THE STATE BANK OF VIETNAM MINISTRY OF EDUCATION AND TRAINING BANKING UNIVERSITY OF HO CHI MINH CITY TRƯỜNG ĐẠI HỌC NGÀN HÀNG THÀNH PHO HÓ CHÍ MINH GRADUATION THESIS FACTORS AFFECTING VIETNAMESE COMMER[.]
INTRODUCTION
Background of the study
The rapid pace of globalization and free trade in recent years has created many great changes in the international economic environment Multinational and transnational companies have expanded their operations and have increasingly influenced countries around the world, and international capital flows have also been increasing sharply In addition, the strong development of technology, "Scientific Revolution 4.0" has brought many opportunities and challenges for the development of the Vietnamese economy in general and the system of joint stock Vietnamese commercial bank in particular.
Joint Stock Commercial Banks or any other business operates with the goal of maximizing profitability and growth For banks, profitability is of great significance, associated with business performance, indicating the development direction of banks.
In addition, profitability is the basis for banks to make business decisions Improving profitability is a condition for joint-stock commercial banks to preserve capital, a condition for joint-stock commercial banks to expand lending markets, and invest in technology innovation attract customers However, between profitability and risk there is a trade-off relationship, the higher the profitability, the higher the risk Therefore, bank managers must always balance the trade-off between risk and return when analyzing ratios measuring profitability achieved and accepted risk.
For the economy Bank is one of the important components of the economy, the profitability of the bank is the driving force, the economic lever of the society. Therefore, if the bank operates effectively, ensures financial stability and growth, and has high profitability, it will be the factor that makes the financial sector healthy, contributes to monetary stability, and curbs inflation development, economic growth.
In an international competitive environment, improving the profitability of each bank is the best way to help the banking system develop in a sustainable way, thereby promoting the development of the national economy and increasing the country's reputation.
Profit is also an important indicator to evaluate the success or failure of banking activities, governance, and strategic activities of managers and is one of the factors to determine the "strength" of a credit institution.
2Therefore, stemming from practical requirements in understanding the performance of Vietnamese commercial banks through profit targets, and knowing the factors affecting their goals, leaders will have Appropriate policies to maximize benefits from available resources, minimize costs that may arise The author chooses the topic "Factors affecting Vietnamese commercial bank’s profitability from 2012 to2020" as the research topic.
Research objectives
Theoretical and practical analysis of factors affecting profitability of Vietnamese commercial bank from 2012 to 2020.
Research on factors affecting the profitability of Vietnamese commercial banks. Consider the impact of each factor on the profitability of Vietnamese commercial banks.
Proposing solutions to improve profits for Vietnamese commercial banks.
Research questions
This thesis is aimed to solve some issues:
What factors affect the profitability of Vietnamese commercial banks?
How do these factors affect the profitability of Vietnamese commercial banks?What solutions to improve profits for Vietnamese commercial banks?
Subject and scope of the study
The subject of this study is system of profit evaluation criteria, factors affecting profit in business activities of the bank.
Space scope: 22 commercial banks in Vietnam.
Research methodology
The thesis combines both qualitative research methods and quantitative methods. Qualitative research methods: The thesis is based on the collected data and information, conducts comparison, from which to make comments, evaluate research content At the same time, the thesis uses the deductive method to argue and explain the
3 characteristics of each detail in the data analysis process.
Quantitative research method: Regression analysis of panel data to determine factors affecting profitability of Vietnamese commercial banks, combined with analysis including: ordinary least squares method (Pooled OLS), random effects model (REM),fixed effects model (FEM) The thesis proceeds to build research model, present independent variables and Dependent variables in the model, data sources are taken from financial statements and annual reports of banks and macro variables are taken from the General Statistics Office In addition, the thesis also uses methods such as synthesis, comparison, analysis, inference, description, etc in order to compare with reality, consider and evaluate factors affecting profitability of Vietnamese commercial banks.
Contribution of the topic
The research results of the thesis bring positive meaning not only to the managers of commercial banks but also to investors.
For commercial banks, the research is the scientific basis for the managers and the bank's executive board to identify the factors and the level of impact of each factor on profitability in banking business, detect inadequacies in business operations as well as policies for using existing resources of joint stock commercial banks From there, it is possible to make rational and effective decisions to help joint stock commercial banks improve operational efficiency, enhance competitiveness, and expand their brands.For investors, the research results help investors have an overview of the bank's operations On that basis, it is possible to evaluate and forecast operational efficiency,which helps investors make informed decisions while investing.
Structure of the thesis
The research thesis will be presented in five chapters, including:
Chapter 1: Introduction to the topic
An overview of the research problem, the reason for choosing the topic, the research problem, the research objective, the object, the research scope and the meaning of the research.
Chapter 2: An overview of the theory of profit and previous studies on factors affecting the profitability of Vietnamese commercial banks
This chapter presents the theories related to the thesis such as: profits, profit
4 evaluation criteria in commercial banks' business activities and factors affecting profitability in commercial banks' business activities, a brief overview of related studies.
Make initial assumptions about the impact of factors on profitability of commercial banks, introduce how to choose data sources, choose appropriate research methods and set up regression models.
Chapter 4: Research results and discussion Research conclusions.
The study will conduct descriptive statistical analysis, analyze the relationship between the variables and analyze the regression results to determine the impact of the independent variables on the dependent variable.
Chapter 5: Conclusion and some recommendations Conclusion and suggested solutions.
Summarize the results of the study, outline the limitations of the research topic and suggest future research directions.
THEORETICAL BASIS AND LITERATURE REVIEW
Theoretical basis about commercial bank
Commercial banks are credit institutions that perform all banking activities and other related business activities for profit purposes (Consolidated documents No. 20/2018/VBHN-NHNN, the State Bank of Vietnam).
Commercial bank is a financial institution which is operating under two business scopes: one is to federally insure deposits and to pay interests to the depositors and the second is to use its charter to issue loans, to check cash balance and clearing services, and to underwrite securities (Getter, 2016) Commercial bank plays prominent role in modern economy in circulating financial resources (Tariq et al., 2014) Other definition of commercial bank is a financial intermediary which effectively channel idle funds in the market to those who need credit to invest into valuable production and business opportunities and personal purposes (Tuyishime et al., 2015) Commercial bank is further divided into public sector bank (the bank with major of stake is hold by the government), private sector bank (the bank with major of stake is hold by private individuals) and foreign bank (the bank with head office located in other countries outside of a nation) (Kalpana & Rao, 2017) Commercial banks establish maladjustment and impediment and contribute to the development of the economy (Mongid et al.,
2012) The operation of commercial banks is aligned with monetary policies of a nation and they play the main role of controlling cashflow given to expected rate of returns and emissions (Erina & Lace, 2013).
In summary, the term of commercial bank used in the study is defined as a financial institution which operates in the way of holding deposit, paying interests to the depositors, opening credit to different economic sectors and facilitates economic development of a country.
Theoretical basis about commercial bank profitability
Profitability is determined as one of that reflect efficient banking system, along with high service quality and sufficient funding indicators (Wang & Wang, 2015).When the banks earn high profitability, their operations are safe and sound (Bikker &Vervliet, 2017) It is also the indicator to reflect whether the banks are in threating situation (Iacobelli, 2017) It is defined as the difference between the profit extracted from its assets and the expenses incurred in its liabilities (Yuksel et al., 2018). Profitability reflects the efficiency of the management in making benefits from all the business operations of an organization, firm or company (Muya & Gathogo, 2016). Profitability refers to amount of money that a company can produce with the resources it has The goal of most organization is to maximize profitability (Niresh & Velnampy,
2014) One precondition for any long-term survival and success of a business is profitable Profitability is generally measured using accounting ratios with the commonly used profitable ratio being ROA ROA determines the amount of the profit earned per shilling of assets This reflects the efficiency with which the bank's managers use bank's investment resources or assets in generation of income (Sehrish, Irshad & Khalid, 2010) It is also determined as the banks' ability in compensation of credit losses, capital retention, and the support for future development (Pastory & Marobhe,
2015) Behind of profitable generated from interest income, banks also earn substantial profit from non-interest income which is collected from the charge to the customers to use financial services (DeYoung & Rice, 2004) Some discussions related to non- interest income of the banks were discussed by other researchers and this income sources implied for less reliance of the banks to interest income while relating to the banks' business and operational stabilization, leveraging risk diversification and the increase of fixed cost to invest into facilities to deliver banking services to the customers (Kohler, 2013).
Given to the difference understandings of bank profitability, the term of bank profitability used in the thesisis defined as a relative number (a percentage), which expresses the ratio between profit and revenue Commercial bank profitability made during the year represents the capability of making profit, in which profit is expressed through the results of business activities of the bank, such as: mobilizing capital, lending, discounting, guaranteeing, providing financial services and other related activities The time for determining annual profit is made at the end of December 31 when the annual settlement, preparing annual financial statements For the determination of profits to be accurate, the total revenue and expenses of the entire system must be accurately determined during the year.
2.2.2 Factors affecting commercial bank profitability
Internal factors or bank-specific factors affect commercial bank profitability Key factors that reflect financial soundness such as liquid asset ratio (liquid assets divided by total assets), non-performing loan ratio (non-performing loans divided by total loans) and regulatory capital to risk-weighted assets affect bank profitability (Albulescu,
2015) Other indicators such as bank size, operating efficiency, asset management efficiency and portfolio management also affect bank profitability (Erina & Lace, 2013). Empirical evidence from different researchers explored more internal indicators affecting bank profitability such as management decision and policy objectives set by the banks (Staikouras & Wood, 2004).
Beside internal factors, bank profitability is also under the influence of external factors or macro-economic factors According to Blerta, B (2014), external factors refer to those which are not under the banks' control such as inflation rate, market share,industry growth and interest rate The contribution of overall banking sector to national gross domestic product (GDP) is also considered as important external factor to the bank profitable (Bezawada & Ranajee, 2018) Economic growth is determined as external factor and its effect on bank profitability is confirmed (Gul et al., 2011;Rehmandet al., 2018).
Theoretical framework
According to Jensen and Meckling (1976) define an agency relationship (or fiduciary relationship) as a contractual relationship whereby shareholders (principals) appoint, appoint another, company managers (representatives-agents) to perform the management of the company for them, which includes giving authority to make decisions about the disposal of the company's assets Agency theory holds that, if both parties to this relationship (shareholders and company managers) want to maximize their own interests, then there is reason to believe that corporate managers will not always act in their own interests, i.e the shareholders This implies that there is always a potential risk of a conflict of interest between a shareholder and an agent due to the separation between shareholder ownership and the agent's controlling function.
Agency Theory suggests that companies should establish an appropriate board structure to monitor the behavior of managers in order to prevent the abuse of power by managers over company resources to pursue personal interests (Jensen and Meckling, 1976).
The theory is applied to explain that the existence of foreign shareholders in the relationship with the company's executive management may affect the company's profits.
Relative Market Power argues that companies with large market shares and differentiated products can rely on market power for uncompetitive profits For example, a large, long-established bank with many advantages in terms of brand name and product quality can position the product at a higher level in the market and earn more profits (Nguyen Cong Tam and Nguyen Minh Ha, 2012) Arguing according to the theory of market power, a bank with advantages in market share and product differentiation or advantages from large capital can use its market power to reap more profits through increasing prices of products and services, increasing constantly market share and scale This increase to a certain extent can create great pressure on competitors, reduce market competition and commercial banks gain more profits thanks to monopoly prices (if any) Therefore, this theory states that commercial banks with larger capital scale have higher profitability.
Balanced Portfolio Theory, also known as Modern Portfolio Theory, suggests that it is possible to minimize market risk in order to achieve expected return through building a portfolio Investments have been diversified, simply say: "Don't put all your eggs in one basket" According to modern portfolio theory, an efficient portfolio is one that has the lowest expected return for risk or one that has the expected risk but offers the maximum return Therefore, commercial banks can increase profitability through diversification of the bank's investment portfolio, which depends on the decisions and effectiveness of the bank's governance (Nguyen Cong Tam and Nguyen Minh Ha, 2012).
This theory is used to explain portfolio diversification, which generates more non- interest income, which increases bank profits.
Trade-off Theory proposed by Kraus and Litzenberger (1973), firms can choose an optimal capital structure to maximize firm value based on the trade-off between the benefits and costs of the debt use This theory aims to explain why banks are often financed partly by debt and partly by equity A big reason why banks cannot finance completely with debt is because besides the existence of tax shield benefits from debt,debt financing incurs many interest costs, affecting bank profits Thus, a bank with a low equity-to-asset ratio due to heavy use of debt has a high expected interest expense,which increases the bank's risks and costs, leading to a decline in the bank's profit.This theory is applied to explain the equity structure in the relationship to profitability.
The meaning of profit assessment
For banks: Evaluating profits as well as identifying factors affecting profitability in business activities of commercial banks helps bank managers and executives see operational efficiency and financial advantages of their own banks, as well as points that have been achieved and have not been achieved, and inadequacies, etc to make timely and appropriate adjustments, aiming at financial goals such as minimizing costs, maximizing profits and growth income in a sustainable way Thus, the evaluation of profits in business activities of banks has always been of primary importance and concern in order to improve the position and competitiveness of commercial banks in the financial market The evaluation of profits in a certain period can help managers see operating trends and predicting operating results in general and profitability in particular in the next periods Besides, with positive profits, healthy financial indicators can increase employees' trust and dedication to the bank and avoid situations human bleeding in the banking industry.
For investors: Through the evaluation of profits in the business activities of commercial banks, investors will see profits and development prospects, this is the basis for investors to make investment decisions Besides, evaluating profits also shows investors the level of dividend payment, ranking Stock market class and stability of share price so that they can evaluate the effectiveness of the investment in order to set a threshold for risk tolerance as well as minimize the opportunity cost of the investment.For state agencies: the assessment of business profits of commercial banks helps state management agencies carry out inspection and control to ensure that commercial banks comply with policies, regimes and laws regulations in banking activities.
On the other hand, the evaluation of profits of commercial banks will be a source of information to help authorities and state banks rate the credit of banks There are timely corrections to avoid inefficient banking operations leading to losses losses, bankruptcy had a knock-on effect, causing stagnation and crisis to the entire economy. Therefore, analysis and evaluation is an indispensable job for each bank This is an important step in banking governance to enhance competitiveness, creating a premise for the overall development of the banking system and towards integration with regional and international banking systems.
The existence and development of commercial banks as well as business performance of commercial banks are mainly based on the bank's profits Currently,domestic and foreign analysts have used many different indicators to reflect the profitability of commercial banks.
The indicators reflect the profitability of commercial banks
Most of the studies on profitability are measured through return on assets (ROA), return on equity (ROE) as the studies so far by Abreu and Mendes (2002), Athanasoglou, Delis and Staikouras (2006), Wahdan and Leithy (2017).
ROA is an indicator reflecting the management effectiveness, measuring the ability of the bank's board of management to convert a bank's assets into net income.
Net Income Average total asset (X) Total assets at end of previous year + Total assets at end of current year
Source: Principals of finance, Scott, B & Eugene, F B (2015)
In which, net income is the earning after-tax, while assets are formed from equity and loans, so ROA is affected by tax policy and interest expense Earnings after-tax is taken from the income statement and total assets are taken from the balance sheet ROA is a measure of how much profit a business is generating from its capital A high value of ROA shows that the bank is functioning well in making profits by utilizing the assets and performance of the bank is good However, it is necessary to review the bank's activities if ROA is above the stable level ROA is calculated from financial report of the firms through an equation of which it is equivalent to net profit after taxes divided by average total assets (Samiloglu et al., 2017) The firms expected that their ROA value to be increased and higher ROA value means higher performance and increasing value of ROA is attractive to the investors (Saragih, 2018).
ROE is an indicator to measure the percentage of income that a shareholder of a bank receives from an investment in a bank In other words, return on equity is an indicator of the efficiency of the equity investment.
Net Income Average total equity (X) Total equity at end of previous year + Total equity at end of current year ( * ) 2
Source: Principals of finance, Scott, B & Eugene, F B (2015)
ROE is defined as the ability of a firm to generate profit upon every share of its capital (Rosikah et al., 2018) ROE is calculated through an equation in which net profit after taxes divided by average total shareholder equity (Kabajeh et al., 2012) LikeROA, the firms always expect higher ROE to attract investors in the market, and ROE valued between 15-20% is generally considered good (Faisal et al., 2018) ROE is a measure of profitability that calculates how many dollars of profit a business generates with each dollar of shareholders' equity (Rose, 2002), so it always receives great attention from investors If this ratio is positive, the bank is profitable In contrast, if the ratio is negative, the bank is trading at a loss At the same time, higher ROE proves that the bank is balanced in the use of shareholder capital compared to its borrowed capital effectively to generate profits during its operation Therefore, a high value of ROE shows that the bank is functioning well in managing the shareholder's equity and generating revenues to shareholders.
RESEARCH METHODS
Research model
According to analyses that have been done in many countries around the world as well as studies in Vietnam In this thesis, profit will be measured by ROA, and ROE along with the effects of other variables Similar to the study of Ho Thi Hong Minh and Nguyen Thi Canh (2015) The estimated model represents as follows:
Yit = α + β1X1it + β2X2it + β3X3it + β4X4it + β5X5it + β6X6it + β7X7it + β8X8t + β9X9t + ei,t, where:
Yit: measures the profit of the “i” commercial bank in year t β1X1it: variable measures variable Bank size of the “i” commercial bank in year t β2X2it: variable measures of the Liquidity ratio of the “i” commercial bank in year t β3X3it: variable measures of the Equity ratio of the “i” commercial bank in year t β4X4it: variable measure the ratio of outstanding loans of the “i” commercial bank in year t β5X5it: variable measure the non-performing loans of the “i” commercial bank in year t β6X6it: variable measure Operational efficiency of the “i” commercial bank in year t β7X7it: variable measure Income diversification of the “i” commercial bank in year t β8X8it: variable measure Inflation rate in year t β9X9it: variable measure Economic growth in year t ei,t: model error term
Based on this construction model, the author uses the OLS method to regress the model in 3 approaches Pooled OLS, FEM, REM; after that, the study uses Hausman test and Likelihood ratio to choose the most suitable approach to test the research hypotheses.
In this thesis, the author limits the test to some of the main factors that clearly affect the profitability of commercial banks In the specific regression model of this study, profit is represented by Profit after tax on average total assets and Profit after tax on average total equity The factors affecting profitability are included in the model: (1) Bank size, (2) Liquidity ratio, (3) Equity ratio, (4) Loan balance, (5) Non- performing loans, (6) Operating Efficiency, (7) Income diversification, (8) Economic growth, (9) Inflation.
Bank size (SIZE) is an independent variable that is calculated as the logarithm of total assets Total assets data is taken from the bank's balance sheet.
Calculation formula: SIZE = Log (total assets)
Liquidity ratio (LIQ): is calculated by taking cash and cash equivalents divided by total assets showing the ability of banks to fulfill their obligations to customers, especially depositors The higher the liquidity ratio, the higher the ability to fulfill obligations to customers, creating a reputation with customers who can develop more profitable services for the bank, collected from the bank's balance sheet.
Calculation formula: LIQ = Cash and cash equivalents/Total assets
Equity ratio (CAP): is measured by the ratio of equity to total assets of the bank. Bank equity and total assets value data is collected from the bank's balance sheet.
Calculation formula: CAP = Total equity/Total assets
Loan balance ratio (TLA): using the ratio of outstanding loans/total assets as a research variable because lending is the main profit-making activity for banks and when the loan balance changes, it will have a direct impact on the revenue of the bank which in turn will affect the profit of the banks The data is based on the bank's balance sheet.
Calculation formula: TLA = Total loans/Total assets
Non-performing loan (NPL): Ratio of bad debts to outstanding loans This variable reflects the quality of the bank's outstanding loans When the bad profit ratio increases,the bank has to make an increase in provision, increasing costs for the bank and reducing the bank's profit, affecting the bank's profit The data is calculated based on the bank's balance sheet.
Calculation formula: NPL = Non-performing loan value/Total Loan value
Operating Efficiency (CIR): The ratio of operating expenses to income This variable reflects the quality of cost management Banks that manage costs well, that is, a dollar of expenses brings more income to the bank will increase profits The data is collected from the bank's income statement.
Calculation formula: CIR = Operating expenses/Operating income
Income diversification (IDR): income diversification index is calculated based on the proportion of interest income, income from service activities, income from business and investment activities, income from other activities to total income Income diversification increases profitability thanks to high profit margins from non- interest activities, minimizing dependence on certain sources of income.
Calculation formula: IDR = Non-interest income/ Interest income
The inflation rate (INF) raises the price level of the economy It shows the level of inflation of the economy The inflation rate is based on the consumer price index collected from the report of the General Statistics Office.
Calculation formula: INF = (CPI t - CPI t-1 )/( CPI t-1 ) * 100%
Economic growth (GDP) is an independent variable collected from the report of the General Statistics Office.
Calculation formula: GDP = (GDP t -GDP t-1 )/( GDP t-1 ) * 100%
Research hypothesis
From the profit theory and empirical evidences done at home and abroad, the research hypothesizes about the influence of 9 independent variables on profit as follows:
• H1: Size has a positive effect on commercial banks' profits
Bank size is frequently used to capture the economies of scale and non- economies of scale in banks (Ayadi and Boujelbene) The larger the asset size, the higher the profitability of the bank due to the advantage of scale With economies of scale, banks with large assets, the ability to expand market share, will have many favorable opportunities in the process of lending to customers, expanding distribution of products and services, and saving transaction costs, which in turn can increase profits However, economies of scale can arise when the size of the bank is too large The management of this asset block requires eminently qualified human resources and costs a lot The unreasonable expansion of the bank's operation scale will cause many difficulties in management, require highly qualified human resources and incur high costs; at the same time, it can cause managers to make wrong decisions in expanding financial leverage and poor quality lenders, leading to the risk of profitability, reducing the bank's profitability Previous studies have also found rather conflicting results when looking at the relationship between these two variables.
Emery (1971) found that larger banks will earn more profits, because large banks will have the advantage of mobilizing capital at a cheaper price, thereby reducing costs to doing business However, Stiroh and Rumble (2006) argue that the above relationship is negative because the larger the bank, the more difficult it is to manage, especially when the bank has to face difficulties, especially when the scale increases just to follow a horizontal growth strategy will add costs without yielding results In addition, agency costs, administrative costs, and other costs also increased significantly.
• H2: Liquidity Ratio has a negative impact on commercial banks' profits
Liquidity ratio is calculated by taking cash and cash equivalents divided by total assets (Doina & Mircea, 2008) This ratio reflects the ability of firms to repay their debt obligations in short-term (Costea & Hostiuc, 2009); Bwacha &Xi (2018) examined the impact of liquidity on profitable in banking sector and they identified that cash and cash equivalents to total assets ratio positively affected ROA of the banks Lipunga (2014) examined the effect of liquidity on profitable commercial banks and this ratio was measured by cash and cash equivalents divided by total assets.
Obtained result showed that liquidity ratio affected positively and significantly ROA of commercial banks Similarly, Karani (2014) also reached the same conclusion.
• H3: Equity ratio has a positive impact on commercial banks' profits
The ratio of equity to total assets is an indicator of a bank's capital adequacy ratio,one of the indicators to assess the financial health of commercial banks according toIMF standards (IMF, 2006) Regarding the ratio of equity to profitability, based on the theory of efficient structure of behavior, banks with lower equity ratio have less linkage,and therefore lower profits In addition, according to the theory of the moral hazard, the lower the equity ratio of banks, the higher the loan risk because the increased risk of bad debt reduces the profitability of commercial banks Athanasoglou (2006) argues that equity is the bank's own capital available to support the business, thus the bank's capital acts as a safety net in the worst case Alper and Anbar (2011) argue that equity to total assets is one of the basic coefficients of capital strength With a higher ratio of VSCH, less external capital will be required to increase the bank's profitability One study tested the direct effect of capital on profitability of commercial banks Barth et al (2004) through the study of data at banks around the world, found that high capital holding ratio means less bad rate Berger et al (2013) empirical research on 42 banks in Asia found that equity has a negative impact on profitability through the variable of reserve ratio and profitability Shrieves & Dahl (1992) also adopted US data and found that the results between the two factors are in the same direction According to research by Nguyen Thi Hong Vinh & Le Phan Thi Dieu Thao (2016), bank capital has a negative impact on profitability In short, banks with large equity capital are able to weather financial shocks as well as bring confidence to investors and savers, helping banks to increase access to capital at low cost and risk, thereby increasing profitability.
• H4: The ratio of outstanding loans has a positive impact on commercial banks' profits
The ratio of outstanding loans reflects the business strategy of the bank, when this variable is high, it shows that the bank focuses more on credit activities Most literature suggests that bank profits are expected to increase as the loan portfolio increases relative to other items Although the cost of holding loans increased, profits increased as the loan-to-asset ratio increased.
In an empirical study, the results show that an increase in the loan ratio creates risk for the loan portfolio leading to a decrease in profitability, whereas a reasonable increase in the loan portfolio will increase interest income, making profits increased (Angela Roman, 2013) The results of (Sufian, 2009) loan balance has a positive effect on return on average assets (ROA) Most of the previous studies suggested that focusing more on credit activities contributes to higher profits.
• H5: The quality of outstanding loans has a negative impact on commercial banks' profits
According to the IMF (2006), the ratio of bad debt to total outstanding loans is one of the core indicators to assess the financial health of a bank This variable reflects the quality of the bank's outstanding loans Profitability is directly related to the quality of outstanding balance on the balance sheet When a customer incurs overdue debt, it means an increase in doubtful assets, requiring the bank to make provision When there is a cost of provision for loans to customers, it will reduce the bank's operational efficiency, thus reducing profits In many empirical studies, it has been shown that a high NPL ratio to total outstanding loans represents inadequate credit management and low credit quality (Halil Emre, 2012) A change in credit risk may reflect a change in the loan portfolio, which affects the bank's profitability (Sufian, 2009) Research results of Ayanda et al (2013), Osuagwu (2014) show that the quality of bank loans has a negative impact on profitability In the reverse causal relationship, Achou and Tenguch
(2008) use data from the Central Bank of Qatar for the period 2001-2005, the research results show that banks with high profitability have low NPLs due to good management strategies Reasonable credit risk management Pham Huu Hong Thai (2013) evaluated the impact of bad debt on the profitability of 34 Vietnamese commercial banks in the period 2005-2012, the results showed that bad debt has a negative impact on profitability of banks.
• H6: Effective cost management has a negative impact on commercial banks' profits
The expense-to-income ratio is an important financial indicator, especially in evaluating banking performance It shows the correlation between expenses and income of that bank Cost effectiveness reflects the ability to adjust the relationship between output and input ratios to achieve efficiency Through this indicator, investors get a more general view of the profitability of the bank's business The smaller the ratio, the better because then it takes less costs to generate the same level of income or in other words, the bank gets more profit, hence the higher profit margin Banks with good cost management, i.e a dollar of expenses bring more income to the bank, will help the bank achieve a high level of profitability.
Based on this inference, Berger & De Young (1997) conducted an audit To investigate the effect of cost effectiveness on credit risk The study found cost- effectiveness to be an important indicator of a bank's future NPLs and risk Therefore,inefficient banks will be under great pressure from credit risks, reducing the bank's profitability Similarly, Hess et al (2008) also chose the quality of cost management as one of the factors affecting profitability for research Previous studies by Alexiou and Sofoklis (2009), Dietrich and Wanzenried (2011) also found a significant effect of efficiency on profitability.
• H7: Income diversification has a positive impact on commercial banks' profits
Income diversification in the banking sector is the non-interest income in a bank's operating income structure This independent variable represents the business strategy of the bank, when the high ratio shows that managers pay more attention to non-credit activities These activities are considered to be more effective for banks than credit activities, partly because they do not require a large amount of capital and do not bear credit risks Banks that offer a wider range of products and services will generate more demand and will earn more income As a result, income diversification changes the bank's performance in terms of profitability.
Theories of financial intermediation imply that an increase in returns to scale is related to income diversification Many studies have provided evidence of positive effects when banks implement income diversification strategies, such as: According to Saunders & Walter (1994), banks can take advantage of the information collected in the process of lending to use and finance other financial services, including underwriting securities Likewise, by providing underwriting services for securities or insurance, banks can gain more information, reduce information asymmetry with customers, and thereby promote lending efficiency.
As a result, banks with diversified operations can support and increase economies of scale Smith et al (2003) found evidence on the stability of non-interest income, thereby contributing to the stabilizing effect of bank profitability Supporting the view that income diversification is beneficial for bank profitability is also the study of Chiorazzo et al (2008) The authors explain that small-sized banks will have an advantage when it comes to income diversification Since non-interest income accounts for a small proportion of total income, the increase in non-interest income increases financial efficiency Thus, income diversification will increase the opportunity to generate higher income, thereby having higher profits.
On the other hand, previous researchers such as Maksimovic and Philips (2002),DeYoung and Roland (2001) and Stiroh (2006) have argued that income diversification is not a guarantee for low levels of bad debt in banks Because too much business will make banks unable to focus on their area of expertise and thereby reduce the effectiveness of loan supervision, as a result, it will increase the possibility of loans turning into bad debt Therefore, banks should focus on one business segment that will be able to take advantage of managers' experience in reducing the probability of bad debt.
With the view that the impact of income diversification can limit the risks of banks, Smith et al (2003) show that, not relying too much on interest income will contribute to stabilizing profits for banks Non-interest income from service fees is usually more stable than interest income from lending, so banks can reduce the risk of income diversification (DeYoung and Roland, 2001).
• H8: Economic growth has a positive impact on commercial banks' profits
Research data
The study uses secondary data including financial and accounting data of commercial banks, macroeconomic data for the period 2012–2020 Financial and accounting data representing factors inside the bank, including the items in the balance sheet and income statement, are collected from the bank's annual audited financial statements Annual GDP and inflation data are collected from the report of the State Bank of Vietnam and the General Statistics Office The research period was selected based on the fact that this is a period of many fluctuations for banks such as mergers and acquisitions deals due to the impact of the economic crisis, leading to a great change in the Vietnamese commercial banking system The study was carried out with the type of joint stock commercial bank, however, one bank did not publish the financial statements or explain the attached financial statements, so the remaining research results were 22 banks with data for the period from 2012 to 2020, forming panel data with 198 observations Panel data are suitable for research because by combining time series of cross-observations, panel data gives us data with more useful information, more bias,less multicollinearity between variables more, more degrees of freedom and more efficient.
Selection of regression model and tests
With the aim of studying the factors affecting the profitability of Vietnamese commercial banks, the study was carried out with the following process: Using descriptive statistics, correlation analysis, and regression analysis methods of panel data with the help of Stata 14 software to determine study results.
Pooled OLS –Pooled Ordinary Least Squares
Pooled OLS –Pooled Ordinary Least Squares is a regression model in which all coefficients are constant over time and on individuals This is the simplest approach and the simplest model as it does not consider the space and time of the combined data but only estimates by conventional OLS regression Therefore, this model may give incomplete results and distort reality about the relationship between independent and dependent variables.
Pooled OLS model basic table data has the form:
Yit = α + β1X1it + β2X2it + + βnXnit + unit, where:
Yit: The dependent variable of the observation i in the period t α: Intercept coefficient β1, β2, , βn: Individual regression coefficients
X1it, X2it, , Xnit: Independent variables of observation I in the period t Unit: the error term
With the assumption that each unit has distinct characteristics that can affect the explanatory variables, FEM analyzes this correlation between the residuals of each unit and the explanatory variables, thereby controlling and separating the influence of these separate characteristics (time-constant) from the explanatory variables so that we can estimate the net effects of the regressor on the dependent variable.
The simple FEM model has the form:
Yit = αi + β1X1it+ β2X2it + + βnXnit + unit
The above model has added the index “i” for the intercept coefficient “α” to distinguish the interception coefficient of each different bank that may be different, this difference may be due to the different characteristics of each bank or the difference between management policies and operations of banks.
This model assumes that variation between units is assumed to be random and uncorrelated with the explanatory variables The simple REM model takes the form:
Yit= α + β1X1it + β2X2it + + βnXnit + εi + uniti + unit
With εi + uniti: Error of composition of different objects (different characteristics of each enterprise)
Unit: Error of other combined components of both individual characteristics by object and over time.
After running the model, perform a model fit test to select a suitable model.
Based on the model's adjusted coefficient of determination R 2 , this coefficient shows how much of the independent variables in the model explain the variation of the dependent variable From there, conclude the appropriateness of the model.
Check the fit of the model
H0: R 2 =0 (All independent variables have no effect on the dependent variable) H1: R 2 ≠0 (There is at least one independent variable that affects the dependent variable)
Based on the regression results, if:
Prob value of F statistic < 0.05: Reject hypothesis H0
Prob value of the F statistic > 0.05: Accept the hypothesis H0
The restricted F test is used to select the appropriate model between the two Pooled OLS and FEM models.
With k, n are the numerator and denominator degrees of freedom, respectively Assumption:
When the P_value < 0.05, we reject H0, so the FEM model is more suitable and vice versa.
To consider the more suitable FEM or REM model, we use Hausman test The essence of this test is to see if there is an autocorrelation between εi + uniti and the independent variables.
H0: εi + uniti and the independent variable are not correlated
H1: εi + uniti and independent variable are correlated
When the value of P_value < 0.05, we reject H0, then εi + uniti and the independent variable are correlated with each other and the FEM model is more suitable In contrast, the REM model is more suitable.
Choose between REM model and Pooled OLS model, with the following hypothesis:
H0: Variance of random errors εi + uniti = 0
H1: Variance of random errors εi + uniti 0
If the P-value > α allows the conclusion to accept the hypothesis H0, then thePooled OLS model will be selected, otherwise the REM model will be suitable for the study if H0 is rejected.
RESEARCH RESULTS AND DISCUSSION
Descriptive statistics
Table 4.1 summarizes the dependent and explanatory variables of 22 banks in Vietnam in the period 2012-2020 From the table above we observe that:
Table 4-1 Descriptive statistics of variables in the regression model
Variabl e Obs Mean Std Dev Min Max
The average ROA value of all 22 banks in the sample is 0,0087 with a standard deviation of 0,0069 According to the collected data, the lowest ROA value is -0,0256 (PGB in 2012) and the highest value is 0,0306 (TCB in 2020).
Meanwhile, the mean of ROE is 0.1044 with a standard deviation of 0.0755. According to the collected data, the lowest value of ROE is -0,1628 (PGB in 2012) and the highest value is 0.2957 (VIB in 2020).
It shows that there is a huge difference in the ratio of return on total assets (ROA), the ratio of return on total equity (ROE) between efficient and inefficient banks. Although the ROA ratio of Vietnamese banks in recent years has tended to quite stable but still quite low compared to banks of other countries in the region The value of ROE is much larger than ROA, showing that the growth rate of total assets tends to be slower than the growth of profit after tax, however, the operation of banks is mainly dependent on credit, so it is difficult to generate income profit breakthrough Profits of Vietnamese banks are better thanks to favorable macroeconomic conditions and growth in earnings from core businesses Regarding profitability, Moody's pointed out that the average return on total assets of banks increased to 0.9% last year, from 0.7% in 2016 Profit will continue to improve in 2021-2022.
In terms of bank size, this variable is transformed by natural logarithm function. Mean and standard deviation values are captured at 18,7283 and 1,1402 Min value is 16,5023 while the max value is 21,1398.
In terms of liquidity ratio, this variable has mean value of 0,0436 while standard deviation value is captured at 0,0643 According to collected data, LienVietPost Banks’ liquidity ratio in 2013 was the lowest at 0,0026 The highest is KienlongBank in 2020 with the rate of 0,2823.
In terms of equity ratio, this variable has mean value of 0,0922 Its standard deviation value is calculated at 0,0374 Min and max values for equity ratio are 0,0406 (BIDV in 2017) and 0,2383 (SGB in 2012).
The ratio of outstanding loans to total assets (TLA) was 0,5845, showing that in commercial banks, lending activities account for the highest market share Although credit growth has many potential risks, lending is still the backbone of the banking industry During the research period in 2020, BIDV had the highest ratio of outstanding loans to total assets at 0,8 and MSB in 2014 had the lowest ratio at 0,2353.
Considering the minimum and maximum values of the variable TLA, it shows that many banks have too high outstanding loans to total assets, not well coordinated in the process of mobilizing and lending, specifically banks often mobilize and borrow capital. short periods of time, then cycle them for longer periods of time As a result, many banks face a mismatch in terms of maturity between assets and liabilities, leading to low liquidity.
In terms of NPL, NPL measures the value of non-performing loans to total loan book values According to regulations, if bad debts increase, that bank must make provisions corresponding to % of those bad debts This will contribute to reducing the profits of banks (although in essence, this deduction still does not run out of the bank's pocket). Techcombank has the highest ratio with 0,1265 in 2020 Meanwhile Vietcombank in 2013 has the lowest ratio with 0,0047 The average ratio of banks during the study period was 0,0229.
The ratio of operating expenses to income (CIR) shows that with VND 0,52 of operating expenses, it will generate 1 VND of income for the bank With the minimum and maximum value of CIR being 0,068 of LienVietPost Bank in 2014 and 0,874 of KienLong Bank in 2020 respectively, showing that there is a clear difference in the performance of banks The smaller the ratio, the more efficient the bank is.
The average income diversification ratio (IRD) of commercial banks in the research period was at 0,1012, showing that although interest income in Vietnamese commercial banks still accounts for a large proportion, banks are tend to diversify income more. Currently, revenue from non-credit services accounts for over 20% to 35% of total bank income on average In which, revenue from non-credit services is mainly from fees (accounting for about 60% of total revenue from non-credit activities) besides revenue from business and investment services (such as foreign exchange trading, gold and financial services) derivative itself) With the aim of increasing the proportion of income from non- credit services to total income to 45- 55% BIDV, Vietinbank and Vietcombank are the commercial banks whose non-credit services are deployed early and with good results.
GDP ratio's mean value is 0.0593 while the standard deviation value is 0,0124 Min value is calculated at 2,91% while max the value is 7,08%.
In terms of the inflation rate, the mean value and standard deviation values are 0.0389 and 0.0188 Min and max values are 0.63% and 6,81%.
4.1.1 Check the correlation between variables
To determine the relationship between the variables in the model, the study uses correlation coefficient analysis to measure the degree of correlation between the independent and dependent variables The positive correlation coefficient reflects the positive correlation relationship between the dependent variable and the independent variable, whereas the negative correlation coefficient reflects the negative correlation relationship between the dependent variable and the independent variable.
Table 4-2 Correlation matrix between variables
SIZE LIQ CAP TLA NPL CIR IDR GDP INF
The results of the correlation coefficient matrix analysis show that the dependent variables are all correlated with the independent variable at different levels The results of the correlation coefficient table between the variables show that the relationship between the variables is at an acceptable level The absolute value of the correlation coefficient of the variables is less than 0.3 (the highest correlation coefficient is 0.2873).
Table 4-3 Test results for multicollinearity
Variable SIZE CAP GDP CIR INF IDR LIQ TLA NPL Mean VIF VIF 3.25 2.47 1.72 1.58 1.54 1.52 1.37 1.27 1.15 1.76
Through Table 4.3, we can see that there is a relationship between the variables and there is a phenomenon of multicollinearity To avoid misinterpreting the regression results from the reality that needs to be evaluated, multicollinearity should be measured From the above table, we can see that the value of the variance inflation factor -VIF (Variance inflation factor) in the range 1.15 to 3.25 is all less than 10, so it can be concluded that there is no strong correlation between the independent variables, multicollinearity in the model is not significant.
Analysis of factors affecting ROA
Table 4-4 Summarize the results of regression analysis with ROA
(Note: ***, **, * are equivalent to significance level of 1%,5% and 10%)
Regression results according to Pooled OLS shown in Table 4.4 show that the coefficient R 2 is 0.4964, implying that the independent variables included in the model explain 49.64% of the change of the dependent variable ROA In which, the independent variables SIZE, TLA, GDP, INF have no statistical significance in the model. The LIQ independent variable is accepted to explain the dependent variable ROA with the significance level of 10%, the variables NPL, CIR, IDR with the significance level of 1% and the variable CAP with the significance level of 5%.
With the FEM method, the results shown in Table 4.4 show that the coefficient R 2 is
0.5906, implying that the independent variables included in the model explain 59.06% of the variation of the dependent variable ROA In which, the independent variables LIQ, GDP have no statistical significance in the model Independent variables NPL, IDR, INF are accepted to explain the dependent variable ROA at 5% significance level, SIZE, CAP, CIR variables with 1% significance level Only the independent variable TLA was accepted at the significance level of 10%.
The regression results according to the REM model shown in Table 4.4 show that the coefficient R 2 is 0.5786, implying that the independent variables included in the model explain 57.86% of the change of the dependent variable ROA In which, the independent variables TLA, GDP have no statistical significance in the model Independent variable SIZE, CAP, NPL, CIR, IDR are accepted to explain the dependent variable ROA at 1% significance level, LIQ variable at 5% significance level and only INF variable at 10% significance level.
There are 3 different regression models to be conducted in the previous section The author needs to determine which model is better than the other Some statistical tests will be conducted to pick the best model in three pairs of comparison, between PooledOLS and FEM, PooledOLS and REM, FEM and REM.
Table 4-5 F test, Breusch -Pagan and Hausman model selection for variable ROA
Breusch and Pagan Lagrangian test
Table 4.5, shows the results of F-test to support whether to choose OLS model or FEM model, the result is that with P-value = 0,0000 < α = 5%, H0 should be rejected (H0: Pooled model is suitable) Thus, the FEM model is more suitable than the OLS model.
Table 4.5, shows the result of Prob.Chibar2 = 0,0000 < α = 5%, so we conclude to reject hypothesis H0 (H0: should choose PooledOLS model) Thus, the REM estimation method will be more suitable than PooledOLS.
Table 4.5, shows the results of Hausman test on whether to choose FEM model or REM model The results show that the Prob.Chi-Square index = 0,0000 < α = 5%, so we reject the H0 hypothesis (H0: should choose the REM model) Thus, the FEM estimation method will be more suitable than the REM estimation method.
In summary , the FEM model is the most suitable model to analyze the results Thus, the next sections of the regression results will discuss on the basis of the FEM fixed-effects model The thesis will conduct testing of hypothesis violations such as multicollinearity, variable variance as well as autocorrelation.
4.2.3 Testing the hypothesis violations of the FEM
Normally, the linear regression model Yit = α + βxit + uit is studied under the assumption that random disturbances uit have constant variance When this assumption is violated, it shows that the model has a variable residual variance (error), which can lead to the following consequences:
Wald test is used to test the variation of variance in the FEM model If P-value < α allows the conclusion to reject the H0 hypothesis, the model has a variable variance phenomenon and vice versa if P-value > α, there is no basis to reject the hypothesis H0, proving that the model has no variance phenomenon change number.
Table 4-6 The results of Heteroskedasticity diagnostics with ROA
The results show that the Pro > chi2 = 0.0000 is less than α = 5% shows that the model has the phenomenon of variance of error.
At first, autocorrelation is identified through Wooldridgetest for autocorrelation in panel data and this test examines null hypothesis of there is no first-order autocorrelation.Obtained result is presented as below:
H1: there is first-order autocorrelation
If the P-value < α allows the conclusion to reject the H0 hypothesis, the model has autocorrelation and vice versa if the P-value > α, there is no basis to reject the H0 hypothesis, proving that the model has no autocorrelation.
Table 4-7 Autocorrelation test results of ROA
In Table 4.7, the Pro > F = 0.0000 is less than α = 5%, indicating that the model has autocorrelation.
4.2.3.3 Fix the defects of the model
In this thesis, using the FGLS method to overcome the autocorrelation defects and variable variance of the FEM model, the regression model is used, giving the following results:
Table 4-8 ROA regression model results after fixing
Regression model: ROA= 0,0009+ 0,0099515LIQ+ 0,420543CAP– 0,0074654TLA– 0,0500802NPL– 0,0260863CIR+ 0,0168739IDR+ 0,0350788GDP+ 0,325066INF
4.2.3.4 Discuss the influence of factors on ROA
The liquidity ratio (LIQ) for ROA is positive at 5% significance level This explains that when a bank's liquidity ratio is high, the bank's reputation increases and the bank can use part of the collateral to liquidate a large investment This will help commercial banks increase their profit after tax significantly However, having too much cash to liquidate a large investment forces commercial banks to bear a high level of risk when making this investment The test of Nguyen Cong Tam and Nguyen Minh Ha (2012) also gives similar results.
Consistent with initial expectations, the regression results show that the ratio of equity to total capital is positively correlated with profitability This means that banks holding more capital will have higher profits This result coincides with a previous series of studies on other emerging economies that found a high capital holding ratio synonymous with high profitability such as those of Athanasoglou et al (2008) and Pasiouras and Kosmidou (2007), Bourke (1989) also suggested that equity holdings are positively correlated with profitability, because banks with larger equity can easily access cheaper and less risky capital Other studies also emphasize that in developing countries, the amount of capital held by banks is a big concern of depositors, through which banks holding a lot of capital will have more cheap and stable deposits, impacting positively on profits When the bank increases the equity/total assets ratio by increasing the owner's equity, the bank can increase the capital source to lend without paying interest, so the bank saves the interest expense on deposits and increases the revenue leading to profit per dollar of assets of the bank increased.
The model results show that GDP has a negative effect on banks' ROA The negative correlation shows that if a bank lends more than its total assets, it can increase the risk of bad debt, the risk of capital loss, and decrease the profit of commercial banks The empirical tests of Lee and Syafri (2012), Ho Thi Hong Minh and Nguyen Thi Canh (2015) also give similar results.
The impact of bad debt on profitability of banks has a negative and significant in the regression with ROA at 1% significance level with regression coefficient -0.0501 coinciding with the study of Trujillo-Ponce (2011), Athanasoglou and al (2008) This can easily be explained as the morebad debts, the more banks are forced to make provision for risks and reduce profits Research by Havrylchyk (2006) shows that the increase in bad debt ratio increases the costs related to bad debt collection and settlement, thereby leading to a decrease in the profitability of commercial banks.
Analysis of factors affecting ROE
Table 4-9 Summarize the results of regression analysis with ROE
Source: Retrieved from Stata 14 (Note: ***, **, * are equivalent to significance level of 1%,5% and 10%)
The regression results according to Pooled OLS shown in Table 4.9 show that the R 2 coefficient is 0,5998, implying that the independent variables included in the model explain59.98% of the change of the dependent variable ROE In which, the independent variablesSIZE, TLA, GDP have no statistical significance in the model Independent variables LIQ and INF are accepted to explain the dependent variable ROE at 5% significance level and
CAP, NPL, CIR, IDR variables at 1% significance level.
With the FEM method, the results shown in Table 4.9 show that the coefficient R2 is 0.5997, implying that the independent variables included in the model explain 59.97% of the variation of the dependent variable ROE In which, the independent variables CAP, TLA have no statistical significance in the model Independent variables SIZE, CIR, INF are accepted to explain the dependent variable ROE at 1% significance level Independent variables NPL, IDR, GDP are accepted to explain the dependent variable ROE at 5% significance level and LIQ at 10% significance level.
The regression results according to the REM model shown in Table 4.9 show that the R2 coefficient is 0.5873, meaning that the independent variables included in the model explain 58.73% of the change of the dependent variable ROE In which, the independent variables CAP, TLA have no statistical significance in the model Independent variables SIZE, LIQ, NPL, CIR, IDR, INF are accepted to explain the dependent variable ROE at 1% significance level, GDP variable at 10% significance level.
Table 4-10 F test, Breusch-Pagan and Hausman model selection for variable ROE
Breusch and Pagan Lagrangian test chibar2 79.16 Prob > chibar2 = 0.000
Hausman test chi2 29.73 Prob > chi2 = 0.000
Table 4.10 shows the results of the F test to support whether to choose the OLS model or the FEM model, the result is that with Prob = 0,000 < α = 5%, H0 should be rejected (H 0 : Pooled model is suitable) Thus, the FEM model is more suitable than the OLS model.
Table 4.10 shows the results Prob.Chibar2 = 0,000 < α = 5%, so we conclude to reject the H 0 hypothesis (H 0 : Pooled OLS model should be chosen) Thus, the REM estimation method will be more suitable than Pooled OLS.
Table 4.10 shows the results of Hausman test on whether to choose FEM model orREM model The results show that Prob.Chi-Square = 0,000 < α = 5%, so we reject hypothesis H 0 (H 0 : should choose REM model) Thus, the FEM estimation method will be more suitable than the REM estimation method.
In summary, the FEM model is the most suitable model to analyze the results In addition, the study also conducts testing of hypothesis violations such as multicollinearity, variable variance as well as autocorrelation The results of testing the hypothesis violations are analyzed in the next sections.
4.3.2 Testing the hypothesis violations of the FEM
Table 4-11 The results of Heteroskedasticity diagnostics with ROE chi2 1692.38 Prob>chi2 0.0000
The results show that Pro > chi2 = 0.0000 is less than α = 5%, showing that the model has the phenomenon of variance of error.
Table 4-12 The results of Autocorrelation diagnostics with ROE
In Table 4.12, Pro > F = 0.000 is less than α = 5%, showing that the model has autocorrelation phenomenon.
4.3.2.3 Fix the defects of the model
In this thesis, using the FGLS method to overcome the autocorrelation defects and variable variance of the FEM model, giving a regression model, giving the following results:
Table 4-13 ROE regression model results after fixing
Regression model: ROE= 0,062307+ 0,0105498SIZE+ 0,0946413LIQ– 0,2883817CAP- 0,4829047NPL- 0,3071198CIR+ 0,1600061IDR+ 0,471428GDP+ 0,4096462INF
4.3.2.4 Discuss the influence of factors on ROE
In the fixed effects regression model, the coefficient of SIZE is 0,01054, SIZE has a positive impact on ROE In the fixed effects regression model, the coefficient of
SIZE is – 0.01054, SIZE has a positive impact on ROE Previous studies have suggested that when increasing in size, banks will gain potential diversification advantages, so that operational efficiency increases in the same direction as size, thereby increasing the profitability of banks The above results are further reinforced by the experimental studies of Obamuyi (2013).
Similar to the dependent variable ROA, Liquidity Ratio (LIQ) for ROE is positive at 5% significance level This explains that when a bank's liquidity ratio is high, the bank's reputation increases and the bank can use part of the collateral to liquidate a large investment This will help commercial banks increase their profit after tax significantly. However, having too much cash to liquidate a large investment forces commercial banks to bear a high level of risk when making this investment The test of Nguyen Cong Tam and Nguyen Minh Ha (2012) also gives similar results.
In the fixed effects regression model, the coefficient of CAP is - 0,2883, and CAP has a negative impact on ROE When firms use a lot of equity, in addition to aversion to risk (Berger, 1995), a high equity ratio reduces the positive impact of the “tax shield”, thereby reducing profitability leads to a decrease in ROE Furthermore, a high equity ratio reduces equity risk which, according to the risk-return theory (Modiglian and Miler, 1963), lower risk leads to lower return on equity, which lowers ROE This result is consistent with the studies of Berger and Bouwman (2013), Lee and Hsieh (2013), Nguyen Thi Hong Vinh and
Le Phan Thi Dieu Thao (2016), Fotios (2007).
In the fixed effects regression model, the coefficient of NPL is – 0,4829, NPL has negative impact on ROE This correlation is explained by the fact that when banks have bad debts increase to an alarming level, credit deterioration occurs, making bad debts worse, leading to their ability to earn profit per dollar of shareholders' profits decrease In addition, the increase in the bad rate makes the cost of risk provisioning also increase, plus the decrease in the difference between lending interest rates and deposit rates at some point in time (loan interest rates decrease faster than interest rates) and slow credit growth have prevented profit after tax from increasing rapidly.
As a result, the growth rate of profit after tax decreases, reducing the profit of shareholders. This empirical result also shows that Vietnamese commercial banks need to strengthen credit risk management in order to achieve higher business results The model results are consistent with the lending situation of Vietnamese commercial banks during the research period, especially in the period 2010-2018 when the credit growth target was more focused while the credit quality was not improved As a result, bad debts are increasing with the growth rate of credit risk provisions, reducing the profits of banks.
Operating Efficiency as measured by the ratio of operating expenses to income has a negative impact on ROE When the efficiency of asset management increases or decreases by 1 unit, the bank's profitability expressed by ROE will decrease (increase) by 0,3071. This means that as operating costs increase, the bank will have to use more assets to put into business to cover operating costs, which means lower return on equity In case the bank performs well, the operating expense ratio is low, this will reduce the pressure on capital Hess et al (2008) found a positive relationship between loan expense ratio and credit risk That is, banks that operate inefficiently with a high ratio will also have a high level of credit risk That result is also consistent with the research results in the thesis and also with the results found in each study by Berger and De Young (1997), Salas and Saurina (2002).
In the ROE regression model, the influence weight of IDR is 0,1600 with a significance level of 1% This result shows that income diversification changes the bank's operational efficiency in a positive direction Smith et al (2003) found evidence of the stability of non-interest income, thereby contributing to the stabilizing effect of bank profitability Supporting the view that income diversification is beneficial for bank profitability is also the study of Chiorazzo et al (2008) The authors explain that small-sized banks will have an advantage when it comes to income diversification Since non-interest income accounts for a small proportion of total income, the increase in non-interest income increases financial efficiency Thus, income diversification will increase the opportunity to generate higher income, thereby having higher profits In addition, income diversification reduces the bank's dependence on income from traditional activities of lending and depositing This will make the bank's income less volatile even when credit activities face difficulties The expansion of business into services and non- traditional investments helps the bank expand its market, increase exposure and serve diversified customers more form Research by Baele et al (2007), when expanding activities in the service of commissions, fees, investment, business, etc the bank saves the cost of human resources and technology At the same time, banks can increase cross-selling of existing products with customers Take advantage of relationships with customers to market more existing products to increase market share Therefore, this indicator shows the correlation between income diversification and return on equity.
The inflation rate and Economic growth (INF and GDP)
The model results show that INF and GDP have a positive effect on bank's ROE These figures indicate that the significant growth of GDP along with a reasonable increase in inflation helps to improve the profitability of the commercial banking system Authors supporting this result include Iannota (2007), Nguyen Thi Hong Vinh and Le Phan Thi Dieu Thao (2015), Van Dan Dang (2019).
CONCLUSION AND RECOMMENDATIONS
Conclusion
The issue of bank profitability is always a matter of special social interest. Experiencing a difficult time after the economic crisis, facing bad debts, liquidity problems, mergers and restructuring, the business situation of Vietnamese commercial banks has gradually stabilized, following the orientation of the State Bank However, the profits of Vietnamese commercial banks still arise problems in the process of operation To understand the causes of these problems, the thesis used qualitative and quantitative methods through regression models, taking data of 22 Vietnamese commercial banks and macro data in the period 2012-2020 to estimate the impact of some profitability factors of Vietnamese commercial banks In which, the thesis chooses ROA and ROE as dependent variables to represent the profitability of banks.
Based on the regression results of the models with the GLS estimation method, the author found some main results as follows:
Research results show that in Vietnam, variables that have a negative impact on return on total assets include: Loan balance (TLA), Non-performing loan (NPL), Operating Efficiency (CIR) Variables that have a positive impact with return on total assets include: Liquidity ratio (LIQ), Equity ratio (CAP), Income diversification (IDR), The inflation rate (INF), Economic growth (GDP).
Variables that have a negative impact on return on equity include: Equity ratio (CAP), Non-performing loan (NPL), Operating Efficiency (CIR) Variables that have a positive impact on return on equity include: Bank size (SIZE), Income diversification (IDR), The inflation rate (INF), Economic growth (GDP).
In this part, the thesis starts from summarizing the main findings of the experimental results Then make recommendations regarding the bank's profitability These suggestions are expected to provide more references for policy makers when implementing solutions to improve profitability for commercial banks At the same time, this chapter also recognizes some limitations that the thesis has not yet solved 5.2 Recommendations
Bank size has a positive relationship with profitability Therefore, in order to increase profits, banks need to increase asset size Bank scale up can help increase the ability to attract mobilized capital, reducing fixed costs In order to have a solid foundation, safe business, banks need to pay special attention to the issue of increasing equity.
Recommended measures to be taken:
Firstly, strengthening own capital from accumulated profits: Accumulated profit is the best and sustainable source of capital not only for the banking sector but for all businesses.
In order to accumulate profits, banks must improve service quality, diversify products, increase service revenue, control costs, use capital effectively by increasing lending to subjects with high interest margins, and at the same time have to manage manage credit risk, limit bad debt, etc.
Secondly, another effective way to increase capital is to issue more shares to existing shareholders or call for investors from foreign strategic shareholders This is an easy measure for banks and a sustainable capital increase channel, and banks will be able to learn more management experience and technology from partners However, in order to attract investors, banks must ensure income and benefits for shareholders, and at the same time develop a roadmap to increase capital in a timely manner, ensuring compliance with current regulations.
Thirdly, merging and consolidating banks: In recent years, the State Bank has been very strong in handling weak and inefficient banks, in which merger and consolidation measures are widely used.
Liquidity has a positive relationship with profitability Psychology of client in lending and depositing money still depends on the reputation of the bank The more reputable the commercial banks, the more deposits they can attract as well as the more loans they can disburse.
Recommended measures to be taken:
The first is stabilize the liquidity system, increase the liquidity defense ratio, and reduce the bad rate through improving asset quality.
The second is focus on implementing the instructions of the State Bank on upgrading the risk management system, debt management, as well as improving the electronic banking system such as automatic ATM, Mobile Banking.
CAP variables affect profitability as measured by ROE and ROA are different.
Specifically, CAP has a negative effect on ROE and a positive effect on ROA Equity is an important criterion that determines the existence and development of a bank Equity is the bank's own capital, formed from the capital contributed by the bank's owners This capital is increased during the operation through additional contributions from shareholders or retained earnings Equity is an active resource in the new stage of operation At the same time, this is also a relatively stable source of capital that can be used with a long term because the non-repayable nature of the business helps the bank to increase profits Although equity accounts for only a relatively small proportion of total capital, it has very important functions for banks The first is the protection function, helping the bank to compensate for larger losses that may arise in the course of business to help the bank avoid bankruptcy and stabilize and maintain operations, refund to customers when the bank faces the risk of insolvency Abundant Equity creates trust in customers to help attract customer deposits. Equity also helps managers determine the safety ratio from which to regulate the bank's operations This indicator helps to assess the solvency of the bank in case the bank encounters a loss The increase in equity ratio will benefit banking operations, creating competitive advantages and the ability to exploit non-interest income generating activities. Besides, the mobilization of capital from customer deposits is not always low cost, due to competitive pressure forcing banks to increase the cost of deposit mobilization and reduce lending interest rates Therefore, banks need to have an appropriate capital mobilization strategy to save costs and increase business efficiency.
Recommended measures to be taken:
Firstly, commercial banks need to ensure the minimum capital adequacy ratio according to international standards, regulations of the State Bank of Vietnam and Basel III standards Accordingly, commercial banks need to determine an appropriate percentage of net profit to be retained annually to increase charter capital or may merge and acquire small banks to form a bank with greater financial potential or call for contributions of shareholders to improve financial potential.
Secondly, banks need to identify levers to reduce capital waste without changing business models; optimize scarce capital resources to achieve efficiency in the use of equity.
Research results shows that increasing the loan ratio will increase the profitability of commercial banks In order to increase loan ratio, or in other words, increase the profit of commercial banks, the author recommends the following:
First is to issue credit policies such as applying attractive and appropriate interest rates for lending activities with diverse loan terms and promotion programs, boosting consumer loans as consumer loans play a very important role in the economy: meeting capital needs to maintain essential needs for customers, as well as contributing to economic development investment, promoting the process of capital concentration.
The second is to diversify the customer base by expanding the appropriate lending packages, serving the needs of many customer segments, increasing the number of customers through marketing and advertising policies Specifically, banks should set up customer experience management department, specializing in designing and implementing demand assessment programs, market surveys fo r internal and external customers as well as customer research programs for improving servicequality and developing new products. Thereby providing research results, customer service quality assessment or information from customer research programs to related units/ personnel to support branches/sub-branches to better understand their customers Banks should regularly conduct measurement, evaluation and perform quality analysis of existing products and services to identify the limitations that need to be improved Developing solutions to improve service quality as well as improve existing products to suit changes in customers' needs.
Limitation of the study
The thesis studies the effects of factors on the profitability of Vietnamese commercial banks, the research model focuses on nine key factors affecting ROA and ROE However,there are many other factors with stronger impact that the author has not mentioned, because the profitability of banks is not only influenced by bank characteristics but also by macro factors such as financial and monetary policies, exchange rate fluctuations, stock market developments, etc The topic has not yet analyzed the macro factors affecting profit.
Data sources of Vietnamese commercial banks are still limited: many small banks do not publish data, full information is difficult to access, so the thesis can only collect data of
22 banks in the observation period from 2012 to 2020 However, the model is good for gathering with many banks With banks of different sizes, the ratio of total assets accounts for a high proportion of the total assets of all banks in Vietnam.
The research model of the thesis has not clarified the impact of the group of policy factors on the performance of commercial banks The reason is that the monetary policy of the State Bank changes in each period, specific economic period, it is difficult to choose and identify the appropriate variable to include in the model.
From the above limitations, the research direction can be given to increase the number of additional research samples In addition, the time period can be extended to enhance the explanation of the research model Next, the dependent variable in the new model only uses
2 variables, ROA, ROE, and can be replaced by other variables such as NIM.
The reason for the above limitations is due to limited time and current capacity. Therefore, in future studies, the author wishes to be further studied to provide a more general assessment of the profitability of the Vietnamese banking system as well as to build a model with better tests and identify many factors affecting the profitability of the Vietnamese banking system banks to make a useful reference for research as well as necessary suggestions for banks in making policies to improve profits.
Chapter 5 has drawn conclusions from the research results in the thesis, on that basis, the author has made some recommendations and policy implications to improve the profits of Vietnam's environmental banks For factors that have a positive impact on ROA andROE, the author provides policy implications to improve these indicators On the contrary,for factors with negative impacts, the author proposes policy implications to limit and minimize negative impacts At the same time, it also points out the limitations of the study,finds out the causes and solutions by expanding the research sample, adding independent and dependent variables so that future studies can better explain the factors affecting the profitability of commercial banks in Vietnam, becoming a useful document, creating a basis for applying measures to increase profits for Vietnamese banks.
The issue of determining the factors affecting the profitability of commercial banks is one of the important contents, attracting the attention of many researchers in the world and in Vietnam in the past period In this research topic, the author shows how the group of internal factors affects the profitability of Vietnamese commercial banks in the period 2012-
2020 and has answered three research questions raised in Chapter 1 including:
What factors affect the profitability of Vietnamese commercial banks?
How do these factors affect the profitability of Vietnamese commercial banks?
What solutions to improve profits for Vietnamese commercial banks?
However, the answer to each question posed has limitations In the future, the author will expand the research direction in both space and time as well as find more independent and dependent variables that affect the profitability of Vietnamese commercial banks.
In summary, from the research results above, the author hopes to provide a more complete picture of the factors affecting the profitability of commercial banks in order to help bank managers improve the profitability of commercial banks in Vietnam so that the banking business is more and more developed safely, healthy, effective and sustainable.
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Appendix 1: List of commercial banks selected for the research
No Name of Banks Abbreviations Indications
1 An Binh Commercial Joint Stock Bank ABBank ABB
2 Asia Commercial Joint Stock Bank ACB ACB
3 Joint Stock Commercial Bank for
Investment and Development of Vietnam
4 Vietnam Export Import Commercial Joint
5 Ho Chi Minh city Development Joint
6 Kien Long Commercial Joint Stock Bank Kienlongbank KLB
7 LienViet Commercial Joint Stock Bank LienVietPostBank LPB
8 The Maritime Commercial Joint Stock
9 Military Commercial Joint Stock Bank MB MBB
10 Nam A Commercial Joint Stock Bank NamABank NAB
11 National Citizen Bank NCB NCB
12 Orient Commercial Joint Stock Bank OCB OCB
13 Petrolimex Group Commercial Joint Stock
14 Saigon Thuong Tin Commercial Joint
15 Saigon Bank for Industry & Trade Saigonbank SGB
16 Saigon-Hanoi Commercial Joint Stock SHB SHB
19 Ngân hàng TMCP Việt Á Vietabank VAB
20 Joint Stock Commercial Bank for Foreign
21 Vietnam Joint Stock Commercial Bank of
22 Vietnam Commercial Joint Stock Bank for
Yea r ROE ROA LIQ TLA CAP IDR CIR SIZE NPL INF
Appendix 03 Research results Picture 1 Descriptive statistics
Variable obs Mean std Dev Min Max
Picture 2 Correlation matrix between variables
AP TLẪ NPL CIR IDR GDP INF
Picture 3 Test results for multicollinearity
Picture 4 Pooled OLS output with ROA
Sourc e ss df MS Number of obs =
G Random-efĩects GLS regression Numbe r
R R-sq: Obs pei group: within = 0.5786 min
Wald Chi2(9) = 231.20 corr(u i, X) = 0 (assumed) Prob
Picture 6 FEM output with ROA
Picture 5 REM output with ROA
Picture 7 Breusch and Pagan Lagrangian test with ROA multiplier test for random effects
Picture 9 Heteroskedasticity diagnostics with ROA corr(u_i, Xb) = -0.6003 Prob
Picture 8 Hausman test with ROA in fixed effect regression model
0363755 0326829 0036927 b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho: difference in coefficients not sỵstematic
Modiíied Wald test for groupwise heteroskedasticity
Picture 10 Autocorrelation diagnostics with ROA between = overall =
(fraction of variance due to u_i)
xtsarial ROA SIZE LIQ CAP TIA NPL CIR IDR GDP INP
Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation
Picture 11 FGLS output with ROA uross-secLionai txme-series te>ij^ regression
Correlation: common AR(1) coefficient for all panels (0.7051)
Estimated covariances = 22 Number of obs = 195
Estimated autocorrelations = 1 Number of groups = 22
Estimated coefficients = 10 obs per group: min — 6 avg = 8.863636 max — 9
Picture 12 Pooled OLS output with ROE
Source ss f d MS Number of obs = 195
E Coef std Err t p> t [55% Conf Interval]
Picture 13 FEM output with ROE
1.124462 -.2133663 sigma_ u 04932685 sigma e 03831607 rh o 62368015 (fractio n of variance due t o u_i)
Picture 14 REM output with ROE
Random-effects GLS regression Number of obs =
R-sq: obs per group: within
Wald chi2(9) = 259.44 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
Breusch and Pagan Lagrangian multiplier test for random effects
ROE[STOCK1,t] = Xb + u[STOCKl] + e[STOCKl,t]
Estimated results: Var sd = sqrt(Var)
Picture 15 Breusch and Pagan Lagrangian test with ROE u I 0009893 0314533
Picture 16 Hausman test with ROE hausman fe re
3 b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, eííicient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic corr(u_i f xb) = -0.6088 Prob F = 0.0000
1.124462 -.213366 sigma 3 u 04932685 sigma_ e 03831607 rh o 62368015 (traction of variance due to u_i)
Picture 17 Heteroskedasticity diagnostics with ROE
Modified Wald test for groupwise heteroskedasticity in fixed effect regression model
HO: sigma(i) A 2 = sigma^2 for all i
Picture 18 Autocorrelation diagnostics with ROE between
(fractio n of variance due to u _i)
xtserial ROE SIZE LIQ GAP TLA NPL CIR IDR GDP INE
Wooldridge test for autocorrelation in panel data H0: no first-order autocorrelation