Factors affecting the competitiveness of vietnamese commercial banks 2022

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM HOCHIMINH UNIVERSITY OF BANKING VO THI THUY LINH FACTORS AFFECTING THE COMPETITIVENESS OF VIETNAMESE COMMERCIAL BANKS BACHELOR’S DISSERTATION S.

MINISTRY OF EDUCATION

AND TRAINING

STATE BANK OF VIETNAM

HOCHIMINH UNIVERSITY OF BANKING

VO THI THUY LINH

FACTORS AFFECTING THE COMPETITIVENESS

OF VIETNAMESE COMMERCIAL BANKS

BACHELOR’S DISSERTATION SPECIALIZATION: FINANCE – BANKING

CODE: 7340201

HO CHI MINH CITY, 03/2022

MINISTRY OF EDUCATION

AND TRAINING

STATE BANK OF VIETNAM

HOCHIMINH UNIVERSITY OF BANKING

VO THI THUY LINH

FACTORS AFFECTING THE COMPETITIVENESS

OF VIETNAMESE COMMERCIAL BANKS

BACHELOR’S DISSERTATION SPECIALIZATION: FINANCE – BANKING

CODE: 7340201

INSTRUCTOR ASSOC PROF DR DANG VAN DAN

HO CHI MINH CITY, 03/2022

ABSTRACT

The argument stems from an urgent need to strengthen the competitiveness of joint-stock commercial banks under market economy settings, as well as the emergence of more and more commercial banks in the Vietnamese banking system Male As a result, this study used a quantitative technique with the Pooled OLS model, Fixed Effects Model (FEM), and Random Effects Model (REM) to examine the variables influencing the competitiveness of 28 joint-stock commercial banks in Vietnam during a 10-year period from 2011 to 2020 (REM) The study discovered that equity, bank size, and inflation all had a substantial and beneficial influence on the LERNER model The expense of the bank's credit risk provision has an opposite effect on the LERNER model, which depicts the bank's competitiveness The GDP component has a negative impact on banks, although the effect is not statistically significant Finally, the author proposes policy recommendations for banks based on the research findings in order to increase the competitiveness of Vietnamese commercial banks

Keywords: competitiveness, commercial banks, LERNER index, Vietnam

ASSURANCE LETTER

I assure that the factors affecting the competitiveness of Vietnamese commercial banks’ dissertation is my own report During this research, the figures and sources of knowledge are derived clearly and honestly from the banks' audited consolidated financial statements Additionally, the tests were conducted publicly and transparently with no intervention to correct the results of regression models

Author

Vo Thi Thuy Linh

Thank you sincerely!

TABLE OF CONTENTS

ABSTRACT 3

ASSURANCE LETTER 4

THANK-YOU LETTER 5

TABLE OF CONTENTS 6

LIST OF ABBREVIATIONS 10

LIST OF TABLES 10

LIST OF GRAPHS 11

CHAPTER 1: INTRODUCTION 12

1.1 Reasonable for research 12

1.2 Research objectives 13

1.3 Research questions 13

1.4 Research subjects and scope 14

1.5 Research methodology 14

1.6 Research empirical significance 15

1.7 Research layout 15

CHAPTER 2 LITERATURE REVIEW 17

2.1 Theory of the competitiveness of commercial banks 17

2.1.1 Commercial banks 17

2.1.2 Banks’ competitiveness 17

2.1.3 The criteria to measure the competitiveness of the bank 18

2.2 Previous studies about factors affecting the competitiveness of commercial banks 19

2.2.1 External factors 20

2.2.2 Internal factors 21

CONCLUSION CHAPTER 2 24

CHAPTER 3: RESEARCH METHODOLOGY 25

3.1 Table data collection 25

3.2 Research process 27

3.3 Research models 29

3.4 Variables explanation 30

3.4.1 Dependent variable – LERNER index 31

3.4.2 Independent variables: 31

3.5 Quantitative methods 33

3.5.1 Descriptive statistics 33

3.5.2 Pooled Ordinary Least Squares (Pooled OLS) Model 33

3.5.3 Fixed Effects Model (FEM) 34

3.5.4 Random Effects Model (REM) 34

3.5.5 Lagrangian multiplier test 34

3.5.6 Hausman test 35

CONCLUSION CHAPTER 3 36

CHAPTER 4: ANALYSIS AND RESEARCH RESULTS 37

4.1 Descriptive statistics 37

4.2 Correlation analysis 39

4.3 Multicollinearity test 39

4.4 Estimating the regression model by Pooled OLS, FEM, and REM methods 40

4.4.1 Pooled ordinary least square (Pooled OLS) 40

4.4.2 Fixed effect model (FEM) 42

4.4.3 Random effect model (REM) 43

4.5 Selecting a regression model 45

4.5.1 Between FEM and REM 45

4.5.2 Between Pooled OLS and REM 45

4.6 Model diagnostics 46

4.6.1 Autocorrelation diagnostics 46

4.6.2 Heteroskedasticity diagnostics 47

4.7 Model fix 47

4.8 Discussing research results 48

4.8.1 Equity capital (CAP) 48

4.8.2 Bank size (SIZE) 49

4.8.3 Credit loss provision ratio (LLP) 49

4.8.4 Gross domestic product growth (GDP) 50

4.8.5 Inflation (INF) 50

CONCLUSION CHAPTER 4 51

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS 52

5.1 Conclusion 52

5.2 Recommendations 53

5.2.1 Mobilize equity capital 53

5.2.2 Increase bank size 53

5.2.3 Cost control 54

5.2.4 Plan for avoiding and dealing with inflationary issues 54

5.3 Limitations of the study 55

CONCLUSION CHAPTER 5 57

REFERENCES 58

Appendix 61

1 Appendix 1 – Research data 61

2 Appendix 2 – Descriptive statistics 70

3 Appendix 3 – Correlation analysis 70

4 Appendix 4 - Multicollinearity test 70

5 Appendix 5 - Pooled OLS 71

6 Appendix 6 – FEM 71

7 Appendix 7 – REM 72

8 Appendix 8 – Hausman test 72

9 Appendix 9 - Breusch and Pagan Lagrangian multiplier test 73

10 Appendix 10 – Autocorrelation diganostics 73

11 Appendix 11 – Model fix 74

LIST OF ABBREVIATIONS

LIST OF TABLES

Table 2 1 Summary of previous research results 21

Table 3 1 List of banks used for the research data 25

Table 3 2 The dependent and independent variables of the model 30

Table 4 1 Descriptive statistics results 37

Table 4 2 Correlation analysis 39

Table 4 3 Multicollinear result 40

Table 4 4 Pooled OLS output 41

Table 4 5 Fixed effect model output 42

Table 4 6 Random effect model output 43

Table 4 7 Model choice between FEM and REM 45

Table 4 8 Model choice between pooled OLS and FEM 46

Table 4 9 Autocorrelation diagnostics 46

Table 4 10 Heteroskedasticity diagnostics 47

Table 4 11 Cross-sectional time-series FGLS regression 47

LLP Credit Loss Provision Ratio

GDP Gross Domestic Product Growth HOSE Ho Chi Minh Stock Exchange HNX Hanoi Stock Exchange

UPCoM Unlisted Public Company Market

Pooled OLS Pooled Ordinary Least Square FGLS Feasible Generalized Least Squares

LIST OF GRAPHS

Figure 3 1 Research process 27

CHAPTER 1: INTRODUCTION 1.1 Reasonable for research

The banking industry now plays an important role in both the economy and our daily lives The banking industry helps the development of the country's economy by mobilizing capital and allocating it to production and business operations As a result, the banking system is regarded as a critical sector of the economy

Competitiveness has become one of the majority's favorite economics topics in recent years Keeley (1990), Allen and Gale (2004), Berger et al (2004), Berger et

al (2009), Beck et al (2010), Martinez-Miera, and Repullo (2010), Wagner (2010) have all questioned whether increased competitiveness is good or bad for financial stability In the past, there have been various issues generated by bank market power that has contributed to instability The opposing narrative contends that the instability was caused by regulatory failings or a lack of market discipline and that greater competitiveness is required to make banks stronger According to Schaeck and Cihák (2014), a bank's competitiveness has a positive relationship with its stability, meaning that as a bank's competitiveness rises, so does its stability Therefore, it’s necessary to find factors affecting the competitiveness of the commercial banking system

The integration process, as well as the implementation of the roadmap for actual international commitments in the financial sector, assists the Vietnamese very commercial banking system in receiving many opportunities while also facing many challenges such as competitive pressures and risks in a subtle way External effects provide the chance to take advantage of exchange rate differences for the most part, and therefore external influences provide the opportunity to take advantage of exchange rate differences in a nuanced manner As a result, Vietnam's general commercial banking system primarily needs to improve its competitiveness and identify factors affecting bank competitiveness to have an appropriate direction and strategy, demonstrating that the integration process, in conjunction with the

implementation of the roadmap for sort of international commitments in the financial sector, generally assists the general Vietnamese commercial banking system in receiving many opportunities but also facing many challenges

Many researchers have investigated the competitiveness of banks all over the world, which is especially significant However, there hasn't been much in the way

of study on this issue for the Vietnam banking market and developing market Because Vietnam is a developing nation, the financial sector is still immature, the central bank is still not independent from the government, the governance structure

is still weak, there is no clarity and transparency, and the danger of bad debt is quite significant Recognizing the importance of empirical evidence as a source of reference information for managers and policymakers, this study investigated how

to measure competitiveness and considers factors that have a significant impact on the competitiveness of Vietnamese commercial banks

Based on the above, the author selected the topic "Factors affecting the

competitiveness of Vietnamese commercial banks" for the research dissertation in

order to identify the factors affecting the banking system's competitiveness and the level of their influence

- What solutions can help Vietnamese commercial banks increase their competitiveness?

1.4 Research subjects and scope

- Research objects: factors affecting the competitiveness of commercial banks

in Vietnam

- Research scope: In the 10 years from 2011 to 2020, secondary data was collected from 28 Vietnamese commercial banks, with the data being completely and clearly published in each bank's financial statements

In which, LERNER: Banking competitiveness

SIZE: Bank's size

INF: Inflation rate GDP: Gross domestic product growth From empirical results and the collected data, the study will explain and evaluate the factors that influence the competitiveness of Vietnamese commercial banks, which is particularly important The study collects data from mostly Vietnamese commercial banks between 2011 and 2020, then uses econometric models to examine the links and their relevance, which is fundamentally highly substantial The research will then examine and explain the influence of various

variables on the competitiveness of mostly Vietnamese commercial banks, resulting

in recommendations to increase competitiveness and orient the sector in the future

1.6 Research empirical significance

This study adds to practice by illustrating the range of factors impacting commercial banks' competitiveness using secondary data on banking performance and an exhaustive research methodology The study gives data that may be used as a reference point, as well as policy suggestions to assist bank administrators and state management agencies in analyzing competitiveness and altering parameters

accordingly, therefore defining acceptable courses of action

Chapter 2: Theoretical Basis

This chapter gives an overview of determinant variables based on reference models from prior research with the goal of building an impact model It also presents the theoretical underpinning connected to the competitiveness of the bank

Chapter 3: Research Methodology

The study model, research methodology, data gathering, and processing methods, and the development and testing of scales to quantify the effect variables

on competitiveness are all covered in this chapter

Chapter 4: Analysis And Research Results

This chapter presents the result from the estimation model and discusses the obtained result

Chapter 5: Conclusions And Recommendations

This chapter outlines the study's primary results, as well as the research's importance and contribution to the banking industry and the economy in general Meanwhile, making recommendations to increase the bank's competitiveness This study should serve as a foundation for others to continue to investigate and improve, while also highlighting some of the study's shortcomings and suggesting new research areas

CHAPTER 2 LITERATURE REVIEW 2.1 Theory of the competitiveness of commercial banks

2.1.1 Commercial banks

Commercial banks are one of the financial intermediaries that play a vital role

in constructing a financial environment, which is defined by offering a range of monetary services with the core business of receiving deposits and lending Banks employ idle money to produce money for customers and other financial institutions through their fundamental operation of moving money from areas with excess capital to places with a shortage of capital A business that they will not be ready to earn, or a minimum of not for an extended time Furthermore, commercial banks offer a good range of other services so as to fulfill society's high demand for goods and services

Besides, banks also create the credit reputation of consumers by ensuring safe money in order that good money is merely permanent loans and not lost on bad loans In other words, banks connect individuals, businesses, and other institutions

to assist keep the economy going So if the banks go bankrupt, it'll cause the collapse of the whole system of the economy, and since banks and money are essential to sustain not only the economy but the entire society, they're extremely strictly regulated and must operate under strict guidelines and procedures

In the US, a commercial bank is a currency trading organization that specializes in financial services and operates in the financial services industry According to Article 4 of the Law on Credit Institutions (Law No 47/2010/QH12), a commercial bank is a type of bank that is permitted by this Law

to undertake all banking activities and other business activities for profit purposes

2.1.2 Banks’ competitiveness

A commercial bank is a business, but banking is a distinct industry that deals with money and related financial services As a result, based on the WEF's level division, the competitiveness of the commercial banking system is measured in terms of enterprise competitiveness Enterprises have the capacity to compete when

they dominate the market, attract many consumers by delivering high-quality products and services, produce customer happiness, and have a strong reputation in the market, in addition to producing enough profit to sustain the business's long-term growth

Banking competitiveness, according to Kazarenkova (2006), is the practical ability as well as the potential of the credit institution to create and develop service products in the face of high market power in order to build a positive image of a reliable modern bank in responding to customer demands

As banks and rivals extend their product and service portfolios, competition in the financial services market is getting increasingly severe Local banks offer lending, savings programs, retirement plans, and financial advice to companies and individuals These are services that are directly competed with by other banks, credit unions, investment banks, and financial firms Competitive pressure functions

as a motivator for future service improvement

2.1.3 The criteria to measure the competitiveness of the bank

This research measures the competitiveness of commercial banks through the Lerner method

Lerner's (1934) methodology is extensively utilized in empirical research on bank competitiveness since it estimates each year and for each form of ownership of each bank This is a way of determining a bank's competitiveness that uses the Lerner index This index measures a bank's market power by taking the ratio of marginal cost to pricing into account In a completely competitive market, the selling price equals the marginal cost, but in a monopolistic environment, the selling price exceeds the marginal cost As a result, the Lerner index is the most generally used approach in the world to quantify monopolistic power, taking into account the difference between the selling price and the marginal cost, as follows:

Where:

- i: the bank

- t: time

- P: output price which is measured by total revenue over total assets

- MC: marginal cost which is not directly observable MC is estimated in a two-step procedure based on the total cost function, as follows:

Step 1: Take the natural logarithm of the total cost function

Where: - TC: the total cost (including interest and non-interest expenses) - Q: the total asset - Three input prices include is the cost of deposits, is the cost of material and is the price of labor - T: a variable reflecting the technological change Step 2: After estimating the total cost function, the marginal cost is determined by taking the first derivative from the above equation (2) and is estimated as:

2.2 Literature review

Fungancova et al (2010) with research “Market power in the Russian banking industry” investigates bank competitiveness in Russia by analyzing the factors of the Lerner index of local banks from 2001 to 2006 Their key results are that competition has only marginally improved, despite the fact that the average Lerner

index is around the same across industrialized nations, and that banks' market power

is favorably impacted by market concentration and adversely influenced by risk (as measured by non-performing loans), whereas larger bank size is related with higher market power only up to a certain point (after which it becomes harmful)

Rakshit and Bardhan (2019) use a sample of 70 Indian commercial banks to quantify and explain the level of competition from 1996 to 2016 Their calculated Lerner indices reveal that operational efficiency, profitability, the percentage of non-interest income, capitalization, and GDP growth are all positively connected, whereas bad loans are adversely related

Aguilar and Portilla (2020) use a conventional and an efficiency-adjusted Lerner index to examine the evolution and drivers of market power in Peru's regulated microfinance business from January 2003 to June 2016 Their key argument is that both indexes fell until 2014, then increased dramatically, and that the largest corporations, as well as the most efficient ones, have higher market power

Coccorese, P., Girardone, C., & Shaffer, S (2021) investigate the elements influencing banking market power in the EU area From 2007 to 2019, they collected data from 13 EU banking sectors They calculated a simultaneous equation model in which pricing surpasses marginal cost - a measure of bank market power - as a function of a vector of variables, in order to discover observable elements that are likely to raise or reduce it The study's findings suggest that banks in the EU region have enormous market power, which may be maintained even when sampling diminishes this number In circumstances when there is a smaller branch network, more capital but a less efficient and stable banking system, more severe macroeconomic conditions but strong market power The ongoing competitive convergence of the EU's banking sectors over time is regarded as a success of the integration process that began in the 1990s

2.2.1 External factors

The competitiveness of a bank is influenced by external or macroeconomic forces External factors, according to Delis (2012), are those that are outside the banks' control, such as the inflation rate Delis (2012) proved that while inflation rate has a negative impact to the competitiveness of commercial banks, in contrast, the GDP has a positive effect The contribution of the whole banking industry to national GDP is also seen as a significant external element in a bank’s competitiveness Mirzaei and Moore (2014) also claimed that market power is greater where GDP is higher

2.2.2 Internal factors

Aside from external influences, internal or bank-specific factors can have an impact on commercial banks' competitiveness According to Tabak et al (2012), the major variables influencing commercial bank competitiveness are bank size and equity capital Various academics' empirical data has further studied internal indicators that impact bank competitiveness, such as the ratio provision for credit losses ratio (Fu et al., 2014)

Table 2 1Summary of previous research results

Correlation between Banks' competitiveness to…

Equity capital

Bank size

Credit loss provision ratio

Ayadi et al (2010) -

Schaeck and Cihák

Efthyvoulou and Yildirim (2014) + Fernandez de

Guevara et al

(2005)

+

Fu et al (2014) -

Equity capital: Investors put money into a company in return for ordinary or

preferred shares, which is known as equity capital This is a bank's primary source

of capital, to which debt financing may be added Equity capital is calculated by

environments are, on average, more stable than banks in low-competition environments Capitalization is important in collusive markets as banks with a higher capital ratio are more stable In contrast, Ayadi et al (2010), for the years 2000-2008, explore the factors of market power in seven EU banking businesses They felt that market power grows with market concentration but decreases with cost-to-income ratio, owing to the fact that over the sample period

Bank size: is measured as the natural logarithm of the value of total assets

Firm size is revealed as a variable with a positive and very significant effect on market power (Fernandez de Guevara et al., 2005) He discovered that the rise in the size and efficiency of businesses has minimized the influence of risk charges on bank expenses for the time being All of this explains the Lerner index's history throughout the years, but whether this evolution can be viewed as a gain in market power is questionable However, research by Schaeck and Cihák (2014) shows that banks under a centralized system are more likely to be regarded as too big to fail

Credit loss provision ratio: is calculated by bad debt provision expense

divided by total assets According to article 12, Circular No 02/2013/TT-NHNN, which governs the classification of assets, the levels and methods of setting up risk provisions, and the use of provisions against credit risks in the banking activity of credit institutions and foreign banks branches, specifies the level of provision for credit losses in banking activities The following are the specific provisioning rates:

Group 1: 0%, group 2: 5%, group 3: 20%, group 4: 50% and group 5: 100% The majority of prior research conducted by Schaeck and Cihák (2014) revealed a negative relationship between the provision for credit losses ratio and bank competitiveness

CONCLUSION CHAPTER 2

In this chapter, the author discusses several of the ideas employed in the study, including the theory of commercial bank competitiveness and its determinants The author also provides an outline of determinant factors based on prior research' reference models Starting from basic theories and previous empirical research models on commercial bank competitiveness, as well as the practical situation of the Vietnam banking market, the author has a foundation to apply and establish a panel regression model of factors affecting the competitiveness of Vietnam commercial banks listed on HOSE, HNX, and UPCoM, which will be presented in the following chapter

CHAPTER 3: METHODOLOGY

The research methodology is presented in Chapter 3 The author outlines the sequence in which the study was conducted, as well as the process for handling the acquired data and the criteria for evaluating the results

3.1 Table data collection

In this thesis, secondary data will be gathered It comes from two separate places The first data source will be audited financial statements and annual reports from 28 commercial banks in Vietnam for the research period 2011–2020, which will be obtained through the websites of the commercial banks The second data source is acquired from the websites of international organizations such as the World Bank to corroborate the thesis's reliability GDP and inflation rate data are available from the World Bank The observation sample was collected between

1 An Binh Commercial Joint Stock Bank ABBank ABB

2 Asia Commercial Joint Stock Bank ACB ACB

3 BAC A Commercial Joint Stock Bank BacA Bank BAB

4 Joint Stock Commercial Bank for

Investment and Development of Vietnam BIDV BID

5 Bao Viet Joint Stock commercial Bank BaoViet Bank BVB

6 Vietnam Joint Stock Commercial Bank of

Industry and Trade Vietinbank CTG

7 Vietnam Export Import Commercial Joint

8 Ho Chi Minh city Development Joint Stock

9 Kien Long Commercial Joint Stock Bank Kienlongbank KLB

10 LienViet Commercial Joint Stock Bank LienVietPostBank LPB

11 Military Commercial Joint Stock Bank MB MBB

12 The Maritime Commercial Joint Stock Bank MSB MSB

13 Nam A Commercial Joint Stock Bank NamA Bank NAB

15 Orient Commercial Joint Stock Bank OCB OCB

16 Petrolimex Group Commercial Joint Stock

17 Sai Gon Commercial Joint Stock Bank SCB SCB

18 Southeast Asia Commercial Joint Stock

19 Saigon-Hanoi Commercial Joint Stock Bank SHB SHB

20 Saigon Bank for Industry & Trade Saigonbank SGB

21 Saigon Thuong Tin Commercial Joint Stock

22 TienPhong Commercial Joint Stock Bank TPBank TPB

23 Vietnam Technological and Commercial

24 Joint Stock Commercial Bank for Foreign

25 Viet A Commercial Joint Stock Bank VietA Bank VAB

26 Vietnam International Commercial Joint

27 Public Vietnam Bank Public Bank VIDBank

28 Vietnam Commercial Joint Stock Bank for

Furthermore, the author planned to gather researched variables by evaluating available sources such as academic papers and articles Collecting the examined

variables thorough examination of literature was a huge benefit to the author since it allowed them to create a theoretical framework and acquire a more thorough image

of all the concerns associated with the study topic

3.2 Research process

The study was carried out according to the approach given in model 1 with the purpose of determining the direction and amount of influence of variables on the competitiveness of 28 joint-stock commercial banks in Vietnam from 2011 to 2020:

Figure 3 1 Research process

 Step 1: A brief review of background theory and previous studies

Review the theoretical basis and related previous studies in Vietnam and other countries, then discuss previous studies to identify research gaps and design orientations for the research model for the topic

 Step 2: Descriptive Statistics

The study's data is provided in statistical form, with the minimum, maximum, mean, median, and standard deviation values Briefly summarize the data features

of Vietnamese commercial banks from 2011 to 2020 in order to depict the overall position of banks during this period in accordance with research requirements

 Step 3: Analysis of the impact of factors affecting the competitiveness of commercial banks in Vietnam

Create a correlation coefficient matrix between all of the independent factors and the explanatory variables to identify the nature of the correlation between these variables, which will serve as a foundation for analyzing the correlation between the variables that have an impact on the research model's quality

 Step 4: Regress the variables based on the models and select the most appropriate model

If one of the conventional linear regression's basic assumptions is broken (variable variance, auto-correlation, multi-collinearity) The derived estimations will thus be altered, and using them for analysis will be incorrect To estimate tabular data, fixed effects model (FEM) or random effects (REM) regression methods will be utilized in addition to the fundamental POLS approach To choose the best model, tests like the F-test, Hausman, and Breusch-Pagan are utilized

 Step 5: Using the best model, analyze the results of the regression and discuss the results of the study

The research will assess the model's defects, such as multi-collinearity, autocorrelation, and variable variance, based on the model that is chosen to be the most suitable If defects are discovered, they will be corrected using tools

 Step 6: Suggest policy implications and restrictions

This is the final step of the process, based on the results of the regression, the topic will discuss, draw conclusions and give relevant suggestions and recommendations to answer the research questions as well as solve the problem stated research objectives

The Lerner index, established by Lerner, A.P., is used in this study to assess the competitiveness of commercial banks (1934) This index measures a bank's market power by taking into account the ratio of marginal cost to pricing In a completely competitive market, the selling price is equal to the marginal cost, but in

a monopolistic environment, the selling price is larger than the marginal cost As a result, the Lerner index is the metric most often used in the world to quantify monopolistic power, taking into account the difference between the selling price and the marginal cost

According to Ariss (2010), the more the value of the Lerner index, the greater the degree of rivalry between the weaker banks, and the greater the competitiveness

of each bank

3.3 Research models

As described in section 2.2, the Lerner index consists of five measures thought

to influence commercial bank competitiveness The Lerner index is used as a proxy

in the study to assess bank competitiveness

The major study method is quantitative research based on a regression model using balanced panel data In order to create the theoretical foundation and test the hypothesis framework for the research, the study provides a clearer theoretical basis

as well as empirical data on the impact of factors on competitiveness among Vietnamese commercial banks

Overall research model:

Where: i represents for bank, t represents for time

: intercept of the model

: error of the model

Internal factors include bank size (SIZE), equity capital (CAP), and credit loss provision (LLP) Gross domestic product growth (GDP) and the inflation rate (INF) are external variables

The other variables are measured by:

Table 3 2 The dependent and independent variables of the model

Independent variable

LLP Credit loss provision

GDP Gross domestic product

3.4 Variables explanation

3.4.1 Dependent variable – LERNER index

In economics, the Lerner index is a measure of a firm's market dominance The Lerner index, which was formalized in 1934 by Russian-British economist Abba P Lerner, is stated in the following formula:

where P represents the firm's established price for the item and MC represents the firm's marginal cost The index essentially calculates the percentage markup that

a company may charge above its marginal cost The index has a low value of 0 and

a high value of 1 The higher the Lerner index value, the more the corporation may charge above its marginal cost, and hence the stronger its monopolistic power

3.4.2 Independent variables:

Some independent variables are offered for usage in this thesis, and they are divided into two groups: bank-specific factors and macro-economic variables Bank size, equity capital, and credit loss provision are instances of bank-specific factors GDP and inflation are macroeconomic variables Each variable is addressed in further detail below:

3.4.2.1 Equity capital (CAP)

Equity is the bank's own capital source contributed and supplemented by the

owner during its operation Variable CAP is assessed by the ratio of equity to total

assets, which analyzes the bank's financial capability, according to Berger (1995) and Gaber (2018)

The higher this ratio, the greater the bank's capital, which encourages increased competitiveness by gaining customer trust and hedging business risks (Pasiouras and Kosmidou, 2008) As a result, it has the potential to boost bank competitiveness

H1: Equity capital have a significant impact to Vietnamese commercial bank competitiveness

3.4.2.2 Bank size (SIZE)

Various studies have found that bank size is an internal factor influencing bank competitiveness Because of the unique characteristics of the monetary business, banks' total assets are very large According to Nicole Petria et al (2015), Syafri (2012), and most other studies, total asset size is measured by taking the natural logarithm of total assets to reduce the difference in values between variables

By raising the bank's capital, the larger the bank becomes, the greater the advantage of scale, and therefore the better the competitiveness and client confidence

H2: Bank size affected positively and significantly the Vietnamese commercial bank competitiveness

3.4.2.3 Credit loss provision ratio (LLP)

The credit loss provision ratio indicates how well a bank is safeguarded against prospective losses A higher ratio indicates that the bank is better able to sustain future losses, especially unexpected losses beyond the loan loss provision Credit loss provision ratio is calculated by the ratio of bad debt provision expense to total assets

The greater the ratio, the higher the bank's bad debt ratio, decreasing its competitiveness

H3: The credit loss provision ratio affected negatively the Vietnamese commercial bank competitiveness

3.4.2.4 Gross domestic product growth (GDP)

Banking, like every other business, is inextricably linked to the economy and society One of the numerous consequences of the economy's expansion, as measured by GDP growth, is a rise in banking activity

The higher this measure, the faster the economy grows This encourages the bank to enhance its operations, attract new clients, and increase revenues As a result, banks' competitiveness in the sector will improve

H4: Gross domestic product growth (GDP) affected negatively and significantly the banks’ competitiveness

3.4.2.5 Inflation rate

The rate of inflation is a macroeconomic element that has a positive association with bank performance The World Bank's yearly inflation rate was used

A high rate of inflation will result in increased loan rates, resulting in a shortage of borrowers and, as a result, lowering bank competitiveness

H5: The inflation rate (INF) has a negative impact on the competitiveness

of Vietnamese commercial banks

3.5 Quantitative methods

Quantitative research methods are utilized to identify the study results of influencing trends and influence levels of variables on the competitiveness of commercial banks in Vietnam including particular methodologies as follows, Descriptive statistics, Pooled Ordinary Least Squares (Pooled OLS) model, the Fixed Effects Model (FEM), and the Random Effects Model (REM)

3.5.1 Descriptive statistics

Descriptive statistics are used to offer general information about the variables

in the research model Descriptive statistics include the following: mean (Mean), minimum value (Minimum), maximum value (Maximum), standard deviation (Standard deviation), and the number of observations (Observations)

3.5.2 Pooled Ordinary Least Squares (Pooled OLS) Model

The Pooled OLS technique is the most basic approach for estimating ordinary least squares (OLS) regression models, and it ignores the panel data's spatial and

temporal aspects This means that we presume the influence of variables on profitability is the same across all banks and is consistent over time using this strategy As we can see, this approach is really basic and straightforward

However, the aforementioned assumptions are obviously quite restricted and unlikely to occur in actuality since each bank is unique, and the influence of these distinct qualities on each bank's competitiveness is diverse and fluctuates from year

to year As a result, the estimated outcomes achieved may be inefficient

3.5.3 Fixed Effects Model (FEM)

The FEM is utilized in estimating with the premise that each bank has unique features that might influence the independent variables in the model, or that there is

a correlation between the variables independent of each entity's error component (containing the unique characteristics of the banking system) These idiosyncratic (time-constant) traits are unique to one bank and unrelated to other banks' characteristics However, the limitation of FEM is that it cannot measure factors that are constant over time and increases the multicollinearity of the model, making

it difficult to estimate accurately

3.5.4 Random Effects Model (REM)

This model implies that the variation across units is random and unrelated to the explanatory factors When it is possible to control for each of the varied features between banks, but there is no association between the model's residuals and the independent variables, the Pooled OLS model is used

In FEM, each bank has its own fixed origin, and 28 banks will have 28 distinct slopes; in REM, just one origin is the mean The error component represents the (random) difference between each origin and the mean of the 28 bank slopes

3.5.5 Lagrangian multiplier test

The Lagrangian multiplier test is used to choose the best model from the two Pooled OLS model and REM The test proves that there is no heteroscedasticity in the Random Effect Model if the P-value is over 5% This means the REM is more appropriate than the Pooled OLS model and vice versa

3.5.6 Hausman test

The author will use the Hausman (1978) test to determine whether to employ FEM or REM The test presupposes that there is no systematic difference, which is H0 If the P-value > 0.1 at a significance level of 10%, then H0 is accepted, and the panel data regression approach with the accepted REM random-effects model will

be more successful than FEM If the P-value is less than 0.1 and H0 is not accepted, the fixed-effects model FEM will be more effective than REM

CONCLUSION CHAPTER 3

The author clearly introduced the research process, research data, research methodologies, and research model in Chapter 3 The author has constructed a research model in the research model section based on the theoretical foundation of prior studies indicated in chapter 2 Furthermore, the author explains the independent variables as well as the dependent variables in depth in Chapter 2, clarifying them through the author's calculation formulae, definitions, and hypotheses based on the theory It then acts as the foundation for model execution and conclusions for the subject

CHAPTER 4: RESULTS AND DISCUSSION

In this chapter, the author use Stata software to process the collected data in accordance with the study procedure listed in Chapter 3 The results will then be presented and discussed

4.1 Descriptive statistics

Description statistics will be collected in this section It provides the mean and standard deviation values for each variable in this research As indicated in the previous chapter, a research model is created with the dependent variable as the LERNER and the independent variables classified into two categories The first category includes bank-specific characteristics such as bank size (SIZE), equity capital (CAP), and credit loss provision (LLP) The second category represents macroeconomic data such as GDP and inflation rate (INF) There are a total of 271 observations in the dataset, which covers 28 commercial banks in Vietnam The following is the outcome of descriptive statistics:

Table 4 1 Descriptive statistics results

Variable Observations Mean Standard

Source: Processing through Stata 14.0 software

According to Table 4.1, all variables in the study model are unbalanced table data from 28 joint-stock commercial banks throughout a decade from 2011 to 2020 The following are the descriptive statistics for each variable:

In terms of LERNER: According to the table 4.1 above, the LERNER mean

value of Vietnam's joint-stock commercial banks is 6.64%, with a standard