
o
d
e
l
2
M
o
d
e
l
3
M
o
d
e
l
4
I
n
d
e
p
v
a
r
i
a
b
l
e
s
C
o
e
f
?
c
i
e
n
t
s
p
-
v
a
l
u
e
C
o
e
f
?
c
i
e
n
t
s
p
-
v
a
l
u
e
C
o
e
f
?
c
i
e
n
t
s
p
-
v
a
l
u
e
C
o
e
f
?
c
i
e
n
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p
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e
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2
1
2
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v
t
2
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o
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g
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3
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o
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2
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6
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.
1
3
0
D
e
v
_
?
n
2
5
.
5
8
6
0
.
0
0
2
*
*
*
2
5
.
0
3
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0
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0
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*
*
2
5
.
3
3
1
0
.
0
0
1
*
*
*
2
5
.
1
3
5
0
.
0
0
1
*
*
*
C
a
r
_
i
n
d
e
x
0
.
2
8
0
0
.
0
0
8
*
*
*
C
a
r
_
i
n
d
e
x
*
R
L
a
w
2
0
.
4
2
9
0
.
0
0
6
*
*
*
P
o
w
_
s
u
p
0
.
0
4
8
0
.
6
1
3
P
o
w
_
s
u
p
*
R
L
a
w
2
0
.
2
5
3
0
.
0
0
3
*
*
*
P
r
i
v
_
m
o
n
0
.
2
8
7
0
.
0
6
3
*
P
r
i
v
_
m
o
n
*
R
L
a
w
2
0
.
2
5
9
0
.
0
2
4
*
*
I
n
d
e
p
0
.
4
4
9
0
.
1
4
8
I
n
d
e
p
*
R
L
a
w
2
1
.
4
7
9
0
.
0
0
1
*
*
*
I
n
t
e
r
c
e
p
t
1
7
.
2
5
9
0
.
0
0
0
*
*
*
1
8
.
5
1
2
0
.
0
0
0
*
*
*
1
7
.
6
4
5
0
.
0
0
0
*
*
*
1
7
.
0
8
2
0
.
0
0
0
*
*
*
R
2
0
.
5
9
0
8
0
.
5
9
0
4
0
.
5
9
9
4
0
.
6
2
9
9
N
b
.
G
r
o
u
p
s
(
O
b
s
.
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
5
9
(
2
9
5
)
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
*
1
0
,
*
*
5
,
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
m
e
t
h
o
d
e
s
t
i
m
a
t
i
o
n
i
s
p
a
n
e
l
c
o
r
r
e
c
t
e
d
s
t
a
n
d
a
r
d
e
r
r
o
r
s
;
w
h
e
r
e
D
i
f
c
a
r
i
s
t
h
e
d
i
f
f
e
r
e
n
c
e
b
e
t
w
e
e
n
t
h
e
C
A
R
a
n
d
t
h
e
m
i
n
i
m
u
m
r
e
q
u
i
r
e
d
;
P
r
o
v
i
s
t
h
e
b
a
n
k
p
r
o
v
i
s
i
o
n
s
t
o
N
P
L
s
;
R
O
A
i
s
b
a
n
k
r
e
t
u
r
n
o
n
a
s
s
e
t
s
;
S
t
a
t
e
i
s
g
o
v
e
r
n
m
e
n
t
-
o
w
n
e
d
b
a
n
k
a
s
s
e
t
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
b
a
n
k
a
s
s
e
t
;
F
o
r
g
i
s
f
o
r
e
i
g
n
-
o
w
n
e
d
b
a
n
k
a
s
s
e
t
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
b
a
n
k
;
C
o
n
e
i
s
p
e
r
c
e
n
t
a
g
e
o
f
a
s
s
e
t
s
h
e
l
d
b
y
t
h
e
?
v
e
l
a
r
g
e
s
t
b
a
n
k
s
;
G
D
P
g
r
i
s
t
h
e
a
n
n
u
a
l
r
e
a
l
g
r
o
w
t
h
r
a
t
e
o
f
G
D
P
;
D
e
v
?
n
i
s
a
d
u
m
m
y
v
a
r
i
a
b
l
e
t
h
a
t
t
a
k
e
s
1
f
o
r
?
n
a
n
c
i
a
l
d
e
v
e
l
o
p
e
d
c
o
u
n
t
r
i
e
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
R
l
a
w
i
s
t
h
e
r
u
l
e
o
f
l
a
w
i
n
d
e
x
;
P
o
w
_
s
u
p
i
s
t
h
e
o
f
?
c
i
a
l
s
u
p
e
r
v
i
s
o
r
y
p
o
w
e
r
;
P
r
i
v
_
m
o
n
i
s
t
h
e
p
r
i
v
a
t
e
m
o
n
i
t
o
r
i
n
g
i
n
d
e
x
;
I
n
d
e
p
i
s
t
h
e
I
n
d
e
p
e
n
d
e
n
c
e
o
f
s
u
p
e
r
v
i
s
o
r
y
a
u
t
h
o
r
i
t
y
;
a
n
d
C
a
r
_
i
n
d
e
x
i
s
t
h
e
c
a
p
i
t
a
l
r
e
g
u
l
a
t
o
r
y
i
n
d
e
x
Table IX.
Panel data regression
of NPLs (interaction rule
of law)
Banking
supervision and
NPLs
307
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
3
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
6. Conclusion
In this paper, we proposed an empirical framework to investigate the bank industry
factors and supervisory determinants of NPLs on a cross-country basis. First, we use
speci?c variables that capture many of the factors suggested by the theory and
highlighted by case studies. Besides, to investigate the role of the regulatory
framework on credit risk outcomes, we introduce variables on banks supervision.
Finally, to assess the impact of the effective implementation of those regulations, we
experiment interactions of three institutional variables (corruption, democracy, and
rule of law) with each of the supervision proxies. In contrast with previous work,
we include interaction terms between political and business environment variables
and each of the supervision variables to investigate their impact on banks credit
exposures.
Using aggregate data on a panel of 59 countries over the period 2002-2006 and
robust econometric techniques, we ?nd strong evidence on the association between
NPLs and bank speci?c variables. Particularly, higher CARs and higher provisions
ratios are negatively associated with the level of problem loans. These results remain
robust even when we split the sample into developing and developed countries. We
also report a desirable impact of private ownership, foreign participation, and bank
concentration on the stability of the bank sector. However, foreign entry is reported to
deteriorate the credit exposure of ?nancial institutions in developed countries. We
contend that due to aggressive commercial strategies when penetrating domestic
markets, foreign banks, and investors tend to take on excessive risks compared to local
banks. Among the control variables, only ?nancial development explains the level of
NPLs. However, economic conditions do not signi?cantly impact bank credit outcomes
in developed countries. Economic cycles seem only matter in developing economies.
Finally, we examine the extent to which supervisory framework has a positive
impact on credit risk exposures. Our primarily results indicate no support for any
relation between of?cial supervision and problem loans. This adds to the growing
evidence against the effectiveness of such devices.
However, our results suffer from the fact that the measures used only relate to
statutory powers. Thus, they do not address the issue of the effective implementation
of supervisory reforms. To investigate this channel, we introduce three interactions
using the level of corruption, the degree of political openness, and the rule of law. All of
these variables are supposed to have an impact on the ef?cacy of regulation. Our
?ndings do not support the view that market discipline (albeit not strongly) leads to
better economic outcomes and to reduce the level of problem loans. Our contention is
drawn upon the absence of any association between the variable private monitoring
and the level of problem loans. Indeed, using various speci?cations (interactions terms
and subsamples of developed and developing countries) the coef?cients never entered
signi?cantly.
Moreover, all regulatory devices either exert a counterproductive impact on
problem loans or do not signi?cantly enhance credit risk exposures for countries with
weak institutions, corrupt business environment, and little democracy. These ?ndings
are con?rmed by the results for the developing countries panel. Moreover, the
coef?cient estimate on the variable supervisory power indicates a positive association
with the level of NPLs. Our results suggest that granting increased power to central
bankers is detrimental for ?nancial stability in developing economies.
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Our results have the following policy implications. First, higher CARs results in less
credit exposures. Second, more developed ?nancial systems experience improved
stability. Hence, international regulators should continue their efforts to enhance
?nancial development. Third, private ownership and foreign participation insure
healthier ?nancial systems in less developing economies. Although we do not show
evidence for causality, our results suggest that foreign participation plays an
important role in reducing credit exposure of ?nancial institutions. However, in
developed countries foreign entry led to more problem loans. Finally, to reduce credit
risk exposure in countries with weak institutions, the effective way to do it is through
enhancing the legal system, strengthening institutions, and increasing transparency
and democracy.
Note
1. For Indonesia, we used values from the third version of the survey of Barth et al. for the
entire period 2002-2006 due to lack of data over the period 2002-2003.
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(Appendices follow overleaf.)
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5
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2
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0
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5
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8
6
5
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7
8
(
c
o
n
t
i
n
u
e
d
)
Table AI.
Descriptive statistics
for banking industry
variables by country
JFEP
1,4
314
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
E
R
S
I
T
Y

A
t

2
1
:
3
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
C
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N
o
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s
:
W
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N
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;
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a
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m
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q
u
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d
;
P
r
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b
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p
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o
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;
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;
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t
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v
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f
G
D
P
Table AI.
Banking
supervision and
NPLs
315
D
o
w
n
l
o
a
d
e
d

b
y

P
O
N
D
I
C
H
E
R
R
Y

U
N
I
V
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R
S
I
T
Y

A
t

2
1
:
3
6

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Appendix 2
N
P
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Table AII.
Correlation matrix
for variables used
JFEP
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Appendix 3
Country
Car index
(Car_index)
Supervisory power
(Pow_sup)
Independence
(Indep)
Private monitoring
(Priv_mon)
Australia 5.8 11.8 2.6 8.4
Belgium 4.2 10.4 2 7.6
Bolivia 4 10.8 2 7.6
Bulgaria 7 11 3 7.6
Canada 3 11 2.4 8.8
Colombia 4.2 13.6 0 9
Costa Rica 5.6 13 0.4 7.6
Croatia 4 11.2 2.4 8.2
Czech 5.2 8.8 2.6 7.6
Denmark 5.8 9.4 0.8 8.8
Egypt 4 14 2.6 8.4
Estonia 5 13 2 7
Finland 4.6 6 2 9.6
France 5.4 7.6 1 7.4
Germany 5.4 8 1 9
Ghana 6 12.4 1.4 5.2
Greece 5.2 11.2 1.6 8.4
Hungary 6 14.2 3 9.6
Iceland 6.8 5 0 8
India 7 10 2 8
Indonesia 7 15 2 10
Israel 5.6 7 1 8.8
Italy 4 7 0.8 8.6
Japan 5 11.4 1.4 9.2
Jordan 6.6 14 2.2 8
Kazakhstan 7 12 1 7.4
Kenya 6.6 13.3 2 9.2
Korea 3.4 12 1.6 9
Kuwait 7.4 9.6 2 10
Latvia 5.6 13 3 8.4
Lithuania 3.6 11 2 8.2
Malaysia 4.2 11 2.4 8.8
Mexico 6 8 0.4 10
Morocco 5.2 12.7 1 8.6
Nigeria 6.6 12.4 2.6 7.2
Norway 7.2 8.6 2.4 8
Oman 6 12 0 7
Pakistan 9 14 3 9
Panama 4.6 11.4 1 7.4
Paraguay 4 14 2 7
Peru 3.8 12 1.6 7.6
Philippines 5.8 11.8 1 8.2
Poland 3.6 8.4 0.8 8.6
Portugal 7.4 14 3 7
Russia 6.8 11.5 2 7.2
Salvador 3.6 10.4 1 9.2
(continued)
Table AIII.
Descriptive statistics
for regulatory variables
by country
Banking
supervision and
NPLs
317
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About the authors
Abdelkader Boudriga is a Professor of Finance at the ISCC, Bizerte, University of Carthage and a
Visiting Professor at the University of Orle´ans, France. He holds a PhD degree in Finance from
the Faculty of Economics and Management of Tunis. He is a Fulbright alumni. He conducts
research on ?nancial systems stability and the informational ef?ciency of ?nancial markets.
He published several papers in international and Tunisian refereed journals. He participates
permanently in international conferences in Tunisia, in the Middle East and in Europe. He is also
appointed as a Consultant at the Tunisian Bankers Association and the Institut Arabe des Chefs
d’Entreprises. Abdelkader Boudriga is the corresponding author and can be contacted at:
[email protected]
Neila Boulila Taktak is a Professor of Accounting at the ESSECT, University of Tunis,
Tunisia. His research interests are accounts manipulations, international accounting standards,
and banking. His research has been published in journals such as Comptabilite´, Controˆ le, Audit
(France).
Sana Jellouli is a PhD student in Finance. She is currently working on her ?nal dissertation on
the determinants of credit risk in Tunisian banks. She participates regularly to international
conferences in Tunisia and abroad. She teaches ?nance and accounting at the School of
Electronic Commerce, Tunis.
Country
Car index
(Car_index)
Supervisory power
(Pow_sup)
Independence
(Indep)
Private monitoring
(Priv_mon)
Saudi Arabia 4.4 13.6 1.4 9.4
Slovak 5.4 13.6 1.6 6.8
South Africa 7.2 6 1.6 9.4
Spain 9 10 1.4 8.4
Sweden 2.8 6.8 2 8
Switzerland 6.4 14 2.2 8.2
Thailand 4.8 9.4 0 9.4
Tunisia 7 13 2 5
Turkey 6 15.5 1 9
USA 5.4 13.6 2.4 11
Uganda 8 15 3 7
UK 6.4 11 1.8 10.6
Venezuela 3.2 11.8 1 6.6
Notes: Where Pow_sup is the of?cial supervisory power; Priv_mon is the private monitoring index;
Indep is the independence of supervisory authority; and Car_index is the capital regulatory index Table AIII.
JFEP
1,4
318
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This article has been cited by:
1. Amit Ghosh. 2015. Banking-industry specific and regional economic determinants of non-performing
loans: Evidence from US states. Journal of Financial Stability 20, 93-104. [CrossRef]
2. Timo Tammi. 2013. Are a culture of trust and morality associated with paying and repaying behavior?.
Journal of Financial Economic Policy 5:3, 313-328. [Abstract] [Full Text] [PDF]
3. Neila Boulila Taktak, Sarra Ben Slama Zouari, AbdelKader Boudriga. 2010. Do Islamic banks use loan
loss provisions to smooth their results?. Journal of Islamic Accounting and Business Research 1:2, 114-127.
[Abstract] [Full Text] [PDF]
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