Tài liệu Macro economic determinants of credit risks in the asean banking system

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERASMUS UNVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS MACROECONOMIC DETERMINANTS OF CREDIT RISK IN THE ASEAN BANKING SYSTEM BY NGUYEN CHI THANH MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2016 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS MACRO ECONOMIC DETERMINANTS OF CREDIT RISK IN THE ASEAN BANKING SYSTEM A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN CHI THANH Academic Supervisor: DR. NGUYEN VU HONG THAI HO CHI MINH CITY, DECEMBER 2016 DECLARATION I declare that the wholly and mainly contents and the work presented in this thesis (Macro Economic Determinants of Credit risk in the ASEAN Banking System) are conducted by myself. The work is based on my academic knowledge as well as my review of others’ works and resources, which is always given and mentioned in the reference lists. This thesis has not been previously submitted for any degree or presented to any academic board and has not been published to any sources. I am hereby responsible for this thesis, the work and the results of my own original research. NGUYEN CHI THANH i ACKNOWLEDGEMENT Here I would like to show my sincere expression of gratitude to thank my supervisor, Dr. Nguyen Vu Hong Thai for his dedicated guideline, understanding and supports during the making of this thesis. His precious academic knowledge and ideas has motivated me for completing this thesis. Besides, I would like to express my appreciation to the lecturers and staff of the Vietnam – Netherlands Program at University of Economics Ho Chi Minh city for their willingness and priceless time to assist and give me opportunity for this thesis completion. Next, I would like to thank all of my classmates for their encouragement and their hard work, which become a good example for me to do the thesis. I wish all of us will graduate at the same date. Lastly, I would like to express my love to my families for their unlimited supports which has led to the completion of this course research project. ii ABBREVIATION ASEAN: Association of Southeast Asian Nations DGMM: the difference generalized method of the moments estimator FE & RE: Fixed-effect and Random-effect estimator GDP: Gross domestic product NPLs: Non-performing loans OECD: Organization for Economic Cooperation and Development OLS: Ordinary Least Square SGMM: the system generalized method of the moments estimator iii ABSTRACT The impact of credit risk, which is caused by the increase in the non-performing loans (NPLs), on the performance and stability of banking system as well as economic activities have recently raised many interests from researchers and policy makers. Motivated by the close connection between the NPLs and macroeconomic environments as proposed by many researchers, this paper will empirically examine the determinants of non-performing loans in commercial banking systems of the five ASEAN countries in the period of 2002 to 2015. The research uses a sample of 162 banks in these countries with 11 variables of macroeconomic and bank-specific factors and applies the System Generalized Method of Moments estimator (SGMM) for dynamic panel models. The empirical results in this paper indicate that the movement of NPLs in the commercial banks of the five studied countries is associated with both macroeconomic variables and bank-specific factors. For the macroeconomic condition, an increase in unemployment rate and the appreciation of domestic currency are found to significantly increase the NPLs. In addition, bank with higher returns on asset and leverage ratio and low ratio of equity to total assets will have lower rate of NPLs. Moreover, with the application of additional statistical analyses, the results indicate that the findings of the main model of this paper are consistent and robust. iv CONTENTS DECLARATION....................................................................................................................... i ACKNOWLEDGEMENT .......................................................................................................ii ABBREVIATION .................................................................................................................. iii CONTENTS.............................................................................................................................. v APPENDIX ............................................................................................................................... 1 LIST OF TABLES ................................................................................................................... 2 CHAPTER 1: OVERVIEW OF RESEARCH ...................................................................... 3 1. Introduction: ..................................................................................................................... 3 1.1 Backgrounds:................................................................................................................. 3 1.2 Problem statements: ..................................................................................................... 4 1.3 Research objectives:...................................................................................................... 5 1.4 Research questions: ...................................................................................................... 6 1.5 Hypothesis of the study: ............................................................................................... 6 1.6 The importance of research: ........................................................................................ 6 1.7 Structure of Research: .................................................................................................. 8 CHAPTER 2: LITERATURE REVIEWS ............................................................................ 9 2.1 Theoretical reviews: ...................................................................................................... 9 2.2 Empirical reviews: ...................................................................................................... 13 2.3 Conclusion: .................................................................................................................. 22 2.4 Research Hypothesis:.................................................................................................. 23 CHAPTER 3: DATA AND METHODOLOGY.................................................................. 27 3.1 Data collection: ............................................................................................................ 27 3.2 Econometric methodology – The NPLs measurement: ........................................... 28 3.3 The variables definition and measurement: ............................................................. 32 v 3.3.1 The dependent variable – the Non-performing loans: .............................................. 32 3.3.2 Macroeconomic variables: ........................................................................................ 32 3.3.3 Microeconomic variables – bank-specific determinants: ......................................... 34 3.4 Econometric strategy – The system GMM estimator:............................................ 38 CHAPTER 4: RESULTS AND DISCUSSIONs .................................................................. 40 4.1 Summary statistics: ..................................................................................................... 40 4.2 Unit root tests: ............................................................................................................. 41 4.3 Empirical results: ........................................................................................................ 41 CHAPTER 5: OTHER ANALYSIS AND ROBUSTNESS CHECK ................................ 51 CHAPTER 6: CONCLUSION, POLICY IMPLICATIONS & LIMITATIONS OF THE REASEARCH ........................................................................................................................ 56 6.1 Main findings: ............................................................................................................. 56 6.2 Policy implications: ..................................................................................................... 57 6.3 Limitations: ................................................................................................................. 58 6.4 Future research recommendation: ............................................................................ 58 REFERENCES ....................................................................................................................... 59 APPENDIX ............................................................................................................................. 66 vi APPENDIX Appendix 1: Number of banks in each country Appendix 2: xtabond2 model selection criteria Appendix 3: Correlation of variables Appendix 4: Additional analyses and Robustness checks Appendix 5: Additional analyses and Robustness checks AP Page | 1 LIST OF TABLES Table 1: Description of variables Table 2: Summary statistics Table 3: Unit root tests for NPLs estimations variables Table 4: Results with SGMM and fixed-effect estimations Page | 2 CHAPTER 1: OVERVIEW OF RESEARCH 1. Introduction: Banks are the financial intermediaries who play an important role in the development of a country. In the financial sector, a commercial bank is a funding channel, which can allocate the cash flows in the economy through their financial services as well as traditional services (taking deposits and make business loans). Whenever a loan is approved, banks gain profits from the borrowers by loan interest rate and services fees. However, banks would expose to credit risk from this service because borrowers could suddenly lost their abilities to pay the loan in time, namely the non-performing loans (NPLs). The main reason for that comes from the movement of the macroeconomic environment, which directly impacts to the revenues and business activities of bank borrowers. Therefore, this paper will conduct an examination about how the economics determinants affect the bank credit risk. In this chapter, the backgrounds, problem statements, research objectives, research questions, significance of the research and the layouts will be discuss around this issue. 1.1 Backgrounds: Along with the expansion of the economy as well as financial liberalization process in developing countries, the financial sector have been grown with surprising rate. Besides, the improvements of technology and management procedures help banks making decisions to grow in financial markets. However, the occurrences of two big economic recessions in 1997 and 2007 have significantly affected the banking systems in developing countries. It associated with the deteriorated quality of bank assets due to a massive increase in the NPLs, which has a close connection to the economic cycle. When borrowers are unable to fulfill their obligations to the loans, it would become credit risk of banks, which is one of the significant risks among many kinds of risks that most of the commercial banks are exposed. Credit risk is distinguished by two components which are systematic and unsystematic credit risk (Castro, 2013) and in fact, it is very hard to set an efficient credit risk management policy and procedure for the banking system. This is because of the unpredictable natures of economic Page | 3 environment that have the impacts to banking-specific factors as well as risks in banking industry. Therefore, this impact has raised many serious concerns to researchers and policy makers to understand the relation between credit risk and the business cycle in order to ensure the stability of a banking system. 1.2 Problem statements: The beginning of recent crisis exploded since the collapse of the Lehman Brothers, the fourth-largest U.S. investment bank. It is because of the subprime mortgage crisis, many loan defaults makes the bank illiquidity to prevent from the crisis. Moreover, the depositors do a massive withdraw their money out of the bank as they lost their confidence in the banks. As a result, the bank do not have enough money to do business and indirectly cause the Washington Mutual bankruptcy. Since the Lehman Brother do business around the world, it also leads banks in many countries face the credit risk. Making loan is the traditional function provided by the bank but it also causes the credit risk, which come from the borrowers who are inability to pay back the loans as they promised. Following to Castro (2013), the increase of bad loans in banks’ balance sheet leads to the problem of liquidity and insolvency, which is the signal for banking crisis. In the case of illiquidity and insolvency, banks will lose their abilities to pay to their debtors and fail to meet their obligations. As a shock have happened, banks will be considered as loss and could be forced to shut down. From there, both banks and their debtors will be struggled by loss and it will effect to economy. Therefore, it is crucial to raise awareness to the credit risk in order to determine the cause of risks and prevent banks from illiquidity and insolvency problems. Consequently, if banks need to control the credit risk efficiently, they must understand the factors that cause the credit risk. However, as suggestion of Garr (2013), the nature of macroeconomic environment is unforetold and also associates with various microeconomic factors, which makes banks’ credit risk management become a very complicated and tough objective in order to manage the credit risk. Lack of knowledge and experience in credit risk management can leads banks to more serious risks. Besides, Ratnovski (2013) points a view that credit risk management may become a burden rather than a solution for banks because it could drain a certain amount of Page | 4 resources and time of banks. For more specific, the managers also have to put many effort in knowledge and experiences to deal with it and it could raise the administrative cost while a low return on highly liquid assets cannot be compensated the cost. A credit risk program requires time to take effect and resources (such as capital and labors) to be employed and managed for a long time in order to prevent banks from a sudden attack of credit risk. Therefore, if the credit risk policy and procedure are not based on the real situation of the factors that impact to credit risk, they will be loss because their money and time for the costly program are wasted, but also they will suffers a significant raise of the credit risk problems. As a result, it has led to many interests of researchers and policy makers in finding the factors that can lead to the bank credit risk, so that they can understand these factors and build an effective credit risk management to limit the probability of credit risk. 1.3 Research objectives: The paper will examine the influence of macroeconomic environment factors to the non-performing loans ratio (NPLs) in the five countries of ASEAN (Indonesia, Malaysia, Philippine, Thailand and Vietnam) covering a 13-year period of time from 2002 to 2015, which are in the same development rate in the area. However, due to the lack of NPLs data at countries level, the NPLs ratio of individual commercial bank will be examined and in order to prevent from bias and to ensure the model consistent, other bank-specific factors will be adopted in this paper, there are 162 commercial banks’ information collected. The data for macro determinants is collected from the World Bank data while bank-specific ones is from the Bank Scope-Fitch’s International Bank Database. Finally, the objectives of this paper are as follows: - To examine the impacts of macroeconomic determinants to the NPLs ratio of the commercial banks in the five countries of ASEAN. - To study the nature of the commercial banks’ specific factors toward the NPLs in the five countries of ASEAN. - To find an appropriated method to measure the relationship between macroeconomic factors and the NPLs ratio Page | 5 - To ensure the consistent of the chosen method through the application of robustness check and additional analytical tests. 1.4 Give recommendation to policy makers. Research questions: The questions of this paper will be raised to match with the objectives above, these are as follows: - Which is the macroeconomic factor that significantly effects the NPLs ratio in the commercial banks of the five ASEAN countries? 1.5 How do banks’ management in these countries affect their NPLs? Hypothesis of the study: This paper will examine the impacts of five macroeconomic factors to the NPLs rate, thus the five hypotheses are as follows: H1: Gross Domestic Product (GDP) has a significant negative relationship with bank credit risk in the five studied ASEAN countries. H2: Interest rate has a significant positive effect on bank credit risk in the five studied ASEAN countries. H3: Inflation rate has a significant impact on bank credit risk in the five studied ASEAN countries. H4: Exchange rate appreciation has a significant relationship with bank credit risk in the five studied ASEAN countries. H5: Unemployment rate has a significantly positive impact on bank credit risk in the five studied ASEAN countries. 1.6 The importance of research: Numerous existing papers are conducted to examine the credit risk determinants within a country or a category of countries (such as in Europe, OECD or developed countries) or a limit of determinant category. In this study, the potential determinants of bank credit risk, which are applied in the model, are 11 factors (including five main Page | 6 macroeconomic determinants and six additional bank-specific factors). This is also the first paper that examines the impacts of these variables on the NPLs of commercial banks in five ASEAN countries (Indonesia, Malaysia, Philippine, Thailand and Vietnam) from 2002 to 2015. In addition, due to the nature of the data sample in this paper and the limit of related research papers, the research methodological design will follow an extensive approach through the dynamic panel data econometric techniques that serve as a robust cross-validation of the results as well as several additional analysis and robustness tests. The results of the research will assist a better understanding into the key factors of credit risk in the commercial banks of studied countries. In addition, the paper will propose useful information in explaining what cause the bank credit risk and in evaluating the performance of the banks toward the NPLs. According to Demirguc-Kunt and Detragiache (1998), banking system of a country with high inflation rate, unemployment and interest rate seem to have higher bank credit risk and banking crisis would be easily occur. Therefore, this study will give more understanding in the connection of the economic developments and the credit risk as well as the information on how the banks’ operation and the economic condition within these countries is. For more specific, the investor and depositor will know how and when the bank performances are in the stable and sound condition through knowing nature of the economic and bank specific factors. With this knowledge, their banking activities are much easier to make exact decisions to use their fund and prevent from bad investments. In addition, the result will provide to bank managers an efficient loan and credit risk management policy with the information of which economic and bank specific determinants of the bank influence credit risk. Therefore, with information such as increase in the inflation rate, interest rate or domestic currency appreciation, banks could issue an appropriated approach to monitor, evaluate and control for bank risk exposures with a more precise way. Consequently, an efficient credit risk management policy will help bank management more effective in capital allocation, banking performance, operating cost and profitability. Page | 7 1.7 Structure of Research: This research paper is organized in six chapters. Chapter 1 is the introduction and overview the general idea of the study context. Chapter 2 gives the literature reviews of the previous studies in both theoretical and empirical frameworks for the effect of the macroeconomic factors on the bank credit risk and it also describes the proposed hypotheses development for the study. Chapter 3 consists of the data and research methodology which includes the research methodology, data collection methods, the model description and variable description. Chapter 4 will present and interpret the results of the econometric analysis with respect to the research’s theoretical and empirical analyses, which are linked to the hypotheses of the research paper. It will show the relationship of the economic factors and the NPLs ratio of banks. Furthermore, chapter 5 conducts additional analysis and robustness test in order to examine the consistent of the estimator and finally chapter 6 will suggest some policy implications, the limitations and the final conclusion of this thesis. Page | 8 CHAPTER 2: LITERATURE REVIEWS 2.1 Theoretical reviews: Credit risk is defined as the risk from borrowers who have lost their ability to pay loans back to lenders partially or totally. In recent years, many banks in the world experienced substantial losses and reduction of capital provision due to rapid deterioration in assets’ quality. This not only increased banks’ exposure to economic crisis but also restricted bank lending ability with both direct and indirect consequences to the financial stability and economic activities. Therefore, the need for the credit risk analysis is crucial because it is not only to ensure a stable banking system for a prosperous economic growth but also can raise the awareness to the regulatory authorities to prevent a possible crisis in the future. Castro (2013) identifies factors affecting systematic and unsystematic credit risk separately. The factors influencing the systematic credit risk are: macroeconomic factors, changes in economic policies and political changes or changes in the goals of leading political parties. While unsystematic credit risk is affected by specific factors: (i) individual-specific factors namely individual personality, financial solvency, capital and credit insurance; (ii) company-specific factors namely management, financial position and reporting, sources of funds, their ability to pay the loan and specific factors of the industry sector. 2.1.1 Business Cycle and Risk: The relationship between the economy and financial system has been argued in a number of theories. Within the framework of business cycles, the connection between macroeconomic factors and loan quality is emphasized by linking to the movement of business cycle with financial vulnerability and banking performance. Specifically, Messai and Jouini (2013) offers a theoretical models from Williamson (1987), which emphasizes the nature of credit risk and proposes the impact of business cycle to the financial sector of a country. In addition, Messai and Jouini (2013) also summarized theoretical review for this relation, the phases of the business cycle relating to banking performance have been studied in order to express the relationship between the macroeconomic environment (such as the yearly GDP growth, the real interest rate, the annual inflation rate, the exchange rate and the unemployment rate) and the quality of Page | 9 loans. During the economic expansion phase, there are only a relatively small proportion of bad loans, borrowers are confident to have adequate income or more cash held to repay for their loans in time of deadlines. Therefore, lenders may not pay much attentions to the credit standards and allow more risk (Koch and McDonald, 2003) or the increased ability of creditors to repay loans leads to reducing of credit risk for lenders (Salas and Saurina, 2002). However, when economic conditions worsen, the studies of Jiménez and Saurina (2006) for Spanish banks and Bohachova (2008) for members of Organization For Economic Cooperation And Development (OECD) reach the conclusion that banks are vulnerable to adverse selection in their financial decisions and moral hazard behavior of their creditors so that this causes an increase in risk of loans. 2.1.2 Interest Rate and Risk: It is also argued that higher interest rate, mostly induced by monetary policy, associates highly with debt burden due to higher interest payment, which leads to high rate of NPLs. For instances, following the theory of asymmetric information, borrowers are able to face adverse selection problem as interest rate surges, it is call “bad risk” (Bohachova, 2008), the result of loan applicants is probably adverse with the borrowers’ selection. In order to pay for their loans, instead of using the loans on safe projects with low returns, creditors tend to have strong motive to riskier projects with much more higher income. In addition, when interest rate increases, banks will earn more returns from new loans and floating interest loans while borrowers have to stand with higher payments and then the probability of increase in credit risk would occur on banks’ balance sheets (Demirguc-Kunt and Detragiache, 1998). However, from the view of the bank side, banks diversify their financial roles in the market, they conduct asset transformation and they lend to a large number of borrowers as well as borrow from a large number of depositors (Williamson, 1987). Moreover, in some countries with interest rate liberalization, because of rises in the costs of funds and the culture of highrisk behaviors; higher rates are charged to high-risk borrowers in order to mitigate risks, hence banks overall risk exposure increases more (Fofack, 2005). Page | 10 When the economy went down, the return on bank assets deteriorates more than the rate that must be paid on depositors and banks would reduce profits or face losses. As bank’s assets are composed of long-term fixed interest rate loans, thus banks cannot handle for the return on assets quickly enough. As a result, banks would raise short-term lending interest rate in order to deal with their liability payments (Mishkin, 1996)1. In addition, when borrowers are likely to be exposed to debt burden, banks also face to a large risky loan portfolio, thus a higher net interest margin is required to compensate the higher risk of default (Ahmad and Ariff, 2007), which leads to a systematic banking sectors problems. 2.1.3 Inflation and Risk: Another factor that should be considered is the inflation, which is caused by the restrained money supply growth and the disposed nominal depreciation of the domestic currency; inflation influences to both banks’ decisions and borrowers’ behaviors to loans. For more specific, inflation is unpredictable and an increase in inflation makes the prices of goods and services go up, thus the volatility of firms’ profits will rises as well as their debt obligations (Peyavali, 2015). An increased rate of inflation also have a negative effect on real rates of return on bank assets as well as incomes of existing borrowers thereby making the quality of previously extended loans worse and resulting to credit rationing (Bohachova, 2008). In addition, if variable loan rates are applied, high inflation leads borrowers to adverse selections because banks will prefer to adjust the lending rates to keep their real returns stable or the government conducts monetary policy to fight against inflation (Nkusu, 2011). On the other hand, disinflation also affects loan quality because in a previously high-inflation economy, there are high real interest rate, which makes the earnings of borrowers declined and encourages risks similar to a rise in nominal interest rate (Mishkin, 1996). 2.1.4 Exchange Rate and Risk: Exchange rate, which indicates the value of domestic currency in terms of another, is also one of macroeconomic sources of economic instability as well as bank risk 1 Most of the United States banking panics follow an increase in short-term lending interest rates. Page | 11 exposure. Because of no currency matching between the income of borrowers and their loan debts, for loans nominated in foreign currency, depreciation of domestic currency increases debts and debtors’ incapacity to pay the loans and then banks would face to loan defaults (Curak et al., 2013). When domestic currency depreciates, the rate of impaired loans would increase, especially for loans nominated in foreign currency. Credit risk for bank loans is likely to increase to importers and decrease to exporters, thus bank’s overall risk exposure will be determined by its net vulnerability to exporting or importing borrowers. As the foreign currency appreciates, it costs more to purchase foreign goods and services, thereby more units of domestic currency are required to secure the same quantity of imported goods and services than before. Accordingly, the demand of financial support for bank credit will increase to cover the raising costs and it would reduce the firm’s profitability, then firm will encounter the problem to serve interest and principal of loans (Poudel, 2013). On the other side, Bochahova (2008) also expresses two theoretical interactions of exchange rate movement on banks’ credit risk. For more specific, banks’ volatility could increase due to the domestic currency depreciation when banks liabilities denominated in foreign currencies are higher than their foreign exchange assets. In addition, a great rate of domestic currency depreciation could lead to disintermediation as depositors decide to withdraw their funds from banks to invest directly to other “hard currency assets” with higher returns, thus banks will face capital shortage and bank credit risks will increase. 2.1.5 Unemployment and Risk: Another theoretical explanation of the source of banking credit risk is viewed from unemployment as an indicator that highly correlate with the economic cycle. For households and individuals, an increase in the unemployment rate during economic recession reduces the incomes, resulting cash flow streams be worse and then the probability of on loan defaults could surge. While in corporate sector, a decrease in production due to a drop in the consumption and demand for goods, causes revenues loss and a weak liquidity position regarding debts. Therefore, it exacerbates bank credit risk (Castro, 2013). Page | 12