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’, ‘procyclical 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 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 Overview of Vietnamese banking sector and non-performing loans 1.2 Research problem 1.3 Research objectives and research question CHAPTER 2: LITERATURE REVIEW .6 2.1 Non-performing loans definition 2.2 Bank-specific determinants of non-performing loans 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 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 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 bank-specific 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 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 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 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 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 also provides research limitation as well as guideline for future studies Truong Ngoc Thanh – Class 19 Page Determinants of nonperforming loans – The case of Vietnamese banking sector APPEDIX 3: CORRELATION BETWEEN NPLS AND BANK-SPECIFIC VARIABLES Correlations Trend 10 15 Variables Negative Bad management II (-) Pro-cyclical credit policy (+) 10 15 ROE INEF 10 NII 15 Positive Positive Diversification (-) Truong Ngoc Thanh – Class 19 Page 44 Determinants of nonperforming loans – The case of Vietnamese banking sector Variables 10 15 Correlations LR CRE 10 15 0 Truong Ngoc Thanh – Class 19 Page 45 Determinants of nonperforming loans – The case of Vietnamese banking sector APPEDIX 4: VARIABLES TEST Mutli-collinearity Multi-co linearity is the problem of model in which there is one or more relationship among the regressors As the consequence of co linearity, the model exist the large confidence interval in which the null hypothesis may not be rejected In addition, the t ratio may be statistically insignificant To test the collinearity, the variance-inflating factor (VIF) is used to measure the degree of estimators inflated by co linearity VIF is calculated as following calculation = − Where r denotes the coefficient of correlation among variables If the VIF is lower than 5, it is conclude that there are less co linearity among variables Following is the result: Variables RLRt-1 UN t-1 ROE t-1 LR t-1 CRE t-1 GDP t-1 INEF t-1 NII t-1 NPLs t-1 Mean VIF According to the result, it is recognized that all VIF indicators are lower than It is concluded that there is no co linearity among variables Unit root test If the means and variance of time series is constant over the time, this time series is said to be stationary In addition, the covariance between two time periods depends only on the distance between the two time periods If time series is non-stationary, the model result is less practical value for forecasting purpose In the case of non-stationary time series, the model will obtain high value of R and significant t However, the result is unreliable To test the stationary for times series, the unit root test is applied In the unit root test, null hypothesis is said that there is unit root in model The stationary Truong Ngoc Thanh – Class 19 Page 46 Determinants of nonperforming loans – The case of Vietnamese banking sector time series is the alternative hypothesis This study will apply the Dickey-Fuller test to check stationary of model The simple model for unit root test is presented as follows yt = ρ yt-1 + ut where y denotes for variable, t denotes for time index A unit root present in the model if ρ equal in which the variable in time t is correlate with variable in time t-1 Following is the results Inverse chi-squared(50) Inverse normal Inverse logit t(104) Modified inv chi-squared According to the result, it is recognized that all variables are stationary, except credit growth Truong Ngoc Thanh – Class 19 Page 47 Determinants of nonperforming loans – The case of Vietnamese banking sector APPEDIX 5: STATA OUTPUT I Stata output without dummy variables:  Model 1: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + εit Fixed-effects (within) regression Group variable: code R-sq: within between = 0.1273 overall = 0.2082 F(4,25) corr(u_i, Xb) Robust NPLs lagNPLs lagGDP lagUN lagRLR _cons sigma_u sigma_e rho Truong Ngoc Thanh – Class 19 Page 48 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 2: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit-1 + Fixed-effects (within) regression Group variable: code R-sq: within between overall corr(u_i, Xb) = -0.2 NPLs lagNPLs lagGDP lagUN lagRLR lagROE lagINEF lagNII lagLR lagCRE _cons sigma_u sigma_e rho Truong Ngoc Thanh – Class 19 = 0.37 = 0.00 = 0.17 Page 49 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 3: NPLs it = NPLs it-1 + β1 GDP it-1 + β3 RLR it-1 + β4 Debtit-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit-1 + β8 LRit-1 + β9 CREit-1 + εit (Eq 3) Fixed-effects (within) regression Group variable: code R-sq: within between = 0.0089 overall = 0.3748 = 0.1768 F(9,24) corr(u_i, Xb) = -0.2616 (Std Err adjusted Robust NPLs lagNPLs lagGDP lagRLR lagDEBT lagROE lagINEF lagNII lagLR lagCRE _cons sigma_u sigma_e 1.3984086 1.5039032 rho Truong Ngoc Thanh – Class 19 Page 50 Determinants of nonperforming loans – The case of Vietnamese banking sector II Stata output with dummy variables:  Model 1: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit-1 + β8 LRit-1 + β9 CREit-1 + d_STATE_ROE + d _FOREIGN_ROE + εit Fixed-effects (within) regression Group variable: code R-sq: within corr(u_i, Xb) Truong Ngoc Thanh – Class 19 Page 51 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 2: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit1 + β8 LRit-1 + β9 CREit-1 + d_STATE_INEF + d _FOREIGN_INEF + εit Fixed-effects (within) regression Group variable: code R-sq: within between = 0.0120 overall = 0.1779 F(11,24) corr(u_i, Xb) (Std Err adjusted Robust NPLs lagNPLs lagGDP lagUN lagRLR lagROE lagINEF lagNII lagLR lagCRE dSTATE_INEF dFOREIGN_INEF _cons sigma_u sigma_e 1 rho Truong Ngoc Thanh – Class 19 Page 52 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 3: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit1 + β8 LRit-1 + β9 CREit-1 + d_STATE_NII + d _FOREIGN_NII + εit Fixed-effects (within) regression Group variable: code R-sq: within corr(u_i, Xb) Truong Ngoc Thanh – Class 19 Page 53 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 4: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it-1 + β5 ROEit-1 + β6 INEFit-1 + β7 NIIit1 + β8 LRit-1 + β9 CREit-1 + d_STATE_LR + d _FOREIGN_LR + εit Fixed-effects (within) regression Group variable: code R-sq: within between = 0.0211 overall F(11,24) corr(u_i, Xb) (Std Err adjusted Robust dS dFOR sigma_u sigma_e Truong Ngoc Thanh – Class 19 Page 54 Determinants of nonperforming loans – The case of Vietnamese banking sector  Model 5: NPLs it = NPLs it-1 + β1 GDP it-1 + β2 UNit-1 + β3 RLR it β7 NIIit-1 + β8 LRit-1 + β9 CREit-1 + d_ST Fixed-effects (within) regression Group variable: code R-sq: within between = 0.0348 overall = 0.3951 = 0.0989 F(11,23) corr(u_i, Xb) = -0.3989 Robust NPLs lagNPLs lagGDP lagUN lagRLR lagROE lagINEF lagNII lagLR lagCRE dSTATE_CRE dFOREIGN_CRE _cons sigma_u sigma_e 1.5666015 1.5118071 rho Truong Ngoc Thanh – Class 19 Page 55 ...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. .. Page 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. .. nonperforming loans – The case of Vietnamese banking sector CHAPTER 5: CONCLUSION The main purpose of this study is to examine the determinants of NPLs in the case of Vietnamese banking sector Both