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Profit on equity or ROE Return on Equity ROE is a ratio calculated by dividing net profit after tax by the total value of equity based on the balance sheet and financial statements at th

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I The theoretical basis

1 Commercial banks

Commercial banks are financial institutions that primarily offer financial services to individuals, businesses, and organizations They engage in various activities such as accepting deposits, providing loans, offering payment services, asset management, and other financial services

2 Profit

Profit is the positive amount of money or financial value that an individual

or organization earns from business activities after deducting costs, tterest expenses, taxes, and other payable amounts It represents the difference between revenue and expenses or production costs associated with the creation and sale of goods or services Profit reflects business efficiency and the ability to generate financial value from business operations It can be used to measure the success and sustainability of an organization or investment decision

3 Profit on equity or ROE (Return on Equity)

ROE is a ratio calculated by dividing net profit after tax by the total value

of equity based on the balance sheet and financial statements at the end of a specific period (such as the first 6 months or the last 6 months of the year) (Ngu6n: Theo vi Wikipedia.org)

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minimizing losses to the maximum extent possible Additionally, it enables the expansion of credit operations, which are the primary profit-generating activities for the bank This variable is expected to move in the same direction as profitability

Hypothesis H1: The capital adequacy ratio has a positive impact on the profitability of the bank

- LOAN: Measuring the loan-to-assets ratio of a bank is important Within the overall asset structure of a bank, the loan-to-assets ratio always holds a significant proportion A higher ratio mndicates that the bank is actively expanding its lending activities to generate higher profits However, as the loan portfolio grows rapidly, the corresponding increase in non-performing loans can lead to a decrease in profitability Following the risk and return trade-off principle, the bank’s lending growth is equivalent to an increase in credit risk, which can negatively impact the bank’s profitability

Hypothesis H2: The loan-to-assets ratio has an inverse impact on the profitability

- ME: Measuring the effectiveness of bank management poses a significant challenge, particularly in cost management This indicator assesses the level of cost incurred by the bank to invest each unit of its assets When the cost ratio increases, it indicates that the bank 1s utilizing a higher amount of expenses for investments This suggests that the bank may not be effectively implementing cost-saving measures, consequently negatively impacting profitability

Hypothesis H3: Management efficiency has an inverse impact on the profitability

- FAR: Measuring the fixed asset ratio of a bank is crucial as it helps evaluate the utilization and management of the company’s fixed assets Analyzing this ratio can determine the effectiveness of the company’s fixed asset management Furthermore, using this ratio in decision-making regarding investment opportunities, reliability, and overall financial health is highly beneficial and insightful Fixed assets are considered significant investments for many companies, highlighting the importance of this ratio They are also essential

components in the company’s operations and production Efficiently managing and effectively utilizing these assets can significantly impact the company’s profitability and financial performance

Hypothesis H4: The fixed asset ratio has a positive impact on the profitability of the bank

- GDP: Measuring the GDP growth rate of an economy is extremely important GDP growth represents the level of expansion of the domestic economy

in a year A stable economy helps businesses operate efficiently in production and business, leading to increased borrowing demand and reduced likelihood of non- performing loans This indirectly brings higher profits to banks

Hypothesis H5: the GDP growth rate has a positive impact on the

profitability of the bank

Table 1: Description of Variables in the Model

4, ROE (Return in Equity) Evaluation Criterion

ROE (Return in Equity) evaluation criterion is the company's efficiency in using equity capital to create profits ROE shows the ratio between profit after tax and equity Criteria to evaluate ROE include:

Relattrve ROE: Comparing ROE with industry peers to evaluate a company's relative performance helps determine whether a company's ROE is better or worse than its competitors

Compare ROE with company goals: Determine the company's ROE target based

on factors such as growth goals, investment levels, and risks Compare the actual ROE with the company's target to evaluate whether it has met its target

ROE Growth: Track ROE changes and growth over time This allows to evaluation of the company's financial performance in terms of increasing ROE from performance improvement measures or business expansion

Compare ROE to return on equity: Evaluate ROE by comparing it to the return on equity required to beat a similar investment If ROE exceeds the return on equity, this indicates that investment in the company achieved a return higher than the minimum return on investment

Financial leverage: Compare the ratio of debt to equity and see if the company using financial leverage brings higher profits or not

Operating performance and asset management: Evaluate the company's financial performance through indicators such as gross profit ratio, net profit ratio, total asset ratio, and company asset ratio

The above evaluation criteria can be obtained from financial reports, research, and reports of financial consulting companies, portfolios, and reports of investment funds

II Research Methodology and Data

1 Research Model and Methodology

1.I Research Model

Based on previous research, this article suggests a research model that includes two groups of variables: macroeconomic factors and internal aspects of a bank The internal bank variables consist of fixed assets ratio (TANG), capital adequacy ratio (CAP), debt-to-equity ratio (LOAN), and management efficiency (ME) The macroeconomic variable used in the model is the growth of the gross domestic product (GDP)

1.2 Research Methodology

The study employed quantitative research using descriptive statistical techniques and regression analysis Regression analysis was conducted using a panel dataset collected for the study The estimation method used was Ordinary Least Squares (OLS) Once the model was established, various tests were conducted, including p-value tests to examine multicollinearity, the Breusch- Pagan test (Breusch and Pagan, 1980) to test for heteroscedasticity, the Breusch- Godfrey test to test for autocorrelation In case the research model encountered issues such as autocorrelation, multicollinearity, and/or heteroscedasticity, the Feasible Generalized Least Squares (FGLS) method would be employed after addressing these issues

1.3 Research Data

The research data consisted of two groups: macroeconomic factors and internal factors of the Bank for Investment and Development of Vietnam (BIDV) The internal factors were collected from audited consolidated financial reports of BIDV The macroeconomic data, specifically the economic growth rate, was collected from the International Monetary Fund (IMF) All data used in the study were collected between 2010 and 2022

III Research results

1 The current situation

In 2020, BIDV's pre-tax profit reached 9.026 trillion VND, exceeding the State Bank of Vietnam's financial plan (106%), but still decreased by 15.9% compared to 2019 This was because BIDV proactively reduced its income by over 6.4 trillion VND to restructure debt and waive interest fees for customers affected by Covid-19, as directed by the State Bank of Vietnam As a result, BIDV's ROE in this year was 9.18%

In 2021, BIDV's ROE reached approximately 13%, while other banks achieved above 20% A low ROE means that the retained earnings for capital replenishment are also reduced, putting pressure on the capital adequacy ratio This is particularly concerning when credit growth is high Therefore, BIDV is facing the pressure to strengthen capital mobilization from external sources to ensure capital adequacy ratio (CAR)

Meanwhile, in 2022, BIDV ranked in the top 10 banks with the highest ROE, with 19.34% This was mainly due to BIDV recording a 70% growth in after-tax profit compared to 2021, reaching over 18 trillion VND This demonstrates that the bank 1s balancing shareholder capital with borrowed capital 1n a harmonious manner

2 Descriptive Statics

Based on the data collected from BIDV's consolidated financial reports for each year from 2010 to 2022, the group presented a descriptive statistical table of the variables used in the study The values in the table include: Mean, Median, Maximum, Minimum, and Standard Deviation of the 5 variables

Table Descriptive statics between observed variables

Source: The group compiled the data using Eviews 10

Comments:

- Capital adequacy ratio: The average rate is 5.15% The minimum value was 4.06% in 2017, and the maximum value was 6.61% in 2010 BIDV achieved

- Management efficiency: The average rate is -1.26% The minimum value was -1.64% in 2012, and the maximum value was -0.94% in 2011

Figure Management efficiency from 2010 to 2022

- Debt-to-equity ratio: According to the descriptive statistics, LOAN has

an average value of 71.50%, a median of 70.91%, a minimum value of 67.51% in

2014, and a maximum value of 78.81% in 2020 During the Covid-19 pandemic, BIDV not only actively issued various credit packages to support customers 1n this difficult period but also reduced lending interest rates for individual customers since August 2020, with the "Connect - Reach Further" loan package, which has a total scale of up to 30,000 billion VND

Figure Debt-to-equity ratio from 2010 to 2022

- Fixed Assets Ratio: The average value is 0.84%, the minimum value is 0.5% in 2022, and the maximum value is 1.03% in 2014

TANG

Figure Fixed Assets Ratio from 2010 to 2022

- GDP Growth: The average value is 9.3%, with a minimum value of 1.68% in 2015 and a maximum value of 19.62% in 2011 During the period from

2011 to 2015, global investment flows continuously declined Specifically,

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according to the State Bank of Vietnam, these flows decreased from 11.8 trillion USD (20% of global GDP) to 2 trillion USD within a span of three years (2007- 2009) Subsequently, they began to grow again and reached 6.1 trillion USD in

2010, but then declined to 5.3 trillion USD and 4.6 trillion USD in 2011 and 2012, respectively, only amounting to one-third compared to 2007, which is equivalent

Figure GDP Growth from 2010 to 2022

3 Testing some limitations of the estimation method

3.1, Multicollinearity testing

In econometrics, multicollinearity is an important issue in regression models It occurs when the independent vanables in the model are highly correlated with each other The presence of multicollinearity can lead to biased indicators in the model, resulting in quantitative analysis results that are not highly meaningful Multicollinearity is a violation of the initial assumption of linear regression models, which states that the independent variables must be linearly independent from each other There are two main causes of multicollinearity: Firstly, nature of variables: Some variables have similar characteristics and show little variation For example, income and salary can be considered similar as they both measure the financial aspect of individuals Similarly, preferences and

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interests can be closely related Age and experience can also lead to multicollinearity as they often increase simultaneously

Secondly, survey environment characteristics: In some cases, differences in the survey environment can cause two variables to become multicollinear For example, two independent variables may not exhibit multicollinearity In survey environment 1 but do exhibit multicollinearity when transitioning to survey environment 2 Therefore, when conducting research in environment 2, it is necessary to adjust the survey design to avoid multicollinearity

To test for multicollinearity in a model, the following methods can be used:

1 Correlation coefficient: We can calculate the correlation coefficient between each pair of independent variables If the correlation coefficient between two independent variables exceeds a threshold (usually 0.8), we can conclude that those variables exhibit multicollinearity

2 Variance Inflation Factors (VIF): VIF is a statistic calculated based

on the regression model It measures the degree of multicollinearity for each independent variable in the model If the VIF value of a variable exceeds a threshold (usually 10), we can conclude that the vanable has high multicollinearity

3, Auxiliary regression model: This method estimates the relationship between independent variables or explanatory variables If the auxiliary regression model indicates that the independent variables are correlated with each other, it suggests the presence of multicollinearity

In this research study, the testing of multicollinearity was conducted using two methods: Variance Inflation Factors (VIF) and auxiliary regression models Testing for multicollinearity helps determine the extent of its impact in a regression model If multicollinearity is detected, it is necessary to consider methods to reduce multicollinearity, such as removing highly correlated variables, using principal component analysis, or employing non-linear regression methods like Ridge regression or Lasso regression This ensures the accuracy and significance of quantitative analysis results in econometrics

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