Institutions and credit risk in banking system, the case of emerging economies

In fact, there are numerous works focusing on the determinants ofcredit risk in banking system including microeconomic factors such asbank liquidity, bank capital, bank size, bank compet

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Institutions and Credit Risk in Banking

System:

The Case of Emerging Economies

SU DINH THANHUniversity of Economics HCMC - dinhthanh@ueh.edu.vn

NGUYEN PHUC CANHUniversity of Economics HCMC - canhnguyen@ueh.edu.vn

Abstract

The extant literature has documented the determinants of bank credit risk, but does not pay much attention to institutions This study fills this gap by investigating the effects of institutions on bank credit risk Our data covers 33 emerging economies over the period of 2002 - 2013 Applying system GMM estimator for unbalanced panel data, the study finds intriguing findings Given credit supply, the effects of bank liquidity and bank profitability are negative, while the effects of bank capital and bank size and bank concentration are significantly positive On the other hand, in terms of credit demand the effect of real GDP growth rate is negative Our main finding is that institutions have negative effects on bank credit risk Particularly, in the present of institutions, the interaction effects of bank liquidity, bank capital and bank size, bank profitability, and real GDP growth rate are strengthened These results imply that improvements in institutions are significant for control over bank credit risk in emerging countries.

Keywords: institution; banking system; credit risk; emerging

economies

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1 Introduction

There has been a growing literature on determinants of bank credit risk

in the recent years, especially since the 2008 global financial crisis.Several studies blame the crisis on excessive risk taking of bankingsystem (Agnello & Sousa, 2012; Hoque, Andriosopoulos, Andriosopoulos, &Douady, 2015) A deep understanding of credit risk determinants is crucialimportance for the proper evaluation of banking system risk and has adirect link with the development of suitable regulation and prudentialtools

In fact, there are numerous works focusing on the determinants ofcredit risk in banking system including microeconomic factors such asbank liquidity, bank capital, bank size, bank competition, creditderivatives, internal rating systems, collateral, relationship between lenderand customer (e.g., Imbierowicz & Rauch, 2014; Agarwal et al., 2016; DeLis et al., 2001; Mandala et al., 2012); and macroeconomic factors such asinflation, unemployment, house price, credit cycles, business cycle, andeconomic growth (e.g., Hoque et al., 2015; Castro, 2013; Chen, 2007;Jiménez et al., 2005; Tajik et al., 2015; Marcucci & Quagliariello, 2009;Jiménez et al., 2005)

The credit activities of banking system are the function of the asymmetricinformation problem (Lindset et al., 2014; Miller, 2015; Neyer, 2004) Thisproblem may be reduced if the institution of a country is improved Thequality of institution and financial regulation are definitely determinants ofbank credit risk since the improvements in institution and financial regulationreduce the asymmetric information problems, thus induce banking system toprovide bank loans with better quality On the other hand, financial insuranceregulation may stimulate banks in taking more risks

Indeed, the role of public institutions or public governance in reducingthe overall risk in the economy is explored in several studies (Cohen et al.,1983; Dal Bó & Rossi, 2007; Dutta et al., 2013; Ho & Michaely, 1988;Williamson, 1981) However, not much is known about public institutions

in determining credit risk in banking system in emerging countries Inaddition, the associations between public institutions and otherdeterminants of credit risk such as bank capital, bank liquidity, bank size,bank competition, and economic growth are ignored

Therefore, this study goes to fill this gap by investigating the effects ofpublic institutions and the associations between them with bankcharacteristics including bank capital, bank liquidity, bank size, and bankcompetition, which reflect the determinants of bank credit supply, on bankcredit risk This paper is not the first to explore the determinants of credit risk

in banking system, but it is innovative in several ways First, this is the first

study using three dimensions of public institutions including governmenteffectiveness, regulatory quality, and rule of law to investigate the effects ofinstitutional quality on credit risk in banking system in emerging countries

Second, we use interaction terms between each institutional indicator and

bank credit supply factors in order to examine the effect of credit supply’sdeterminants on bank credit risk when institutions are present In addition, weuse interaction terms between each institutional indicator and real economic

growth in order to examine the effect of bank credit demand factors wheninstitutions are present These methodologies ensure

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that our model catches all the main drivers of credit activities relating tocredit risk in banking system

With these strategies, we believe that our study has significant contribution

to both scholar and practice In fact, our empirical results show thatinstitutional quality has significant negative effect on credit risk in bankingsystem, indicating that improvements in institutions (such as governmenteffectiveness, rule of law, and regulatory quality) have good effects onbanking system stability and reducing systematic risk This result has strongcontribution to the literature of institution, where the institutional qualityimpacts not only on economic growth (e.g., Acemoglu & Robinson, 2008;Dollar & Kraay, 2003; Fatás & Mihov, 2005), but also on the stabilization offinancial market Most notably, we find that improvements in governmenteffectiveness and rule of law in line with the higher of liquidity, capital, size,competition, and lower of profitability in banking system increase bank creditrisk The interaction terms between regulatory quality with bank credit supplycharacteristics have same effects as government effectiveness and rule of lawexcluding the profitability and competition in banking system, which haveopposite impacts on bank credit risk More precisely, we find that theinteraction terms between improvements in institutions with economic growthincrease bank credit risk This results show the risk-taking activities ofbanking system with higher liquidity, capital, size, competition, and lowerprofitability in emerging economies in the case of better governmenteffectiveness and rule of law Better regulations also simulate banks takingmore risks excluding banking system with lower profitability and highercompetition, which means that better regulations help banking system morestabilization and more safety

The rest of the paper proceeds as following manner Section 2 reviewsrelated bank credit risk determinants through the drivers of credit demandand credit supply Section 3 introduces methodology and data Section 4presents our empirical evidences from three dimensions of institutionsincluding government effectiveness, rule of law, and regulatory quality.Final section concludes

2 Literature review

Many previous empirical studies analyze determinants of bank creditrisk or nonperforming loans, including macroeconomic factors and specificbanking sector characteristics (Castro, 2013) The bank credit risk isgenerally defined as the risk that a loan is not being paid by borrowers tobank partially or totally The analysis of bank credit risk determinants inbanking system is essential for policy makers since it provides earlyalarms for macroeconomic management in front of shocks and preventingfinancial system from a possible crisis (Agnello et al., 2011; Agnello &Sousa, 2012; Beltratti & Stulz, 2012)

In the literature, bank credit risk is divided into systematic credit risk andunsystematic credit risk (e.g., Ahmad & Ariff, 2007; Aver, 2008; Frye et al.,

2000; Dietsch & Petey, 2002) The drivers of systematic credit risk include: (i)

macroeconomic factors such as unemployment, economic growth,

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inflation, and exchange rate; (ii) changes in economic policies such as

monetary policy, fiscal policy, economic legislation changes, or trade policy,

(iii) and political changes These factors may influence the probability of

borrowers paying their loans For instance, Aver (2008) finds thatemployment, long-term interest rates, and the value of stock market haveimportant impacts on credit risk of the Slovenian banking loan portfolio.Kattai (2010) and Fainstein and Novikov (2011) show that banking systemshighlight the importance of economic growth in Estonia, Latvia, and Lithuania.Salas and Saurina (2002) and Jakubík (2007) also point out that GDP growthand interest rates are the main macroeconomic factors affecting bank creditrisk for the Spanish and Czech, respectively

The divers of unsystematic credit risk includes: (i) the factors related to

borrowers such as personality, financial solvency, and capital of

individuals; (ii) management, financial position, sources of funds, and

financial reporting, and specific factors of the industry sector of firms(Castro, 2013) Zribi and Boujelbène (2011) studies ten commercial banks

in Tunisia over the period 1995-2008 by estimating a panel modelcontrolling for random effects find that ownership structure, prudentialregulation of capital, profitability are main drivers of bank credit risk.Furthermore, Ahmad and Ariff (2007) point out the importance of microcharacteristics from commercial banks of some emerging and developedeconomies on the bank credit risk including regulatory capital andmanagement quality Meanwhile, Jiménez and Saurina (2004) use datafrom several Spanish credit institutions to investigate the role of collateral,type of lender, bank-borrower relationship, and the effects ofcharacteristics of the borrowers and of the loan on bank credit risk Theyfind that collateralized loans have a higher probability of default, and thatwhile loans granted by savings banks are riskier, a close bank-borrowerrelationship increases the willingness for risk-taking behavior of banks

Nevertheless, there is a multitude of empirical studies looking at maindrivers of bank credit risk and highlighting that macroeconomic andmicroeconomic variables should be included into the analysis due to theirconsiderable influence The vast majority of these empirical works considerthe macroeconomic and microeconomic factors as the most important drivers

in the determinants of bank credit risk based on a single country analysis.Some provide a multi-country comparative analysis without concerning to theeffects of institution and its associations with microeconomic factors andmacroeconomic factors In this study, we inspect the determinants of creditrisk in banking system under the aspects of credit supply and credit demandfactors to better understanding the influence of institution on credit functionand risk-taking behavior of overall banking system

The institution of a country which is defined as the rules of the game in

a society (North, 1990), includes three features: (i) “humanly devised”which contrasts with other economic fundamentals;

(ii)“the rules of the game” to set “constraints” on human behavior; and (iii)their major effect will be through incentives (see North, 1981; Acemoglu &Robinson, 2008) Several works have studies the effects of institution, which

is named as the new institutional economics, but the effects of institution on

credit risk in banking system are still ignored Therefore, we try to build ourarguments to explain for this issue by four directions.

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First, better institutional quality induces higher economic growth, and then

reduces credit risk in banking system In the literature of economic growth,

institution is considered the differences in residuals of economic growth.Previous studies agree that better institutional quality is positively andsignificantly correlated with economic growth (Young & Sheehan, 2014) Forinstance, Djankov et al (2002) finds that the lower cost of opening a medium-size business in the United States in comparison with Nigeria, Kenya, Ecuador,and Dominican Republic is highly correlated with economic growth.Meanwhile, Beekman et al (2014) find that corruption reduces incentives ofindividuals in both voluntary contributions and investments in Liberia, andthus impacts on economic growth Therefore, better institutional quality will

be in line with higher economic growth and hence improving the financialsituation of borrowers and reducing credit risk in banking system

Second, better institutional quality reduces asymmetric information

problems (Cohen et al., 1983; Ho & Michaely, 1988; Williamson, 1981);

hence, banks will be less probability of making wrong decisions in lending

to bad borrowers

Third, better institutional quality reduces overall risk in the economy

(Cohen et al., 1983; Ho & Michaely, 1988; Williamson, 1981), thereby

inducing a lower systematic risk and reducing credit risk of bank creditportfolio In fact, better institutional quality helps economic agents moretrustable in business transactions Thus, institutional quality positivelyimpacts the efficiency of businesses (Dal Bó & Rossi, 2007), and mitigatessystematic risk in overall economy Dutta et al (2013) find that worsecorruption situation leads to high inequality, poverty, and employment andthus undermines the effectiveness of economic growth in India

Four, better institutional quality reduces transaction cost in economic

activities in general and credit activities in particularly As a result, better

institutional quality induces higher efficiency of credit activities and bettercontrol of credit risk in banking system

Although the views of systematic and unsystematic credit risk dominate

in the literature of bank credit risk, we can examine the determinants ofcredit risk in banking system under the basic determinants on demand andsupply sides of credit function The approach of the systematic andunsystematic credit risk is suitable for bank level studies due to definingfactors relating to systematic or unsystematic risk, but the approach ofdetermining the drivers of credit risk from the views of supply and demandside in credit function is better at the banking system level or countrylevel, since it is easy to define the drivers of credit risk in the overallbanking system

In the literature, the function of credit is impacted by supply anddemand side factors On the demand side, income level and growth rate ofGDP per capita are main determinants of credit demand (Backé & Wójcik,2008) For instance, Duprey (2012) uses real GDP growth in explaining thedifferent pattern of bank behaviors over macroeconomic fluctuations at

459 public banks in 93 countries Similarly, Elekdag and Han (2015) findthat domestic factors such as economic growth and monetary policy

shocks are more dominant than external factors in driving rapid creditgrowth in emerging Asia.

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Indeed, economic growth increases the expected income and profit in linewith better financial conditions of private sector, thus allowing for higherlevels of indebtedness (Kiss, et al., 2006), while households may want toincrease debt levels to smooth consumption in current time since they expecthigher income in the future (Backé & Wójcik, 2008) In addition, highereconomic growth increases the disposable income of people and thusstimulates them in consumption and investment Firms are also induced toexpand their operations to catch up with increasing demand, therebystimulating the increased credit demand Even though the profit of firms may

be higher due to economic growth, thus stimulating them to rely more oninternal funds instead of bank loans (Kiss et al., 2006), this effect may be notstrong as the positive effects of economic growth on credit demand indeveloping or emerging economies since high economic growth needs abundle of capital

Accordingly, fluctuations in economic growth definitely change creditdemand and then, in turn, impact on credit risk in banking system, whichexplains the relation between credit risk and business cycle (Marcucci &Quagliariello, 2009) For example, using lagged percentage change in GDP

to explain for the banking crisis in the Nordic countries in the period of1980s-1990s, Pesola (2001) finds that the shortfalls of GDP growth belowforecast contribute to their banking crises Salas and Saurina (2002) findsthat the GDP growth rate in line with other microeconomic factors such asfirms, and family indebtedness, rapid past credit or branch expansion,inefficiency, portfolio composition, size, net interest margin, capital ratio,and market power are drivers of credit risk in Spanish commercial andsavings banks in the period 1985-1997 Meyer and Yeager (2001) andGambera (2000) find that macroeconomic variables are good predictorsfor the non-performing loans in the US Marcucci and Quagliariello (2008)use data from Italian banks and find that the credit risk is increased ineconomic downturns Similarly, Hoggarth et al (2005) provide the sameevidence for the case of the UK

There are some possible explanations to the cyclicality of credit risk such

as disaster myopia, over-optimism, herd behaviors, and insufficient marketdisciplines (Marcucci & Quagliariello, 2008) Marcucci and Quagliariello (2008)

verify the cyclicality of credit risk from the following perspectives: (i)

economic growth increases the profit of firm, which raises asset prices riseand customers’ expectations at the beginning of expansionary phase andthen increases aggregate demand As a result, the increasing of aggregatedemand induces a rapid growth in bank credit portfolio and in economy'sindebtedness, where banks usually underestimate their risk exposure andrelax their credit standards due to over-optimism in the increasing of creditdemand, which causes the deterioration of borrowers’ creditworthiness; and

(ii) customers’ profitability will be worsened when an exogenous shock

occurs The over-optimism is likely to become over-pessimism that cantrigger the pitfall of asset prices and worsens customers’ financial wealthdepressing deeper, while the downturn in asset prices worsens the value ofcollaterals of banking system Therefore, non-performing assets emerge,while firms’ financial distress increases, causing losses in banks’ balance

sheets, and thus both banks’ profitability and capital adequacy deteriorateconsequently as cyclicality.

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In fact, the effect of economic growth on credit risk in banking systemfollows the explanations of over-optimism, herd behaviors, and insufficientmarket disciplines, which depend much on institutional environment of acountry Since better institutional quality reduces asymmetric informationproblems, transaction cost, and risk, while improving the efficiency ofasset allocations, and property right protection (Cohen et al., 1983; Ho &Michaely, 1988; Williamson, 1981), better institution in association withhigher economic growth may stretch cyclicality of credit risk in bankingsystem under the impact of risk-taking behavior of banks

The literature of banking activities have concluded that there are manydeterminants of bank risk-taking behavior such as capital requirement,bank size, bank leverage and financial liberalization (Ashraf et al., 2016;Bhagat et al., 2015; Blaško & Sinkey Jr., 2006; Borio & Zhu, 2012; Cubillas

& González, 2014; Efing et al., 2015; Galloway et al., 1997; García-Marco &Robles-Fernández, 2008) Ashraf et al (2016) find strong evidence thatbank risk-taking is significantly higher in countries, which have highindividualism, low uncertainty avoidance, and low power distance culturalvalues Buch and DeLong (2008) examine cross-border bank mergers andfind that the supervisory structures of the partners’ countries influencechanges in post-merger total risk and strong host regulators limiting therisky activities of their local banks

As a summary, the higher economic growth makes both people andbanks more confidence and more optimistic, while better institutionalquality boosts this confidence and optimistic higher due to better quality

of government, regulation, law system, property right protection, and alsoreduces corruption problem, therefore banks may take riskier activities intheir credit portfolio Therefore, we argue that better institutional quality inline with higher economic growth will simulate risk-taking activities ofbanks, hence increasing the credit risk of overall banking system

On the supply side, banks are assumed to make decisions on their creditportfolios depending on all available information and their internal financialconditions such as capital, liquidity, profitability, assets, therefore theseinternal characteristics of banks have strong impacts on credit risk Theextent literature has examined the drivers of credit supply of banks (Auel &

de Mendonça, 2011; Aysun, 2016; Bhaumik et al., 2011; Ciccarelli et al., 2015;Liu & Minford, 2014; Ramos-Tallada, 2015; Yagihashi, 2011) Marcucci andQuagliariello (2008), for instance, document that banks may react stronger toexternal shocks such as recession in economy by cutting their credit supplyhigher if they face to constraints such as capital in their balance sheet While,Bernanke and Gertler (1995) argue that banks can adjust their credit supply

in responding with external shocks such as a contractionary or expansionarymonetary policy, where a contractionary monetary policy leads to adecreasing in available fund such as deposits or other funds, and thus bankshave to reduce their credit portfolio

Many empirical studies show that banks may not response to externalshocks in the line of what the authorizers want in some cases For instance,banks may do risk-taking activities by increasing their credit supply despite

contractionary monetary policy (Angeloni et al., 2015; Buch et al., 2014; deMoraes et al., 2016; DellʼAriccia et al., 2014; García-Kuhnert et al., 2015;Montes & Peixoto, 2014).

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Particularly, studies on credit channel argue that the actions of banks intheir credit portfolio depend on their internal conditions including capital,liquidity, size, profitability, and competition on banking sector (Aiyar et al.,2016; Aysun, 2016; Gunji & Yuan, 2010; Imbierowicz & Rauch, 2014; Khan

et al., 2016; Leon, 2015; Yang & Shao, 2016)

There is usually an adequate requirement in the minimum capital ratio thatevery bank needs to meet Whenever, there is an external shock such as adownturn in economic growth or a contractionary monetary policy, banks withlower capital buffers above the minimum capital requirement will reduce theircredit supply much more (Bliss & Kaufman, 2002) If firms cannot substitutebank loans by other sources, they may face to insufficient funding for theirinvestment projects, and in turn, increasing the credit risk of banks Hence,banks with higher capital will be less credit risk But, banks with lower capitalratio have to raise additional capital before expanding credit to bind risk-based capital requirement, thus they may optimally forgo profitable loans toreduce the risk of future capital inadequacy (Van den Heuvel, 2002) As aresult, they may choose to reject bad projects for lending to reduce creditrisk Konishi and Yasuda (2004) find that the implementation of the capitaladequacy requirement reduces risk taking at Japanese commercial banks,while banks with higher capital ratio may take riskier activities for higherprofits, leading to increasing credit risk

The liquidity is also very important for banking system due to the risk of

bankruptcy (Diamond

& Rajan, 1999; Gatev et al., 2009; Imbierowicz & Rauch, 2014) In fact, bankshave to consider their liquidity situation when they make credit decisions.Banks with higher liquidity may be more flexible in supplying their creditportfolio, thus they are better management their credit risk However, higherliquidity may simulate banks taking risk in their credit activities such as thestudies of Nguyen and Boateng (2013) and Nguyen et al (2015)

The size of bank is usually mentioned as the main driver of credit risk(Demsetz & Strahan, 1997; Kishan & Opiela, 2000) At bank level, largerbanks have higher market power and thus they have higher advantages inmanaging their credit portfolio, while smaller banks may take risk due tolower market share However, larger banks may be impacted by thetheory “too big to fail” (O'hara & Shaw, 1990; Papachristos, 2011); thus,they take more risk-taking activities than smaller ones and have highercredit risk (Bhagat et al., 2015; Chen et al., 2015; Hakenes & Schnabel,2011; Stever, 2007) At country level, larger banking system measuringunder the relative size of assets in banking system with GDP defines thehigher domination of banks in financial system and the more importance

of their role in the economy, which creates more incentives for banks intaking risk due to the higher probability of government in interveningwhenever they face to financial distress to protect people from panic astheory of “too big to fail”

At the last characteristic mentioned in our arguments, the profitability ofbanks measured by return on asset or return on equity may have

goodness on bank credit risk The higher profitability of banks makes themmore flexible in managing their credit portfolio, and also reduce pressuresin

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expanding credit too quick so that the probability of wrong credit decisions

or risk-taking activities will be limited

The competition in banking sector has strong impacts on bank choicesand thus it has impacts on bank credit risk through the effects on bankrisk-taking behaviors A large amount of literature argues that highercompetition makes banks take more risk to aim at getting higher marketshare (Agoraki et al., 2011; Boyd & De Nicolo, 2005; Jiménez et al., 2013).Hou et al (2014), for example, find that intense market competitioncompels Chinese commercial banks to develop advanced technicalexperience and skills, thus improving their technical efficiency and thenthe technical efficiency is positive associated with the risk taking

However, countries with a few of large banks dominated reducecompetitive pressures between banks When large banks have moreconfidence in taking risk and thus authorizers have to make sure they aresafe (Boyd & De Nicolo, 2005; Hakenes & Schnabel, 2010; Jiménez et al.,2013; Wagner, 2010) Matutes and Vives (2000) study the links betweencompetition for deposits and risk taking incentives, and conclude that thewelfare performance of the market and the appropriateness of alternativeregulatory measures depend on the degree of rivalry and the depositinsurance regime

As a summary, bank’s internal conditions such as liquidity, capital, size,profitability, and competition within banking sector have strong impacts oncredit risk through credit activities Credit activities truly depend on bank’smanager expectations and financial behaviors The expectations are builtfrom the available information that is faced to the problem of asymmetricinformation, while the financial behaviors of banks managers are impacted

by the macroeconomic institution such as regulations and law system.Therefore, institution definitely has associations with these drivers of bankcredit risk Chen et al (2015) use bank-level data from more than 1200banks in 35 emerging economies during the period 2000-2012 and findthat the impact of monetary policy on banks' risk-taking behavior is morepronounced with the increasing severity of corruption da Silva and Divino(2013) use data for the Brazilian economy in the period from 1995 to 2009and find that credit risk is pro-cyclical and default risk depends onstructural features

In the first view of associations between institution with bankcharacteristics and banking sector competition, better institution in linewith higher capital, higher liquidity, bigger size, lower profitability, andlower competition may stimulate banking system in taking more risk due

to lower asymmetric information problems, transaction cost, and overallrisk in the economy

However, the difference aspects of institution including governmenteffectiveness, regulation quality, and rule of law may have difference impacts.Since government effectiveness reflects perceptions of the quality of publicservices and civil service, and the degree of its independence from politicalpressures in policy formulation and implementation, and the credibility of thegovernment's commitment to such policies, so better government

effectiveness may stimulate risk-taking behavior in banking system due tobetter public services and thus lower transaction cost and better conditionsfor the growth in private sector Regulatory quality reflects perceptions of theability of the

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government to formulate and implement sound policies and regulationsthat permit and promote private sector development, thus betterregulatory quality may induce some risk-taking activities of better banksdue to the less harmful of policies from political pressures so that the “toobig to fail” may be less impacts on bank’s managers Meanwhile, rule oflaw reflects perceptions of the extent to which agents have confidence inand abide by the rules of society, and in particular the quality of contractenforcement, property rights, and the police, therefore banks have morecommitment in contract agreement and the property rights protectionsthus they may take risk more

3 Methodology and data

3.1 Methodology

This section presents our methodology in estimating the effects ofinstitution and its associations with bank characteristics and bankingsector competition through three step procedures First, we use thepercentage change in government effectiveness indicators from the WorldGovernance indicators to proxy for the change in institutional quality asfollowing formula:

(1)

Since institutional quality indicators are scaled from -2.5 to +2.5 foreach indicator, thus we standardize these indicators by calculating thepercentage change of each indicator for better measuring changes ininstitutional quality This proxy of changes in institutional quality is used toevaluate the impacts of institution on credit risk in banking system in 33emerging countries3 from 2002 to 2013 through the followingmodification

(3)

in which Crerisk is the ratio of non-performance loans to total

outstanding loans which is used to proxy for credit risk in banking system;

Inqua is the changes in institutional quality, including government

effectiveness (Goveff), regulatry quality (Reguqua) and rule of law (Rulelaw); X is a set of control variables including bank liquidity (Bankliq), bank capital (Bankcap), Bank asset (Bankasset), bank profitability (Bankroa), competition in banking sector (Bankcon), and real GDP growth rate (Gdpg) All definitions and calculations of variables are presented in

Table 1

3 List of emerging economies: Brazil, Bulgaria, Chile, Colombia, China, Czech Republic, Egypt Arab Rep., Estonia, Greece, Hungary, India, Indonesia, Latvia, Lithuania, Malaysia, Mexico, Morocco, Nigeria, Oman, Pakistan,

Peru, Philippines, Poland, Romania, Russian Federation, Slovenia, South Africa, Korea Rep., Thailand, Turkey, Ukraine, Venezuela RB, and Vietnam.

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Table 1

Definitions and sources of data

Bankcap The ratio of bank capital to total assets (%) GFDD

Bankasset The ratio of deposit money bank’s assets to GDP (%) GFDD

Goveff

Percentage change in Government effectiveness indicator (%)

Calculation from WGI

Rulelaw Percentage change in Rule of law indicator (%)

Calculation from WGI

Reguqua Percentage change in Regulatory quality indicator (%)

Calculation from WGI

Based on the work of Yurdakul (2014), the real GDP growth is used asthe explanatory variable to proxy for the demand side of credit functions.Other explanatory variables are based on the works of Ramos-Tallada(2015), Altunbas et al (2012), and Altunbas et al (2010) All theexplanatory are lagged to capture data characteristic, where the year-enddata to bank characteristics and bank competition will have impacts onbank’s manager decisions in following year The real GDP growth rate ofthis year will impact on the expectation of people in the future, and thusimpacts on the next year credit demand

After examining the impacts of changes in government effectiveness oncredit risk in banking system, we use interaction terms betweeninstitutions and the factors of credit demand side and credit supply side toevaluate interaction effects on credit risk in banking system In which, weadd each interaction term one by one into our estimations to test theconsistence of our results, which is proved for the robustness of ourfindings This is the second step in our study

Then, in the third step, we use changes in rule of law (Rulelaw) and regulatory quality (Reguqua), respectively to replace for the government

effectiveness and replicate all test procedures as mentioned above Withthis strategy, we believe our study is robustness in testing the impacts ofinstitutions and interactions terms between institutions and the drivers ofdemand and supply on credit risk We use the system GMM estimatorsfollowing the study of Arellano and Bond (1991), Arellano and Bover(1995), extended by Blundell and Bond (1998) and Blundell and Bond(1998) for advantage of addressing the bias associated with the fixedeffects in short panels and solving the problem of endogeneity in dynamicpanel data, which is suitable for this study due to the endogeneity

emerging from the relationship between credit risk with other bankcharacteristics such as bank liquidity, bank profitability, or bank capital.