TOPIC FACTORS AFFECTING NON PERFORMING LOANS OF COMMERCIAL BANKS IN VIETNAM IN THE PERIOD 2010 2019

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: Nguyễn Hà Vy - 1234567654323456 2014340215 Nguyễn Thị Phương Thảo - 2345432123456787654 2014340209 Đỗ Thị Thu Hương - 234567uy5456u 2014340204 1234567876543 Nguyễn Thị Thu Hằng -2014340213 Hanoi, 2021 TABLE OF CONTENTS ABSTRACT…………………………………………………………………… …… INTRODUCTION……………………………… …………………………… …… 2 Rationale of the study…………………… ……………………… …… … Research methodology… ……………… ……………………… ……… … Goals and Purpose… ……………… ……………………… …… … … Research subject and scope………… ……………………… ….… ……… The structure of report………… ………………….…… ….…… ……… SECTION 1: OVERVIEW OF THE TOPIC ………….…………………………… 1.1 Overview about commercial bank………….……………………… ……… 1.2 Overview about non-performing loans………….…………………………… 1.3 The determinants affecting non-performing loans………….……………… 1.3.1 Bank-specific determinants………….…… …………………… .……… 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 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 List of commercial banks … ………………………………………………… 41 TABLE OF FIGURES Exhibit 1.1: Research model 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 INTRODUCTION 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 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 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 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 The Structure of report     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 Based on findings and results in the Section 3, give conclusions and some recommendations 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 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 Exhibit 3.2: Testing specification error Comment: P-value=0.0563> α=0.05→ Do not Reject H0 >Model has no omitted variables 3.1.3 Sample regression model and explain the results According to the estimated result from Stata using OLS method, we obtained the SRF as below: lnNPL= 1.545534 + 0.5613392*lnpNPL - 0.144781 *GDP + 0.0237141*INF - 0.1173223*lnCreG - 0.0669493* lnROE + 𝒖 𝒊𝒕 3.1.3.1 Explain general results: ● The raw data has 30 commercial banks researched in 10 year (means that we have 300 observations),but OLS regression shows only 271 observations The reason is: there are 29 missing values generated by the gen command ● F(5,265)= 56.61 shows the value of F-test with factors and 265 degrees of freedom Pro>F=0.0000: P-value of F-test for overall significance is smaller than the level of significance 5%, thus 𝑅2 does not equal In other words, the regression coefficients 27 not equal simultaneously.==> The overall model is statistically significance level at 5% ● Explained sum of squares(ESS) indicates how much of the variation in the dependent variable NPL that the model can explain: ESS= 49.7975528 with degree of freedom is k-1=5 ● Residuals sum of squares(RSS) shows how much of the variation in the dependent variable that the model cannot explain: RSS=46.6181499, degree of freedom is n-k=265 ● Total sum of squares (TSS) shows how much variation there is in the dependent variable of the model:TSS=96.4157026, degree of freedom is n-1=270 ● 𝑅2 =0.5165 means changes in lnNPL are 51.65% explained by independent variables in the model and the rest 48.35% may be explained by the other factors not mentioned in this regression model It is not an impressive number but can be accepted 3.3.3.2 Testing the significance of an individual regression coefficient and explain the estimated coefficient: At the level of significance α=0.05, if an independent variable has P-value< α → Reject H0, it means that this independent variable affects the dependent variable Testing the hypothesis: H0:𝐵𝑖 = H1:𝐵𝑖 ≠ Table 3_2: Testing significance of variables of new model and explain the estimated coefficient Variable P-value Coefficient Conclusion lnpNPL 0.000