MINISTRY OF EDUCATION AND TRAINING HO CHI MINH UNIVERSITY OF BANKING GRADUATION THESIS FACTORS AFFECTING CAPITAL ADEQUACY RATIO OF VIETNAMESE COMMERCIAL BANKS Major: Finance – Banking Code: 7 34 02 01 TRINH BAO NGOC HO CHI MINH CITY, 2023 MINISTRY OF EDUCATION AND TRAINING HO CHI MINH UNIVERSITY OF BANKING GRADUATION THESIS FACTORS AFFECTING CAPITAL ADEQUACY RATIO OF VIETNAMESE COMMERCIAL BANKS Major: Finance – Banking Code: 7 34 02 01 Student’s name: TRINH BAO NGOC Student’s ID: 030135190375 Class: HQ7 – GE06 SUPERVISOR DR. LE HA DIEM CHI HO CHI MINH CITY, 2023 i ABSTRACT The thesis “Factors affecting capital adequacy ratio of Vietnamese commercial banks” aims to specify the bank-specific factors and macroeconomic factors as they affect the capital adequacy ratio (CAR) of commercial banks in Vietnam. The secondary panel dataset is collected from annual reports of 29 operating commercial banks in Vietnam in the timespan of thirteen years from 2010 to 2022. The author uses regression models such as Pooled-OLS, FEM, REM with the assistance of Microsoft Excel office software program and STATA 15 statistical software program to examine the significant level of each instrumental variable in the database.
The FEM model chosen for the research appears to have autocorrelation, heteroscedascity and endogenous phenomenons so by applying GMM method, the author manages to find a statistical significant relationship between seven out of nine determinants and CAR. According to the study result, leverage ratio (LEV) is proven to have a positive impact on CAR. Conversely, profitability (ROA), non-performing loans (NPL), loan loss reserves (LLR), liquidity (LTD), deposite rate (DEP), and inflation rate (INF) have a negative effect on CAR. Keywords: Capital Adequacy Ratio, Commercial Banks, Vietnam.
ii DECLARATION My name is Trinh Bao Ngoc. My student ID is 030135190375, and I am enrolled at the Ho Chi Minh University of Banking in the HQ7-GE06 class. I hereby state that the thesis topic for my Finance - Banking major is "Factors affecting capital adequacy ratio of Vietnamese commercial banks" and that Dr. Le Ha Diem Chi is my supervisor.
Except for the properly cited citations in the thesis, the data and research findings in this thesis are entirely original and have never been published or made by anyone else. Ho Chi Minh City, August , 2023 Author Trinh Bao Ngoc iii APPRECIATION First and foremost, I would like to thank my research supervisor, Dr. Le Ha Diem Chi. Without her assistance and dedicated involvement in every step throughout the process, this paper could have never been accomplished.
I am extremely grateful to her for supporting and understanding me during the past time. Additionally, I want to express my gratitude to the professors who have taught me a lot over the course of four years at the university. I appreciate the chance they gave me to study and acquire knowledge at Ho Chi Minh University of Banking. I owe a huge debt of gratitude to all of my lecturers for their education over the past four years, as finishing my dissertation required more than just academic help.
Finally, at the very end of this journey, I thank all my family and friends, especially the father whom I hold dear, exceed blood bound is his nurture and care, hidden in time is his silent declare, through ups and downs he’s been by side, and through it all he’ll be my guide. Ho Chi Minh City, August , 2023 Author Trinh Bao Ngoc iv TABLE OF CONTENTS ABSTRACT. iii LIST OF ACRONYMS. ix LIST OF TABLES AND FIGURES.
REASONS FOR CHOOSING THE TOPIC. RESEARCH SUBJECT AND SCOPE .7 CHAPTER 2: LITERATURE REVIEW. BASIC CONCEPT OVERVIEW. The concept of capital adequacy ratio.
The measurement of capital adequacy ratio. FACTORS AFFECTING CAPITAL ADEQUACY RATIO. Bank-specific factors. PREVIOUS STUDIES OVERVIEW.
MEASUREMENT OF RESEARCH VARIABLES. Capital adequacy ratio (CAR). Non-performing loans (NPL). Loan loss reserves (LLR).
Non-performing loans (NPL). Loan loss reserves (LLR). Standard Ordinary Least Squares Model (Pooled – OLS). Fixed Effects Model (FEM).
Random Effects Model (REM). Feasible Generalized Least Squares (FGLS). Generalized Method of Moments (GMM). RESEARCH RESULTS AND DISCUSSION.
DESCRIPTIVE STATISTICAL ANALYSIS. ESTIMATING THE REGRESSION MODELS AND TESTING THE REGRESSION HYPOTHESES. Estimating the Pooled – OLS, FEM, REM models. Comparing Pooled – OLS model and FEM model.
Comparing FEM model and REM model. Comparing Pooled – OLS model and REM model. TESTING FOR MODEL DEFECTS. OVERCOMING THE RESEARCH MODEL DEFECTS.
Feasible generalized least squares (FGLS). Generalized method of moments (GMM). SUMMARIZE AND DISCUSS RESEARCH RESULTS. Non-performing loans (NPL).
Loan loss reserves (LLR) .58 CONCLUSION OF CHAPTER 4. CONCLUSIONS AND RECOMMENDATIONS. LIMITATION AND FUTURE DIRECTION FOR THE RESEARCH 64 viii 5. Future direction for the research .v ix LIST OF ACRONYMS No.
Acronym Meaning 1 CAR Capital Adequacy Ratio 2 DEP Deposit Rate 3 FEM Fixed Effects Model 4 FGLS Feasible Generalized Least Squares 5 GDP Economic Growth 6 GMM Generalized Method of Moments 7 INF Inflation Rate 8 LEV Leverage Ratio 9 LLR Loan Loss Reserves 10 LTD Liquidity 11 NPL Non-performing Loans 12 Pooled-OLS Standard Ordinary Least Squares Model 13 REM Random Effects Model 14 ROA Profitability 15 SIZE Bank Size x LIST OF TABLES AND FIGURES LIST OF TABLES Table 3. Research measurement and hypotheses summary .1 Summary of descriptive statistics .2 Correlation coefficients between research variables. Estimated results with Pooled – OLS, FEM, REM models. Estimated result with FGLS model.
Estimated result with GMM model. Summary of research model results. 51 LIST OF FIGURES Figure 3. Relationship between CAR and ROA.
Relationship between CAR and LEV. Relationship between CAR and NPL. Relationship between CAR and LLR. Relationship between CAR and LTD.
Relationship between CAR and DEP. Relationship between CAR and INF. REASONS FOR CHOOSING THE TOPIC The Covid-19 pandemic from 2019 to 2022 has negatively impact the economic health of the world due to long quarantine period, many production lines have been disrupted, transportation prices have skyrocketed, and the cost of raw materials has escalated leading to many businesses closing their businesses. Not only the economic sector suffered serious damage, health and education sector with other key industries also faced difficulties, putting pressure on the state budget and draining the financial reserves of many enterprises.
In that context, the Russia-Ukraine conflict starting from 2020 and the strong economic sanctions of the West against Russia have added fuel to the fire, creating a comprehensive and profound negative impact on the world economy in general and Vietnamese economy in particular. These impacts include: difficulties in commercial trade, investment, and agricultural production, delays in supply chain of fuels for production, increase in logistics costs because of high oil prices, and lastly an unavoidable escalation in inflation (Ngoc Dien Nguyen, 2023). Apart from the stated challenges, the intense competitive environment among banks also takes part in shrinking market share of banking sector, leading to many quick but risky decisions such as raising deposit interest rates, reducing lending rates, and even choosing customers that are in the sub-standard debt group. These high-risk investment decisions can easily cause future bankruptcy.
Chiu et al (2009) concluded in their study that capital adequacy and corporate governace are negatively correlated with the bankruptcy of 36 Taiwanese commercial banks. Because of the important role of commercial banks as financial intermediary, a spillover effect can quickly spread bankruptcy in one area to another due to the vast economic globalization (Kawai et al, 2005), especially when spillovers are highly local and concentrated in the non-commercial and service sectors (Bernstein et al, 2 2019). A study on Tunisian banks showed empirical evidence of regulations impact on promoting bank capitalization, the research also demonstrates the risk-taking behavior of Tunisian banks as they often exceed minimum requirements and are fully capitalized to maintain an appropriate level of capital commensurate with aggregate risk (Chakroun & Abid, 2016). In order to improve risk management capacity and strengthen resilience to consecutive shocks from the economy, the State Bank of Vietnam issued Decision No.
457/2005/QD-NHNN (Capital adequacy standards of Basel I ) and Circular No. 41/2016/TT-NHNN (Capital adequacy standards of Basel II) with a minimum ratio of 8% to meet the requirements of the Basel accord. According to the Project “Restructuring the system of credit institutions associated with bad debt settlement in 2021 – 2025”, with the general trend to ensure the safety of the commercial banking system, capital adequacy ratio (CAR) is not only required to increase to 10- 11% by 2023 and 11%-12% by 2025, but also required to calculate equity and risky assets in accordance with Basel II standards, then the net interest margin of commercial banks will increase, business activities will be more effective. At the present, Vietnamese commercial banks must increase their own Tier 1 capital and Tier 2 capital to improve CAR to meet Basel II requirements (The State Bank of Vietnam, 2005, 2016).
Therefore, the author chooses the topic "Factors affecting capital adequacy ratio of Vietnamese commercial banks" to study the bank-specific factors and macroeconomic factors affecting the CAR in the case of Vietnamese commercial banks. The study result will serve as an useful reference for bank managers and financial researchers when they search for appropriate policies to improve CAR and stabilize the operation of Vietnamese banking system. General objectives 3 The overall objective of this research is to specify, measure and analyze the determinants of CAR in Vietnamese commercial banks, thereby offering recommendations based on the study's findings to enhance CAR and safeguard the operational security and future competitiveness of Vietnam's banking system in general and Vietnamese commercial banks in particular. Specific objectives The specific objectives of this research are: Specify and analyze factors affecting CAR of Vietnamese commercial banks.
Determine the impact level and direction of the influential factors on CAR of Vietnamese commercial banks. Based on the theoretical foundation and prior research models, thereby building the most suitable research model. Propose appropriate recommendations to enhance the CAR and improve the operational efficiency of Vietnamese commercial banks. RESEARCH QUESTIONS To achieve the research goals, the thesis focuses on answering the following research questions: What are the determinants of CAR in Vietnamese commercial banks? How do these determinants affect CAR of Vietnamese commercial banks? Which model and method used to measure the chosen CAR determinants? What policy suggestions are proposed to enhance CAR of Vietnamese commercial banks? 1.
RESEARCH SUBJECT AND SCOPE 1. Research subject The research subject of this study is the determinants of CAR in Vietnamese commercial banks. Research scope Scope of spatial research: The research secondary dataset was collected from the annual reports of 29 operating commercial banks in Vietnam. Scope of time research: The research secondary dataset was collected in a period of thirteen years between 2010 and 2022.
RESEARCH CONTRIBUTION This reseach result can be used as references to help bank managers specify and analyze the impact of bank-specific and macroeconomic determinants on the CAR, thereby making timely decisions to enhance CAR and safeguard the operational security and future competitiveness of these banks. The author's thesis can also serve as a reference for readers who are interested in learning about CAR of Vietnamese commercial banks, thereby enriching the scientific treasure about CAR, using Vietnamese data. RESEARCH GAP Up to now, there have been many domestic and foreign studies on CAR, but most of the research papers in Vietnam have taken data from about 22-25 commercial banks during a short period of time (usually 7-10 years). The lack of studies using big data may lead to less accurate and incomplete research results.
Therefore, for stronger evidence, the author uses the data of 29 commercial banks for 13 years from 2010 to 2022.