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Tiêu đề Factors Affecting the Profitability of Commercial Banks in Vietnam
Tác giả Cao Nguyễn Ngọc Giàu
Người hướng dẫn Ph.D. Ngô Văn Tuấn
Trường học Ho Chi Minh University of Banking
Chuyên ngành Finance – Banking
Thể loại University Graduation Thesis
Năm xuất bản 2024
Thành phố Ho Chi Minh City
Định dạng
Số trang 109
Dung lượng 2,81 MB

Cấu trúc

  • 1.1. REASON FOR CHOOSING TOPIC (12)
  • 1.2. RESEARCH OBJECTIVE (14)
    • 1.2.1. General research objective (14)
    • 1.2.2. Specific research objective (14)
  • 1.3. RESEARCH QUESTION (14)
  • 1.4. SUBJECT AND SCOPE OF RESEARCH (15)
    • 1.4.1. Subject of research (15)
    • 1.4.2. Scope of research (15)
  • 1.5. RESEARCH METHOD (16)
  • 1.6. CONTRIBUTION (17)
  • 1.7. THESIS LAYOUT (17)
  • CHAPTER 2: THEORETICAL BASIS AND RELATED RESEARCH (19)
    • 2.1. OVERVIEW OF COMMERCIAL BANKS (19)
      • 2.1.1. Definition (19)
      • 2.1.2. Main operationns Commercial Banks (19)
    • 2.2. OVERVIEW COMMERCIAL BANKS’S PROFITABILITY (20)
      • 2.2.1. Definition (20)
      • 2.2.2. Indicators to measure the profitability of Commercial Banks (20)
    • 2.3. FACTOR AFFECTING COMMERCIAL BANKS’S (23)
    • 2.4. RELATED RESEARCH (31)
      • 2.4.1. Oversea research (31)
      • 2.4.2. Vietnamese research (33)
    • 2.5. RESEARCH GAP (36)
  • CHAPTER 3: RESEARCH METHOD (18)
    • 3.1. RESEARCH PROCESS (39)
    • 3.2. SELECTION AND DESIGN OF RESEARCH MODEL (40)
    • 3.3. DESCRIPTION OF RESEARCH VARIABLES AND (41)
      • 3.3.1. Dependent variable (41)
      • 3.3.2. Independent variable (42)
    • 3.4. DATA ANALYSIS (49)
    • 3.5. RESEARCH METHODS AND TESTING (50)
  • CHAPTER 4: RESEARCH RESULTS AND DISCUSSION (53)
    • 4.1. DESCRIPTIVE STATISTICS (53)
    • 4.2. CORRELATION ANALYSIS (56)
    • 4.3. REGRESSION RESULTS OF DEPENDENT VARIABLE ROA 47 1. Summary of regression analysis results with the dependent (58)
      • 4.3.2. Select the appropriate regression model for the ROA variable (60)
      • 4.3.3. Fix model defects using the FGLS method (63)
    • 4.4. REGRESSION RESULTS OF DEPENDENT VARIABLE ROE 53 1. Summary of regression analysis results with dependent variable (64)
      • 4.4.2. Test model selection (67)
      • 4.4.3. Overcoming model defect using FGLS method (69)
    • 4.5. DISCUSS RESEARCH RESULT (72)
  • CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS (18)
    • 5.1. CONCLUSION (79)
    • 5.2. POLICY SUGGESTIONS (80)
      • 5.2.1. Management suggestions for commercial banks to improve (80)
      • 5.2.2. Suggestions for the government and State Bank of Vietnam (81)

Nội dung

The results are as follows: For the ROA model, out of 11 factors, there are 5 factors that affect profits in banks in the same direction equity size, bank size, outstanding loans, non-in

REASON FOR CHOOSING TOPIC

The banking sector is one of the major sectors in VietNam and it plays a central role in the operation of the economy The banking sector fulfills an important economic function in providing financial intermediation by converting deposits into productive investments Banks are the providers of funds needed for investment High profits in banking sector always leads to financial stability If banking activities are poor, it will negatively affect economic growth and development, possibly leading to a crisis Thus, it can be seen that commercial banks are still the main channel to attract deposits and provide credit to individual and corporate customers In addition, commercial banks are also the place to implement the monetary policy of the central bank, supporting the central bank to stabilize the economy (Siddiqui and Shoaib

2011) Therefore, according to (Truong Quang Thong 2009), analyzing the profitability of commercial banks is necessary to evaluate the efficiency of the bank's business operations and propose solutions to improve profitability

Therefore, banks must constantly improve operational efficiency and service quality to ensure the safety of the banking system and enhance competitiveness Given the above situation, a bank that wants to survive and develop sustainably must operate effectively, so profit is the top concern Profitability is considered a solid foundation that helps banks innovate and operate more effectively This is not only a source of accumulated finance to expand production but also an important source of finance to fulfill financial obligations to the State, increase national income and encourage workers (To Ngoc Hung and Nguyen Duc Trung 2011) Reviewing and evaluating factors affecting profits not only helps managers and bank executives find timely and reasonable solutions to improve, consolidate and increase profits in the operations of Vietnamese commercial banks but also serves the decision-making of existing investors, potential investors, customers as well as the State Bank and other functional agencies Therefore, study the determinants of bank profitability is more important to the economy Bank specific determinants are more important to among these factors

In terms of academics, the impact of factors on the profits of commercial banks is one of the topics that has been exploited and researched in many countries around the world In Bangladesh, Gazi et al (2022) conducted a study with 26 banks in the country by the fixed-effect regression model to explore the impact of the bank’s specific variables and macroeconomic variables along with the banks’ variables on the banks’ profitability The banks that performed better during the pre-pandemic period of COVID-19 also performed better during the pandemic period of COVID-

19 The outcome of this study will help bank authorities detect loopholes and take preventive measures that can improve their profitability during a crisis period like COVID-19 In Vietnam, the study by (Bui Dan Thanh and Tran Minh Tam 2021) used variables representing profitability, respectively ROA, NIM, combined with micro and macro factors to find out the level of influence of factors on the profitability of commercial banks in Vietnam with different research contexts, thereby promoting banking activities from policy implications for the government However, the gap in most related studies is that the use of explanatory variables is quite small and will not be able to comprehensively demonstrate the multidimensional impact of variables on the model The authors have limitations in the ability to access the number of banks and time, the limited research model method can also cause bias in the research results affecting the ability to explain the variables set out in the research expectations From the gaps that related studies have not been able to do, the author conducts empirical research using explanatory variables as well as a more appropriate and comprehensive sample size with the topic "Factors Affecting the Profitability of Commercial Banks in Vietnam".

RESEARCH OBJECTIVE

General research objective

The thesis analyzes factors affecting the profitability of Vietnamese Commercial Banks in the period 2013 - 2023 Based on the research results, the author recommends several the main implications policy to support the improvement of the profitability of Vietnamese Commercial Banks.

Specific research objective

Firstly, identify the factors and their impact on the profitability of Vietnamese commercial banks

Secondly, identify a model to measure the impact of these factors on the profitability of Vietnamese commercial banks

Thirdly, discuss and propose some implications to improve the profitability of Vietnamese commercial banks

RESEARCH QUESTION

The banking system is increasingly asserting its necessary role in the economy

To have a developed economy, the banking system must also be strong Therefore, banks need to increase their competitiveness and profitability in the context of international integration

On that basis, the thesis wishes to clarify the following research questions:

- What factors affect the profits of Vietnamese commercial banks? In what direction?

- Which model is suitable to measure the level of influence of the factors?

- What is the significance of improving the profits of Vietnamese commercial banks?

SUBJECT AND SCOPE OF RESEARCH

Subject of research

The research object is the system of criteria for evaluating profits and factors affecting profits in banking business activities.

Scope of research

Up to now, Vietnam has a total of 31 commercial banks in operation, but in this study, the author uses secondary data of 20 commercial banks listed on the Vietnam Stock Exchange Of these, these 20 commercial banks, specifically joint- stock commercial banks, do not have state capital because the capital scale and total assets of these commercial banks are too large compared to the remaining commercial banks If combined, it will be difficult to draw appropriate policy implications According to the form of ownership, these 20 commercial banks are all within the scope of joint-stock commercial banks managed and operated by the State Bank And these 20 joint-stock commercial banks represent commercial banks in Vietnam Information and data on commercial banks are publicly announced and easily accessible Researching these 20 commercial banks can help increase the feasibility and effectiveness of the research Specifically, the 20 joint stock commercial banks include the following banks:

Vietnam International Commercial Joint Stock Bank (VIB), Vietnam Joint Stock Commercial Bank for Industry and Trade (BVB), An Binh Commercial Joint Stock Bank (ABB), Vietnam Prosperity Joint Stock Commercial Bank (VPB), Kien Long Commercial Joint Stock Bank (KLB), Tien Phong Commercial Joint Stock Bank (TPB), Vietnam Technological and Commercial Joint Stock Bank (TCB), Saigon Thuong Tin Commercial Joint Stock Bank (STB), Southeast Asia Commercial Joint Stock Bank (SSB), Vietnam Maritime Commercial Joint Stock Bank (MSB), Saigon Commercial Joint Stock Bank (SHB), Military Commercial

Joint Stock Bank (MBB), Orient Commercial Joint Stock Bank (OCB), Lien Viet Post Joint Stock Commercial Bank (LPB), Vietnam Export Import Commercial Joint Stock Bank (EIB), Ho Chi Minh City Urban Development Joint Stock Commercial Bank (HDB), Bac A Commercial Joint Stock Bank (BAB), Asia Commercial Joint Stock Bank (ACB), Viet A Commercial Joint Stock Bank (VAB), Nam A Commercial Joint Stock Bank (NAB)

The thesis research is in the period 2013-2023 The thesis chooses this period because it can be considered a period with many fluctuations in the financial system in the world as well as in the country In the period 2016-2020, institutions on restructuring the economy in general and the financial market in particular have been built, supplemented and completed Resolution 24/2016/QH14 on the Economic Restructuring Plan for the period 2016-2020 of the National Assembly, including the restructuring of credit institutions This is the time frame for the banking industry to implement reform policies, improve the financial situation, and speed up the process of handling bad debts From the above fluctuations, the period reflecting data related to the profits of Vietnamese commercial banks is a suitable time period to conduct research.

RESEARCH METHOD

The thesis combines both qualitative and quantitative methods

Qualitative research method: The thesis is based on available data collected from many different sources, creating comparison tables and drawing charts From there, comments and evaluations of the research content are made to determine the factors affecting the profitability of Vietnamese commercial banks

Quantitative research method: The research mainly uses quantitative analysis

Specifically, regression analysis on panel data using Pooled OLS, REM, FEM methods to estimate the most suitable equation for the set of observed results of dependent and independent variables Next, use F test and Hausman test to select the appropriate model for the study (F test OLS and FEM, Hausman test FEM and REM) The final step is to use the FGLS method to overcome model defects such as multicollinearity, autocorrelation, and heteroscedasticity (if any) Thereby, the final suitable model is proposed for the topic of factors affecting the profitability of commercial banks.

CONTRIBUTION

The research results of the topic contribute more empirical evidence on the factors affecting the profits of Vietnamese commercial banks, including both micro and macro factors In practice, it contributes to providing policy implications for managers and bank leaders to identify factors and the level of impact of each factor on profits in the bank's business operations, and to detect shortcomings in the bank's business operations From there, reasonable and effective decisions can be made to help commercial banks improve their operational efficiency, contributing to increasing profits for banks.

THESIS LAYOUT

The structure of the thesis consists of 5 chapters with the following basic contents

Chapter 1: Introduction to the research overview

This chapter aims to introduce the general content of the research topic, the author's reasons for choosing the topic, the research objectives of the thesis, the research questions, the research objects and scope, the research method, the contribution of the thesis and the structure of the thesis

Chapter 2: Theoretical basis and research overview

The thesis will provide an overview of the definitions and measurements of variables affecting profits In this chapter, the thesis will review previous studies and comment on the factors that will be selected in the research model

The author will develop research hypotheses and explain the variables in the model, present the research process as well as collect and process data, and research methods in this chapter

Chapter 4: Analysis of research results

This chapter presents the results of the thesis from the estimation methods after the author ran the software, then analyzed the data to clarify the meaning of the coefficients and the final results of the model after overcoming the shortcomings

Chapter 5: Conclusion and policy implications

Summarizing all the issues and research results, the author will give policy implications suitable for the purpose of improving the profitability of commercial banks in Vietnam In addition, chapter 5 also presents the limitations of the study and future research directions

In chapter 1, the author has presented a summary of the issues that need to be researched as well as the research methods that the author will conduct in this thesis The author has raised the basic issues of the specific topic such as the reason for choosing the topic, research objectives, research methods, research objects and scope, research methods and policy implications This is considered the premise for completing the following chapters.

THEORETICAL BASIS AND RELATED RESEARCH

OVERVIEW OF COMMERCIAL BANKS

Commercial banks, according to (S Rose, Sylvia C Hudgins 2004) are also regarded as business groups that operate for the purpose of maximizing profits while minimizing risk Commercial banking is a type of bank that deals directly with companies, corporations, economic organizations, and individuals, by receiving deposits and savings, and then using that capital to lend, discount, provide payment facilities and provide banking services to the aforementioned entities Commercial banking is a type ofbank with large numbers and is common in the economy

According to (Nguyen Xuan Hoang 2010), Joint Stock Commercial Banks have

Capital activities: This is the main activity that creates the main source of operating capital for Joint Stock Commercial Banks This activity includes: Equity activities, capital mobilization activities and other capital creation activities The most important activity is capital mobilization, this activity aims to ensure capital for lending and payment activities There are many ways that banks can mobilize capital such as: receiving non-term deposits, term deposits, savings deposits and other types of deposits; issuing deposit certificates, promissory notes, bonds to mobilize capital domestically and internationally; borrowing capital from domestic and foreign credit institutions and financial institutions; short-term loans from state banks in the form of refinancing

Capital use activities: To meet the capital needs of economic entities and bring profits to commercial banks, this activity is very important and includes the following activities: Investment in basic construction and asset purchase, provisioning, credit granting activities, investment activities

Intermediary activities: Commercial banks, as intermediaries, perform a number of tasks on behalf of customers under the authorization of customers to receive service fees such as payment services, treasury services and other services Guarantee services, foreign exchange trading services, trust services, agents, etc.

OVERVIEW COMMERCIAL BANKS’S PROFITABILITY

According to (S Rose, Sylvia C Hudgins 2004) profitability is an aim that banks are interested in, since high income would assist banks to conserve capital, expand market share, and attract investment capital.

According to (Sakshi Varshney 2000) “The profitability of a joint stock commercial bank is the ability of a bank to generate income and earn profits in a sustainable manner over time The profitability of a joint stock commercial bank depends on many factors, including its business model, risk profile, market conditions, and the regulatory environment Joint stock commercial banks generate profits primarily through their lending activities, which include providing loans and advances to borrowers at interest rates higher than their cost of funding In addition, they may also earn income from fee-based services such as maintaining accounts, using ATMs, and bank transfers, etc Banks may also engage in investment banking and other business activities to generate profits However, a bank’s profits are subject to various risks, such as credit risk, market risk, and operational risk Therefore, effective risk management practices are essential to ensure sustainable profitability and long-term success Overall, a commercial bank’s profit potential is determined by its ability to effectively manage these risks and adapt to changing market conditions while maintaining a competitive advantage in its core business areas.”

2.2.2 Indicators to measure the profitability of Commercial Banks

Profitability is an indicator that can be calculated in absolute or relative terms through ratios Bank profitability is measured in many different ways and financial ratios are considered the most commonly used method (Mamatzakis and Remoundos

2003) Financial ratios allow for the analysis and interpretation of bank financial data and accounting information From there, the performance of the bank can be assessed Furthermore, financial ratios allow for comparison between banks of different sizes and act as industry standards, which can help compare the ratio of each bank with the industry average (Vasiliou 2000) There are many financial ratios that can be used to assess the profitability of a bank In previous studies, financial ratios such as Return on Assets (ROA); Return on Equity (ROE) and Net Interest Margin (NIM) are commonly used indicators Or for example (Ong Tze San and Teh Boon Heng 2013), (Nguyen Tuan Duy 2020), (Nguyen Thi Thu Hien 2017), used ROA, ROE to measure the profitability of banks

Bank profitability is often expressed as a function of internal and external factors Internal factors are mainly influenced by management decisions and policy objectives of the bank (DaWood 2004) while external factors focus on macroeconomic and industry-related variables reflected in the economic and legal environment in which banks operate (Athanasoglou et al 2006)

According to (Truong Quang Thong 2009), the return on assets ratio represents the correlation between the bank's ability to generate profits and its total assets, and is used to assess the profitability of bank assets, specifically measuring the profitability per unit of bank assets That is, on average, for every unit of assets, how much net profit can the bank generate through its business activities The profitability of assets is determined by the formula:

ROA is a suitable measure of the efficiency of a bank's business operations, showing the bank's ability to convert assets into net income and is used to assess profitability regardless of the bank's financial structure Research by (Syafri 2002) with banks in Indonesia, (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022), (Ong Tze San and Teh Boon Heng 2013), used the ROA coefficient to measure the bank's profitability Research results show that the ROA coefficient is affected by many factors such as bank size, customer deposit size, liquidity, risk provision, economic growth, inflation rate, etc

In addition to international studies, some Vietnamese economic experts also use the ROA coefficient in empirical research on the profitability of Vietnamese commercial banks (Nguyen Thi Canh and Ho Thi Hong Minh 2015), (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022)

Return on equity is the most important indicator for bank shareholders, used to measure the profitability of each capital invested by the owner The ROE indicator is determined by dividing profit after tax by equity using the following formula:

According to (Nguyen Thi Canh 2009), ROE is an indicator used to evaluate financial profitability, so it is used to measure the business performance of each bank The greater the bank's ability to generate profit per unit of capital, the higher the efficiency and effectiveness of capital use in that bank According to the study of (Ong Tze San and Teh Boon Heng 2013), ROE is rated higher than ROA because this indicator implies that the management is effective in managing the shareholders' funding and generating revenue for shareholders, meaning that shareholders benefit from their own capital invested in the bank The study used the ROE ratio to measure the profitability of banks and found that the ROE ratio is affected by factors such as bank size, equity capital, customer debt, bank deposits, economic growth, inflation, etc In Vietnam, studies by (Nguyen Thi Canh and Ho Thi Hong Minh 2015), (Le Dong Duy Trung 2022) also used the ROE coefficient as a measure of bank profitability However, research models using ROE as a dependent variable have a lower level of explanation of independent variables than models with ROA as a dependent variable This can be explained by the fact that banks often make full use of financial leverage in mobilizing capital for monetary business activities to generate profits and bank assets are mainly formed from equity and capital mobilized from customers; Therefore, the larger the capital structure mobilized in total assets, the smaller the ratio of equity to total assets, leading to the ROE index being enhanced even though the bank may bear potential liquidity risks in the future In short, the ROE index is only a reference parameter in assessing the profitability of a bank's business operations.

FACTOR AFFECTING COMMERCIAL BANKS’S

The profitability of banks is affected by many factors, however, because this study only focuses on factors such as: Bank size (SIZE), Cost of operating expenses to income ratio (CIR), Capital structure (CAP), Loan ratio (LOAN), Liquidity (LIQ), Deposit ratio (DEP), Credit risk provision (LLP), Economic growth (GDP), Inflation (INF), Non-interest income (NII), so in this presentation the author will focus on the above factors

Increasing the profitability of banks, specifically improving the ability to generate net profit from total assets and equity capital is always the top concern of bank managers In the world, there have been many studies on factors affecting the profitability of banks in many different spatial scopes: countries in the same region or with similar characteristics, or just one country The research results collected on the factors affecting the profitability of banks are concentrated in two main groups:

Group of factors within the bank

According to (Nguyen Xuan Hoang 2020), each bank has its own characteristics as well as strengths and weaknesses corresponding to those characteristics This is the group of factors that determine the profitability of the bank and are often directly affected by the management, operation, controllable and adjustable decisions of bank administrators Analyzing the internal characteristics of each bank helps administrators to establish appropriate business development policies, goals and strategies to take advantage of the strengths and limit the weaknesses within the bank, aiming to maximize the profitability of the bank The group of factors specific to the bank includes:

Bank size is considered one of the most controversial independent variables for researchers While (Nguyen Thanh Phong 2015) believes that large-scale banks with a wide branch network will always have a significant advantage in mobilizing and developing products and services from customers, reaching more customers and making it more convenient to borrow capital This is explained by the presence of branches close to customers, creating trust and loyalty In addition, large banks also have the financial capacity to invest in modern technology, which helps make business operations more efficient Therefore, the scale and wide branch network are important factors in building the bank's reputation and attracting customers On the contrary, (Athanasoglou 2006) argues that the larger the bank, the more it faces problems of poor management, moral hazard, and risky business operations, thereby reducing the profits of commercial banks In addition, when exceeding the economic scale, the scale will then adversely affect the profitability of the bank (Adreas Dietrich

2011) In short, the argument from previous studies shows that the larger the bank size, the higher the bank's profitability due to the advantage of scale, however, at a certain threshold of scale, diseconomies of scale appear, at which point the larger the scale, the lower the bank's profitability

(Albertazzi and Gambacorta 2009) study of bank profitability and business cycles in major industrialized countries in the European region concluded that the cost-to-income ratio has been reduced almost everywhere at different levels This shows that banks are trying to reduce operating costs to achieve expected net profit

According to (Phung Van Tuan 2022) bank operating costs should be considered a decisive and prerequisite factor to improve bank performance Because costs can be controlled and if managed effectively, they can contribute positively to the performance of commercial banks

Many previous studies have found an inverse relationship between operating costs and net profit of banks (Syafri 2012), (Ong Tze San 2013), (Dawood 2014), (Serwadda 2018), These conclusions imply that operating costs are one of the prerequisites to improve the net profit of the banking system Banks with lower costs achieve higher net profit

The capital of a commercial bank is the total source of money that the bank creates and mobilizes for investment, lending and meeting other needs in the bank's business operations Capital governs all operations as well as determines the existence and development of the bank Commercial bank capital includes capital owned by the bank, mobilized capital, borrowed capital and other types of capital Normally, mobilized capital accounts for a decisive proportion of the total capital of the bank and almost all capital use activities of the bank are carried out thanks to on this source of mobilized capital

According to the study of (Berger et al 1995), the equity ratio has a positive effect on the profitability of banks, higher capital levels generate higher profitability because with more capital, banks can easily comply with capital regulations to be able to provide excess capital in the form of loans Along the same line of reasoning (Athanasoglou 2006), it is also argued that the positive relationship between capital and net income may be the result of banks using equity to act as a safety channel in case the bank encounters financial difficulties At that time, banks are financed at more favorable interest rates, contributing to increasing expected net income and offsetting the cost of equity capital

Studies conducted by (Syafri 2012), (Athanasoglou 2006), (Lam Dao Quang

2021), (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022), also found that when a bank has abundant equity capital, the bank's profitability is higher

Liquidity risk is a factor that can arise due to the inability of banks to meet the reduction of liabilities, due to difficulty in raising capital due to increasing demand for loans This shows that liquidity risk is a serious factor affecting the operations of commercial banks The relationship between bank liquidity and profitability has shown some mixed results in the past Some studies have found a positive relationship between liquidity and profitability of banks (Dawood 2014), (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022) Liquidity is considered a determinant of profitability in models measuring profitability ROA and NIM (Ong Tze San and Te Bong Heng 2013) Liquidity can improve the profitability of banks because banks with sufficient assets have a lower risk of insolvency because they can withstand financial risks (Ong Tze San and Te Bong Heng 2013) This is because they can reduce the cost of borrowing from external sources, thereby bringing higher profits

In a research paper by (Ong Tze San and Te Bong Heng 2013) The author stated that the higher LIQ proves that the commercial bank is more liquid; the bank may lose profitable investment activities and is at risk of leading to lower profits Therefore, the author of the research paper expected that LIQ has a negative impact on profitability

According to (Nguyen Tuan Duy 2022), this is an important item in the capital sources of all banks Receiving customer deposits is to perform the function of the banking industry: circulating capital in the market For banks, this is the main source of capital for banks to use for lending and investing to generate income for the bank The larger the scale of customer deposits, the more capable the bank is to lend and invest to increase profits, thereby increasing the rate of return

The income of commercial banks mainly depends on the mobilization of funds that banks have from customers (including individual customers and corporate customers, as well as other credit institutions) The mobilization sources of commercial banks include payment deposits, savings deposits, term deposits and non- term deposits For payment deposits, or non-term deposits, banks will not have to pay interest to customers when keeping money in the account or pay a very low interest Therefore, customers can withdraw at any time when they need capital Meanwhile, term deposits or savings deposits do not allow customers to withdraw money before the agreed maturity date, so customers can get a higher interest rate in this case Therefore, it can be seen that customer deposits will be able to directly affect the operating efficiency of banks through net interest income In addition, most previous studies have argued that customer deposits can positively affect the performance of commercial banks such as (Sehrish Gul 2011), (Dawood 2014), (Abdus Samad 2015) Because the more abundant the source of mobilization shows that the bank has enough capital to finance its activities, thereby bringing more efficiency to the bank (Holden and El-Bannany 2006) However, for savings deposits or term deposits, customer deposits show a relatively high cost of capital Therefore, when a bank has a lot of customer deposits, it implies that the bank is facing a higher cost of capital, and therefore the bank's performance will be lower (Ommeren 2011) Therefore, it can be seen that customer deposits will have a significant impact on the profitability of banks

Outstanding loans to customers (LOAN)

According to (Nguyen Tuan Duy 2022), lending to customers is a basic function of the banking industry For the economy, lending represents the leading economic function of banks, which is capital circulation in the financial market, closely related to economic development For banks, it is one of the main sources of profit Therefore, this index is one of the measures of banks' profitability However, banks themselves are always cautious in promoting lending Although the more loans they lend, the higher the bank's profit, on the other hand, banks face two types of risks that negatively affect profitability: liquidity risk and credit risk When the economy is not operating effectively, rising interest rates create a debt repayment burden for low- income people, and unemployment increases, the risk of subprime loans increases the fastest, thereby reducing the profitability of banks But in general, most studies show that outstanding loans have a positive impact on the profitability of commercial banks such as (Syafri 2012), (Abdus Samad 2015), (Lam Dao Quang 2021) Outstanding loans are the amount of money from which banks can earn interest to pay interest on mobilized capital sources, the remaining difference is the contribution to profits At Vietnamese commercial banks, outstanding loans always dominate the total asset value and at the same time generate the majority of income for banks

RELATED RESEARCH

(Panditharathna and Kawshala 2017) This study examines the effect of bank specific factors of profitability in Sri Lankan domestic commercial banks.This study conducted with a complete panel data and utilized the sample frame annual reports of the domestic commercial banks in Sri Lanka A regression analysis is built on a strongly balanced panel data set including 60 observations of 12 Sri Lankan domestic commercial banks over the period 2011-2015 SIZE, CAP, DEP, LIQ have been identified as independent variables and Profitability as the dependent v ariable.Regression findings reveal that SIZE, CAP, DEP are significant bank specific determinants of bank profitability in Sri Lanka There is a positive relationship between those factors and bank profitability LIQ is an insignificant determinant and it has a negataive relationship.In view of these findings, some recommendations may be functional for bank regulatory authorities to sustain strength and stability of the banking sector The results provide the effect of bank specific factors on Sri Lankan domestic commercial banks This paper intends to fill a gap in the existing literature by improving an understanding of bank profitability in Sri Lanka

(Farkasdi, Septiawan and Alghifari 2021) This study aims to determine the determinants of profitability in commercial banks in Germany The population is 7 banking sector companies listed in the DAX (Deutscher Aktienindex) Bank during the 2017-2020 period, with a sample of 5 banks and producing 20 observational data The method used is descriptive and verification with multiple regression analysis The results show that SIZE, CAP, DEP, NII have a significant positive effect on profitability Partially, SIZE, CAP, DEP, NII have a significant positive effect, while

DEP has a significant negative effect on profitability The most dominant factor affecting profitability is NII

(Purna Man Shrestha 2023) This paper has assessed the determinants of the profitability of commercial banks operating in Nepal The effect of macroeconomic as well as internal factors on profitability is estimated For this purpose, ROA is used to measure a bank's profitability Similarly, liquidity (LIQ), management efficiency (ME), assets quality (AQ), and operational efficiency (OE) are used as internal factors, and consumer price index (CPI), interest rate (IR), and growth rate of broad money supply (M2) are used as macro-economic factors Based on the result of panel data analysis, this paper revealed that bank-specific and macroeconomic factors play an essential role in determining profitability Further, this paper found that LIQ, ME,

AQ, CPI, and IR substantially influence the profitability of banks operating in Nepal Thus, this paper concluded that the bank management should improve its liquidity, efficiency of management, and quality of assets to improve profitability Likewise, the bank management can benefit from increasing CPI and IR to improve profitability

(Inthoulath, Viphommavongsa, Phimphachane and Wongpit 2024) The study uses unbalanced panel data from 35 banks in Laos of ten years covering the period from 2012 to 2021 The relationship is estimated using a random effects approach The results show that policy rate (macroeconomic factors), bank size and organizational structure (CEO) have a significant and positive impact on the profitability of Lao banks Meanwhile, CAP, LLP, LIQ, CIR, and TECH have a significant negative influence on bank profitability To the authors’ knowledge, this study is considered one of the earliest studies of its kind, in which the main factors affecting Lao bank profitability are determined That said, this paper makes a significant contribution to the theoretical literature, the industry, and policymakers, so that the performance of Lao commercial banks can be improved

Research results by (Lam Dao Quang 2021) the result of the regression analysis show that for bank- specific factor such as the bank size and the capital structure have positive impact on profitability; The cost to income ratio, the deposit ratio and loan loss provision ratio have negative impact on the profitability; Loan ratio has a positive impact on ROE, while there is no evidence to determine the relationship between loan ratio For macroeconomic factor, GDP has a positive impact on the profitability of commercial banks

The authors (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022) use multiple linear regression models and factor analysis models to process the data The research results show that the bank’s asset size, equity size, liquidity risk, interest income and non-interest income have a positive and statistically significant impact on profitability Meanwhile, administrative costs, credit risk and tax have opposite and statistically significant effects on profitability

(Le Dong Duy Trung 2020) This study uses a sample of data from the annual financial statements of 30 commercial banks in Vietnam from 2009 to 2017 The author relies on the GMM (Generalized Method of Moments) method to estimate the impact of variables such as asset size, equity ratio, marginal interest income, customer deposit ratio, credit risk provision fee ratio, OEAR operating expense ratio, market concentration ratio, money supply growth rate, inflation rate, etc on ROA and ROE The research results show that asset size (S) has a small positive impact on ROA but is not statistically significant in the case of ROE Equity ratio (CAP) has a positive impact on ROA but a negative impact on ROE Marginal interest income (NIM) has a positive impact on ROA and ROE The ratio of non-interest income to total assets (DIA) also has a positive impact on ROA and ROE, especially a strong impact on ROE when diversifying products, focusing on non-interest business activities The credit risk provision expense ratio (LPCLR) has a negative impact on ROA and ROE at the same level of significance, indicating that the weakening credit quality and high provision expenses will affect the bank's profitability

(Phung Van Tuan 2022) The objective of the study is to examine the factors affecting the profitability of commercial banks The study was conducted on a sample of 34 commercial banks in Vietnam during the period 2010 - 2020 The profitability of banks is represented by the average income on total assets (ROA) The results of the study show that EQAS (capital adequacy level), SIZE (bank size), GDPGGR (GDP growth rate) and ASSGDP (ratio of total assets of deposit banks to GDP) increase the profitability of commercial banks On the contrary, COST (cost) and LOFUND (liquidity) decrease the profitability

Table 2 1: Summary of related Vietnamese research

Source: Compiled by the author

Author(year) Topic Research method and data

The Factors Effecting on Bank

Panel data and utilized the sample frame annual reports of the domestic commercial banks in Sri Lanka

Determinants of commercial banks profitability: evidence from Germany

Descriptive and verification with multiple regression analysis

-SIZE(+), CAP(+), DEP(+), NII(+) -LIQ(-)

Affecting the Profitability of Commercial Banks

-CAP(-), LLP (-) LIQ (-), CIR(-), TECH (-)

Factors affecting the profitability of commercial banks in Vietnam

FEM, REM, FGLS SIZE (+); CAP(+);

Factors affecting the profitability of commercial banks in Vietnam

Multiple linear regression models and factor analysis models to process the data

-SIZE(+), LIQ (+), NII(+) -CIR(-), LLP(-), TAX (-)

Factors affecting the profitability of commercial

CAP(+), NIM(+), DIA(+),LPCLR(-) banks in Vietnam: A dynamic empirical approach

Factors affecting the profitability of commercial banks in Vietnam in the period 2010 -

RESEARCH METHOD

RESEARCH PROCESS

Step 1: Review the theoretical basis and relevant previous studies in Vietnam and other countries, then discuss previous studies to identify research gaps

Step 2: Based on the theoretical basis and empirical studies, the topic designs a research model, thereby explaining and determining how to measure variables and building research hypotheses for independent variables

Step 3: Determine the research sample, data source as well as the appropriate research subjects, scope and methods, from which to collect and process data according to the research model in step 2 In particular, determine specific analysis and estimation techniques such as: descriptive statistics, correlation analysis and panel data regression analysis according to the Pooled Least Squares regression model (Pooled OLS) if there is no serious multicollinearity, fixed effects model (FEM) and random effects model (REM) At the same time, the author conducts a test of the model's suitability at the significance level of 1%, 5%, 10% to determine the independent variables that are statistically significant to explain the dependent variable, in parallel with the Hausman test to choose between FEM and REM, the F- test to choose between FEM and Pooled OLS, thereby choosing the most suitable regression result Conduct a test of the defects of the selected most suitable model, including: the phenomenon of heteroskedasticity and autocorrelation If there are no defects, combine with the test of the model's suitability to perform step 4 If there is one of the defects, it will be overcome by the generalized least squares model (FGLS) to find the final regression result

Step 4: Based on the results of the research model, the author will discuss and comment on the impact of factors on the profitability of commercial banks in Vietnam based on the theories and perspectives of previous studies mentioned in Chapter 2

Step 5: The author will draw conclusions and make relevant suggestions and recommendations to answer the research questions as well as solve the proposed research objectives.

SELECTION AND DESIGN OF RESEARCH MODEL

In most previous studies, authors have chosen ROA as the dependent variable for the research model However, for this thesis, in order for the analysis results to be presented in a more general way, the author will add ROE as the dependent variable

In addition, the profitability of banks is determined by many factors from micro to macro factors Specifically, the dependent variables and independent variables of the study are as follows:

Independent variables: CAP, SIZE, LIQ, CIR, DEP, LOAN, NII, LLP, GDP, INF

Through the research strategies in chapter 2, it can be seen that many different econometric models are used However, to be suitable and easy for the research process, the author chooses the panel data regression model, this model is used by many authors in articles studying factors affecting the profitability of commercial banks such as: (Nguyen Thi Thu Hien 2017), (Le Dong Duy Trung 2020), (Syafri 2012),

Based on the above, the author proposes the following research model:

Model 1: ROA and influencing factors

ROAit = 0 + 1 (SIZE)it+ 2 (CIR)it + 3 (CAP)it + 4 (LOAN)it +5(DEP)it

+6 (LLP)it +7 (GDP)it + 8 (INF)it + 9 (LIQ)it + 10 (NII)it + àit

Model 2: ROE and influencing factors

ROEit = 0 + 1 (SIZE)it+ 2 (CIR)it + 3 (CAP)it + 4 (LOAN)it +5(DEP)it +

6 (LLP)it +7 (GDP)it + 8 (INF)it + 9 (LIQ)it + 10 (NII)it + àit

+ SIZE: Bank size - Independent variable

+ CIR: Operating expenses to income ratio - Independent variable

+ CAP: Capital structure - Independent variable

+ LOAN: Loan rate - Independent variable

+ DEP: Deposit ratio - Independent variable

+ LLP: Credit risk provision - Independent variable

+ GDP: GDP growth – Independent variable

+ NII: Non-interest income - Independent variable

DESCRIPTION OF RESEARCH VARIABLES AND

ROA is the return on assets ratio and it is considered a financial indicator, this indicator will measure the profitability of each asset of the bank ROA is calculated by dividing the profit after tax by the total assets of the bank Among the indicators representing profitability, ROA is the indicator with the simplest calculation method and is also the most effective and reliable measurement However, ROA also has a notable disadvantage when this index only considers the bank's profit based on the total assets of that bank without taking into account other important factors such as leverage structure Although there are still many limitations in ROA, it is still highly appreciated and used by many people in many studies, for example, the research of: (Syafri 2012), (Petria et al 2015), (Lam Dao Quang 2020), ROA is calculated by dividing the profit after tax by total assets:

The higher the ROA, the greater the bank's management efficiency and the more reasonable the bank's use of assets, or in other words, the higher the bank's profitability

ROE is return on equity and this index measures the profitability of each dong of equity of the enterprise In other words, ROE measures the ability of the enterprise to use capital effectively and in theory, the higher the ROE, the more effective the use of capital However, when using ROE as a measurement, it is necessary to pay attention because this index is only really effective when evaluating in the long term, besides, the financial capacity of banks is not accurately reflected by ROE and like ROA, ROE does not consider financial leverage and the risks that come with it Therefore, the re-establishers often combine ROE with other indexes Authors who use a combination of the two indexes ROA and ROE include: (Ong Tze San and Teh Boon Heng 2013), (Nguyen Thi Thu Hien 2017), (Nicolae Petria 2015), ROE is calculated by dividing after-tax profit by equity

Like previous studies, this project also calculates the bank size variable as the natural logarithm of total commercial bank assets to reduce the skewness of the distribution of total assets (Almaqtari et al 2019) argue that increasing bank size is positively related to bank profitability With large banks, the level of product and loan diversification will be higher than with small banks

In fact, most large-scale banks will have certain advantages over smaller-scale banks, especially in accessing loan customers However, the larger a bank is, the more risks it will have when it is difficult to manage In addition, if it exceeds the economic scale, the profitability of banks will also be affected However, most research results show that bank size will have a positive impact on bank profits Research by (Le Dong Duy Trung 2020) shows that bank size is the result of a small positive impact on ROA and statistically insignificant on ROE through data of 30 banks in Vietnam during the period from 2009 to 2017 The implication is that when growing in size, banks will have more advantages in terms of scale and scope, often accompanied by a growing network Authors agreeing with this opinion include: (Sehrish Gul et al

2011), (Ong Tze San and Teh Boon Heng 2013), Because of this, the author expects that bank size has a positive relationship with bank profitability

Hypothesis H1: Bank size has a positive influence on the profitability of commercial banks in Vietnam

The author uses the ratio of equity to total assets to examine whether the level of capital is a decisive factor in the profitability of the bank The total equity of the bank includes the bank's own capital, asset revaluation difference, exchange rate difference, funds and retained earnings for reinvestment On the other hand, Ong Tze San and Teh Boon Heng also said that a well-capitalized bank will have more business opportunities The bank will have the ability and flexibility to handle risks and reduce the risk of insolvency, which will reduce the demand for loans and then the bank's profits will increase This higher ratio means that the bank's net profit will also be improved (Athanasoglou, 2006) Because of this, many authors have studied and concluded that the size of equity capital has a positive impact on the profitability of banks, typically the authors: (Nguyen Thanh Phuong and Dang Thi Lan Phuong

2022), (Syafri 2012), (Vo Phuong Diem 2016) From here, the author expects that the size of equity capital has a positive relationship with the profitability of banks

Hypothesis H2: The size of capital resources has a positive influence on the profitability of Vietnamese commercial banks

To measure the impact of operating efficiency on the profitability of banks, the author uses a proxy variable for efficiency, which is the ratio of total operating costs to total operating income (denoted as CIR) This percentage reflects the amount of costs that the bank has used for its operations, which accounts for how much of the total income that the bank has achieved (excluding other types of costs) In the components of operating costs of the banking system, salaries often account for a very high proportion The higher the total operating costs, the lower the level of operating efficiency, and the lower the net profit that the bank achieves (Huynh Tan Giau 2016) Because of this, most authors in the studies expect low operating costs to improve the profitability of banks Specifically, including the authors: (Nguyen Thi Thu Hien 2017), (Syafri 2012), Therefore, the author expects that operating costs have an inverse relationship with profitability in this thesis

Hypothesis H3: Operating costs have a negative influence on the profitability of Vietnamese commercial banks

Deposits are one of the main sources of funding for banks, so they affect the profitability of that bank This index is calculated by dividing the total deposits by the total assets When a bank mobilizes a lot of deposits from customers, this will be a less expensive and more stable financial resource compared to other alternative sources of financial funding, helping the bank to operate its business profitably A bank with a higher amount of deposits shows that the bank has a good customer attraction strategy and from here there are more opportunities in credit, so previous research authors have assessed that deposits at banks have a significant impact on the bank's profits Specifically, the authors: (Sehrish Gul et al 2011), (Gremi 2013)

Hypothesis H4: Customer deposits have a positive influence on the profitability of Vietnamese commercial banks

For banks, lending is considered the most important activity in generating profits This ratio assesses the bank's specialization in traditional lending activities Although there are many services, for banks, lending is still one of the main sources of income that brings profits to banks In the current volatile economic environment, bank lending activities greatly affect the bank's profitability Studies by (Syafri 2012), (Abdus Samad 2015), (Lam Dao Quang 2021) show that the ratio of outstanding loans to total assets tends to be similar to the bank's profitability because it is believed that the higher the ratio of outstanding loans to total assets, the greater the bank's profitability Through the above analysis, the author also expects that outstanding loans to customers have a positive impact on the bank's profitability in this study

Hypothesis H5: Loan rate have a positive influence on the profitability of Vietnamese commercial banks

According to (Gemechu 2016), liquidity is the quality of an asset that makes it easily convertible into cash with little or no risk of loss The ratio of liquid assets to total assets will better reflect the liquidity of a bank A bank is considered liquid when it has enough cash and other liquid assets, along with the ability to quickly raise funds from other sources to be able to meet payment obligations and financial commitments on time In this study, the ratio of liquid assets to total assets (LIQ) is used to quantify liquidity This ratio increases as the liquidity of a bank increases One of the main causes of bank failure is lack of liquidity However, retaining liquid assets comes at the cost of better profits According to (Dawood 2014), (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022) there is a significant positive relationship between bank liquidity and profitability However, banks may choose to increase cash holdings to reduce risks during periods of uncertainty In this thesis, the author also expects liquidity to have a positive effect on profitability as the above studies

Hypothesis H6: Liquidity has a positive influence on the profitability of Vietnamese commercial banks

The author uses the provision for credit losses on outstanding loans (Beatty and Liao 2009) asserts that provision for credit losses is a policy that commercial banks adopt by setting aside a sum of money (reserves) in case a loan fails, helping to protect the bank's profitability and capital position By using provision for credit losses, a number of domestic and international organizations have made many efforts to minimize the adverse effects of credit risk Due to the previous problems and crises that banks have encountered, the ratio of provision for credit losses on outstanding loans has become increasingly important in supporting banks to strengthen their financial position The main objective of credit risk provisioning is to control the volatility of revenue (Norden and Stoian 2013); and to prevent volatility in risky assets from affecting the risk and profitability of banks (Norden and Stoian 2013) Many empirical studies use credit risk provisioning to demonstrate credit quality or in short, credit risk of commercial banks According to the general view, when the bad debt ratio or the ratio of credit risk provisioning expenses increases, it shows that the credit quality of commercial banks is declining and credit risk is increasing However, empirical studies give different results depending on each country, time, as well as the criteria for measuring the performance of banks The inverse relationship between credit risk provisioning and profitability (ROA, ROE) has been observed by (Ahmad et al 2014) in Pakistan As a result, larger loan loss provisions will harm profitability and stability); (Athanasoglou et al 2006); (Sufian 2011); (Tan and Floros

2012) also found evidence of a negative correlation between credit loss provisions and profitability In this thesis, the author expects credit loss provisions to have a negative impact on profitability

Hypothesis H7: Credit risk provisions have a negative influence on the profitability of Vietnamese commercial banks

In this study, the author uses the ratio of non-interest income to total assets to measure this variable Nowadays, banks are looking for new sources of revenue based on diversifying service types, expanding non-interest business activities, specifically switching to fee-based business transactions: Commissions, guarantees, profits from securities trading, etc When the bank's products are more diverse and come with good services, the profitability will also increase and from there, there will be less dependence on risky credit activities Thereby, it can be seen that non-interest income is a positive signal or, in other words, it will have a positive impact on the bank's profits Most of the analyses of previous authors also suggest that NII will have a positive impact on the bank's profits, specifically the authors: (Le Dong Duy Trung

2020), (Farkasdi 2021), (Nguyen Thanh Phuong and Dang Thi Lan Phuong 2022),

Hypothesis H8: Non-interest income of banks has a positive influence on the profitability of Vietnamese commercial banks

GDP is a commonly used macroeconomic indicator It measures the value of income generated from production and services in a country over a period of time GDP growth is often used to measure the macroeconomic situation and represents the development of GDP GDP growth is defined as the annual change in GDP and it reflects the economic cycle GDP growth affects the supply and demand for loans and deposits During a strong economic growth period, the demand for loans and deposits increases, and the quality of bank assets also improves This can lead to increased profits for banks Conversely, when the economy slows down, the GDP growth rate also decreases The demand for loans decreases and banks face higher default risks and increased provisioning costs, leading to reduced bank profits Many studies by (Athanasoglou 2006), (Nguyen Pham Nha Truc and Nguyen Pham Thien Thanh 2016) demonstrated the positive impact of GDP growth on profitability

Hypothesis H9: Economic growth has a positive influence on the profitability of Vietnamese commercial banks

Inflation determines the percentage growth rate of the Consumer Price Index (CPI) for all goods and services The inflation rate is also an important macroeconomic factor affecting the profitability of banks, through the purchasing power of money, the main business of banks The importance of inflation to the profitability of banks has been widely debated in the literature, largely due to the impact of inflation on the sources and users of bank financial resources Depending on whether inflation is predictable or unpredictable, "inflation can have both positive and negative effects on profitability" (Perry 1992) In the event that inflation is expected to increase, banks can adjust interest rates to increase revenues and simultaneously reduce costs However, if inflation is unpredictable, banks will not be able to make the necessary interest rate changes, leading to costs increasing faster than revenues However, most studies show that inflation and profitability have a positive relationship (Syafri 2012), (Sehrish Gul 2011), (Capraru 2014) In Vietnam, (Le Dong Duy Trung 2020) proves that inflation rate has a positive impact on bank profitability (through two research models ROA and ROE), but the actual statistical significance is not high

Hypothesis H10: Inflation has a positive influence on the profitability of Vietnamese commercial banks.

DATA ANALYSIS

Due to lack of information and limited time, the author could only collect data from 20 commercial banks in Vietnam Data on banking characteristics of 20 Vietnamese commercial banks based on audited financial statements were fully synthesized through Fiinpro software Data on macroeconomic indicators were obtained from the World Bank The author combined the data synthesized and calculated according to the formula stated in Chapter 3 to enter the model using secondary data sources Specifically, 220 observations starting from December 2013 and ending in December 2023 were included in the model to evaluate the indicators affecting the profitability of banks The panel data method was used in the study, because it has many advantages over time series data and cross-sectional data, for example:

First, the panel data method shows the difference or heterogeneity of cross- sectional data, because cross-sectional data are often not the same Panel data provide cross-sectional information over time and contain heterogeneity between them Panel data analysis is capable of taking into account the unique characteristics of cross- sectional data (Pham Thi Tuyet Trinh et al 2016)

Second, the panel data method combines the time factor and the cross-sectional unit, providing a larger number of observations thanks to the two-dimensional dimension, while providing more information When applying the panel data method, the researcher only needs to combine multiple cross-sectional units in a certain period of time, thereby increasing the number of observations, degrees of freedom and increasing the power of the test Moreover, combining data by this method reduces the phenomenon of multicollinearity that often occurs in time series models with many explanatory variables (Pham Thi Tuyet Trinh et al 2016)

Third, the panel data method helps research approach problems with a larger scope and solve more complex problems The use of a combination of cross-sectional and time series data in a panel structure allows for both time-based analysis and cross- sectional analysis of differences between units (Pham Thi Tuyet Trinh et al 2016)

Fourth, the panel data method allows the author to construct and estimate more complex models than time-series and cross-sectional data, such as technical efficiency models (Pham Thi Tuyet Trinh et al 2016)

Finally, biases in aggregating data from firms or individuals are minimized or eliminated in the panel data method, as it produces more precise variables than measuring data at the macro level (Pham Thi Tuyet Trinh et al 2016).

RESEARCH METHODS AND TESTING

The author uses the panel data regression method for the research sample of 20 Vietnamese commercial banks from 2013 to 2023

Panel data is a combination of time series data and cross-sectional data This is a widely used data type in research, combining two different types of data: time series data and cross-sectional data Time series data is a set of observations of a variable collected over time with a specific frequency of observation Cross-sectional data collects information of many variables at a specific point in time

There are two types of panel data structures: Balanced and Unbalanced A balanced table is when the objects have complete data in all observation years, without missing data (Missing value) in any observation year An unbalanced table is when in the observation years of one or more objects there is no value To estimate a panel data model, we can estimate through 4 common ways:

• Pooled Ordinary Least Squares-Pooled OLS

Ordinary Least Squares -Pooled OLS

The Pooled OLS model applies the Ordinary Least Squares (OLS) methodology to panel data This model assumes that there are no unobservable entity-specific effects, meaning that all entities in the data set are considered to have the same underlying characteristics Consequently, 𝛼𝑖αi is assumed to be constant across individuals and there is no dependence within individual groups (firms) Estimating the Pooled OLS model obtains unbiased estimates of the regression coefficients, under the condition that the other assumptions of the OLS model are satisfied

Acording to (Truong Quang Thong 2009) assuming that each entity has its own unique characteristics affecting explanatory variables, FEM performs an analysis of the correlation between the residuals of each entity and the explanatory variables and thereby establishing control and separating the influence of individual characteristics (constant over time) from the explanatory variables to estimate the real effect of explanatory variables on dependent ones

Random effects approach indicates that the difference in specific conditions of cross units contained in random error Specific characteristics between entities are assumed to be random and not correlate with the explanatory variables

FGLS is a regression technique that is used when the researchers want to estimate the coefficients of a multiple linear regression model and their covariance matrix in the presence of non-spherical innovations with an unknown covariance matrix The key benefit of using FGLS is that it helps the author remove the issue related to heteroskedasticity and autocorrelation in the regression model In practice, the author conducts FLGS to estimate the coefficients in the model in case there is autocorrelation, cross-sectional correlation, and heteroskedasticity in the panel data

The content of chapter 3 mentioned the research process, model design for the topic based on the theoretical basis presented in chapter 2 In which, the author also clearly identified 2 dependent variables ROA and ROE and 10 independent variables From there, the thesis developed 10 research hypotheses as the basis for implementing the model and concluding the topic for the next chapter Finally, the author introduced the research methods and tests used to determine the specific regression model results

In the next chapter, chapter 4, will present in detail how to implement the research model based on the collected data including descriptive statistics, correlation analysis, regression and testing according to the models From the research results obtained, the chapter will also provide related analysis

RESEARCH RESULTS AND DISCUSSION

DESCRIPTIVE STATISTICS

Descriptive statistics for factors affecting the profitability of commercial banks in Vietnam are presented in Table 4.1 This table shows the minimum value, maximum value, mean value and standard deviation of the variables in the study

Source: Research result from author’s Stata/MP 17.0

Variable Observations Average Standard deviation

Based on Table 4.1, it can be seen that this is balanced data with a sample size of 220 observations from 20 commercial banks in the period from 2013 to 2023 The descriptive statistics of each variable are as follows:

For dependent variables, also known as variables representing indicators measuring the profitability of banks (ROA, ROE)

ROA: Through the table above, we can see that the average value of ROA of Vietnamese commercial banks is 0.96% and has a standard deviation of 0.71% In which, ROA has the highest value of 3.23% at TCB bank (2021) and the lowest value is 0.01% at BVB bank (2016) It can be seen that the data is quite stable because the difference between the average value and the standard deviation is not significant With a standard deviation of 0.71%, the difference in efficiency between banks is almost similar

ROE: The average value of ROE of Vietnamese joint stock commercial banks is 10.89% with a standard deviation of 6.74%, the highest ROE value is at VIB bank

(2021) with the figure of 26.39% and the lowest value is at BVB bank (2016) with the figure of 0.081% Thereby, it can be seen that BVB's ROA and ROE are the lowest among 20 joint stock commercial banks These figures show that VIB has had an impressive record in growing its return on equity and is identified as one of the outstanding banks in the industry

Regarding the capital size (CAP): CAP fluctuates between 4.91% and 17.09% with an average value of 8.71% and a standard deviation of 2.6%, which shows that the capital size of joint stock commercial banks in Vietnam is quite similar In the period 2013-2021, the highest CAP was at TCB bank in 2020 (16.97%) and the lowest was at NAB bank in 2020 (4.91%) For bank size (SIZE): Bank size fluctuates in the range of 12.02 to 20.67 with an average value of 18.51% corresponding to a standard deviation of 1.52% The bank size of MBB bank is the highest in 2022 (20.40) and the lowest is at ACB bank in 2013 (12.02) For liquidity (LIQ): Through descriptive statistics of the variables, it can be seen that liquidity has an average value of 16.97% corresponding to a standard deviation of 6.8% The smallest fluctuation is 4.52% at STB bank (2018), the highest is 42.57% at KLP bank (2021)

For operating costs (CIR): CIR has an average value of 51% with a standard deviation of 14.08% In the period 2013-2021, the highest CIR was at BVB bank in

2016 with the figure of 88.06% and the lowest was at SHB bank in 2022 (22.71%)

For outstanding loans (LOAN): This variable has an average value of 58.93%, standard deviation of 10.1% This shows that joint stock commercial banks in Vietnam use 58.38% of the total amount of money for lending In which, STB bank

(2021) has the highest ratio with 74.44% and the lowest is MSB bank (2014) with 22.53%

For bank deposits (DEP): In the 9 years from 2013-2021, this ratio of joint stock commercial banks in Vietnam reached an average value of 66% with a standard deviation of 10.74% In which the largest value belongs to STB bank (2015) with the figure of 89.37% and the lowest value belongs to TPB bank in 2014 (42.01%)

For the risk provision ratio (LLP): This variable has an average value of 13%, standard deviation of 0.41% The bank with the highest risk provision level is VPB in 2022 with 3.12%, EIB has the lowest risk provision level with 0.6% in 2020

For the bank's non-interest income ratio (NII): NII has an average value of 0.74% and a standard deviation of 0.55% In which the bank with the highest ratio is TCB (2017) with 2.794% and the lowest ratio is VAB (2015) with -0.542%

For inflation (INF) and annual economic growth rate (GDP): The average values are 3.2% and 5.8%, respectively, with standard deviations of 0.014 and 0.016 Since Vietnam is a developing country, the average economic growth is also high and inflation is also affected The highest inflation rate was in 2013 and the lowest in

2015, similar to the highest average growth rate in 2018 and the lowest in 2021.

CORRELATION ANALYSIS

Table 4 2: Correlation coefficient matrix between variables in the ROA model

Source: Research result from author’s Stata/MP 17.0

ROA CAP SIZE LIQ CIR LOAN DEP LLP NII INF GDP

Based on the results of the correlation coefficient matrix analysis, it shows that the dependent variables are all correlated with the independent variables at different levels, specifically, these correlation coefficients are all less than 0.8 The independent variables CAP, SIZE, LOAN, LLP, NII are linearly correlated and have a positive relationship with ROA, in which the independent variable NII is the strongest The remaining variables in the model all have a negative relationship with the dependent variable ROA, but the strongest relationship is CIR and DEP, the rest have very weak linear correlations or even no linear correlation In theory, if the correlation coefficient between the variables in the matrix is greater than 0.8, the possibility of multicollinearity may occur Therefore, the above matrix does not have any variables with a correlation greater than 0.8, so multicollinearity does not occur for the ROA model However, to be sure whether there is multicollinearity or not, the VIF coefficient should still be checked

Table 4 3: Correlation coefficient matrix between variables in the ROE model

Source: Research result from author’s Stata/MP 17.0

ROE CAP SIZE LIQ CIR LOAN DEP LLP NII INF GDP

Based on the results of the correlation coefficient matrix analysis, it shows that the dependent variables are all correlated with the independent variables at different levels, specifically, these correlation coefficients are all less than 0.8 The independent variables CAP, SIZE, LOAN, LLP, NII are linearly correlated and have a positive relationship with ROE, in which the independent variable NII is the strongest The remaining variables in the model all have a negative relationship with the dependent variable ROE, but the strongest relationship is CIR and DEP, the rest have very weak linear correlations or even no linear correlation In theory, if the correlation coefficient between the variables in the matrix is greater than 0.8, the possibility of multicollinearity may occur Therefore, the above matrix does not have any variables with a correlation greater than 0.8, so multicollinearity does not occur for the ROE model However, to be sure whether there is multicollinearity or not, the VIF coefficient should still be checked.

REGRESSION RESULTS OF DEPENDENT VARIABLE ROA 47 1 Summary of regression analysis results with the dependent

4.3.1 Summary of regression analysis results with the dependent variable ROA Table 4 4: Results of regression analysis with the dependent variable ROA

Source: Research result from author’s Stata/MP 17.0

Pool OLS FEM REM FGLS

For the regression results of the Pooled OLS model, the significance is as follows: equal to 76.7%, meaning that the independent variables of the model will explain 76.7% of the change in the dependent variable ROA Independent variables such as CAP, CIR, LOAN, DEP, NII, are all statistically significant with a significance level of P_value < 1% Only the variable LLP is statistically significant with a significance level of 5% Variables such as SIZE, LIQ, INF, GDP are not statistically significant in the model

For the regression results of the FEM model, it is explained as follows: equal to 73.8%, meaning that the independent variables of the model will explain 73.8% of the change in the dependent variable ROA Independent variables that are statistically significant with a significance level of P_value < 1% include: CAP, CIR, LOAN, DEP, LLP, NII Only the variables SIZE and LIQ are statistically significant with a significance level of

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