Tài liệu Determinant of non performance loans the case of vietnamese banking sector

UNIVERSITY OF ECONOMIC INSTITUDE OF SOCIAL STUDIES HOCHIMINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A. IN DEVELOPMENT ECONOMICS DETERMINANTS OF NONPERFORMING LOANS THE CASE OF VIETNAMESE BANKING SECTOR A thesis submitted in partial fulfillment of the requirements for degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By TRUONG NGOC THANH Academic Supervisor DR. NGUYEN THI THUY LINH HO CHI MINH CITY, DECEMBER 2016 Determinants of nonperforming loans – The case of Vietnamese banking sector ABSTRACT The main purpose of this study is to examine the determinants of non-performing loans (NPLs) in the case of Vietnamese banking sector by analyzing the unbalanced panel data of 30 Vietnamese banks over the period of 2008 – 2012. Both of macroeconomic and bank-specific determinants are employed when modeling the regression of NPLs’ determinants. Macroeconomic factors including Gross Domestic Product (GDP) growth rate, unemployment rate, real lending interest rate and sovereign debt are exogenous variables that effect on NPLs. Besides that, the study examine the bank-specific determinants by analyzing relevant hypothesis such as ‘bad management’, ‘pro-cyclical credit policy’, ‘skimping’, ‘diversification’, ‘too big to fail’, ‘moral hazard’ hypothesis. According these hypotheses, return on equity, inefficiency rate, proportion of non-interest income and leverage ratio are the endogenous variables which effect to NPLs. In addition, credit growth rate is added into model to examine its effect on NPLs. Moreover, the effects of government intervention and foreign investment on NPLs are also examined in this study by investigating the difference in NPLs of state-owned banks and fully foreign-owned banks. The fixed effect of unbalance panel data is employed to test these hypotheses. Regarding bank-specific factors, the inefficiency rate and credit growth rate statistically affect on NPLs. However, return on equity, non-interest income rate, leverage ratio do not statistically significant effect on NPLs. According to regression result, it shows the negative and significant relationship between the inefficiency rate and NPLs that is consistent with ‘skimping’ hypothesis. Moreover, the relationship between credit growth and NPLs is significant and negative. As the regression result, all of macroeconomic determinants including GDP growth rate, unemployment rate, real lending interest rate and sovereign debt statistically significant affect on NPLs. The regression shows the positive and significant relationship between the sovereign debt and NPLs which is consistent with hypothesis. The increase in sovereign debt will reduce payment ability that increases the future NPLs. However, the regression shows the positive relationship between GDP growth rate and NPLs and negative relationships between the unemployment rate, lending interest rate and NPLs that is not consistent with hypothesis. Truong Ngoc Thanh – Class 19 Determinants of nonperforming loans – The case of Vietnamese banking sector Regarding the government intervention, the regression shows that return on equity and leverage ratio are affected in state-owned bank that lead to higher NPLs. However, the effect of foreign investment in fully foreign-owned banks on NPLs is not supported in this study. There are some policy implications based on the regression results. Firstly, the sovereign debt should be strictly control in order to enhance the payment ability of debtors. Secondly, the underwriting and monitoring loans process should be controlled to reduce NPLs expansion at bank level. Finally, the operations of state-owned banks should be controlled to reduce NPLs expansion in state-owned banks. Truong Ngoc Thanh – Class 19 Page ii Determinants of nonperforming loans – The case of Vietnamese banking sector TABLE OF CONTENT CHAPTER 1: INTRODUCTION................................................................................................. 1 1.1. Overview of Vietnamese banking sector and non-performing loans .................................... 1 1.2. Research problem .................................................................................................................. 2 1.3. Research objectives and research question ............................................................................ 4 CHAPTER 2: LITERATURE REVIEW .................................................................................... 6 2.1. Non-performing loans definition ........................................................................................... 6 2.2. Bank-specific determinants of non-performing loans ........................................................... 7 2.3. Macroeconomic determinants of non-performing loans ..................................................... 12 2.4. Government intervention and foreign investment in banking system ................................. 16 CHAPTER 3: METHODOLOGY AND DATA ....................................................................... 19 3.1. Methodology........................................................................................................................ 19 3.2. Data ...................................................................................................................................... 21 3.3. Estimation approach ............................................................................................................ 23 CHAPTER 4: ANALYSIS RESULTS ....................................................................................... 25 4.1. Descriptive statistics ............................................................................................................ 25 4.2. Economic results.................................................................................................................. 27 4.3. Result discussion ................................................................................................................. 30 CHAPTER 5: CONCLUSION ................................................................................................... 35 5.1. Main findings and policy implication .................................................................................. 35 5.2. Limitation of the study ........................................................................................................ 36 REFERENCES ................................................................................................................................... 38 APPENDIX ........................................................................................................................................ 41 Truong Ngoc Thanh – Class 19 Page i Determinants of nonperforming loans – The case of Vietnamese banking sector LIST OF TABLE Table 1: Definition of variables used in modeling NPLs determinants ............................................. 17 Table 2: Specific calculation of variables .......................................................................................... 22 Table 3: Methodology test.................................................................................................................. 24 Table 4: Descriptive statistics ............................................................................................................ 25 Table 5: The correlation matrix .......................................................................................................... 26 Table 6: Summarize NPLs ................................................................................................................. 27 Table 7: The regression result ............................................................................................................ 28 Table 8: Regression result of dummy variables ................................................................................. 29 Table 9: Empirical evidence for tested hypothesis............................................................................. 34 Truong Ngoc Thanh – Class 19 Page ii Determinants of nonperforming loans – The case of Vietnamese banking sector CHAPTER 1: INTRODUCTION 1.1. Overview of Vietnamese banking sector and non-performing loans There are three types of ownership in Vietnamese banking sector including state-owned commercial banks, joint stock commercial banks, foreign banks (Kalra, 2012). State-owned commercial banks play an important responsibility in international financial by lending to main sectors in Vietnamese economy. In particular, loans of trade and industry sectors central is granted by Bank for Industry and Trade (ViettinBank) while foreign payments is in-charged by Bank for Foreign Trade (VietcomBank). In additional, loans of agriculture and fishing are supported by Bank for Agricultural Development (AgriBank). Concerning the bank market share, state-owned commercial bank account for large bank market share in 2010 (Kalra, 2012). Besides that, the growth of joint stock commercial banks also contributes in the banking sectors throughout their financial services. In Vietnam, banking sector is under the control of government throughout the State bank operations. Besides the financial responsibility, some duties of state-owned bank are expected. In particular, loans of main sectors in the economy are financed by state-owned commercial banks. In addition, money supply and demand are controlled by state bank by opening the market operation, reserve system, bank rate policy. Moreover, all regulation as well as guideline of banking operations must be complied with state bank’s regulation. The Vietnamese banking system is significantly impacted by the economic depression over the period of 2008 – 2012 which leads to NPLs expansion. The main cause of bank problem is the deterioration of loan portfolio. As the same situation with international banking system, Vietnam experienced with a period of the housing bubble and rapid growth in the stock market. Allowing easy access to loans and rapid credit growth, Vietnamese banking sector had to face with the credit exposure when economy went down. According to report of State Vietnamese Bank, the loan portfolio significant increased from 2005 to 2007. Specially, the credit growth rate was 52.42% in 2007 that doubly increases comparing with this in 2006. In addition, high unemployment rate in period of economic downturn strongly impact to the payment debt ability. Moreover, the weakness of Vietnamese banking sector is one cause that expand the problem loans. Excessive loans, loose credit policy assessment, less mortgage loans, lose control in loan monitoring are the problems of Vietnamese banking sectors. Truong Ngoc Thanh – Class 19 Page 1 Determinants of nonperforming loans – The case of Vietnamese banking sector As the consequence, the NPLs rate was 3.4% in 2012 which doubly increases comparing with this in 2009. Many reactions were implemented by State bank of Vietnam to solve the bank’s NPLs. The number of policies was implemented including increasing capital adequacy ratio to 9%, increasing restriction for lending credit, establishing Vietnam asset management company (VAMC), buying NPLs of weak banks, restructuring weak banks, issuing new loan classification, etc. In addition, minimum of charter capital of banking sector was increased. Interest rate ceilings were re-imposed to control operation of banking sector as well stable the economy. However, the NPLs rate was not significantly improved. According the World Bank’s report, the NPLs declined to 3.107% by the end of 2013 because of transferring bad loans to the VAMC. However, the NPLs in 2013 also emphasizes that this rate could be 9% if all restructured loans were included (Mellor, Minh, & Thuc, 2014). In the other sides, according to rating agency Moody’s estimation, NPL could be higher and exceed 15% in the case of implement international standard assessment. The concern of NPLs was raised in Vietnamese banking sectors in recent years. In addition, the root cause of NPLs of bank’s sector was examined to find out best measure for NPLs solving. Therefore, the main purpose of this research is to examine the determinants of NPLs in the case of Vietnamese banking sector in order to find out the appropriate policy implication for solving banking NPLs. 1.2. Research problem Reviewing empirical studies, there are many approaches to examine the determinants of NPLs. On the one hand, macroeconomic factors could be employed to evaluate their effect on NPLs. Berge and Boye (2007) conclude that real interest rate and unemployment are highly sensitive with the problem loans. They find out that one of primary contribution in real interest rate and unemployment rate improvement is the problem loans’ declining (Berge & Boye, 2007). Besides that, according to study of Reinhart and Rogoff (2011), they made conclusion that NPLs could be considered as the one root cause of banking crisis. According International Monetary Fund working paper, basing on the NPLs in Central, Eastern and South Eastern Europe, the research indicates that strong feedback of macroeconomic condition including GDP growth, unemployment and inflation on NPLs (Klein, 2013). The econometric result suggests GDP growth is one of the macro explanatory of NPLs. Besides that, the significant linkage between macroeconomic condition and NPLs is also supported by the Truong Ngoc Thanh – Class 19 Page 2 Determinants of nonperforming loans – The case of Vietnamese banking sector investigation of determinant of NPLs of 85 banks in three countries including Italy, Greece and Spain (Messai & Jouini, 2013). However, this approach does not consider the effect of banking specific variables that illustrate the characteristic of each bank, which generates different effect on the risk exposure at the bank level. On the other hand, some empirical studies attempt to find out the linkage between bank-specific variables and NPLs including bank capitalization, bank profitability, bank regulation, etc. This approach is more powerful in explanation of difference of banking NPLs. For instance, using the aggregate banking data from 59 countries, internal factor including the capital adequacy ratio, prudent provisioning policy, private or foreign ownership, strengthening the legal system have significant impact on banks’ NPLs (Boudriga, Taktak, & Jellouli, 2009). Moreover, the insolvency of financial institution is also the result of high NPLs (Farhan, Sattar, Chaudhry, & Khalil, 2012). In addition, other study attempts to find out impact of ownership status or market power on NPLs. It generally accepted that NPLs associated with the inefficiency, failures of the banks in the financial crisis period (Ahmad & Bashir, 2013). Other approach to examine NPLs’ determinant is analyzing the effect of both macroeconomic and bank-specific factors on NPLs. In particular, the macroeconomic and microeconomic factors are combined to examine the NPLs of commercial and saving bank in Spain. It concludes that all macroeconomic and microeconomic factors have specific effect on NPLs (Salas & Saurina, 2002). Using the data of Greek banking system, the empirical study combines both macroeconomic and bankspecific factors to assess NPLs’ determinant. This study finds out that bank-specific factors have a different impact on NPLs of different loan categories including mortgage, business and consumer loan portfolios (Louzis, Vouldis, & Metaxas, 2011). Government intervention and foreign investment are also considered as the endogenous variables that affect to NPLs. Some arguments show that government intervention play important role to manage economic in which market failure are balanced (Garcıa-Marco & Robles-Fernandez, 2008). Other arguments supported for private-sector monitoring hypothesis. Regarding foreign investment, it is general accepted that bank will get advantages from experience of management as well as capital from foreign investment. However, its effect varies in different studies. In summary, the financial problem raise more concern in the NPLs in recent years. The determinants of NPLs are examined in many empirical studies. However, the determinants of NPLs in the case of Truong Ngoc Thanh – Class 19 Page 3 Determinants of nonperforming loans – The case of Vietnamese banking sector Vietnamese banking sector are not examined. Therefore, this study will examine the NPLs’ determinants in the case of Vietnamese banking sector. 1.3. Research objectives and research question 1.3.1. Research objectives As discussion above, the main purpose of this study is to examine the determinants of NPLs. The unbalanced panel data of 30 Vietnamese banks over the period of 2008-2012 is used in this study. Both macroeconomic and bank-specific factors are employed in order to model the NPLs’ determinant. In particular, this study will examine the effect of exogenous variables including GDP growth, unemployment rate, lending interest rate and sovereign debt on NPLs. The endogenous variables including return on equity, inefficiency rate, non-interest rate, leverage ratio and credit growth are also examined. In addition, the effect of government intervention and foreign investment on NPLs is investigated by assessing the difference of NPLs in state-owned bank and fully foreignowned bank. In finally, the policy implication for NPLs solving is suggested after examining the regression results. 1.3.2. Research questions According to the research objectives, this study will attempt to answer following research questions. The first question is which factors will affect on the NPLs. The second question is how they affect on NPLs. The third question is what the cause of these effect. And the final question is which policy applicant could be raise from analyzing the effect of these factors. The rest of study will be arranged as follows. Chapter 2 briefly presents the theories and empirical studies regarding NPLs’ determinant. In this part, specific influence of each factor on NPLs will be analyzed basing analyzing the result of previous studies. Chapter 3 will provide methodology analysis of previous empirical literature. This part will give overview of all methodologies were applied in previous study and suitable mythology will be selected to analyze NPLs’ determinants in Vietnamese banking sector. Detailed data and data sources are also presented in this part. Next chapter will present the analysis results. The descriptive statistic as well as economic results is provided in this part. This Truong Ngoc Thanh – Class 19 Page 4 Determinants of nonperforming loans – The case of Vietnamese banking sector part also provides regression explanation and comparison with expectation of literature review. The conclusion as well as policy implication will be presented in final chapter. Chapter 5 also provides research limitation as well as guideline for future studies. Truong Ngoc Thanh – Class 19 Page 5 Determinants of nonperforming loans – The case of Vietnamese banking sector CHAPTER 2: LITERATURE REVIEW 2.1.Non-performing loans definition Non-performing loans are loans either in default or close to being in default. It means that the borrower cannot pay the loan back in full. In generally, three kinds of debts could be defined as NPLs. Firstly, debts whose interest and principal are past due by 90 days or more compared with stipulated time governed in credit contract. Secondly, at least 90 days of interest payments have been capitalized, refinanced or delayed by agreement. Finally, payments are less than 90 days overdue, but there are other good reasons to doubt that payments will not be made in full. In particular, the loan is considered as NPLs if they belong to following exposures (Basel III, 2011). Firstly, all exposures are classified as the defaulted or impaired loans in which loans experience with the deterioration of their creditworthiness. Secondly, other exposures have more than 90 days past due. Thirdly, one exposure could be considered as the NPL if there is evidence that the customer could not fully pay principal or interest. NPLs definition used in empirical researches is consistent. Louzizs at el (2011) used to dataset of Greek banks to analyze the impact of NPLs. According that, NPLs refer to loan which are 90 days past due. Basing on the study of Louzis at el (2011), Klein (2013) employed the NPLs of Central, Eastern and South-Eastern Europe to investigate their determinants in which NPLs is defined as the loan with 90 days past due. In Vietnamese banking sector, definition of NPLs is nearly the same with international cases. The NPLs is the loan is classified as Group 3 to Group 5 (Decision 493/2005/QD_NHNN, 2005). As stipulated in loan classification regulation, following debts are classified into group 3 to group 5. Firstly, NPLs are debts overdue for a period of more than 90 days. Secondly, debts are restructured and extended payment term. Thirdly, loan issuing to customer who is not allowed or restricted to get loan as regulation is considered to classify as NPLs. In addition, loans must be classified to higher group if there is evidence of disadvantage change in environment or business that negatively effect to payment ability of customer. In summary, NPLs in this study is understand as the NPLs rate which is rate of non-performing loans over the gross loans. NPLs used in this study will based on the regulation of Decision 493/2005/QD_NHNN and other empirical studies in which non-performing loans is loans with 90 Truong Ngoc Thanh – Class 19 Page 6 Determinants of nonperforming loans – The case of Vietnamese banking sector days past due. Next sections will continue to examine the effect macroeconomic and bank-specific factors on NPLs by reviewing the discussion in theory and previous empirical studies. 2.2. Bank-specific determinants of non-performing loans Besides major studies investigating the effect of macroeconomic factors on NPLs, fewer empirical research attempt to analyze the effect of bank-specific factors on NPLs. While macroeconomic factors are reflected as exogenous for bank performance, bank-specific is the endogenous factors which directly effect on credit exposure. Difference in bank regulation, bank capacity as well as profit enhance will generate different change in NPLs. In general, moral hazard, operating efficiency, loan diversification, banking leverage, credit policy, etc. is one of the bank-specific factors which are usually used to analyze NPLs. Following is the discussion regarding effect of specific factors to NPLs by analyzing relevant hypotheses in previous empirical studies. 2.2.1. ‘Bad management’ and ‘Skimping’ hypothesis According to ‘bad management’ hypothesis, cost efficiency is considered as the endogenous factor effecting to NPLs. This hypothesis suggests that NPLs will expand in bank with low cost efficiency (Berger & DeYoung, 1997). Problem loans strongly links with the management which is reflected in internal control system. Furthermore, bank with bad management do not have enough skill to manage bank’s operation as well as credit risk. According that, poor skill in risk definition, risk assessment will perform in poor skill of defining risk policy, underwriting, collection as well as problem loans solving. In contrast with ‘bad management’ hypothesis, the ‘skimping’ hypothesis suggests that the high cost efficiency is associates with the NPLs’ increase. According this hypothesis, resources is allocated for management including underwriting and monitoring loans which are traded off with cost efficiency. In this assumption, it is expected that the bank with high cost efficiency will lead to NPLs expansion in future by less focusing on loan monitoring including underwriting, debt collection, credit scoring, etc. (Berger & DeYoung, 1997). Employing Ganger-causality technique, Berger and DeYoung (1997) proposes that NPLs associate with cost efficiency. Using U.S commercial banks in 1985 and 1994, the data and regression result Truong Ngoc Thanh – Class 19 Page 7 Determinants of nonperforming loans – The case of Vietnamese banking sector confirm the strong linkage between cost efficiency and NPLs. According that, the increase in future NPLs is the consequence of low cost efficiency that is consistent with ‘bad management’ hypothesis. In addition, ‘bad management’ hypothesis is also supported by the research in Czech banks in 1994 and 2005. Applying GMM model, this research finds that NPLs is forecasted by cost efficiency’s deterioration (Podpiera & Weill, 2008). However, the study of Spanish banks over the period 19851997 find out cost efficiency in statistically affects on problem loans that do not support for hypothesis estimation (Salas & Saurina, 2002). Basing on aforementioned research, ‘bad management’ hypothesis is considered to analyze bank-specific determinants of NPLs in mortgage, business and consumer loans in Greek banking system (Louzis, Vouldis, & Metaxas, 2011). The inefficiency rate is use as proxy for this hypothesis. The regression gives result that the linkage between cost efficiency and NPLs is statistically significant. According that, this study suggests that one of leading indicators of the increase in NPLs is the low cost efficiency. This conclusion is quite consistent with ‘bad management’ hypothesis and the results of large of studies. In sum, the ‘bad management’ hypothesis is more supported by different empirical studies. Therefore, this hypothesis will be continued to examine by measure the effect of inefficiency of bank on NPLs. Hypothesis 1: Higher cost inefficiency in bank operations is associated with higher NPLs. 2.2.2. ‘Diversification’ hypothesis ‘Diversification’ hypothesis suggests the bank’s diversification generates a potential of low NPLs. According that, the negative relationship between bank’s diversification and NPLs is expected (Berger & DeYoung, 1997). It explains that diversification in income sources will reduce dependence of bank’s income of one or few of bank’s that could generate centralization risk. According to centralization risk, bank is not flexible for adapt new operations and it is difficult for bank to cover lose in case of sudden incident happen for main income source. As the result of centralization risk, loan portfolio could not be controlled which leading to increase in NPLs. Therefore, diversification will reduce centralization risk which reduce NPLs expansion. Many studies attempts to analyze effect of diversification on NPLs, however, the proxy for this variable distinguish in each research. First of all, size of bank is used as the proxy for diversification. According this approach, more diversification opportunities are driven by bigger size of bank which allows reducing NPLs (Salas & Saurina, 2002). The research in India is also supported this argument Truong Ngoc Thanh – Class 19 Page 8 Determinants of nonperforming loans – The case of Vietnamese banking sector which bigger size will reduce NPLs (Ranjan & Dhal, 2003). Secondly, the entropy index regarding share of different revenue is set up to analyze the diversification hypothesis. However, the result shows statistically insignificant effect of diversification on NPLs (Hu, Li, & Chiu, 2004). Income growth is used to consider verifying impact of benefit from diversification on NPLs. Because of high correlation between income growth and net interest income, diversification’s benefit does not generate any effect on NPLs reduction (Stiroh, 2004). In the other hand, proportion of non-interest income is counted when modeling NPLs determinant (Louzis, Vouldis, & Metaxas, 2011). On that ground, this ratio will reflect the dependence of income in interest rate income. This study suggests that NPLs negatively related to banks size as well as the proportion of non-interest income over total income. As the aforementioned discussion, this study will employ the proportion of non-interest income over the total income to examine the effect of diversification on NPLs. Hypothesis 2: Higher non-interest income ratio is associated with lower NPLs. 2.2.3. ‘Moral hazard’ hypothesis and ‘Too big to fail’ hypothesis In ‘moral hazard’ hypothesis, the moral management is considered as variables which effecting to NPLs. According that, it is assumed that the increase in NPLs is the consequence of bank’s lowcapitalization (Berger & DeYoung, 1997). The moral hazard incentive will vary in different bank that is influenced by bank’s manager. This hypothesis assumes that the riskiness of loan portfolio expanded by bank’s manager because of thin capital. Furthermore, the hypothesis suggests that there is excessive risk taking in low-capitalization bank. As the result, credit risk’s increase will associate with problem loans expansion that increases future NPLs. Salas and Saurina (2002) strongly confirm this hypothesis. The lagged of solvency ratio is used to analyze the moral hazard hypothesis. As the result, lagged solvency of bank is significant negative with NPLs that is consistent with moral hazard hypothesis. In addition, moral hazard hypothesis is tested in the case of Greek banks. However, the increase of solvency ratio - a proxy for moral hazard hypothesis insignificantly effects on NPLs declining (Louzis, Vouldis, & Metaxas, 2011). ‘Too big to fail’ hypothesis is based on the moral hazard problem of key banks in the economy. According that, bank is supported by other institutions in case of incident, there is less effort for defend and recover the risk (Stern & Feldman, 2004). This hypothesis assumes that moral hazard problem will maintain key banks having many customers or playing a key role in the banking system of one Truong Ngoc Thanh – Class 19 Page 9 Determinants of nonperforming loans – The case of Vietnamese banking sector country. The liquidity and solvency of key banks will strong link with other bank in the economy. Because of their nature, the failure of this bank could create domino effects which continuously effecting to other banks and their creditors. The failure in whole of banking system is beginning if there is no prevention of institutions. Therefore, government usually plays a role to support and maintain the operation of key banks. As the consequence, the moral hazard problem happens in which risk prevention is not strongly prevented. The banks have a probability to accept excessive risk and issue loan for lower quality customer that increases future problem loans. In sum, according too big to fail hypothesis, the increase in NPLs could be driven from the moral hazard problem in the large bank. This hypothesis is not clearly supported by empirical study. According the study regarding U.S banks, the research suggests that riskier portfolio in large bank is motivated by U.S government in 1980s which supports for too big to fail hypothesis (Boyd & Gertler, 1994). In the other hand, the study analyze to US bank performance over the period 1983-2003 by investigate size classes do not give evidence for this hypothesis (Ennis & Malek, 2005). This hypothesis is also applied to analyze NPLs’ determinant in Greek banks. This hypothesis is strong supported at all loan categories including mortgage, business loans (Louzis, Vouldis, & Metaxas, 2011). However, in the case of consumer loans, this hypothesis is not supported. In sum, both ‘moral hazard’ and ‘too big to fail’ hypothesis examine the effect of moral management on NPLs. According these hypotheses, the lower solvency ratio associates with higher leverage ratio that lead to an increase the future NPLs. Hypothesis 3: Higher leverage ratio is associated with higher NPLs. 2.2.4. ‘Bad management II’ and ‘Pro-cyclical credit policy’ hypothesis ‘Bad management II’ hypothesis suggests that bank performance is considered as the proxy for management skill in lending activities. Lower quality of skill management in lending activities associates with low performance that will deteriorate future loans. Therefore, past performance or earnings negatively link with NPLs (Louzis, Vouldis, & Metaxas, 2011). In addition, bank with high profitability, which is not under pressure increasing loan portfolio and profitability, will be more careful when assessing new loan and risk exposure reduction will belong. Using return on equity as proxy for bank profitability, Godlewski (2004) reports the negative relationship between return on Truong Ngoc Thanh – Class 19 Page 10 Determinants of nonperforming loans – The case of Vietnamese banking sector equity and NPLs. This indicates that higher bank profitability will be lower NPLs (Godlewski, 2004). Furthermore, ‘bad management II’ hypothesis is applied to consider NPL’s determinant in Greek banking system. The return on equity is used as the proxy for this hypothesis. The regression result suggests that there is negative relationship between NPLs and earnings in the case of mortgage loans (Louzis, Vouldis, & Metaxas, 2011). In contrast, ‘pro-cyclical credit policy’ hypothesis suggests distinguish assumption with ‘bad management II’ hypothesis. According that, positive relationship between current bank performance and future NPLs is expected that supports for liberal credit policy. According to the model of Rajan (2004), the credit policy is affected by earning expectation as well as management’s concerns regarding short-term reputation. As the consequence, to increase bank’s profitability, the current earnings and future problem loans are distorted and inflated. Loan loss provision is also used to adjust current earnings. Therefore, future NPLs positively links with past earnings. This assumption is consistent with the result when analyzing risk taking behavior and ownership in the Spanish banks. This empirical study argues that higher bank profitability will associated with higher NPLs (GarcıaMarco & Robles-Fernandez, 2008). In the other side, relationship between bank profitability and NPLs is not supported when lagged return on asset is used as proxy of bank profitability. The researchers argue that return on asset is appropriate when applied in firm level instead of country level (Boudriga, Taktak, & Jellouli, 2009). As aforementioned empirical studies, most of studies supported for ‘bad management II’ in which bank with high profitability will be more carefully in granting credit that lead to NPLs reduction. Hypothesis 4: Profitability negatively related with lower NPLs 2.2.5. Credit growth In this hypothesis, the credit growth in banking sector is analyzed to find out their effect on NPLs. Credit growth is the increasing rate of banking credit loan which reflects the speed of credit growth. According that, it assumed that rapid growth in credit loan will effect on quality of risk control. Because of large credit loan assessment, the quality of underwriting as well as credit loans is not ensured, which enhance risk exposure and NPLs in the future. Many recent empirical studies give clear evidence that is consistent with this hypothesis. Using data of Argentine banking sector, the study suggests there is strong linkage between credit growth and Truong Ngoc Thanh – Class 19 Page 11 Determinants of nonperforming loans – The case of Vietnamese banking sector impaired loans. The study make conclusion that impaired loan and credit growth are relevant (Bercoff, Giovanni, & Grimard, 2002). In addition, rapid past credit or branch expansion is associated with NPLs. Using the dataset of Spanish problem loans of both commercial and saving banks, the research concludes that rapid credit growth associated with problem loans (Salas & Saurina, 2002). Furthermore, Jimenez and Saurina (2006) suggest the positive linkage between credit growth and impaired loans. The research concludes that lagged there credit growth positively effects to the loan losses. It explained that low quality of customer and mortgage loans declining increase in the period of economy downturn. According that, the credit is more risky which affecting loan losses (Jimenez & Saurina, 2006). This conclusion is also affirmed by other researches. Khemraj and Pasha (2009) used the dataset of Guyanese banking system to analyze the relationship excessive lending and NPLs. Using the panel data with fixed effect model, the regression result is consistent with those of Jimenez and Saurina (2006). According that, excessive lend could generate the likelihood of higher NPLs (Jimenez & Pasha, 2009). In the contrast, high credit growth could be considered as high profitability in a certain period. With high bank profitability, bank is not under pressure to spread out rapidly their market that affects on credit quality. Ahmad and Bashir (2013) supported the negative relationship between credit growth and NPLs. They argued that large bank would diversify the loan portfolio and reduce risk by increasing their market. However, this dimension is rarely supported. Hypothesis 3: Credit growth is positively associated with higher NPLs. 2.3. Macroeconomic determinants of non-performing loans Reviewing the empirical studies regarding NPLs’ determinant, the major of study assess NPLs at the aggregate level by investigating macroeconomic environment. GDP growth rate, unemployment and lending interest rate are general investigated when modeling macroeconomic determinants of NPLs. 2.3.1. Economic growth Many previous studies confirm the linkage between NPLs and business cycle. GDP growth gets the negative effect to the NPLs rate (Salas & Saurina, 2002). GDP growth rate and other macroeconomic factors such as family indebtedness, rapid past credit are taken into account to explain the credit risk Truong Ngoc Thanh – Class 19 Page 12 Determinants of nonperforming loans – The case of Vietnamese banking sector in Spanish bank over the period 1985-1997. Two categories of banks are taken into account to analyze the determinant of problem loans including commercial and saving banks. The result shows that NPLs is negatively affected by GDP growth rate. This is explained that the ability to serve the debt including problem debt is improved by macroeconomic development (Salas & Saurina, 2002). As the same expectation of previous studies, the NPLs of Italian banks are largely affected by the business cycle over the period 1985-2002 (Quagliariello, 2007). This study suggests that bad debt as well as loan loss is tentative to be low in period of rapid growth. As the result, the research confirms that the revolution have significant impact on new bad debts (Quagliariello, 2007). Furthermore, the effect of business cycle on credit default is affirmed by analyzing the relationship between production cycle and credit default in Turkish financial system (Ciftera, Yilmazerb, & Cifter1, 2009). At the different time scale over the period 2001-2007, this study finds that production cycle generated impact on NPLs and the effect vary in different levels. Reviewing the data of 26 advanced countries over the period 1998-2009, the result show the strong linkage between NPLs and macroeconomic exposure (Nkusu, 2011). This study finds that the macroeconomic performance is vulnerable by sharp increase in NPLs. Nkusu (2011) also points out the key indicator of macroeconomic performance is GDP growth which effected to NPLs. Based on previous study regarding the determinants of NPLs, the study of NPLs in Greece affirmed the macroeconomic impact on NPLs. The result shows that GDP growth rate mainly explains the NPLs of all loan categories in Greek bank (Louzis, Vouldis, & Metaxas, 2011). Using dynamic panel data of Greek banks database, this study attempts to combine both macroeconomic and bank-specific factors to analyze NPLs of mortgage, business as well as consumer loan portfolio. The research suggests that all GDP growth rate statistically impacts on NPLs. However, the quantity effect to different category of loans is not consistent. The mortgage and business loans are less sensitive to the change of macroeconomic factors compared with consumer loans. As regression result, the increase of GDP growth rate is associated with NPLs declining. It could be explained that the slowdown of economic generate negative effect on NPLs. In addition, basing on the NPLs in Central, Eastern and South Eastern Europe, the research indicates that strong feedback of macroeconomic condition including GDP growth, unemployment and inflation on NPLs (Klein, 2013). The econometric result suggests GDP growth is one of the macro explanatory of NPLs. Besides that, the significant linkage between macroeconomic condition and NPLs of bank Truong Ngoc Thanh – Class 19 Page 13 Determinants of nonperforming loans – The case of Vietnamese banking sector is also supported by the investigation of determinant of NPLs of 85 banks in three countries including Italy, Greece and Spain (Messai & Jouini, 2013). Hypothesis 6: Economic growth negatively related with lower NPLs 2.3.2. Unemployment Unemployment is other primary contribution in the increase of NPLs. Many previous studies confirm the linkage between NPLs and unemployment rate. Current income as well as unemployment rate effect could be considered as the probability of credit default (Rinaldi & Sanchis-Arellano, 2006). Using dataset of seven euro areas over the period 1989-2004, this study finds that unpredictability of future income is the consequence of current income as well as unemployment, which effect on the likelihood of credit default. In addition, Berge and Boye (2007) conclude that unemployment is highly sensitive with the problem loans. The NPLs in household as well as enterprise sector in the Norges bank is respectively investigated. They find out that one of primary contribution on unemployment rate improvement is the problem loans’ declining (Berge & Boye, 2007). Furthermore, reviewing the data of 26 advanced countries over the period 1998-2009, the result show the strong linkage between NPLs and macroeconomic factors (Nkusu, 2011). This study points out the key indicator of macroeconomic performance including unemployment effect to NPLs. The linkage of unemployment rate and NPLs is confirmed when analyzing panel data of Greek banks. The result shows that unemployment rate mainly explains the NPLs of all loan categories in Greek bank (Louzis, Vouldis, & Metaxas, 2011). According to regression result, the NPLs are also positively affected by unemployment rate. It could be explained that NPLs is reduced when unemployment rate declined and customer had enough capacity to pay the overdue debts. Basing on the NPLs in Central, Eastern and South Eastern Europe, Klein (2013) indicates strong feedback of macroeconomic condition including unemployment and inflation on NPLs. The econometric result suggests that unemployment rate is one of the macro explanatory of NPLs. Hypothesis 7: The higher unemployment rate is associated with higher NPLs. 2.3.3. Lending interest Truong Ngoc Thanh – Class 19 Page 14 Determinants of nonperforming loans – The case of Vietnamese banking sector Besides other macroeconomic factors, lending interest rate is other macroeconomic factors affecting to NPLs. Many previous studies confirm the linkage between NPLs and lending interest rate. This study concludes that riskier financial position is set up for household having debt increase (Rinaldi & Sanchis-Arellano, 2006). In addition, Berge and Boye (2007) conclude that real interest rate is highly sensitive with the problem loans. The NPLs in household as well as enterprise sector in the Norges bank is respectively investigated. They find out that one of primary contribution in real interest rate is the problem loans’ declining (Berge & Boye, 2007). Based on previous study regarding the determinants of NPLs, the study of NPLs in Greece affirmed the effect of lending interest rate on NPLs of all loan categories in Greek bank (Louzis, Vouldis, & Metaxas, 2011). According that, the NPLs are positively affected by real lending rate. It could be explained that higher lending interest rate is usually charged for riskier loans that have more ability to debt default. Hypothesis 8: Higher lending interest rate is associated with higher NPLs 2.3.4. Sovereign debt Sovereign debt plays an important role in investigating NPLs’ determinant, especially after recent financial crisis. There are two effects of sovereign debt on banking system. Firstly, because of the public finance failure, market evaluation ‘ceiling’ is set up. As the consequence, the bank’s liquidity is affected in which lending is decreasing and debtors could not be able to finance their debt. This lead to credit default in the banking system. In addition, fiscal measures are applied in the case of high sovereign debt. As the consequence, the social expenditure and wage for government are cut. Affecting by these measures, the debtors are shocked and could not be able to serve their debts which increase future NPLs. Therefore, it is expected that sovereign debt will increase future NPLs. Many studies give evidence for the linkage between sovereign debt and financial crisis. According to the regression result, this empirical study concludes that financial crisis leads to sovereign debt (Reinhart & Rogoff, 2011). Based on previous study, Louzis et al (2011) confirm the effect of government debt on NPLs by investigating all loan categories in Greek banks. This study uses ratio of central government debt over the nominal GDP as the proxy for sovereign debt. According to regression, the results show that sovereign debt statistically effect to NPLs of all loan categories including mortgage, business and consumer loan portfolio. Truong Ngoc Thanh – Class 19 Page 15