Banking regulation and supervision can it enhance stability in Europe

Description
This paper aims to find the effects of regulatory and supervisory policies on bank
risk-taking. The same regulation and supervision have different effects on bank risk-taking
depending on influence factors. These factors were considered and a sample of the largest
European banks from France, Germany, UK, Italy, Spain and Greece was used over the period
2005-2011.

Journal of Financial Economic Policy
Banking regulation and supervision: can it enhance stability in Europe?
Faten Ben Bouheni
Article information:
To cite this document:
Faten Ben Bouheni , (2014),"Banking regulation and supervision: can it enhance stability in Europe?",
J ournal of Financial Economic Policy, Vol. 6 Iss 3 pp. 244 - 269
Permanent link to this document:http://dx.doi.org/10.1108/J FEP-11-2013-0059
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J ames R. Barth, Gerard Caprio, Ross Levine, (2013),"Bank regulation and supervision in 180
countries from 1999 to 2011", J ournal of Financial Economic Policy, Vol. 5 Iss 2 pp. 111-219 http://
dx.doi.org/10.1108/17576381311329661
Mikael Petitjean, (2013),"Bank failures and regulation: a critical review", J ournal of Financial Regulation and
Compliance, Vol. 21 Iss 1 pp. 16-38http://dx.doi.org/10.1108/13581981311297803
Galina Hale, J oão A.C. Santos, (2014),"Do banks propagate debt market shocks?", J ournal of Financial
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Banking regulation and
supervision: can it enhance
stability in Europe?
Faten Ben Bouheni
TELECOM Business School and University of Evry-Val-d’Essonne,
Evry, France
Abstract
Purpose – This paper aims to fnd the effects of regulatory and supervisory policies on bank
risk-taking. The same regulation and supervision have different effects on bank risk-taking
depending on infuence factors. These factors were considered and a sample of the largest
European banks from France, Germany, UK, Italy, Spain and Greece was used over the period
2005-2011.
Design/methodology/approach – In this paper, the author analyses the effects of regulation and
supervision on risk-taking. The author uses a sample of the biggest banks from six European
countries (France, UK, Germany, Italy, Spain and Greece) over the period 2005-2011. Because the
applicable entry of IFRS was in 2005, thus data of European banks are not available before this
date. For each country in the sample, the 10 largest banks (defned by total assets) that lend money
to frms were identifed. The author does not include central banks or postal banks, which generally
do not lend money to frms and are described as non-banking institutions (La Porta et al., 2002).
Findings – It was found that restrictions on bank activities, supervisors’ power and capital
adequacy decrease risk-taking. Thus, regulation and supervision enhance bank’s stability. While,
deposit insurance increases the risk due to its association to moral hazard. Finally, it was found
that strengthening regulatory and supervisory framework raises the risk-taking and weakens the
stability of European banks.
Originality/value – The author contributes to existing empirical analyses in three ways. First, the
existing literature has drawn a lot of attention on US banks. However, the purpose of this paper is
to examine the biggest banks of three European leaders (France, Germany and UK) and three more
European countries infuenced by the recent crisis (Spain, Italy and Greece) over the period
2005-2011. Second, most studies focus mainly on the relationship between regulation and
proftability, yet seldom on the relationship between regulation, supervision and risk-taking. The
author focuses on this relationship. Third, this study applies the two-step dynamic panel data
approach suggested by Blundell and Bond (1998) and also uses dynamic panel generalized method
of moments (GMM) method to address potential problems. The two-step GMM estimator that the
author uses is generally the most effcient.
Keywords European banks, Risk-taking, Restriction on bank activities, Deposit insurance,
Banking supervision, Dynamic panel, Capital adequacy
Paper type Research paper
1. Introduction
Risk-taking has been widely debated in the fnancial literature since the 80s,
especially Bowman (1980); Tversky and Kahneman (1981) and McCrimmon and
JEL classifcation – G28, G21, G32, C23
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. 6 No. 3, 2014
pp. 244-269
©Emerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-11-2013-0059
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Wehrung (1986). Nowadays, further to the recent international crisis of 2007/2008,
managerial risk-taking has been specifcally emphasized. Indeed, it becomes worth
pointing out the determinants of managerial risk-taking. In fact, this crisis makes
risk-taking a fundamental economic theme, bringing also attention to the
supervisory and regulatory environment, and thereby becoming a most challenging
topic of worldwide research.
Although banking regulation and supervision are being rewritten and
restructured in response to the global fnancial crisis, their implementation requires
complex steps depending on each country’s national policies, which could have
different effects on bank risk-taking depending on the fnancial and institutional
environment in which the banks operate (Ben Bouheni, 2013a). It is thus no surprise
that the relationship between bank regulation and risk has recently become a hot
topic. However, empirical studies on this topic are inconclusive and mixed:
Demirguc-Kunt and Detragiache (2002), Beck et al. (2006) and Chortareas et al. (2012)
found that banking supervisory reforms were positively associated with the
stability of banks. Alternatively, powerful supervisors may exert a negative
infuence on bank stability. Powerful supervisors may use their powers to beneft
favoured constituents, attract campaign donations and extract bribes (Shleifer and
Vishny, 1998). However, according to Barth et al. (2001), there is mixed evidence
regarding the impact of regulatory restrictions on bank stability. Leaven and Levine
(2009) conclude that capital requirements do not have an independent effect on bank
stability, while activity restrictions are associated with a particularly large increase
in bank risk-taking. Recently, Murphy (2013) shows that the pending European
Union (EU) regulations restrictions will increase rather than decrease incentives for
excessive risk-taking.
In this paper, the author analyses the effects of regulation and supervision on
risk-taking by European banks over the period 2005-2011. The author contributes to
existing empirical analyses in three ways. First, while the existing literature has drawn
a lot of attention on US banks, the purpose of this paper is to examine the biggest banks
of three European leaders (France, Germany and UK) and three more European
countries infuenced by the recent crisis (Spain, Italy and Greece) in 2005-2011. Second,
most studies focus mainly on the relationship between regulation and proftability, yet
seldomon the relationship between regulation, supervision and risk-taking. The author
focuses on this relationship. Third, this study applies the dynamic panel data techniques
and the two-step generalized method of moments (GMM) method developed by Blundell
and Bond (1998) to address potential problems. The two-step GMM estimator that the
author uses is generally the most effcient.
The paper seeks to assess the effects of regulatory and supervisory policies on bank
risk-taking. When infuence factors were considered, it was found that restrictions on
bank activities and offcial supervisors’ power decrease risk-taking. However, the
deposit insurance increases the risk because it is strongly associated with moral hazard
(Demerguc-Kunt and Detragiache, 2002). Nevertheless, when the bank-level indicators
are considered, it was found that capital adequacy decreases risk-taking, as the capital
requirement aligns a bank’s interests with those of its depositors.
The remainder of this paper is organized as follows. Section 2 reviews the relevant
literature; Section 3 describes the methodology and the data used herein; Section 4
discusses the empirical results; and Section 5 presents the conclusions.
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2. Regulation, supervision and risk-taking
Theory predicts that each category of regulations and supervisions infuences the
risk-taking differently. For example, deposit insurance intensifes the ability and
incentives of stockholders to increase risk (Merton, 1977; Keeley, 1990). The impetus
for greater risk-taking generated by deposit insurance is due to the moral hazard. As
a second example, consider capital regulations. One purpose of capital regulations is
to reduce the risk-taking incentives of owners by forcing owners to place more of
their personal wealth at risk in the bank (Kim and Santomero, 1994). However, while
capital regulations might induce the bank to raise capital, they might not force
infuential owners to invest more of their own wealth in the bank. Furthermore,
capital regulations might increase risk-taking. Owners might compensate for the
loss of utility from more stringent capital requirements by selecting a riskier
investment portfolio (Koehn and Santomero, 1980; Buser et al., 1981). As a third
example, many countries attempt to reduce bank risk by restricting banks from
engaging in non-lending activities, such as securities and insurance underwriting
(Boyd et al., 1998). As for capital requirements, however, these activity restrictions
could reduce the utility of owning a bank, intensifying the risk-taking incentives of
stakeholders. As a fnal example, banking supervisors are aiming to reduce
risk-taking. Buch et al. (2008) used the database compiled by Barth et al. (2001) and
found that the supervisory systems infuence the total risk of cross-bank mergers.
Thus, the impact of banking reforms on risk depends on the infuence of each
category of regulations and supervisions.
The managerial risk-taking must not be led in the same way, as the legal setting
varies through activities. It seems that legislation not only greatly discourages
managers from incurring risks but also punishes them when they do not maximize the
frm value. Its impact on managerial risk-taking is then confused and it depends on the
specifcity of the business itself (Beasley et al., 2005). In countries with low accounting
and auditing requirements, more power on offcial supervisory authorities may reduce
risk-taking behaviour by managers (Buch and DeLong, 2008). Moreover, they indicate
that higher restrictions on bank activities can diminish the probability of a banking
crisis (Fernandez and Gonzalez, 2005).
Alternatively, Barth et al. (2001) fnd that there is mixed evidence regarding the
impact of regulatory and supervisory policies on bank stability. Thus, Barth et al.
(2004) provide empirical evidence for the impact of specifc regulatory and
supervisory practices on bank development, performance and stability using survey
data from a sample of 107 countries. The results suggest that there is no statistically
signifcant relationship between capital stringency, offcial supervisory power,
bank performance and stability. However, they conclude that regulatory and
supervisory practices that force accurate information disclosure empower private
sector monitoring of banks, and foster incentives for private agents to exert
corporate control, work best to promote bank performance and stability.
Specifcally, in a cross-country setting, they show that regulatory and supervisory
regimes with these features have suffered fewer crises in the past two decades, have
lower non-performing loans and have deeper credit markets.
Traditional approaches to bank regulation emphasize the positive features of capital
adequacy requirements. Capital serves as a buffer against losses and failure.
Furthermore, with limited liability, the proclivity for banks to engage in higher-risk
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activities is curtailed with greater amounts of capital at risk. Capital adequacy
requirements, especially with deposit insurance, play a crucial role in aligning the
incentives of bank owners with depositors and other creditors (Berger et al., 1995; Keeley
and Furlong, 1990).
Recently, in his report, Murphy (2013), based on the decision of the EU in 2013 that
has focused on limiting the ratio of variable remuneration to fxed remuneration,
demonstrated that the pending EU regulations restrictions will:
• increase rather than decrease incentives for excessive risk-taking;
• result in signifcant increase in fxed remuneration;
• reduce incentives to create value;
• reduce the competitiveness of the EU banking sector; and
• result in a general degradation in the quality of EU investment bankers, thereby
decreasing access to capital and increasing the cost of capital in the EU.
Ben Shlomo et al. (2013) discussed, from a literature overview and empirical evidence,
the recent reforms in European lawregarding remuneration policy. They argued that an
effcient regulation of remuneration policy should be directed at ensuring that
remuneration policies and practices are aligned with effective risk management, and
that the fnancial authorities should therefore closely observe market developments in
this perspective and take countermeasures if necessary. Moreover, Ben Shlomo and
Nguyen (2013) demonstrated that excessive risk-taking in the banking industry has led
to the default of frms and to increased systemic risks as demonstrated during the
previous fnancial crisis, and that inappropriate remuneration structures can contribute
to excessive risk-taking. Their analysis also showed the reformefforts to aimin the right
direction. They concluded that:
• effcient regulation should ensure remuneration policies and structures to be
aligned with an effective risk management;
• the fnancial authorities should therefore closely observe the market development
in this perspective and take countermeasures; and
• an elimination of existing regulatory faws in national laws is needed.
3. Methodology and data
To determine whether and how banking supervisions and regulations infuence
risk-taking by banks, the author uses a sample of the biggest banks from six
European countries (France, UK, Germany, Italy, Spain and Greece) over the period
2005-2011. Because the applicable entry of IFRS[1] was in 2005, data of European
banks are not available before this date. For each country in the sample, the ten
largest banks (defned by total assets) that lend money to frms were identifed. The
author does not include central banks or postal banks, which generally do not
lend money to frms and are described as non-banking institutions (La Porta
et al., 2002).
This study applies the two-step dynamic panel data approach suggested by Blundell
and Bond (2000) and uses the dynamic panel GMM method. The GMM approach is
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superior to traditional ordinary least-squares (OLS) analysis in examining fnancial
variable movements. Driffll et al. (1998) indicate that a conventional OLS analysis of the
actual change in the short rate on the relevant lagged term spread yields coeffcients
with some incorrect signs and size.
There are two different estimators for the dynamic panel models:
(1) the difference panel estimator, which eliminates a potential source of omitted
variable bias in the estimation; and
(2) the system panel model estimator, which combines the regression difference
with the regression in levels to reduce the potential biases and imprecision
associated with the difference estimator (Arellano and Bover, 1995).
Linear GMM estimators have one- and two-step variants. The two-step estimator that
the author uses is generally more effcient than the one-step estimator, especially for the
system GMM.
The dynamic panel model technique and the GMMmodel are particularly well-suited
to handling short macro panels with endogenous variables and are also helpful in
amending the bias induced by omitted variables in cross-sectional estimates and the
inconsistency caused by endogeneity. Even though there is correlation or
heteroscedasticity among the equations, the estimated standard deviation still appears
to be robust (Lee and Hsieh, 2013).
To specify whether the instruments are valid, the author adopts the specifcation test
suggested by Blundell and Bond (2000) and use the Sargan test of over-identifying
restrictions, which examines the validity of the instruments. If the null hypothesis of the
Sargan test for validly over-identifying restrictions cannot be rejected, then the
instrumental variables are valid. On the other hand, if the null hypothesis is rejected,
then the instrumental variables are inappropriate. The second test examines the
hypothesis that the error termis not serially correlated. In both the difference regression
and the system difference-level regression, whether the residuals are second-order
serially correlated is tested.
The dependent variable “risk-taking” is measured by the following proxies:
• standard deviation of return on assets (VOL_ROA);
• standard deviation of return on equities (VOL_ROE);
• standard deviation of return on average equities (VOL_ROAE);
• standard deviation of return on average assets (VOL_ROAA); and
• risk of insolvency (RISK_INSOLV ?1/z-score).
The z-score measures the distance from insolvency (Roy, 1952). Insolvency is
defned as a state in which losses surmount profts. A higher z-score indicates that
the bank is more stable. The z-score, therefore, equals (ROA?CAR)/? (ROA), where
ROA is the return on assets, ? (ROA) is the standard deviation of ROA and CAR is
the capital asset ratio. Following the literature[2], the author defnes the inverse of
the z-score as the risk of insolvency. A lower risk of insolvency indicates that the
bank is more stable. Thus, those fve measures of risk-taking indicate the stability of
each bank.
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The author frst estimates the following panels:
Panel 1: Risk-taking: regulations, supervisions, capital adequacy and infuence
factors:
RISK_TAKING
i,t
? ?
0
? ?
1
(RISK_TAKING)
i,t-1
??
2
(
RESTRICT
)
i,t ? ?
3
(
DEPO_INSR
)
i,t ? ?
4
(
CAP_ADQ
)
i,t
??
5
(SRP)
i,t
? ?
6
(ISA)
i,t
??
7
(BS)
i,t
? ?
8
(CAR)
i,t
? ?
9
(LLGL)
i,t
??
10
(NLTA)
i,t
? ?
11
(NPL)
i,t
??
12
(INSQ)
i,t
? ?
13
(FD)
i,t
??
14
(CPI)
i,t
? ?
15
(GDP)
i,t
? ?
i,t
Panel 2: Risk-taking: regulations, supervisions, capital adequacy and bank-level
indicators:
RISK_TAKING
i,t
? ?
0
? ?
1
(RISK_TAKING)
i,t-1
??
2
(
RESTRICT
)
i,t ? ?
3
(
DEPO_INSR
)
i,t ? ?
4
(
CAP_ADQ
)
i,t
??
5
(SRP)
i,t
? ?
6
(ISA)
i,t
??
7
(BS)
i,t
? ?
8
(CAR)
i,t
? ?
9
(LLGL)
i,t
??
10
(NLTA)
i,t
? ?
11
(NPL)
i,t
? ?
i,t
Where, i represents banks fromthe six countries of the sample: i ?60; t denotes the time
period from 2005 to 2011: t ? 7; ß
i
are the parameters to be estimated. While ?
1
is the
estimated persistence coeffcient for risk, a signifcant ?
1
implies that risk will last from
one year to the next (Goddard et al., 2004, 2010); ß
0
is the constant of the model and ?
it
is
the error term.
RISK_TAKING
it
: Refers to i the bank’s risk-taking in year t, it is measured by fve
alternatives proxies:
(1) The volatility of return on assets (VOL_ROA).
(2) The volatility of return on equities (VOL_ROE).
(3) The volatility of return on average equities (VOL_ROAE).
(4) The volatility of return on average assets (VOL_ROAA).
(5) The risk of insolvency (RISK_INSOLV).
(6) The fnancial regulations and supervisions followed from Lee and Hsieh (2013),
Chortareas et al. (2012), Agoraki et al. (2011), Delis et al. (2011), Laeven and
Levine (2009) and Barth et al. (2001, 2004, 2006, 2008) are:
(7) RESTRICT: Restriction on banking activities measures the degree to which
national regulatory authorities allow banks to engage in some activities. The
summation value for this variable is determined on the basis of the level of
regulatory restrictiveness for bank participation in:
• securities activities;
• insurance activities;
• real estate activities; and
• bank ownership of voting shares in non-fnancial frms.
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These activities can be unrestricted, permitted, restricted or prohibited and receive
values of 1, 2, 3 or 4, respectively. The author creates an overall index by calculating the
natural logarithmof summation value of the four categories. The higher values indicate
higher restrictions on banking activities.
• DEPO_INSR: Deposit insurance is calculated by answering 11 questions
(Appendix). The method sums the individual zero/one answers, and then uses the
natural logarithm of the summation value to get an index. According to
Demirguc-Kunt and Kane (2002), under the explicit deposit insurance schemes,
banks have more incentives for risk-taking.
• CAP_ADQ: Capital adequacy is measured by total equity/total assets (TE_TA)
and total capital ratio (CAPR), referring to IMF (2000).
• SRP: Supervisory power measures the extent to which offcial supervisory
authorities have the authority to take specifc actions to prevent and correct
problems. This variable is determined by adding 1 if the answer is yes and 0
otherwise, for each of the six questions presented in the Appendix.
• ISA: Independence of supervisory authority measures the degree to which the
supervisory authority is independent fromthe government (political infuence)
and legally protected from the banking industry (big fnancial institutions’
infuence). This variable is determined by adding 1 if the answer is yes and 0
otherwise, for each of the four questions presented in the Appendix.
As for the related internal control variables, according to Lee and Hsieh (2013),
Chortareas et al. (2012) and Klomp and De Haan (2011), they include:
• CAR: Bank capital to assets ratio. The traditional view suggests a higher CAR
is linked with a lower proftability because a higher CAR decreases the risk on
equity the tax subsidy provided by interest deductibility (Ben Nacer and
Omran, 2011).
• NPL: Bank non-performing loans to total gross loan (per cent).
• NLTA: Net loans/total assets.
• LLGL: Loan loss reserve/gross loans (per cent).
• BS: Bank size measured by the log of total assets.
A higher level of loans implies a higher risk will be generated. Empirical studies fnd
that a higher loan ratio is associated with higher interest margins, which suggests that
risk-averse shareholders seek larger earnings to compensate higher credit risk
(Demirgüç-Kunt and Huizinga, 1999; Chirwa, 2003; Maudos and Fernandez de Guevara,
2004; Flamini et al., 2009).
However, Demirgüç-Kunt and Huizingua (1999) fnd that the sign on loans to total
assets ratio is negative in the before-tax proft over total assets equation, but when
it is interacted with gross domestic product (GDP) becomes positive, indicating that
at higher income level, banks’ lending activities tend to be more proftable.
The related external control variables, following Lee and Hsieh (2013), Chortareas
et al. (2012), Ben Naceur and Omran (2011), Demirgüç-Kunt and Huizingua (1999),
Dietrich et al. (2010) and Laeven and Majnoni (2005), are fnally included:
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• INSQ: Institutional quality indicators which are measured by freedom from
corruption (CORRUP), fnancial freedom (FIN_FRED) and government stability
(GOV_STAB).
• FD: The fnancial development factors are measured by liquid liability (LL),
private credit by deposit money banks and other fnancial institutions/GDP (PC),
stock market capitalization/GDP (SMC), stock market total value traded/GDP
(SMVT) and stock market turnover ratio (SMTR). CPI is the infation which is
measured by Consumer Price Index, and GDP which represents the annual
percentage of GDP per capita growth.
• The data are sourced from Bankscope (2012) for banking fnancial factors; Bank
regulation and supervision database; World Bank; Barth et al. (2001, 2003, 2004,
2006, 2008) for banking supervision and regulation; International Country Risk
Guide and Heritage Foundation (2012) for institutional variables; Financial
Structure Database (2012) for fnancial development variables; and World
Development Indictors (2012) for macroeconomic variables.
4. Results and discussion
This study analyses a panel data set comprising six European countries over the period
2005-2011. Table I presents descriptive statistics for the dependent and explanatory
variables used in the regression analysis. As shown in the Table I, on average, the
volatility of return on average equities (VOL_ROAE), the volatility of the return on
average assets (VOL_ROAA) and the volatility of the return on equities (VOL_ROE)
tend to have high values (11.582, 0.454 and 0.271, respectively). However, on average, the
volatility of the return on assets (VOL_ROA) and the risk of insolvency (RISK_INSOLV)
tend to have low values (0.005 and 0.001, respectively).
Table II provides the matrix of correlation coeffcients. The correlation coeffcients
are usually less than 0.8, indicating that the correlation between variables has weak
association (Table II Kennedy (2008) indicates that multicollinearity is a critical problem
when the correlation is above 0.80.
4.1 Major fndings
Table III provides the empirical results when Panel (1) is considered for the full sample,
as well as the estimation results of the impact of regulations, supervision and capital
adequacy on risk-taking. The ratios of capital adequacy are statistically insignifcant.
However, the restriction on bank activities (RESTRICT) is statistically signifcant at 1
per cent level of signifcance, and it is negatively correlated with the volatility of the
return on average assets (VOL_ROAA). This means that when a government imposes
restrictions on bank activities, managers become more risk-averse and, therefore, the
banking risk decreases. This result does not coincide with that of Murphy (2013), who
found that the EU regulations restrictions will increase rather than decrease incentives
for excessive risk-taking. In addition, the variable deposit insurance is positively
correlated with bank risk-taking at 1 per cent level of signifcance. Indeed, when deposit
insurance increases by 1 per cent, the volatility of the return on average assets
(VOL_ROAA) increases by 16.91 per cent. The offcial supervisors power (SRP) is
statistically signifcant and negatively related to risk-taking, so the empowerment of
supervisors promotes banking stability through the reduction of banking risk-taking.
251
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For cons, the independence of supervisory authorities (ISA) is not statistically
signifcant. The results are consistent with the studies of Barth et al. (2003, 2004, 2006)
and Demirguc-Kunt and Detragiache (2002), which concluded that deposit insurance
increases the fragility of banks and the probability of suffering a crisis, and the power of
supervisors is positively related to corruption. In contrast, they found that there is no
connection between capital adequacy and risk-taking by banks. Similarly, for
supervision, there is no strong correlation with the stability of banks.
The fndings show that different risk-taking variables have different results on the
persistence of risk. The coeffcients of VOL_ROA and RISK_INSOLV with one period
lag are both positive at 1 per cent signifcance, exhibiting that variables such as
VOL_ROE, VOL_ROAEand VOL_ROAAdo not showpersistence of risk. Their related
coeffcients are signifcantly positive at 0.255 and 0.255, respectively.
Other control variables also perform differently. For example, the size of the bank
(BS) and the capital asset ratio (CAR) are statistically signifcant. Indeed, the size of the
bank is negatively correlated with risk-taking to a 1 per cent of signifcance. However,
the CAR is positively associated with risk-taking. A view based on relaxation of the
symmetric information assumption claims that an increase in CAR raises proftability
and risk by reducing the expected costs for fnancial distress (Berger, 1995).
Moreover, the variables of the asset quality (NPL, NLTAand LLGL) remain statistically
signifcant. Also, the institutional quality (GOV_STAB, FIN_FRED and CORRUP) and
Table I.
Summary statistics for the
entire sample
Variable Obs Mean SD Minimum Maximum
VOL_ROE 269 0.271 2.175 0.001 34.418
VOL_ROA 271 0.005 0.013 0 0.103
VOL_ROAE 285 11.582 47.092 0.021 701.221
VOL_ROAA 278 0.454 0.9350 8.712
RISK_INSOLV 271 0.001 0.002 0 0.022
TE_TA 362 5.186 4.479 ?3.930 73.300
CAPR 318 12.303 4.417 ?5.000 47.000
RESTRICT 420 0.871 0.144 0.602 1.079
DEPO_INSR 420 0.513 0.241 0 0.698
SRP 420 0.410 0.222 0 0.778
ISA 420 0.518 0.145 0.301 0.778
BS 365 8.312 0.691 5.434 9.412
CAR 380 5.789 1.322 4.100 9.300
LLGL 334 2.919 2.067 0 18.840
NLTA 354 62.601 28.119 0.010 223.880
NPL 360 4.088 2.483 0.700 11.500
GOV_STAB 420 8.949 0.634 6.791 9.756
CORRUP 420 0.643 0.132 0.430 0.900
FIN_FRED 420 0.677 0.147 0.380 0.870
LL 420 111.525 33.566 58.786 181.193
PC 420 128.813 42.814 73.185 214.883
SMC 420 69.935 35.098 15.171 141.456
SMTR 420 135.587 53.133 28.170 271.693
PIB 420 0.158 2.829 ?6.812 5.121
CPI 420 107.326 5.440 100.000 121.109
JFEP
6,3
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Table II.
Pearson correlation
coeffcients
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253
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Table II.
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0
.
2
5
5
5
0
.
0
3
4
1
N
P
L
0
.
3
7
9
6
0
.
5
6
3
5
0
.
0
9
0
4
1
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
1
1
7
4
(
c
o
n
t
i
n
u
e
d
)
JFEP
6,3
254
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Table II.
V
O
L
_
R
O
E
V
O
L
_
R
O
A
V
O
L
_
R
O
A
E
V
O
L
_
R
O
A
A
R
I
S
K
_
I
N
S
O
L
V
T
E
_
T
A
C
A
P
R
R
E
S
T
R
I
C
T
D
E
P
O
_
I
N
S
R
S
R
P
I
S
A
G
I
_
R
S
B
S
G
O
V
_
S
T
A
B
0
.
0
5
6
8
0
.
0
4
2
8
0
.
0
5
2
6
0
.
1
5
2
8
0
.
0
4
0
8
0
.
0
3
4
2
?
0
.
0
0
0
2
?
0
.
4
5
4
0
0
.
3
2
2
7
0
.
0
9
9
0
?
0
.
2
1
0
4
0
.
0
1
2
2
?
0
.
0
9
5
2
0
.
3
5
3
0
0
.
4
8
3
0
0
.
3
7
6
7
0
.
0
1
0
7
0
.
5
0
3
4
0
.
5
1
9
6
0
.
9
9
6
5
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
4
2
6
0
.
0
0
0
0
0
.
8
0
3
1
0
.
0
9
6
4
C
O
R
R
U
P
?
0
.
0
1
8
3
?
0
.
0
8
8
8
?
0
.
0
5
0
9
?
0
.
0
8
7
6
?
0
.
0
4
7
7
?
0
.
2
1
5
2
0
.
0
7
2
4
?
0
.
7
7
1
4
0
.
1
7
3
7
0
.
0
0
7
7
?
0
.
1
9
8
4
?
0
.
3
1
3
3
0
.
3
8
4
6
0
.
7
6
5
1
0
.
1
4
5
0
0
.
3
9
1
5
0
.
1
4
5
4
0
.
4
3
4
5
0
.
0
0
0
0
0
.
1
9
7
9
0
.
0
0
0
0
0
.
0
0
0
3
0
.
8
7
4
8
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
F
I
N
_
F
R
E
D
?
0
.
0
9
2
4
?
0
.
2
5
8
2
?
0
.
0
9
7
1
?
0
.
2
3
7
1
?
0
.
2
2
7
1
?
0
.
2
7
7
2
0
.
2
2
6
4
?
0
.
5
9
0
6
?
0
.
4
0
8
6
0
.
1
9
0
3
?
0
.
1
5
9
0
?
0
.
5
3
4
6
0
.
5
8
9
3
0
.
1
3
0
5
0
.
0
0
0
0
0
.
1
0
1
8
0
.
0
0
0
1
0
.
0
0
0
2
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
1
0
.
0
0
1
1
0
.
0
0
0
0
0
.
0
0
0
0
L
L
?
0
.
0
0
6
9
?
0
.
1
5
1
3
?
0
.
0
1
4
2
0
.
0
0
5
9
?
0
.
1
5
5
7
?
0
.
1
2
4
3
0
.
2
2
2
8
?
0
.
7
9
9
0
?
0
.
1
6
2
8
0
.
3
0
2
3
?
0
.
3
5
9
6
?
0
.
4
5
3
5
0
.
1
9
7
6
0
.
9
1
0
4
0
.
0
1
2
6
0
.
8
1
0
7
0
.
9
2
2
3
0
.
0
1
0
2
0
.
0
1
8
0
0
.
0
0
0
1
0
.
0
0
0
0
0
.
0
0
0
8
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
1
P
C
?
0
.
0
4
1
9
?
0
.
1
7
5
2
?
0
.
0
7
5
9
?
0
.
0
7
7
4
?
0
.
1
7
2
7
?
0
.
1
0
7
5
0
.
1
1
9
6
?
0
.
6
8
0
7
0
.
1
2
4
1
0
.
0
2
4
7
?
0
.
2
7
6
9
?
0
.
3
3
4
5
0
.
3
1
4
8
0
.
4
9
3
9
0
.
0
0
3
8
0
.
2
0
1
6
0
.
1
9
8
5
0
.
0
0
4
4
0
.
0
4
1
0
0
.
0
3
3
0
0
.
0
0
0
0
0
.
0
1
0
9
0
.
6
1
3
2
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
S
M
C
?
0
.
1
1
4
0
?
0
.
1
6
8
8
?
0
.
1
4
0
6
?
0
.
1
6
4
0
?
0
.
1
1
1
7
?
0
.
1
0
3
8
0
.
0
4
7
2
?
0
.
7
2
8
4
0
.
2
2
0
3
?
0
.
2
3
0
2
?
0
.
2
5
1
4
?
0
.
4
5
3
1
0
.
3
0
9
1
0
.
0
6
1
9
0
.
0
0
5
3
0
.
0
1
7
6
0
.
0
0
6
1
0
.
0
6
6
3
0
.
0
4
8
4
0
.
4
0
1
7
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
S
M
T
R
?
0
.
0
8
0
0
?
0
.
1
3
6
4
?
0
.
0
8
5
4
?
0
.
1
5
4
8
?
0
.
1
2
2
8
?
0
.
1
6
9
6
?
0
.
0
0
3
6
?
0
.
2
4
2
1
?
0
.
1
7
0
3
?
0
.
2
3
7
0
0
.
1
3
7
5
?
0
.
3
5
2
7
0
.
4
3
6
6
0
.
1
9
0
7
0
.
0
2
4
7
0
.
1
5
0
5
0
.
0
0
9
7
0
.
0
4
3
4
0
.
0
0
1
2
0
.
9
4
9
5
0
.
0
0
0
0
0
.
0
0
0
5
0
.
0
0
0
0
0
.
0
0
4
8
0
.
0
0
0
0
0
.
0
0
0
0
P
I
B
?
0
.
1
1
5
4
?
0
.
0
7
1
5
?
0
.
0
8
0
4
?
0
.
0
9
2
4
?
0
.
0
4
2
4
0
.
0
0
8
1
0
.
1
2
3
9
?
0
.
0
7
9
0
?
0
.
2
1
7
6
?
0
.
1
2
6
7
?
0
.
0
8
7
2
?
0
.
3
3
9
9
0
.
0
5
5
8
0
.
0
5
8
7
0
.
2
4
0
4
0
.
1
7
5
8
0
.
1
2
4
2
0
.
4
8
7
0
0
.
8
7
7
9
0
.
0
2
7
1
0
.
1
0
5
8
0
.
0
0
0
0
0
.
0
0
9
3
0
.
0
7
4
4
0
.
0
0
0
0
0
.
2
8
7
9
C
P
I
0
.
2
0
0
0
0
.
1
8
5
6
0
.
2
1
5
1
0
.
3
5
7
6
0
.
1
2
4
3
?
0
.
0
4
9
5
0
.
0
3
6
2
?
0
.
1
3
6
3
0
.
1
1
1
0
0
.
4
9
3
2
?
0
.
0
7
0
3
0
.
3
4
5
4
?
0
.
0
6
3
1
0
.
0
0
1
0
0
.
0
0
2
1
0
.
0
0
0
3
0
.
0
0
0
0
0
.
0
4
0
8
0
.
3
4
7
2
0
.
5
2
0
0
0
.
0
0
5
1
0
.
0
2
2
9
0
.
0
0
0
0
0
.
1
5
0
3
0
.
0
0
0
0
0
.
2
2
8
8
255
Banking
regulation and
supervision
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Table II.
C
A
R
L
L
G
L
N
L
T
A
N
P
L
G
O
V
_
S
T
A
B
C
O
R
R
U
P
F
I
N
_
F
R
E
D
L
L
P
C
S
M
C
S
M
T
R
G
D
P
C
P
I
G
O
V
_
S
T
A
B
0
.
0
0
9
8
0
.
0
0
8
8
?
0
.
2
3
1
5
0
.
0
0
3
8
1
.
0
0
0
0
0
.
8
4
8
2
0
.
8
7
3
2
0
.
0
0
0
0
0
.
9
4
3
3
C
O
R
R
U
P
?
0
.
3
3
9
9
?
0
.
2
6
1
0
?
0
.
3
6
4
9
?
0
.
5
4
4
0
0
.
4
7
3
9
1
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
F
I
N
_
F
R
E
D
?
0
.
3
1
9
8
?
0
.
3
5
8
4
0
.
0
9
3
2
?
0
.
6
8
1
7
0
.
0
1
7
9
0
.
5
0
5
0
1
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
8
0
1
0
.
0
0
0
0
0
.
7
1
5
1
0
.
0
0
0
0
L
L
?
0
.
1
7
8
9
?
0
.
0
7
0
6
0
.
0
6
0
5
?
0
.
2
4
6
5
0
.
5
3
9
8
0
.
5
3
9
0
0
.
6
0
9
4
1
.
0
0
0
0
0
.
0
0
0
5
0
.
1
9
8
3
0
.
2
5
6
2
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
P
C
?
0
.
0
2
9
6
?
0
.
1
1
6
0
?
0
.
1
1
1
9
?
0
.
3
9
6
4
0
.
4
9
8
3
0
.
6
2
1
1
0
.
6
6
4
7
0
.
7
0
4
9
1
.
0
0
0
0
0
.
5
6
5
0
0
.
0
3
4
0
0
.
0
3
5
3
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
S
M
C
?
0
.
2
5
1
6
?
0
.
3
1
8
9
?
0
.
3
2
3
8
?
0
.
7
5
0
6
0
.
4
4
3
7
0
.
7
2
0
1
0
.
4
7
8
9
0
.
4
8
3
7
0
.
6
1
6
1
1
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
S
M
T
R
0
.
0
1
5
3
?
0
.
2
5
9
7
0
.
0
1
5
2
?
0
.
5
3
8
3
?
0
.
0
1
0
5
0
.
2
4
6
9
0
.
5
9
7
9
0
.
2
7
9
6
0
.
4
3
0
2
0
.
2
5
0
7
#
#
#
#
#
0
.
7
6
5
7
0
.
0
0
0
0
0
.
7
7
6
0
0
.
0
0
0
0
0
.
8
3
0
5
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
0
0
P
I
B
?
0
.
1
6
1
8
?
0
.
2
5
6
3
0
.
0
7
1
6
?
0
.
5
2
7
0
?
0
.
1
5
4
6
?
0
.
0
8
4
0
0
.
1
3
1
3
?
0
.
1
7
4
3
?
0
.
1
8
4
3
0
.
3
0
8
0
#
#
#
#
#
1
.
0
0
0
0
0
.
0
0
1
6
0
.
0
0
0
0
0
.
1
7
8
7
0
.
0
0
0
0
0
.
0
0
1
5
0
.
0
8
5
5
0
.
0
0
7
0
0
.
0
0
0
3
0
.
0
0
0
1
0
.
0
0
0
0
#
#
#
#
#
C
P
I
0
.
1
1
7
7
0
.
3
3
2
9
0
.
0
0
8
2
0
.
5
8
5
7
0
.
5
3
8
6
0
.
0
5
2
7
?
0
.
0
4
6
1
0
.
5
2
4
2
0
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4
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#
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.
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0
0
0
0
0
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2
8
1
7
0
.
3
4
6
3
0
.
0
0
0
0
0
.
0
0
0
0
0
.
0
0
4
2
#
#
#
#
#
0
.
0
0
0
0
JFEP
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256
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2
1
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4
9

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4

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a
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6

(
P
T
)
Table III.
Risk-taking: regulations,
supervisions, capital
adequacy and infuence
factors
(
1
)
V
O
L
_
R
O
A
(
2
)
V
O
L
_
R
O
E
(
3
)
V
O
L
_
R
O
A
A
(
4
)
V
O
L
_
R
O
A
E
(
5
)
R
I
S
K
_
I
N
S
O
L
V
L
A
G
0
.
2
5
5
*
*
*
(
7
.
3
6
0
)
?
0
.
0
4
0
(
?
0
.
0
5
0
)
0
.
1
8
5
(
1
.
0
4
0
)
?
0
.
1
5
5
(
?
0
.
9
8
0
)
0
.
2
5
2
*
*
*
(
8
.
9
9
0
)
T
E
_
T
A
0
.
0
0
1
(
1
.
1
5
0
)
?
0
.
0
0
3
(
?
0
.
0
3
0
)
0
.
0
5
0
(
1
.
5
9
0
)
?
5
.
7
9
6
(
?
1
.
1
9
0
)
0
.
0
0
1
(
1
.
4
4
0
)
C
A
P
R
?
0
.
0
0
1
(
?
0
.
3
8
0
)
?
0
.
0
1
9
(
?
0
.
2
3
0
)
0
.
0
0
4
(
0
.
1
1
0
)
2
.
9
6
0
(
1
.
0
4
0
)
?
0
.
0
0
1
(
?
1
.
5
2
0
)
R
E
S
T
R
I
C
T
?
1
.
5
6
5
(
?
0
.
6
8
0
)
?
3
0
.
7
3
0
(
?
0
.
7
4
0
)
?
9
.
5
4
0
*
*
*
(
?
5
.
3
1
0
)
?
5
7
.
3
0
0
(
?
0
.
7
4
0
)
?
3
.
3
3
4
(
?
1
.
4
6
0
)
D
E
P
O
_
I
N
S
R
0
.
7
4
1
(
0
.
7
2
0
)
1
0
.
9
0
0
(
0
.
8
9
0
)
1
6
.
9
1
0
*
*
*
(
4
.
0
7
0
)
1
8
.
3
0
0
(
0
.
7
1
0
)
1
.
3
8
3
(
1
.
5
4
0
)
S
R
P
?
0
.
0
3
6
*
*
(
?
3
.
2
3
0
)
?
2
.
1
7
1
(
?
1
.
5
0
0
)
?
2
.
5
8
9
*
*
(
?
2
.
9
0
0
)
?
1
4
.
2
0
0
*
*
*
(
?
5
.
0
9
0
)
?
0
.
0
0
6
*
*
(
?
2
.
9
4
0
)
I
S
A
0
.
1
2
1
(
0
.
0
9
0
)
3
.
5
7
3
(
0
.
1
4
0
)
?
2
.
4
8
6
(
?
0
.
2
0
0
)
?
1
8
.
9
0
0
(
?
0
.
4
9
0
)
1
.
8
1
6
(
1
.
5
0
0
)
B
S
?
0
.
0
1
8
*
*
*
(
?
5
.
8
0
0
)
?
0
.
0
1
0
(
?
0
.
0
1
0
)
?
1
.
5
8
8
*
*
*
(
?
9
.
1
8
0
)
7
.
5
8
9
(
0
.
5
4
0
)
?
0
.
0
0
3
*
*
*
(
?
5
.
4
9
0
)
C
A
R
0
.
0
0
2
*
*
(
2
.
9
1
0
)
?
0
.
0
1
5
(
?
0
.
1
5
0
)
0
.
2
2
9
*
*
(
2
.
6
3
0
)
?
0
.
1
2
8
(
?
0
.
0
5
0
)
0
.
0
0
1
(
1
.
5
2
0
)
L
L
G
L
?
0
.
0
0
1
(
?
1
.
7
9
0
)
?
0
.
0
6
7
(
?
0
.
5
8
0
)
?
0
.
1
3
9
*
(
?
2
.
1
6
0
)
?
3
.
0
4
7
(
?
1
.
0
0
0
)
?
0
.
0
0
1
(
?
1
.
3
3
0
)
N
L
T
A
?
0
.
0
0
1
(
?
0
.
8
6
0
)
?
0
.
0
0
1
(
?
0
.
0
1
0
)
?
0
.
0
0
8
*
*
(
?
2
.
5
9
0
)
?
1
.
1
1
0
*
*
*
(
?
5
.
5
8
0
)
?
0
.
0
0
1
(
?
0
.
8
9
0
)
N
P
L
0
.
0
0
2
*
*
(
2
.
6
2
0
)
0
.
2
2
5
(
1
.
6
2
0
)
0
.
2
3
1
*
*
(
2
.
6
4
0
)
1
2
.
9
1
0
*
*
(
2
.
9
9
0
)
0
.
0
0
1
*
(
2
.
5
3
0
)
G
O
V
_
S
T
A
B
?
0
.
0
9
9
(
?
0
.
4
3
0
)
?
9
.
8
4
9
(
?
0
.
8
5
0
)
?
1
6
.
8
8
0
*
*
*
(
?
3
.
3
3
0
)
?
7
2
.
7
0
0
(
?
0
.
6
7
0
)
?
0
.
1
6
8
(
?
0
.
7
8
0
)
C
O
R
R
U
P
?
0
.
0
9
3
*
*
*
(
?
6
.
1
5
0
)
?
3
.
1
9
9
(
?
1
.
5
4
0
)
?
4
.
1
2
6
*
*
*
(
?
4
.
1
1
0
)
?
5
8
.
8
5
0
(
?
1
.
7
0
0
)
?
0
.
0
1
5
*
*
*
(
?
5
.
3
7
0
)
F
I
N
_
F
R
E
D
?
0
.
0
5
9
*
*
*
(
?
3
.
3
8
0
)
?
1
.
8
4
3
(
?
1
.
6
4
0
)
?
2
.
1
9
8
*
*
(
?
2
.
8
6
0
)
?
1
0
.
3
0
0
(
?
0
.
2
6
0
)
?
0
.
0
0
9
*
*
(
?
2
.
5
9
0
)
L
L
?
0
.
0
0
1
*
*
*
(
?
5
.
0
0
0
)
?
0
.
0
3
5
(
?
1
.
6
4
0
)
?
0
.
0
5
0
*
*
*
(
?
4
.
5
0
0
)
?
2
.
0
6
2
*
*
*
(
?
3
.
8
4
0
)
?
0
.
0
0
1
*
*
*
(
?
4
.
4
1
0
)
S
M
T
R
0
.
0
0
1
(
1
.
5
7
0
)
0
.
0
0
1
(
0
.
0
3
0
)
0
.
0
0
1
(
0
.
0
9
0
)
?
0
.
0
9
8
*
*
(
?
2
.
8
5
0
)
0
.
0
0
1
(
0
.
8
1
0
)
G
D
P
?
0
.
0
0
1
(
?
0
.
0
7
0
)
0
.
0
0
2
(
0
.
0
7
0
)
0
.
0
0
9
(
0
.
3
1
0
)
1
.
0
9
2
(
1
.
3
7
0
)
?
0
.
0
0
1
(
?
0
.
0
5
0
)
C
P
I
0
.
0
0
4
*
*
*
(
9
.
7
7
0
)
0
.
2
1
9
(
1
.
9
5
0
)
0
.
3
2
7
*
*
*
(
8
.
9
8
0
)
1
1
.
0
7
0
*
*
*
(
6
.
8
9
0
)
0
.
0
0
1
*
*
*
(
9
.
1
2
0
)
_
C
O
N
S
1
.
6
3
2
(
0
.
6
6
0
)
4
.
0
2
0
(
0
.
6
6
0
)
1
6
.
7
0
0
*
*
(
3
.
0
7
0
)
2
0
.
3
0
0
(
0
.
6
8
0
)
2
.
8
0
4
(
1
.
0
1
0
)
N
1
7
3
1
7
2
1
7
9
1
8
4
1
7
3
A
R
(
2
)
?
0
.
5
3
4
?
0
.
2
4
9
0
.
5
4
5
?
1
.
0
2
3
?
0
.
8
6
6
P
-
v
a
l
u
e
A
R
(
2
)
(
0
.
5
9
3
)
(
0
.
8
0
3
)
(
0
.
5
8
5
)
(
0
.
3
0
6
)
(
0
.
3
8
6
)
S
a
r
g
a
n
T
e
s
t
1
5
.
4
1
0
4
.
1
4
4
1
6
.
0
2
0
5
.
5
3
3
1
4
.
4
4
0
P
-
v
a
l
u
e
S
a
r
g
a
n
(
0
.
0
8
0
)
(
0
.
9
0
1
)
(
0
.
0
6
6
)
(
0
.
7
8
5
)
(
0
.
1
0
7
)
N
o
t
e
s
:
*
,
*
*
,
a
n
d
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
f
c
a
n
c
e
a
t
t
h
e
1
0
p
e
r
c
e
n
t
,
5
p
e
r
c
e
n
t
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
257
Banking
regulation and
supervision
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
the fnancial development indicators (LL and SMTR) are still statistically signifcant
and negatively associated with risk-taking. Finally, the infation (CPI) is positively
associated with risk, but GDPis not signifcant, and the Sargan and the serial correlation
tests accept the null hypothesis of correct specifcation, which means that valid
instruments are there and no serial correlation of the error term.
Referring to Table IV, only the ratio of capital adequacy (TE_TA) is statistically
signifcant and negatively correlated to banking risk-taking. This implies that if the
capital adequacy increases by 1 per cent, the volatility of the return on assets
(VOL_ROA) and the risk of insolvency (RISK_INSOLV) is decreased by 0.001 per cent.
This means that the capital requirement encourages managers to take less risk, thus
enhancing a bank’s stability.
In contrast, all the variables of regulation and supervision are not statistically
signifcant. This does not mean that fnancial regulations and supervisions are not
important for the stability of European banks, but can be explained by the weakness in
the regulation and supervision and the presence of a fnancial crisis in Europe. In
addition, all variables that refect the specifc environment of banks are statistically
signifcant (BS, CAR, LLGL, NLTAand NPL), which confrms the importance of taking
into account the bank-specifc environment when upgrading or implementing fnancial
regulations and supervisions.
The null hypothesis of the Sargan test is not rejected, which means that the
instruments are valid (p-value ? 5 per cent) and the null hypothesis of the serial
correlation test is accepted. It also implies the absence of serial correlation and confrms
the validity of the instruments.
4.2 Robustness analysis
To check the robustness of the empirical results, the author tests the impact of
regulation and supervision on risk-taking without any control variables. Then, the
author uses an overall index of regulations and supervisions. The global index is
calculated as a natural logarithm of summation values of all calculated regulations and
supervisions (Appendix).
Referring to Table V, it was found that restrictions on bank activities and deposit
insurance are not signifcant. However, banking supervisions (SRP and ISA) are
statistically signifcant and positively associated with risk-taking at 10 per cent
signifcance. According to the approach of private monitoring, this implies that the
empowerment of supervisors may be associated with corruption or other factors that
hamper banks (Pasiouras et al., 2009). Thus, banking supervisions may be associated
with a high level of non-performing bank loans (Barth et al. 2002). They may also be
harmful for the development of banks (Barth et al. 2003), and can infuence negatively all
aspects of bank performance (Pasiouras et al., 2006). Moreover, the ratios of capital
adequacy are statistically signifcant and have mixed signs which change between the
alternative variables that measure the risk of banks.
Table VI shows that the global index of fnancial regulations and supervisions is
statistically signifcant and positively correlated with bank risk-taking. Also, capital
adequacy is statistically signifcant. The positive relationship between the overall index
and the potential variables of bank risk indicates that the strengthening of the
regulatory and supervisory framework increases the risk-taking by banks to
compensate the shortfall due to restrictions, so managers tend to take more risk. They
JFEP
6,3
258
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Table IV.
Risk-taking: regulations,
supervisions, capital
adequacy and bank-level
indicators
(
1
)
V
O
L
_
R
O
A
(
2
)
V
O
L
_
R
O
E
(
3
)
V
O
L
_
R
O
A
A
(
4
)
V
O
L
_
R
O
A
E
(
5
)
R
I
S
K
_
I
N
S
O
L
V
L
A
G
0
.
2
8
7
*
*
*
(
1
4
.
2
0
0
)
?
1
.
4
5
8
*
*
*
(
?
4
.
0
4
0
)
?
0
.
2
2
4
(
?
1
.
1
0
0
)
?
0
.
5
5
0
*
(
?
2
.
0
2
0
)
0
.
5
0
9
*
*
*
(
2
9
.
7
4
0
)
T
E
_
T
A
?
0
.
0
0
1
*
*
(
?
2
.
9
2
0
)
?
0
.
0
5
7
(
?
0
.
6
7
0
)
?
0
.
0
0
7
(
?
0
.
2
7
0
)
?
4
.
3
5
9
(
?
1
.
1
7
0
)
?
0
.
0
0
1
*
*
*
(
?
5
.
0
4
0
)
C
A
P
R
?
0
.
0
0
1
(
?
1
.
7
5
0
)
?
0
.
0
4
0
(
?
0
.
6
8
0
)
?
0
.
0
6
8
(
?
1
.
8
4
0
)
?
2
.
8
9
4
(
?
1
.
1
4
0
)
?
0
.
0
0
1
(
?
0
.
5
5
0
)
R
E
S
T
R
I
C
T
?
0
.
3
7
8
(
?
0
.
2
5
0
)
0
.
3
0
7
(
0
.
0
2
0
)
1
3
.
4
6
0
(
0
.
6
1
0
)
6
.
8
0
0
(
1
.
1
3
0
)
?
0
.
0
0
1
(
?
0
.
0
0
0
)
D
E
P
O
_
I
N
S
R
0
.
1
6
1
(
0
.
2
5
0
)
?
2
.
4
1
0
(
?
0
.
4
6
0
)
8
.
8
5
5
(
0
.
5
7
0
)
1
2
.
6
0
0
(
0
.
5
8
0
)
0
.
0
0
1
(
0
.
0
0
0
)
S
R
P
?
0
.
0
0
1
(
?
0
.
2
5
0
)
?
0
.
8
3
2
(
?
1
.
5
3
0
)
0
.
5
6
5
(
1
.
1
4
0
)
7
.
0
1
8
(
0
.
3
6
0
)
?
0
.
0
0
1
(
?
0
.
3
9
0
)
I
S
A
0
.
2
7
9
(
0
.
3
2
0
)
?
6
.
7
0
5
(
?
0
.
4
7
0
)
2
0
.
1
9
0
(
0
.
9
0
0
)
?
3
.
2
0
0
(
?
0
.
7
7
0
)
0
.
0
2
0
(
0
.
0
4
0
)
B
S
?
0
.
0
2
7
*
*
*
(
?
4
.
6
3
0
)
?
0
.
4
1
0
(
?
1
.
0
1
0
)
?
2
.
3
3
2
*
*
*
(
?
3
.
9
1
0
)
?
1
5
.
9
5
0
(
?
1
.
0
7
0
)
?
0
.
0
0
4
*
*
*
(
?
6
.
2
9
0
)
C
A
R
0
.
0
0
2
*
(
2
.
1
7
0
)
?
0
.
0
2
0
(
?
0
.
3
9
0
)
0
.
1
8
4
*
*
(
2
.
7
7
0
)
4
.
6
8
8
(
1
.
3
3
0
)
0
.
0
0
1
(
1
.
2
5
0
)
L
L
G
L
?
0
.
0
0
1
(
?
0
.
9
5
0
)
?
0
.
1
2
3
(
?
1
.
5
3
0
)
0
.
0
0
1
(
0
.
0
0
0
)
?
3
.
6
8
8
(
?
1
.
5
9
0
)
?
0
.
0
0
1
*
(
?
2
.
2
6
0
)
N
L
T
A
?
0
.
0
0
1
*
*
*
(
?
5
.
4
3
0
)
?
0
.
0
0
2
(
?
0
.
5
0
0
)
?
0
.
0
1
2
*
(
?
2
.
0
1
0
)
?
0
.
6
8
6
(
?
1
.
6
9
0
)
?
0
.
0
0
1
*
*
*
(
?
3
.
5
3
0
)
N
P
L
0
.
0
0
3
*
*
*
(
3
.
4
5
0
)
0
.
3
2
4
*
*
(
2
.
7
5
0
)
0
.
1
4
4
(
1
.
6
5
0
)
9
.
4
5
2
*
*
*
(
3
.
3
9
0
)
0
.
0
0
1
*
*
*
(
3
.
8
0
0
)
_
c
o
n
s
0
.
3
5
2
(
0
.
5
9
0
)
9
.
1
0
0
(
0
.
6
2
0
)
?
5
.
8
3
0
(
?
0
.
1
9
0
)
?
2
2
.
4
0
0
(
?
1
.
1
1
0
)
0
.
0
3
0
(
0
.
0
9
0
)
N
1
7
3
1
7
2
1
7
9
1
8
4
1
7
3
A
R
(
2
)
?
1
.
4
1
3
?
0
.
3
4
3
?
0
.
5
6
6
?
2
.
1
4
6
?
1
.
2
7
8
P
-
v
a
l
u
e
A
R
(
2
)
(
0
.
1
5
7
)
(
0
.
7
3
1
)
(
0
.
5
7
0
)
(
0
.
0
3
1
)
(
0
.
2
0
1
)
S
a
r
g
a
n
T
e
s
t
1
0
.
4
3
3
1
0
.
3
4
2
1
0
.
7
8
8
1
3
.
4
8
7
1
0
.
5
1
7
P
-
v
a
l
u
e
S
a
r
g
a
n
(
0
.
4
0
3
)
(
0
.
4
1
1
)
(
0
.
3
7
4
)
(
0
.
1
9
7
)
(
0
.
3
9
6
)
N
o
t
e
s
:
*
,
*
*
,
a
n
d
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
f
c
a
n
c
e
a
t
t
h
e
1
0
p
e
r
c
e
n
t
,
5
p
e
r
c
e
n
t
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
259
Banking
regulation and
supervision
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Table V.
Risk-taking: regulation
and supervision
(
1
)
V
O
L
_
R
O
A
(
2
)
V
O
L
_
R
O
E
(
3
)
V
O
L
_
R
O
A
A
(
4
)
V
O
L
_
R
O
A
E
(
5
)
R
I
S
K
_
I
N
S
O
L
V
L
A
G
0
.
4
3
8
*
*
*
(
2
0
.
8
3
0
)
?
0
.
2
4
7
(
?
0
.
9
4
0
)
0
.
0
8
4
(
0
.
8
4
0
)
?
0
.
2
1
5
*
*
*
(
?
6
.
1
1
0
)
0
.
5
2
8
*
*
*
(
4
3
.
2
5
0
)
T
E
_
T
A
?
0
.
0
0
1
(
?
0
.
5
1
0
)
?
0
.
0
0
1
(
?
0
.
0
1
0
)
0
.
0
7
1
*
*
*
(
3
.
4
3
0
)
?
0
.
7
9
7
(
?
1
.
1
6
0
)
?
0
.
0
0
1
*
*
(
?
2
.
8
1
0
)
C
A
P
R
0
.
0
0
1
*
(
2
.
2
2
0
)
0
.
0
4
6
(
1
.
5
4
0
)
?
0
.
0
0
1
(
?
0
.
0
4
0
)
?
0
.
9
9
6
*
*
*
(
?
3
.
9
4
0
)
0
.
0
0
1
*
*
*
(
8
.
2
8
0
)
R
E
S
T
R
I
C
T
0
.
0
2
8
(
0
.
3
8
0
)
6
.
6
1
0
(
1
.
8
9
0
)
?
3
3
.
9
5
0
(
?
0
.
7
5
0
)
2
2
.
8
0
0
(
3
.
9
8
0
)
?
0
.
0
0
4
(
?
0
.
5
6
0
)
D
E
P
O
_
I
N
S
R
?
0
.
0
0
7
(
?
0
.
3
0
0
)
?
1
.
3
6
4
(
?
1
.
2
8
0
)
1
.
6
5
1
(
0
.
1
8
0
)
?
3
2
.
5
0
0
(
?
0
.
3
7
0
)
0
.
0
0
1
(
0
.
0
8
0
)
S
R
P
0
.
0
0
1
(
0
.
4
8
0
)
0
.
8
7
3
(
1
.
6
9
0
)
0
.
6
7
7
*
(
2
.
0
1
0
)
2
2
.
0
7
0
(
1
.
9
6
0
)
0
.
0
0
1
(
0
.
1
2
0
)
I
S
A
?
0
.
0
0
2
(
?
0
.
0
4
0
)
1
0
.
8
3
0
*
(
2
.
1
5
0
)
9
.
1
2
0
(
0
.
4
7
0
)
?
1
6
9
.
4
0
0
(
?
0
.
4
0
0
)
0
.
0
1
2
(
0
.
9
9
0
)
_
c
o
n
s
?
0
.
0
2
6
(
?
0
.
8
0
0
)
?
1
1
.
1
8
0
*
(
?
2
.
2
8
0
)
2
4
.
1
7
0
(
0
.
8
0
0
)
?
2
2
.
3
0
0
*
(
?
2
.
2
1
0
)
?
0
.
0
0
3
(
?
0
.
6
5
0
)
N
1
8
9
1
8
8
1
9
6
2
0
2
1
8
9
A
R
(
2
)
?
1
.
3
8
3
?
1
.
5
4
0
?
1
.
9
2
7
?
1
.
3
1
7
?
1
.
2
5
3
P
-
v
a
l
u
e
A
R
(
2
)
(
0
.
1
6
6
)
(
0
.
1
2
3
)
(
0
.
0
5
3
)
(
0
.
1
8
7
)
(
0
.
2
0
9
)
S
a
r
g
a
n
T
e
s
t
1
3
.
2
3
7
1
1
.
5
8
1
1
7
.
7
7
2
8
.
6
2
5
1
6
.
3
1
4
P
-
v
a
l
u
e
S
a
r
g
a
n
(
0
.
3
5
2
)
(
0
.
4
7
9
)
(
0
.
0
5
8
)
(
0
.
5
6
8
)
(
0
.
1
7
7
)
N
o
t
e
s
:
*
,
*
*
,
a
n
d
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
f
c
a
n
c
e
a
t
t
h
e
1
0
p
e
r
c
e
n
t
,
5
p
e
r
c
e
n
t
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
JFEP
6,3
260
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
:
4
9

2
4

J
a
n
u
a
r
y

2
0
1
6

(
P
T
)
Table VI.
Risk-taking: global index
of regulations and
supervisions
(
1
)
V
O
L
_
R
O
A
(
2
)
V
O
L
_
R
O
E
(
3
)
V
O
L
_
R
O
A
A
(
4
)
V
O
L
_
R
O
A
E
(
5
)
R
I
S
K
_
I
N
S
O
L
V
L
A
G
0
.
4
6
5
*
*
*
(
7
6
.
7
9
0
)
0
.
3
8
0
*
(
2
.
2
2
0
)
?
0
.
2
3
5
*
*
(
?
3
.
0
6
0
)
?
0
.
0
2
5
(
?
1
.
0
8
0
)
0
.
5
0
8
*
*
*
(
9
3
.
3
6
0
)
T
E
_
T
A
0
.
0
0
1
*
*
*
(
7
.
0
0
0
)
?
0
.
0
0
6
(
?
0
.
2
3
0
)
0
.
1
2
4
*
*
*
(
7
.
0
2
0
)
?
1
.
9
6
8
*
*
(
?
2
.
6
8
0
)
?
0
.
0
0
1
*
*
*
(
?
7
.
4
8
0
)
C
A
P
R
0
.
0
0
1
*
*
*
(
1
3
.
4
4
0
)
0
.
0
8
5
*
*
(
3
.
0
3
0
)
?
0
.
0
1
6
*
(
?
2
.
0
7
0
)
?
1
.
2
3
3
*
*
*
(
?
9
.
7
2
0
)
0
.
0
0
1
*
*
*
(
1
6
.
0
9
0
)
G
I
_
R
S
0
.
0
0
8
*
*
*
(
1
2
.
6
4
0
)
1
.
0
6
6
*
*
(
2
.
8
7
0
)
0
.
8
1
8
*
*
(
2
.
6
9
0
)
1
6
.
9
0
0
*
*
*
(
5
.
0
0
0
)
0
.
0
0
1
(
1
.
1
8
0
)
_
c
o
n
s
?
0
.
0
2
9
*
*
*
(
?
1
3
.
9
0
0
)
?
3
.
1
2
7
*
*
(
?
2
.
8
2
0
)
?
1
.
8
0
2
*
*
(
?
2
.
6
2
0
)
?
1
1
.
0
5
0
*
*
*
(
?
3
.
2
9
0
)
?
0
.
0
0
1
*
*
(
?
3
.
0
4
0
)
N
1
8
9
1
8
8
1
9
6
2
0
2
1
8
9
A
R
(
2
)
?
1
.
4
6
8
?
1
.
5
7
7
?
1
.
9
1
6
?
1
.
2
3
1
?
1
.
2
7
3
P
-
v
a
l
u
e
A
R
(
2
)
(
0
.
1
4
2
)
(
0
.
1
1
4
)
(
0
.
0
5
5
)
(
0
.
2
1
8
)
(
0
.
2
0
3
)
S
a
r
g
a
n
T
e
s
t
2
2
.
6
7
1
1
6
.
5
7
0
2
3
.
3
6
4
2
4
.
7
6
5
1
6
.
7
1
0
P
-
v
a
l
u
e
S
a
r
g
a
n
(
0
.
0
9
1
)
(
0
.
3
4
5
)
(
0
.
0
3
7
)
(
0
.
0
2
4
)
(
0
.
3
3
6
)
N
o
t
e
s
:
*
,
*
*
,
a
n
d
*
*
*
i
n
d
i
c
a
t
e
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are blinded and made greedy by high returns, and rely on regulation and supervision to
fx the consequences of their excessive risk-taking. The higher regulated system
encourages them to take more risks. However, the literature on this subject is divided
into two views: the frst considers the strong regulated institutional environment
encourages risk-taking (Amihud et al., 2002; Esty and Megginson, 2003). While the
second viewnotes that the same strongly regulated environment reduces risk-taking by
banks (Buch and DeLong, 2008; Demirguc-Kunt et al., 2008).
Finally, the Sargan and the serial correlation tests accept the null hypothesis of
correct specifcation, which means that valid instruments are there and the absence of
serial correlation of the residuals.
5. Conclusions
In the spring of 2007, it was clear that a housing bubble had burst on American
mortgages; since then USA has cautiously overcome the banking crisis. However, the
banking problems were still plaguing many European countries in 2013 (Barth et al.,
2013). The central theme on the agenda of European governments is fnancial regulation
and supervision, and their concern is howto promote banking proftability and stability,
as the emerging consensus was that the crisis has revealed signifcant weaknesses in the
regulatory and supervisory system, (Ben Bouheni, 2013b). Resulting calls for reform
have led to numerous proposals, and policymakers in many countries are hard at work
to upgrade their regulatory frameworks. This paper aimed to study the effects of
regulatory and supervisory policies on bank risk-taking. When infuence factors are
considered, it was found that restrictions on bank activities and offcial supervisors
power decrease risk-taking. However, the deposit insurance increases the risk because
deposit insurance is strongly associated with moral hazard (Demerguc-Kunt and
Detragiache, 2002). Nevertheless, when the bank-level indicators are considered, it was
found that capital adequacy decreases risk-taking. It means that the capital requirement
aligns a bank’s interests with those of depositors, which increases banking stability.
Finally, it was found that the global index of regulations and supervisions enhances the
banking risks, which indicates that the strengthening of the regulatory and supervisory
framework increases the risk-taking by European banks and weakens banking
stability. It is concluded that effects of regulation and supervision on bank risk-taking
depend on a number of infuence factors.
Notes
1. International Financial Reporting Standards.
2. Laeven and Levine (2009), Agoraki et al. (2011) and Soedarmono et al. (2013).
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International Review of Finance, Vol. 12 No. 1, pp. 39-56.
About the author
A Doctor in Management Sciences, Faten Ben Bouheni is an Associate Professor at TELECOM
Business School and University of Evry-Val-d’Essonne, France. She is also a researcher at LITEM
research laboratory in France. Her research focuses on fnancial institutions, mainly conventional
and Islamic banks, with special emphasis on regulatory and supervisory issues. Faten Ben
Bouheni can be contacted at: [email protected]
To purchase reprints of this article please e-mail: [email protected]
Or visit our web site for further details: www.emeraldinsight.com/reprints
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Appendix
Table AI.
Summary of variables,
descriptions and data
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269
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doc_406342270.pdf