Trang 1 BANKING ACADEMY OF VIETNAM FACULTY OF FOREIGN LANGUAGES ------ GRADUATION THESIS DETERMINANTS OF NON-PERFORMING LOANS: EVIDENCE FROM VIETNAMESE JOINT-STOCK COMMERCIAL BANKS
BANKING ACADEMY OF VIETNAM FACULTY OF FOREIGN LANGUAGES - GRADUATION THESIS DETERMINANTS OF NON-PERFORMING LOANS: EVIDENCE FROM VIETNAMESE JOINT-STOCK COMMERCIAL BANKS Student : Nguyen Thi Chung Class : K22ATCA Academic Year : 2019-2023 Student ID : 22A7510014 Instructor : Dr Can Thuy Lien Hanoi, May 2023 BANKING ACADEMY OF VIETNAM FACULTY OF FOREIGN LANGUAGES - GRADUATION THESIS DETERMINANTS OF NON-PERFORMING LOANS: EVIDENCE FROM VIETNAMESE JOINT-STOCK COMMERCIAL BANKS Student : Nguyen Thi Chung Class : K22ATCA Academic Year : 2019-2023 Student ID : 22A7510014 Instructor : Dr Can Thuy Lien Hanoi, May 2023 CERTIFICATE OF ORIGINALITY " I hereby declare that the graduation thesis titled "Determinants of non-performing loans: evidence from Vietnamese joint-stock commercial banks" is an original work done by myself, under the guidance and supervision of Mr supervised by Ms Can Thuy Lien, lecturer of the Faculty of Foreign Languages at Vietnam Banking Academy I certify that I did not use any unethical methods to carry out this work and take full responsibility for any errors or omissions in this research Hanoi, May, 2023 Author Nguyen Thi Chung i ACKNOWLEDGMENT I would like to express my sincere gratitude to all those who contributed to the successful completion of my thesis on " Determinants of non-performing loans: evidence from Vietnamese joint-stock commercial banks " First and foremost, I would like to express my sincere gratitude to Ms Can Thuy Lien, lecturer in the Faculty of Foreign Languages at Banking Academy, who provided invaluable guidance and support during this study Her insightful feedback and constructive criticism helped me clarify ideas and produce higher quality research Second, I would like to express my gratitude to all the lecturers at Banking Academy in general and Faculty of Foreign Language’s lectures in particular for their teaching enthusiasm throughout my academic journey Third, I am also grateful to my colleagues and friends who always supported me during the research Finally, I would like to thank my family for their constant support and understanding throughout my academic journey Their love and encouragement has always been an unchanging source of motivation and inspiration for me ii TABLE OF CONTENT CERTIFICATE OF ORIGINALITY .i ACKNOWLEDGMENT ii TABLE OF CONTENT iii LIST OF ABBREVIATIONS v LIST OF TABLES vi LIST OF FIGURES vii ABSTRACTS viii CHAPTER I: INTRODUCTION 1 Introduction 1.2 Background of the study Significance of the study Scope and Limitations of the study 1.6 Definition of terms 1.7 Structure of the thesis .9 CHAPTER II: LITERATURE REVIEW 10 Overview of non-performing loans and the current situations in Vietnamese joint stock commercial banks 10 1.1 Overview of non-performing loans 10 1.1 Concept of non-performing loans 10 1.1 Classification of types of loans 10 1.1 Consequences of non-performing loans 11 2.2.2 The current situation of non-performing loans of Vietnamese joint stock commercial banks 12 2.2.2.1 Overview of operations of Vietnamese commercial banks 12 2.2.2.2 The current situation of non-performing 18 2.2 Researches on factors determining non-performing loans at commercial banks .20 iii CHAPTER III: RESEARCH METHODOLOGY 25 3.1 Locale of the study 25 3.2 Research model .25 3.3 Research method 32 3.4 Research data and sample 33 3.5 Validity and Reliability 34 3.5.2 Reliability 35 CHAPTER IV: RESULTS AND DISCUSSIONS 36 4.1 Results 36 4.1.1 Bank-specific and macro determinants of NPLs in the Vietnamese banking sector 36 4.1.1.1 Descriptive statistics for a research sample 36 4.1.1.2 Correlation and multicollinearity analysis of variables .38 4.1.2 The impact of bank-specific and macro factors on NPLs in the Vietnamese banking sector 43 4.2 Discussion 44 CHAPTER V: SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS 49 5.1 Summary of findings 49 5.2 Conclusion .49 5.3 Recommendations 50 5.3.1 From Government of Vietnam 50 5.3.2 From the State Bank of Vietnam 51 5.3.2 From joint-stock commercial banks .53 REFERENCES 57 APPENDICES 61 iv LIST OF ABBREVIATIONS Abbreviations Meanings FEM Fixed effects model GDP Economic growth IMF International Monetary Fund INF Inflation LLR Loan loss reserve ratio NPLs Non-performing loans REM Random effects model ROA Return on assets SBV State Bank of Vietnam SMEs Small and medium enterprises SIZE Size of bank VACM Vietnam Asset Management Company WB World Bank WTO World Trade Organization v LIST OF TABLES Table Page Table 2.1: The number of commercial banks over the 13 years Table 3.1 Summary of variables and sign expectation 30 Table 4.1: Descriptive statistics of the variables 36 Table 4.2: The correlation matrix among variables in 38 the study Table 4.3: Variance inflation factor index of the model 39 Table 4.4: The result of Hausman test 40 Table 4.5: The estimation results of FGLS method 41 Table 4.6: Summarising the results of regression 42 models Table 4.7: Summary the results of the study vi 44 LIST OF FIGURES Figure Page Figure 2.1: Scale of total assets in the period 2014- 14 2022 Figure 2.2: Credit growth rate in the period 2014-2022 15 Figure 2.3: Loan-to-deposit ratio in the period 2014- 17 2022 Figure 2.4: Non-performing loan ratio of banking 18 system from 2014 – 2022 Figure 2.5: Theoretical framework 23 vii ABSTRACTS Title: Determinants of non - performing loans: evidence from Vietnamese joint - stock commercial banks Author: Nguyen Thi Chung Advisor: Dr Can Thuy Lien This study investigates the determinants of non-performing loans (NPLs) in the Vietnamese banking system using a sample of 20 joint stock commercial banks from 2014 to 2022 Secondary data analysis and linear regression model used to analyze bank-specific factors, including return on assets (ROA), loan loss reserve ratio (LLR), and size of bank (SIZE), as well as macro factors, including economic growth (GDP) and inflation (INF) The results show that except GDP has no impact on NPLs, the remaining factors have a significant impact Specifically, ROA and SIZE have a negative relationship with NPLs, while the LLR ratio has a positive relationship The inflation macro factor has a negative effect on NPLs Based on the results, this study proposes some recommendations to help banks reduce NPL ratio, improve the stability of the commercial banking system in particular and the economy in general Keywords: Non-performing loans, Vietnamese commercial banks, bank-specific factors, macro factor viii Radivojevic, N., & Jovovic, J (2017) Examining of determinants of non-performing loans Prague Economic Papers, 26(3), 300-316 Rajha, K S (2016) Determinants of non-performing loans: Evidence from the Jordanian banking sector Journal of Finance and Bank Management, 4(1), 125-136 Singh, s k., basuki, b., & setiawan, r (2021) The effect of non-performing loan on profitability: Empirical evidence from Nepalese commercial banks The Journal of Asian Finance, Economics and Business, 8(4), 709-716 Thịnh, T V., & Loan, N.N.H (2021) Các yếu tố tác động đến nợ xấu ngân hàng thương mại Việt Nam Tạp chí cơng thương Vinh, N T H (2015) Yếu tố tác động đến nợ xấu ngân hàng thương mại Việt Nam Tạp chí Phát triển kinh tế Vuko, T., & Čular, M (2014) Finding determinants of audit delay by pooled OLS regression analysis Croatian Operational Research Review, 81-91 Waqas, M., Fatima, N., Khan, A., & Arif, M (2017) Determinants of nonperforming loans: A comparative study of Pakistan, India, and Bangladesh International Journal of Finance & Banking Studies (2147-4486), 6(1), 5168 Yamane, Taro (1967) Statistics: An Introductory Analysis, 2nd Edition, New York: Harper and Row Yulianti, E., Aliamin, A., & Ibrahim, R (2018) The effect of capital adequacy and bank size on non-performing loans in Indonesian public banks Journal of Accounting Research, Organization and Economics, 1(2), 205-214 60 APPENDICES APPENDIX List of 20 researched commercial banks: No Commercial banks Abbreviation Joint Stock Commercial Bank for Foreign Trade of Vietcombank Vietnam Vietnam Joint Stock Commercial Bank for Industry Vietinbank and Trade Joint Stock Commercial Bank for Investment and BIDV Development of Vietnam Ho Chi Minh City Development Joint Stock HDBank Commercial Bank Military Commercial Joint Stock Bank MBBank Vietnam Technological and Commercial Joint Stock Techcombank Bank Vietnam Prosperity Joint Stock Commercial Bank VPBank Asia Commercial Joint Stock Bank ACB Tien Phong Commercial Joint Stock Bank TPBank 61 10 Saigon Thuong tin Commercial Joint Stock Bank Sacombank 11 Saigon-Hanoi Commercial Joint Stock Bank SHB 12 An Binh Commercial Joint Stock Bank ABBank 13 Vietnam Export Import Commercial Joint Stock Bank Eximbank 14 Vietnam International Commercial Joint Stock Bank VIB 15 Southeast Asia Commercial Joint Stock Bank SeABank 16 Petrolimex Group Commercial Joint Stock Bank PgBank 17 Bao Viet Joint Stock Commercial Bank BaoVietBank 18 LienViet Post Joint Stock Commercial Bank LienVietpostBank 19 Orient Commercial Joint Stock Bank OCB 20 Vietnam Asia Commercial Joint Stock Bank VietABank 62 APPENDIX Macroeconomic regression data: Year GDP INF 2014 6,40 4,10 2015 7,00 0,60 2016 6,70 2,70 2017 6,90 3,50 2018 7,20 3,50 2019 7,20 2,80 2020 2,90 3,20 2021 2,60 1,80 2022 8,00 3,20 APPENDIX Bank-specific regression data: BANKS YEAR NPLs ROA LLR SIZE Vietcombank 2014 2,31 0,80 1,44 20,17 Vietcombank 2015 1,84 7,91 1,60 18,03 Vietcombank 2016 1,45 0,87 1,42 20,48 Vietcombank 2017 1,11 0,88 1,16 20,76 Vietcombank 2018 0,97 13,61 1,19 18,49 Vietcombank 2019 0,78 1,52 0,94 20,92 Vietcombank 2020 0,62 1,39 1,22 21,01 63 Vietcombank 2021 0,67 1,55 1,26 21,07 Vietcombank 2022 0,67 1,65 0,63 21,32 Vietinbank 2014 0,90 0,87 0,90 20,31 Vietinbank 2015 0,73 0,73 0,88 20,47 Vietinbank 2016 0,93 0,72 0,77 20,67 Vietinbank 2017 1,14 0,68 1,07 20,81 Vietinbank 2018 1,56 0,46 0,91 20,88 Vietinbank 2019 1,16 0,76 1,41 20,94 Vietinbank 2020 0,94 1,02 1,21 21,02 Vietinbank 2021 1,60 0,92 1,66 21,15 Vietinbank 2022 1,2 0,93 1,94 21,32 BIDV 2014 2,03 0,77 1,59 20,29 BIDV 2015 1,68 0,75 0,96 20,56 BIDV 2016 1,99 6,19 1,29 18,43 BIDV 2017 1,62 0,58 1,74 20,91 BIDV 2018 1,69 0,56 1,94 21 BIDV 2019 1,74 0,56 1,83 21,12 BIDV 2020 1,76 0,46 1,95 21,14 BIDV 2021 0,82 0,60 2,22 21,29 BIDV 2022 0,96 0,87 1,62 21,47 HDBank 2014 1,40 0,48 1,10 18,42 HDBank 2015 1,08 0,59 1,67 18,48 HDBank 2016 1,26 0,61 1,22 18,83 HDBank 2017 1,50 1,03 0,96 19,06 HDBank 2018 0,97 1,48 0,82 19,19 64 HDBank 2019 0,98 1,75 0,89 19,25 HDBank 2020 0,93 1,46 1,01 19,58 HDBank 2021 1,26 1,72 1,15 19,74 HDBank 2022 1,30 1,97 1,18 19,85 MBBank 2014 2,73 1,23 2,06 19,12 MBBank 2015 0,71 1,13 2,14 19,21 MBBank 2016 1,31 1,11 1,37 19,36 MBBank 2017 1,20 1,10 1,79 19,56 MBBank 2018 1,32 1,71 1,44 19,71 MBBank 2019 1,16 1,96 1,98 19,84 MBBank 2020 0,92 1,74 2,08 20,02 MBBank 2021 1,04 2,18 2,26 20,22 MBBank 2022 1,09 2,49 1,79 20,41 Techcombank 2014 2,38 0,62 2,85 18,99 Techcombank 2015 1,67 0,80 3,28 19,07 Techcombank 2016 1,58 1,34 2,59 19,28 Techcombank 2017 1,61 23,93 2,27 17,11 Techcombank 2018 1,75 2,64 1,17 19,59 Techcombank 2019 1,33 2,67 0,40 19,77 Techcombank 2020 0,50 2,86 0,95 19,90 Techcombank 2021 0,60 3,24 0,78 20,16 Techcombank 2022 0,90 2,92 0,47 20,36 VPBank 2014 2,54 0,77 1,27 18,91 VPBank 2015 2,43 1,24 2,85 19,08 VPBank 2016 2,03 1,72 3,73 19,25 65 VPBank 2017 3,39 2,32 5,61 19,44 VPBank 2018 3,51 2,28 5,15 19,59 VPBank 2019 3,42 2,19 5,41 19,75 VPBank 2020 2,90 2,49 5,11 19,85 VPBank 2021 5,02 2,10 5,56 20,12 VPBank 2022 2,19 2,68 5,29 20,26 ACB 2014 2,18 0,53 0,85 19,01 ACB 2015 1,32 0,51 0,67 19,12 ACB 2016 0,90 0,57 0,75 19,27 ACB 2017 0,70 0,74 1,30 19,47 ACB 2018 0,73 1,56 0,41 19,61 ACB 2019 0,54 1,57 0,10 19,76 ACB 2020 0,60 1,73 0,31 19,91 ACB 2021 0,78 1,82 0,94 20,08 ACB 2022 0,74 2,25 0,02 20,26 TPBank 2014 1,01 1,04 0,03 17,76 TPBank 2015 0,66 0,74 0,48 18,15 TPBank 2016 0,71 0,53 0,59 18,48 TPBank 2017 1,10 0,78 0,74 18,64 TPBank 2018 1,12 1,33 0,68 18,73 TPBank 2019 1,29 1,88 1,37 18,92 TPBank 2020 1,17 1,70 1,51 19,14 TPBank 2021 0,65 1,65 2,09 19,50 TPBank 2022 0,84 1,91 0,01 19,61 Sacombank 2014 1,18 1,16 0,76 19,06 66 Sacombank 2015 5,85 0,39 1,16 19,49 Sacombank 2016 6,68 0,03 0,35 19,62 Sacombank 2017 4,59 0,32 0,37 19,72 Sacombank 2018 2,12 0,44 0,63 19,82 Sacombank 2019 1,90 0,54 0,74 19,93 Sacombank 2020 1,60 0,54 0,91 20,02 Sacombank 2021 1,47 0,65 0,93 20,07 Sacombank 2022 0,98 0,85 2,05 20,2 SHB 2014 2,20 0,47 0,60 18,95 SHB 2015 1,72 3,88 0,65 16,83 SHB 2016 1,87 3,9 0,81 16,97 SHB 2017 1,92 0,54 0,83 19,47 SHB 2018 2,40 0,52 0,67 19,59 SHB 2019 1,83 0,66 0,92 19,72 SHB 2020 1,71 0,63 1,54 19,84 SHB 2021 1,69 0,99 2,09 20,04 SHB 2022 2,80 0,50 0,13 20,06 ABBank 2014 2,75 1,73 1,68 15,72 ABBank 2015 1,72 0,14 2,17 17,98 ABBank 2016 1,95 0,33 1,68 18,13 ABBank 2017 2,03 0,58 1,05 18,25 ABBank 2018 1,88 0,08 0,61 18,32 ABBank 2019 1,72 0,98 0,88 18,45 ABBank 2020 1,50 0,96 0,82 18,57 ABBank 2021 2,06 1,29 1,1 18,61 67 ABBank 2022 2,88 1,04 0,96 18,68 Eximbank 2014 1,85 0,03 0,96 18,90 Eximbank 2015 1,86 0,03 1,71 18,64 Eximbank 2016 5,30 0,24 1,27 18,67 Eximbank 2017 2,27 0,55 0,60 18,82 Eximbank 2018 1,71 0,43 0,70 18,84 Eximbank 2019 2,52 0,52 0,62 18,94 Eximbank 2020 1,96 0,67 0,67 18,89 Eximbank 2021 1,80 0,58 0,87 18,93 Eximbank 2022 1,80 1,59 0,80 19,03 VIB 2014 2,51 0,65 3,19 18,21 VIB 2015 2,07 0,62 1,08 18,25 VIB 2016 2,58 0,54 1,02 18,46 VIB 2017 2,64 0,91 0,44 18,63 VIB 2018 2,52 1,58 0,69 18,75 VIB 2019 1,68 1,77 0,49 19,03 VIB 2020 1,46 1,90 0,56 19,32 VIB 2021 1,74 2,07 0,80 19,55 VIB 2022 1,79 2,47 0,56 19,65 SeABank 2014 2,86 0,11 0,64 18,20 SeABank 2015 1,60 0,11 0,22 18,26 SeABank 2016 1,83 0,11 1,11 18,45 SeABank 2017 0,91 0,24 0,78 18,64 SeABank 2018 1,57 0,35 0,67 18,76 SeABank 2019 2,31 0,70 1,88 18,87 68 SeABank 2020 1,86 0,75 0,63 19,01 SeABank 2021 1,65 1,23 0,98 19,17 SeABank 2022 1,60 1,75 0,78 19,26 PgBank 2014 2,26 0,12 1,29 17,08 PgBank 2015 2,75 0,17 1,34 17,02 PgBank 2016 2,47 0,49 1,17 17,03 PgBank 2017 1,99 0,22 2,17 17,19 PgBank 2018 2,46 0,42 2,38 17,21 PgBank 2019 1,89 0,24 2,33 17,27 PgBank 2020 2,44 0,47 1,10 17,40 PgBank 2021 2,98 0,64 0,65 17,52 PgBank 2022 2,60 0,82 0,90 17,71 BaoVietBank 2014 3,25 0,26 0,95 17,15 BaoVietBank 2015 1,20 0,28 0,91 17,24 BaoVietBank 2016 1,70 0,27 1,43 17,35 BaoVietBank 2017 2,70 0,24 1,87 17,70 BaoVietBank 2018 3,96 0,14 1,34 17,84 BaoVietBank 2019 3,98 0,14 1,52 17,91 BaoVietBank 2020 5,22 0,10 0,92 17,90 BaoVietBank 2021 2,63 0,10 2,78 18 BaoVietBank 2022 2,09 0,50 1,47 18,17 LienVietpostBank 2014 1,40 0,46 0,56 18,43 LienVietpostBank 2015 0,88 0,33 0,91 18,49 LienVietpostBank 2016 1,35 0,75 0,63 18,77 LienVietpostBank 2017 1,07 0,84 0,52 18,91 69 LienVietpostBank 2018 1,41 0,55 0,53 18,98 LienVietpostBank 2019 1,47 7,92 0,31 16,82 LienVietpostBank 2020 1,43 0,77 0,40 19,31 LienVietpostBank 2021 1,37 0,99 0,64 19,48 LienVietpostBank 2022 1,46 1,38 1,38 19,61 OCB 2014 2,85 0,56 1,43 17,48 OCB 2015 1,94 0,42 1,31 17,72 OCB 2016 1,51 0,61 0,86 17,97 OCB 2017 1,48 0,97 0,54 18,25 OCB 2018 2,29 1,76 1,69 18,42 OCB 2019 1,84 2,19 1,33 18,59 OCB 2020 1,69 2,99 1,43 18,59 OCB 2021 1,32 2,39 0,99 19,03 OCB 2022 2,23 1,81 0,90 19,08 VietABank 2014 2,33 0,23 1,86 17,24 VietABank 2015 2,26 0,20 1,60 17,55 VietABank 2016 2,14 0,16 1,21 17,93 VietABank 2017 2,68 0,15 0,91 17,98 VietABank 2018 2,40 0,17 1,24 18,08 VietABank 2019 1,18 0,27 0,87 18,15 VietABank 2020 2,30 0,38 1,58 18,28 VietABank 2021 1,89 0,65 0,88 18,43 VietABank 2022 1,53 0,85 0,10 18,47 70 APPENDIX Regression result of models: - Pooled OLS model - 71 - Fixed effects model - Random effects model 72 - Hauseman test - Lagrangian test 73 74