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FOREIGN TRADE UNIVERSITYFACULTY OF INTERNATIONAL ECONOMICS------------------------------------------------ECONOMETRICS REPORTTOPIC: FACTORS AFFECTING NON-PERFORMING LOANSOF COMMERCIAL BANKS IN VIETNAM IN THE PERIOD2010 - 2019CLASS ID: KTEE310.Lecturer: Dr. Vũ Thị Phương Mai Members: 1. Nguyễn Hà Vy ...

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FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS ------------------------------------------------

ECONOMETRICS REPORT TOPIC: FACTORS AFFECTING NON-PERFORMING LOANS OF COMMERCIAL BANKS IN VIETNAM IN THE PERIOD 2010-2019 CLASS ID: KTEE310.1 Lecturer: Dr. Vũ Thị Phương Mai Members: 1. Nguyễn Hà Vy - 1234567654323456 2014340215 1 2 3 4 5 6 7 2. Nguyễn Thị Phương Thảo - 2345432123456787654 2014340209 3. Đỗ Thị Thu Hương - 234567uy5456u 2014340204 1234567876543 4. Nguyễn Thị Thu Hằng -2014340213

Hanoi, 2021

TABLE OF CONTENTS ABSTRACT……………………………………………………………………...…… 1 INTRODUCTION………………………………..……………………………..…… 2 1. 2. 3. 4. 5.

Rationale of the study……………………..………………………..……......… 2 Research methodology…...………………..………………………..………..… 3 Goals and Purpose…...………………..………………………..……...…...…... 3 Research subject and scope…………..………………………....….…...……… 3 The structure of report…………..………………….……....….…….....……… 3

SECTION 1: OVERVIEW OF THE TOPIC ………….…………………………… 5 1.1. Overview about commercial bank………….………………………...……… 5 1.2. Overview about non-performing loans………….…………………………… 6 1.3. The determinants affecting non-performing loans………….……………… 8 1.3.1. Bank-specific determinants………….……..…………………….......……… 8 1.3.2. Macroeconomics factors………….………………….............……..……… 11 SECTION 2: MODEL SPECIFICATION…….....………………………...……… 15 2.1. Methodology in the study………….…….…………...…..………...……… 15 2.2. Methodology to collect and analyze the data………...……………........… 15 2.2.1. Collect the data………….…...........……………...……………….………… 15 2.2.2. Analyze the data………….…...........……………...……………………….… 15 2.3. Building the research model…………..…….……………………….……… 20 2.3.1. Population Regression Model………….…...………………...…….……… 20 2.3.2 Sample Regression Model………….………….………….....………...…… 21 2.4. Description of the data………….………………………...................……… 21 2.4.1. Statistical description of the variables ………….………..…………......… 21 2.4.2. Correlation matrix between variables……………………………...……… 23 SECTION 3: ESTIMATED RESULTS AND STATISTICAL INFERENCES.... 25 3.1. OLS regression and conclude the model……..….……………………….… 25 3.1.1. Testing the significance of an individual regression coefficient…………………………………………..……...... 25 3.1.2. Testing specification error………..………………..……...………………… 26 3.1.3. Sample regression model and explain the results …….……………..…… 27 3.1.3.1. Explain general results…………………………………..…….. 27 3.3.3.2. Testing the significance of an individual regression coefficient and explain the estimated coefficient……...……. 28

3.2. Testing the model’s defect……………………………………………….…… 29 3.2.1 Testing multicollinearity error………………………………………….……. 29 3.2.2 Testing heteroskedasticity error……………………………………….…….. 30 3.2.3 Testing autocorrelation………………………………………………….……. 30 3.2.4 Testing disturbance’s distribution………………………………………..….. 31 3.3 Comparison to the literature and interpretation of result………………… 32 3.3.1 Bank Specific Determinants………………..……………………………..….. 32 3.3.2 Macroeconomic determinants………………..…………………………..….. 33 SECTION 4. CONCLUSION AND RECOMMENDATION…………………….. 34 4.1. Conclusion…………………………………………………………………….. 34 4.2. Recommendation……………………………………………………………... 34 4.2.1 Recommendations for Vietnamese Commercial Banks ……………………. 34 4.2.2 Recommendations for Governments and the State Bank of Vietnam……. 36 REFERENCES…………………………………………………………………..…. 38 APPENDIX………………………………………………………………………..… 41 1. List of commercial banks …..………………………………………………….. 41

TABLE OF FIGURES Exhibit 1.1: Research model......................................................................................... 8 Exhibit 2.1: The distribution of some variables........................................................... 16 Exhibit 2.2: The relationship between and the dependent variable (NPL) and some independent variables................................................................................................... 17 Exhibit 2.3: Statistical description of the variables...................................................... 22 Exhibit 2.4: Correlation matrix between variables....................................................... 23 Exhibit 3.1: OLS regression results.............................................................................. 25 Exhibit 3.2: Testing specification error........................................................................ 27 Exhibit 3.3:Testing multicollinearity.................................................................................. 30 Exhibit 3.4:Testing heteroskedasticity.............................................................................. 30 Exhibit 3.5: Testing disturbance’s distribution.................................................................. 31

TABLE OF TABLES Table 2_1: Variable description................................................................................... 18 Table 3_1: Testing significance of variables................................................................ 25 Table 3_2: Testing significance of variables of new model and explain the estimated coefficient..................................................................................................................... 28 Table 3_3: Hypothesis conclusion................................................................................ 41

ABSTRACT The term “Non-performing Loans” (NPLs) has become more common . Since the 2008 global crisis, NPLs have been monitored worldwide and became systemically important. NPLs are important variables on a macro scale for the financial stability as well as microscale for banks profitability itself in Vietnam.In the research, we aim to examine the determinants of Non-performing Loans (NPLs) in the Vietnamese banking system by using regression models. To address the research problem, data of commercial banks in Vietnam from 2010 to 2019 were collected. Macroeconomics factors such as: GDP, Inflation,Unemployment rate and bank specific factors such as: Return on equity, equity-to-asset ratio,credit growth, and previous non-performing loans are studied to analyze the effect on NPLs in 30 commercial banks in Vietnam. Factors were observed and estimated by quantitative method Ordinary Least Square in order to declare the relationship between them and the rate of changes in NPLs. The results show that non-performing loans this year will positively affect those in the next year. In addition, a raise in average return on equity and credit growth also leads to the reduction in non-performing loans from banks. Regarding macroeconomics factors, the result implies that GDP is significant and negatively affects NPLs, meanwhile inflation has positive effects related to NPLs. However, inflation resulted in an insignificant relationship with NPLs contrary to our expectation. The result of this research is useful to assist financial institutions and the regulators for policy formulation so as to minimize the negative effects of NPLs to the Vietnamese banking system.

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INTRODUCTION 1. Rationale of the study A sound financial system is crucial for every economy since financial institutions, especially commercial banks, not only facilitate the credit flow in the economy but also promote the productivity of business units via funding investment.Therefore, it is difficult for a country’s economy to develop sustainably if its financial system is inefficient and unstable During past decades, studies have shown that most banking failures or crises are caused by nonperforming loans (NPL) (Brownbridge, 1998) As the main operations of commercial banks are to accept deposits and provide loans, they are exposed to the credit risk of having bad loans, which are known as NPL. NPLs is considered as blood clot of the economy which prevents the development of the economy . Bad debts can affect liquidity risks, reduce operating profits, and the bank’s reputation with customers. As the increase in NPL has been found to put banks in danger of bankruptcy and financial crises in both developing and developed countries explained by Barr and Siems (1944) and Khemraj and Pasha ( 2009) NPL are also claimed as one of the main reasons causing a significant decrease in the Vietnamese banks’ profitability during Vietnam’s economic slowdown in 2012 when the ratio of NPLs in Vietnam sharply increased, appearing in most of the commercial banks’ announcements. The annual NPLs growth rate had sharply increased from 2007 to 2012, with an average growth rate of approximately 43.11% per year. Therefore, this study is conducted to explore the reasons behind these NPL.Currently, recent research on the problems of NPLs in Vietnam was not easy to find out, particularly quantitative research. There was a little quantitative research which used an econometric model to find out the main factors (particularly the endogenous factors) that influence the rate of changes in NPLs in Vietnamese commercial banks. Therefore , it is significantly necessary to make the studies on the factors affecting the capital structure and propose the recommendations, to solve the nonperforming loan of commercial banks in Vietnam. This is the rationale for the author to choose the research topic:Factors affecting non-performing loans of commercial banks in Vietnam in the period 2010-2019. We also expect that the research can contribute a part into the financial management of commercial banks to help policymakers and bank administrators to devise policies of minimizing risks, limiting non-performing debts, as well as provide appropriate solutions for commercial banks, thereby contributing to raise efficiency of banking operations.

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2. Research methodology To conduct the study, we used statistical,comparative and regression methods from annual financial data of 30 Vietnamese commercial banks in the period of 20102019. Accordingly, the method applied mainly is the regression analysis that runs the econometric model to examine and investigate the correlation between the independent variables and dependent variables. In specific, a multivariate regression model using OLS method (Ordinary Least Squares) was employed to test the factors and its impacts on the non-performing loans ratio of commercial banks in Vietnam. 3. Goals and Purpose The main objective of this study is to detect and discuss the factors that determine the rise or fall of the rate of NPLs in commercial banks; specifically, analyzing the sensitivity of NPL to the macroeconomic factors and bank variables within 10 years. Based on the results obtained , it also aims to enable policymakers and bank managers to develop risk-reduction policies and solutions which will help reduce bad debt and improve banking efficiency. 4. Research subject and scope Research subject: Determinants affecting the ratio of NPLs in Vietnamese commercial banks in the period 2010-2019 In terms of Scope: Employing data of 30 commercial banks in Vietnam. Banks are selected based on size diverse and having continuous operate from 2010 to 2019 In terms of Time: Collect data in the period of 10 recent years from 2010 to 2019 . 5. The Structure of report 

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The structure of study is organized into three main section as followings: Section 1: Overview of the topic The first section aims to provide literature reviews related to in the research topics including definition, classifications, economic theories and research hypothesis used in the study. Section 2: Model Specification In this section, we present research methodologies to collect and analyze data. Section 3: Estimated results and statistical references This part is to demonstrate the results of estimated model, tests for the model's possible problems and correct them. Section 4: Conclusion and Recommendations

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Based on findings and results in the Section 3, give conclusions and some recommendations.

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SECTION 1: OVERVIEW OF THE TOPIC 1.1.

Overview about commercial bank

● The term commercial bank refers to a financial institution that accepts deposits, offers checking account services, makes various loans, and offers basic financial products like certificates of deposit (CDs) and savings accounts to individuals and small businesses. A commercial bank is where most people do their banking. ● How commercial banks work: ○ Commercial banks provide basic banking services and products to the general public, both individual consumers and small to mid-sized businesses. These services include checking and savings accounts, loans and mortgages, basic investment services such as CDs, as well as other services such as safe deposit boxes. ○ Banks make money from service charges and fees. These fees vary based on the products, ranging from account fees (monthly maintenance charges, minimum balance fees, overdraft fees, non-sufficient funds (NSF) charges), safe deposit box fees, and late fees. Many loan products also contain fees in addition to interest charges. ○ Banks also earn money from interest they earn by lending out money to other clients. The funds they lend comes from customer deposits. However, the interest rate paid by the bank on the money they borrow is less than the rate charged on the money they lend. For instance, a bank may offer savings account customers an annual interest rate of 0.25%, while charging mortgage clients 4.75% in interest annually. ● The primary functions of commercial banks are: ○ Commercial banks accept various types of deposits from the public, especially from its clients, including saving account deposits, recurring account deposits, and fixed deposits. These deposits are returned whenever the customer demands them or after a certain time period. ○ Commercial banks provide loans and advances of various forms, including an overdraft facility, cash credit, bill discounting, money at call, etc. They also give demand and term loans to all types of clients against proper security. They also act as trustees for the wills of their customers etc. ○ The function of credit creation is generated on the basis of credit and payment intermediary. Commercial banks use the deposits they absorb to make loans. On the basis of check circulation and transfer settlement, the loans are converted into derivative deposits. To a certain extent, the derivative funds of several times the original deposits are increased, which 5

greatly improves the driving force of commercial banks to serve the economic development. 1.2.

Overview about non-performing loans

Non-performing loans are, in a way, a natural result of the banking system and the whole of the financial sector’s operation. Financial institutions assume risks, some of which materialize, turning loans into non-performing loans. ● Definition According to Bank for International Settlements (2004), Non-performing loans (or Bad Debts, Doubtful Debt) are loans that customers do not meet the bank's ability to repay debts for more than 90 days. According to Circular No. 02/2013/TT-NHNN dated January 21, 2013, bad debts are debts of group 3 ( non-standard loans ), group 4 (doubtful loans) and group 5 (loss-making loans). Therefore, the bank bad debt data with groups 3, 4,and 5 were used in this research. ● Reasons for Non-performing loans a. Reduced attention to borrowers This is related to the Hawthorne effect. Researchers at Hawthorne Electric Company in the US in the 1920s wondered what effect changes in lighting, heating and similar variables would have on factory workers. To the researcher's amazement, productivity increased throughout the study, during which time lighting varied greatly from normal to dim to brilliant and back, the heat was turned up and down, etc. The puzzled researchers eventually concluded that the workers were responding positively because they were the subjects of interest, not because of changes in their working conditions. Workers' perceptions that someone is paying attention to them get better results than perceptions of being ignored. Borrowers may also perform in this manner. b. Lenders lack plans to deal with risk Donor-funded credit programs are usually designed without a clear focus on risk. In microfinance promotion there seems to be no clear vision of risk or no industry-wide concern about means of addressing it, other than running a tight ship. The literature is largely concerned with outreach, measured by number of borrowers, and covering administrative costs. The jury is still out on micro-lender performance, which is currently supported by a tidal wave of donor funds that lifts all but the most leaky of ships. This inattention to risk may be called The Pollyanna Effect. c. Borrowers probe a credit operation's weaknesses Credit programs have no special claim to infallibility. A borrower may be determined to repay on time but is unable to do so due to unforeseen circumstances. If the lender does not follow up promptly with a query, the borrower will take note. She 6

may simply be grateful not to have been embarrassed. A second way in which borrowers are tempted to probe a credit program's weaknesses is when some borrowers blatantly refuse to pay on time or skillfully avoid payment. Borrower's probing of a lender's weaknesses may be called the Jurassic Park Effect. The dinosaurs in this popular film tested the structures and devices used to contain them within certain areas of Jurassic Park and eventually gained control over the entire park to the dismay, discomfort and eventual departure or demise of their human captors. In addition, the park's dinosaurs became more aggressive after the developers lost control of dinosaur breeding as a result of unexpected risks. This was captured by the remark of one actor that, “life finds a way. d. Lack of good models Another possibility is that lenders are simply not familiar with successful examples of dealing with bad and doubtful debts. This is likely in transaction economics in North and Central Asia where commercial banking is still something of a novelty compared to banking in service to economic planning. It also occurs, as in Bangladesh and Nepal, where state domination of the banking system has been accompanied by a high tolerance of non-repayment associated with politicization of financial markets. Legal recourse in these situations is remote, costly, and uncertain. This lack of credible models can be called High Default Culture Effect. ● Non-performing loans issues in Vietnam In Vietnam, bad debts also hit the economy and result in many consequences. Under the impacts of the global crisis in 2007, the Vietnam economy has experienced a gloomy period with the buildup of bad debts from 2010 up to now. A backlog of old debts has not been handled efficiently, and now new difficulties have also arisen. New difficulties relate to the NPL ratio in 2020 being at a low level, but debt Group 4 and Group 5 were on strong increase. At Techcombank, the bank with the lowest NPL ratio in the system in 2020, the total bad debt ratio decreased by 58%, to VND 1,295 billion, and the NPL ratio was only 0.47%. However, in terms of absolute value, Group 4 debt increased by 75%, reaching nearly VND 534 billion. NamABank is also in the group of banks with a bad debt ratio below 1% after total bad debts decreased by 44% to VND 744 billion, but Group 5 debt increased by 77% compared to the beginning of the year, at nearly VND 468 billion. The bank's accrued interest will also increase by 100% in 2020, at VND 2,632 billion. Group 5 debt at BIDV increased by more than VND 5,000 billion, to VND 16,525 billion, equivalent to an increase of 46% compared to the beginning of the year. MB's total bad debt was nearly VND 3,248 billion, of which Group 5 debt increased by 124%, accounting for VND 1,384 billion. Another phenomenon is the remarkable debt at Group 2 at the end of 2020 at some banks which increased dramatically. Specifically, OCB increased by 118%, VIB by 76%, and Vietcombank by 70%. This is also a matter 7

of concern because if customers continue to be unable to repay their debts, these debts will jump from Group 2 to bad debt groups. 1.3.

The determinants affecting non-performing loans

The literature identifies two s...