Determinants of bank profitability evidence from 16 listed commercial banks in vietnam

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY -oOo - PHAN THANH PHUONG ANH DETERMINANTS OF BANK PROFITABILITY: EVIDENCE FROM 16 LISTED COMMERCIAL BANKS IN VIETNAM GRADUATION THESIS MAJOR: FINANCE & BANKING CODE: 7340201 HO CHI MINH CITY, 2021 MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY -oOo - PHAN THANH PHUONG ANH DETERMINANTS OF BANK PROFITABILITY: EVIDENCE FROM 16 LISTED COMMERCIAL BANKS IN VIETNAM GRADUATION THESIS MAJOR: FINANCE & BANKING CODE: 7340201 SCIENCE INSTRUCTOR Ph.D DUONG THI THUY AN HO CHI MINH CITY, 2021 ABSTRACT The article focuses on using the CAMEL assessment framework to assess the business profitability of 16 commercial banks in Vietnam from 2010 to 2020 in order to evaluate the business performance of commercial banks in Vietnam Aims to identify the factors influencing commercial bank profitability and to assist banks in improving their operational and business capabilities At the same time, because research based on the CAMEL evaluation framework for bank profitability in Vietnam is still uncommon, the author decided to conduct the study "Determinants of banking profitability: evidence from 16 listed commercial banks in Vietnam" from 2010 to 2020 The author gathered 176 observed variables with dependent variables and independent variables using 16 commercial banks to represent the banking system in Vietnam The article employs three models to analyze the data The author continues to compare the fit of the three models with different dependent variables in order to provide the best model and improve the feasibility of the article results The findings indicate that the variables asset quality and management efficiency have no effect on bank profitability From this, it is clear that the variables capital ratio, capital to risk weighted assets, loans to deposit, loans to assets, bank size, annual GDP growth and inflation ratio all have a significant impact on bank profitability in banking operations and management These findings are in accordance with the data and with the findings of previous studies Based on the findings of this study, the author hopes that commercial banks will implement policies to promote better business activities Keywords: Commercial Banks, profitability, CAMEL framework, Vietnam DECLARATION This thesis is the result of the author's own research The article's analysis, data, statistics, and results are entirely accurate All of the information and materials in the article have clear origins, are properly cited, and are allowed to be published The author Phan Thanh Phuong Anh ACKNOWLEDGEMENTS First and foremost, I would like to express my heartfelt gratitude to the enthusiastic lecturers at Banking University of Ho Chi Minh City for their encouragement and assistance in gaining important fundamental knowledge throughout the time spent at school studying and completing the course In particular, I would like to express my heartfelt gratitude to my supervisor, Ms Duong Thi Thuy An, who has consistently supported and guided me in order for me to complete my graduation thesis completely Because of my limited practical experience, the content of my graduation thesis cannot avoid some flaws; however, I am looking forward to receiving additional advice from teachers in order to gain more experiences These experiences, I believe, will be extremely beneficial to my future development I sincerely thank you! CONTENTS LIST OF ABBREVIATIONS LIST OF FIGURES LIST OF TABLES CHAPTER INTRODUCTION 1.1 Problem statement 1.2 Research objectives 10 1.2.1 Overall objectives 10 1.2.2 Detail objectives 10 1.3 Research questions 10 1.4 Research subjects 11 1.5 Research scope 11 1.5.1 Research space 11 1.5.2 Research time 11 1.6 Research content 11 1.7 Methodology 11 1.8 Thesis structure 12 CHAPTER VIETNAM OF BANKING SYSTEM AND LITERATURE REVIEW 14 2.1 Vietnam’s banking system: An overview 14 2.2 Literature review 16 2.2.1 Theoretical review 16 2.2.1.1 Bank performance 16 2.2.1.2 Principles of banking performance evaluation and modeling 18 2.2.2 Empirical review 21 CHAPTER EMPIRICAL STRATEGY AND DATA 32 3.1 Empirical strategy 32 3.1.1 Hypothetical model 32 3.1.2 Research methodology 33 3.2 Data 34 CHAPTER RESULTS AND DISCUSSIONS 42 4.1 Descriptive statistics result of the variables 42 4.2 Correlation analysis 43 4.3 Regression analysis 46 CHAPTER CONCLUSION AND RECOMMENDATION 58 5.1 Conclusion and recommendation 58 5.2 Limitation of the thesis and future research direction 59 REFERENCES 61 LIST OF ABBREVIATIONS FEM Fixed-effects model HNX Ha Noi stock exchange HOSE Ho Chi Minh stock exchange NIM Net interest margin POLS Pooled Ordinary Least Square REM Random effects model ROA Return on assets ROE Return on equity SBV State bank of Vietnam LIST OF FIGURES Figure 2.1 Vietnam Banking system 14 Figure 3.1 Research process 33 LIST OF TABLES Table 3.1 List of variables 40 Table 4.1 Descriptive statistics of variables 43 Table 4.2 Correlation matrix analysis 44 Table 4.3 Variance inflation factor 45 Table 4.4 Empirical results of regression on ROE 47 Table 4.5 Empirical results of regression on ROA 48 Table 4.6 Empirical results of regression on NIM 49 Table 4.7 Empirical results of regression 52 Table 4.8 Conclusion on the determinants of bank profitability 57 50 Tables 4.4, 4.5, and 4.6 present the results of regression of factors affecting ROA, ROE, and NIM of banks on the entire sample collected using the random effects model (REM), fixed effect model (FEM), and pooled regression model (POLS) The estimation and testing results show that all three models have Prob < α = 1% The F-statistics in the three models REM, FEM, and POLS are all statistically significant at the 1% level This result implies that simultaneous regression coefficients of zero are rejected at the 1% significance level This means that all three models, REM, FEM, and POLS, fit and are statistically significant The empirical results of regression on ROE in table 4.4 have a coefficient of determination R2 of 0.286 for the POLS model, 0.274 for the REM model, and 0.280 for the FEM model This result implies that the independent variables in the POLS model explain approximately 28.6 percent of the change in the bank's ROE, while the independent variables in the REM model explain approximately 27.4 percent of the change in the bank's ROE In the FEM model, the independent variables account for approximately 28.0 percent of the change in the bank's ROE Table 4.5 shows that the empirical results of regression on ROA have a coefficient of determination R2 of 0.387 for the POLS model, 0.416 for the REM model, and 0.424 for the FEM model This result implies that the independent variables in the POLS model explain approximately 38.7 percent of the change in the bank's ROA, whereas the independent variables in the REM model explain approximately 41.6 percent of the change in the bank's ROA In the FEM model, the independent variables account for approximately 42.4 percent of the change in the bank's ROA The empirical results of regression on NIM in table 4.6 have a coefficient of determination R2 of 0.341 for the POLS model, 0.271 for the REM model, and 0.288 for the FEM model This result implies that the independent variables in the POLS model explain approximately 34.1 percent of the change in the bank's NIM, while the independent variables in the REM model explain approximately 27.1 percent of the 51 change in the bank's NIM In the FEM model, the independent variables account for approximately 28.8 percent of the change in the bank's NIM The author created this article using three models: POLS, REM, and FEM However, due to the unbalanced nature of our panel data, econometricians recommend the REM method as an efficient estimator for unbalanced panel data (Baltagi, 2005) As a result, the author conducted a test of the appropriateness of the three models in order to select the most appropriate model to improve the effectiveness of the article The author uses the Breush and Pagan Lagrangian test to determine the appropriateness of the POLS and REM models, and the Hausman test to test the fit between the REM and FEM models The Chi2 index for the ROE variable is 0.96, and the Prob > Chi2 index is greater than 5%, indicating that the POLS model is more appropriate than the REM model However, the Hausman test provides a choice for the REM model between the REM and FEM models with Chi2 equal to 7.62 and Prob > Chi2 greater than 5% From this, it can be seen that the POLS model best fits the ROE variable For the ROA variable, both tests offer the REM model because the Prob > Chi2 index in the Breush and Pagan Lagrangian tests is greater than 5% and the Prob > Chi2 index in the Hausman test is less than 5%, the Chi2 index being 10.43 and 9.88, respectively This has resulted in the REM model being selected as the most appropriate model The NIM variable, on the other hand when the POLS and REM models are compared, the test results show that the REM model is chosen because the Prob > Chi2 index is less than 5% and the Chi2 index is 65.2 However, the Hausman test results for the NIM variable show that the FEM model is more appropriate than the REM model, with the Prob > Chi2 index less than 5% and the Chi2 index of 22.61 From this, it can be seen that the FEM model best fits the NIM variable 52 Table 4.7 Empirical results of regression ROE (POLS) ROA (REM) NIM (FEM) Independent Variables Std Coef Err Std Coef Err Std Coef Err CAP 0.515 0.313 0.138*** 0.023 -0.023 0.157 CAR -1.129*** 0.336 -0.100*** 0.026 0.357* 0.184 AQ -0.561 0.594 -0.040 0.043 -0.244 0.280 ME 0.093** 0.035 0.006* 0.003 -0.011 0.028 LQ1 0.184*** 0.053 0.021*** 0.004 0.021 0.031 LQ2 -0.161 0.099 -0.018** 0.008 0.116** 0.055 SIZE 0.036*** 0.012 0.003*** 0.001 0.021** 0.010 GDP 0.425 0.625 0.017 0.043 0.579** 0.283 IFL -0.051 0.177 -0.009 0.013 0.589*** 0.098 c -0.550 0.252 -0.055 0.022 0.944 0.194 Obs 176 176 176 R2 0.286 0.416 0.288 Prob 0.000 0.000 0.000 Note: ***, **, and * denote significance levels at the 1%, 5%, and 10% respectively As can be seen, each dependent variable has a unique fitting model As a result, in the following presentation, the author will present the ROE variable in the POLS model, the ROA variable in the REM model, and the NIM variable in the FEM model to analyze 53 the influencing factors profitability of 16 listed commercial banks in Vietnam from 2010 to 2020 The capital ratio (CAP) and capital to risk weight assets (CAR) variables were used to assess the capital determinant It is clear that CAP has a positive and highly significant significant relationship with ROA indicator at significant levels of 1% However, there is no statistically significant relationship between CAP and ROE and NIM This demonstrates that banks with a lot of capital can increase their profits A large amount of capital allows the bank to pursue more investment and business opportunities, as well as diversify its investment portfolio Furthermore, banks with high capital can provide credit at a higher level, not rely as heavily on deposits, and avoid many other risks related to liquidity, credit reputation, and bankruptcy risk Overall, CAP has a positive and statistically significant effect on commercial bank profitability This finding is also consistent with previous research by PP.Athanasoglou et al (2006) and Phan Dai Thich (2017), Elisa Menicucci and Guido Paolucci (2016), Le Thanh Tam, Pham Xuan Trang & Le Nhat Hanh (2017) In contrast, the variable CAR has a negative effect on ROA and ROE, with a significant level of 1%, but a positive but insignificant effect on NIM This demonstrates that the higher the bank's CAR, the greater the risk that the bank can bear, thereby increasing the bank's business profit According to Beckmann (2007), CAR is regulated for regulatory hazards capital requirements in lowering moral; high capital is risk-averse and can result in lower profit due to un-expansion into potential investment opportunities with high risk This result of CAR is not intended by the author, but it is consistent with the previous research findings of Echekoba.F.N., Egbunike Chinadu Francis, and Ezu Gideon Kasie (2014) 54 The results for assets quality (AQ) show that the relationship between this variable and commercial bank profitability is unclear Furthermore, the regression coefficients in the model are not statistically significant This could be due to the fact that bad debts account for a relatively small proportion of commercial banks' total assets, so the impact of AQ on profitability indicators is unknown The ratio of bad debt to total assets, on the other hand, is an important indicator of a bank's business performance and ability to collect debts The relationship between the variable ME and the variables ROE, ROA is positive and has a high level of significance for the management efficiency variable (ME) ME, on the other hand, is not statistically significant with the NIM variable This finding is consistent with previous research by Jonathan Batten and Xuan Vinh Vo (2019) As a result of improving management efficiency, business activities will be more efficient, resulting in higher business profits for banks when revenue growth exceeds cost growth The liquidity factor includes the variables loans to deposit (LQ1) and loans to assets (LQ2), which are used to assess the impact of liquidity on commercial bank profitability According to the regression results table of the profitability indicators, the variable LQ1 is positive and statistically significant at 5% for ROE and 10% for ROA Despite having a positive relationship with NIM, LQ1 is not significant in the model According to Abdulazeez et al (2017) and Khemaies Bougatef (2017), the ability to convert when a customer's deposit is used as a source of lending, combined with the substantial profit from this lending activity, has a significant impact on commercial banks' business profits Lending activities, particularly in the context of commercial banks in Vietnam, are the main source of profits for banks, particularly the use of leverage, using capital mobilized from society as a resource This result is consistent with the findings of the research papers Abdulazeez YH Saif-Alyousfi, Asish Saha, Rohani Md-Rus (2017) a study of the 55 profitability of Saudi Commercial Banks 20 of the 24 listed and unlisted banks from 2000 to 2014, Khemaies Bougatef (2017) analyzing bank profitability on the basis of a balanced panel of ten commercial banks in Tunisia from 2003 to 2014, loan to total deposit ratio (LQ1) has a positive and significant impact on ROA and NIM As a result, the ability of transferrin deposit will increase in loan amount, influencing the bank's profitability The regression results for the variable LQ2 show that LQ2 has a positive relationship with NIM with a significance level of up to 5% LQ2 has a negative relationship with ROA and ROE, but the significance level of 5% only appears in the relationship between LQ2 and ROA; the relationship between LQ2 and ROE is not significant in this model As can be seen, this result is comparable to previous studies conducted by Saira javaid et al (2011), Mohammad Morshedur Rahman, Md Kowsar Hamid, and Md Abdul Mannan Khan (2015) This implies that making more loans increases the likelihood of a higher return Furthermore, higher lending rates generate higher income, with NIM having a significant impact It is clear from the model that the relationship between variable bank size (SIZE) and profitability indicators (ROE, ROA, NIM) is positive and has a high significance In line with expectations, Kosmidou and colleagues (2002), Alper et al (2011), and Khrawish (2011) discover a positive relationship between bank size and profitability indicators Banks are becoming increasingly larger, which has an impact on a variety of activities such as investment opportunities, portfolio diversification, reputation, and accessibility Finally, bank size has a hugely positive impact on bank profitability The expected sign of bank size in Vietnam is still unknown; in my research, bank size was found to have a positive effect on the dependent variables but was not significantly related to bank profitability Growth in annual gross domestic product (GDP) is positive and significant at the 5% level for the NIM variable, as expected GDP has a positive but non-significant 56 relationship with the variables ROA and ROE in this model In line with expectations, studies by Valentina Flamini, Calvin McDonald, and Liliana Schumacher (2009) for 389 banks in 41 Sub-Saharan Africa (SSA) countries from 1998 to 2006; Nicolae Petria, Bogdan Capraru, and Iulian Ihnatov (2015) for evidence from EU 27 banking systems from 2004 to 2011; and Nimesh Salike (2017) for the determinants of Asian banks' profitability of 947 banks from 12 Asian economies from 2001 to 2015 cross-country Asian countries has a positive and significant impact on bank profitability In most studies, this variable is regarded as an important macroeconomic factor The result implied that higher GDP growth is associated with higher profits, but the determinant is beyond bank management's control At the 1% significance level, the regression results for the inflation rate variable (IFL) show that IFL has a positive and significant relationship with NIM In contrast, IFL has a negative relationship with ROE and ROA, but it is insignificant in this model The regression results are as expected by the author This finding is consistent with Phan Dai Thich (2017) with the study of the impact of bank-specific and macroeconomic variables on the profitability of Vietnam-listed banks from 2007 to 2016 Because of an improvement in forecasting inflation, the inflation ratio, which is presented as the sign for this macroeconomic factor, is positive According to this, revenue can be generated faster than costs by correctly predicting inflation 57 Table 4.8 Conclusion on the determinants of bank profitability Variables Abbreviations CAP Expected signs + Actual signs + Hypothesis accepted/rejected Accepted + on NIM Capital CAR + - on ROA Rejected - on ROE Asset quality Management efficiency AQ - Unclear No conclusion ME - + Rejected LQ1 + + Accepted LQ2 + + Accepted SIZE +/- + Accepted GDP + + Accepted IFL + + Accepted Liquidity Bank size Growth in gross domestic product Inflation 58 CHAPTER CONCLUSION AND RECOMMENDATION The conclusion for Chapter will be presented in this final chapter, as well as some solutions to help banks increase their profitability Furthermore, limitations and future research directions for this thesis will be presented 5.1 Conclusion and recommendation The article produced a desirable research result after chapters of analysis The article investigated the factors influencing the profitability of commercial banks in Vietnam from 2010 to 2020 using 12 research variables, dependent variables, and independent variables Among 12 research variables, there are variables are internal variables, while the remaining are external, namely bank size, GDP, and inflation ratio Following the tests and analysis of the model in chapter 4, the model has suitable independent variables that affect the bank's overall profitability In this case, there are two independent variables that have a significant impact on bank profitability and can help banks improve their profits if they focus on developing these two factors Based on the study's findings, the author has proposed some solutions to help commercial banks in Vietnam increase their profits To begin, the research results show that loans to deposit and loans to assets have the same impact, implying that it is likely to increase the bank's profits To increase profits, the author proposes that commercial banks use financial leverage and optimize their money sources in lending and investment activities However, if the allocation is not reasonable, banks may face risks when using short-term capital to make long-term loans Ensure that the interest rate differential is reasonable, resulting in maximum profit for the bank Furthermore, during the complicated Covid-19 epidemic, banks should have an appropriate business plan in place to avoid any unfortunate events Second, for the variable bank size, the results show that bank size has a positive impact on commercial bank profitability A bank with a large capital base, a competitive 59 advantage, and a strong credit reputation will be more popular and trusted, allowing the bank's business activities to expand and generate higher profits According to the marketing strategy, one of the factors that banks should deploy and expand is location Because a bank has many branches and large transaction offices, it can help the bank increase public awareness of its brand; additionally, the variety of locations improves convenience Increase customers’ benefits will increased their satisfaction, lead to more business opportunities for the bank, and assistance in improving profitability Furthermore, in the 4.0 era, banks should promote the digital banking system, which is suitable and adaptable to market needs Third, in order to maximize the positive impact of the macroenvironment, the author suggests that banks should increase their service activities during periods of good economic development while decreasing business activities during periods of poor economic development The market economy has deteriorated, allowing losses to be avoided and credit risks to be reduced Furthermore, banks should anticipate the inflation period in advance, allowing them to avoid the risk of declining profits At the same time, take advantage of the opportunity to increase your profit potential 5.2 Limitation of the thesis and future research direction Although the article's results are as expected by the author, it still has many limitations Regarding the research object, the article only takes 16 commercial banks representing the overall commercial banks in Vietnam from 2010 to 2020 because the market economy is experiencing many fluctuations at that time, resulting in some banks having unstable business activities As a result, the author can only choose 16 banks with the most stable business activities to represent Vietnam's commercial banking system Regarding the data source, the original data was of poor quality, which had a significant impact on the results Despite the author's efforts to obtain audited financial statements from commercial banks However, some information is difficult to obtain and may differ from reality 60 Based on the limitations stated above, the author intends to conduct additional research for this article in order to improve it and make it a reference value for the future development of the commercial banking system in Vietnam The article will broaden the scope of its research object in order to diversify the samples and improve the feasibility of the research findings It is proposed to broaden and investigate the impact of factor (S)ensitivity in the CAMELS assessment framework on the profitability of Vietnamese commercial banks Furthermore, in order to improve the feasibility of the research findings, the study should include the global economic crisis factor in order to clearly examine the impact of the economic crisis on the profitability of commercial banks 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(3) What solutions aid in increasing the profitability of commercial banks in Vietnam? 11 1.4 Research subjects The 16 listed commercial banks in Vietnam. .. business profitability of 16 commercial banks in Vietnam from 2010 to 2020 in order to evaluate the business performance of commercial banks in Vietnam Aims to identify the factors influencing commercial. ..MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY -oOo - PHAN THANH PHUONG ANH DETERMINANTS OF BANK PROFITABILITY: EVIDENCE FROM 16 LISTED COMMERCIAL