Finance dissertation on the impact of credit risk on bank stability evidence in vietnam context

Research results, based on a data set of 22 Vietnamese commercial banks, show that credit risk has a negative impact on not only the stability but also the profitability of banks.. The r

Dissertation submitted in partial fulfillment of the

Requirement for the MSc in Finance

FINANCE DISSERTATION ON THE IMPACT OF CREDIT RISK ON BANK STABILITY: EVIDENCE IN VIETNAM

CONTEXT

NAME OF STUDENT: NGUYEN THI MINH NGOC

ID No: 22080951 Intake 6

September 2023

ABSTRACT

The purpose of this study is to determine the impact of credit risk on the stability of Vietnamese commercial banks Specifically, research the relationship between credit risk and stability using an unbalanced panel dataset of Vietnamese commercial banks from 2012

to 2022, a critical period for implementing the Prime Minister's Decision Prime Minister (254/QD-TTg) on restructuring the Vietnamese commercial banking system To describe the credit risk of Vietnamese commercial banks, the author uses the bad debt index Research results, based on a data set of 22 Vietnamese commercial banks, show that credit risk has a negative impact on not only the stability but also the profitability of banks The dissertation also has some implications for policy makers and bank managers First, it suggests that reducing credit risk is crucial for enhancing bank stability in Vietnam, especially in the context of high economic uncertainty and volatility due to the COVID-19 pandemic Second, it suggests that improving capital adequacy, asset quality, liquidity management, and risk management practices is essential for maintaining bank stability in Vietnam Third, it suggests that monitoring both ROA and ROE as indicators of bank stability is important for capturing different aspects of bank performance

ACKNOWLEDGEMENT

First and foremost, I would like to acknowledge with thanks to my supervisor TS Robert Ercole for his guidance, academic encouragement and welcoming support Thank you for helping me, wholeheartedly guiding me, giving me valuable advice, comments and suggestions throughout the process of writing my thesis so that I can have the most complete work

I would also like to extend my thanks to Stata Systems for the turning of the technical equipment with the skills in running data which help me so much in the research

Finally, I would like to thank my family and friends for the support and appearance when always being by my side caring me throughout my research work

The research process has many limitations in terms of time and personal knowledge, so the assignment cannot avoid shortcomings Therefore, I hope to receive the attention and suggestions from teachers to be able to improve knowledge as well as gain more experience for yourself

Thank you sincerely!

TABLE OF CONTENT

LIST OF TABLES 6

I INTRODUCTION 1

Rationale 1

Research goal and questions 3

Object and scope of the research 4

II LITERATURE 4

1 The definition and theory of credit risk 4

2 The bank stability and its determinant 6

Bank size 7

Capital structure 8

Solvency 9

Credit risk 9

GDP 9

3 Empirical review 9

III THE OVERVIEW OF VIETNAMESE BANK STABILITY IN THE PERIOD FROM 2012 TO 2022 15

IV METHODOLOGY 17

1 Data 17

2 Methodology 18

2.1 Method 18

2.2 Pooled OLS 18

2.3 Fixed effect model (FEM) 19

2.4 Random effect model (REM) 19

2.5 FGLS model 19

3 Variables 20

a Dependent variables 21

b Independent variables 21

V RESEARCH RESULTS AND DISCUSSION 25

1 Descriptive statistics 25

2 Correlation analysis 27

3 VIF Test for Multicollinearity 28

4 Dignosis test 30

4.1 Wald Test for Heteroskedasticity 30

4.2 Wooldridge Test for Serial correlation 30

4.3 Regression analysis 31

4.4 Recommendations 34

VI CONCLUSION 35

REFERENCES 37

APPENDICES 41

LIST OF TABLES

Table 1: Model specification (Author’s construction) 24

Table 2 : Descriptive statistics (Author's calculation on Stata) 26

Table 3: Correlation matrix (Author's calculation on Stata) 27

Table 4: VIF Test (Author's calculation on Stata) 29

Table 5: Wald test results (Author's calculation on Stata) 30

Table 6: Woodridge Test (Author's calculation on Stata) 31

Table 7: Regression result (Author's calculation on Stata) 32

I INTRODUCTION

Rationale

Bank is defined in various ways but in general, it is a financial institution that provides customers’ deposits, borrowers’ loans, and other monetary services such as currency exchange, credit cards, moreover banking system also plays a vital role in assisting the central bank in achieving national monetary policy objectives According to various previous theories, the banking system has played an important role in human, social, and economic development In

a well-functioning economy, banks provide an intermediation service that connects savers and investors by diverting investment funds to the uses that give the highest rate of return, hence boosting specialization and the division of labor, and becoming the main engine of economic growth (Todaro & Smith, 2003) Therefore, it is evitable that in the era of integration and globalization, to gain financial development the banks’ stability should be seen as the utmost important priority by the authority which also be seen as the most vital driver leading to the GDP growth The question about determinants of preserving financial system stability has long been at the foundation of bank supervision and regulation However, the topic has received even more attention since the global financial crisis of 2007/2008 This is because evidence abounds that major banks were to blame for the crisis, which caused enormous harm to many

economies throughout the world

The recent global financial crisis and its effects on the financial sector globally serve as evidence of how crucial it is to keep the banking system stable The topic of bank risk taking channels has also received a lot of attention recently (Batten & Vo, 2019), (Borio & Zhu, 2012) For the assessment and management of the banking system, it is critical to have a thorough understanding of the factors that affect bank stability It is much more crucial in a nation like Vietnam where banks provide the majority of the funding for private enterprises and economic expansion This essay initially aids in a deeper comprehension of the factors influencing bank stability that have been brought to light by the severe downturn that has followed the global

crisis Additionally, the article advances knowledge of factors that affect bank stability generally and in an emerging economy like Vietnam in particular By permitting comparison

of the bank behaviors across different country datasets, this method also enables us to determine whether there are any differences in the factors of bank stability in an emerging country The results of this study indicate that bank size (measured as natural logarithm of total assets), capital structure, profitability (measured as return on equity-ROE), solvency, credit risk ( measured by Non-Performing Loan), inflation and gross domestic product (GDP) have generally supported bank stability The results also indicate that credit risk and solvency have

generally undermined bank stability

These financial risks, according to Cecchetti and Schoenholtz (2014), include the possibility of depositors withdrawing money suddenly (liquidity risk), borrowers not being able to repay debt (credit risk), interest rate changes interest rates (interest rate risk) and bank computer system failure or building fire (operational risk) However, the traditional function of the bank is to create deposit and loan accounts for the clients, which also means that the main resources of the bank (Njanike, 2018) In other words, lending and credit operations are the primary sources

of income for banks, so credit risk has a significant impact on the effectiveness as well as stability of banks

Furthermore, banking crises can emerge as a result of macroeconomic changes such as a reduction in GDP, an increase in the unemployment rate, interest rates, and inflation, all of which can affect credit risk (Festić, Kavkler and Repina, 2011; Nkusu, 2011) Credit risk is an important concern for both banks and the economy It appears and has a direct impact on banks' capital resources, such as capital loss, as well as the chance of bank insolvency The necessity

to focus on credit risk management is an unavoidable requirement for the majority of developing market countries Credit risk is influenced by banking parameters such as total assets, size scale, bad debt, liquidity, and so on, in addition to macro concerns

In Vietnam, since political and economic reforms began in 1986, banking sector has been seen

as a major engine for promoting financial system development and achieving economic growth

of around 7% (V.C Nguyen & Do, 2020; Tran & Foroudi, 2020), due to a weak governance system, and the swings in macroeconomic conditions prior to global financial effects Since

2012, the commercial banking system has been undergoing restructuring in order to limit credit risk, reduce bad debts, restructure capital and assets, and improve governance capacity in accordance with international standards in order to gradually improve the business efficiency

of banks as well as the Vietnamese banking system However, profit in the banking sector fell dramatically between 2012 and 2015 due to poor debts in lending and the economic downturn Specifically, the bad debt ratio on commercial banks' balance sheets climbed to 17.2%, while the overall system should maintain an acceptable bad debt percentage of less than 2% In the last year, the Vietnamese banking sector has seen substantial changes in terms of development and stability According to a recent survey conducted by the State Bank of Vietnam (SBV), loan growth remained stable at 8-9%, while capital mobilization increased by 9-10%

Research goal and questions

The previous part emphasizes the significance of credit risk to the financial system and the economy's overall stability Therefore, this study mainly contributes to the discussion by investigating the impact of a bank's credit risk on its stability in the setting of Vietnam, particularly in a recovering economic climate following the 2008-2009 financial crisis One of the motivations for writing this study is to investigate the relationship between credit risk and bank stability, as well as other drivers of bank stability In the first phase, it is evaluated

if there is a positive or negative reciprocal relationship between credit risk and bank stability

as well as the other factors that may impact on the stability of banks Based on this initial result,

it is examined whether credit risks and other drivers individually and/or together contribute to bank instability After that, recommending solutions to reduce credit risk and increase banks operation efficiency in Vietnam

To approach these research goals, the study raises the following research questions:

What factors influence bank stability?

What is the relation between credit risk and bank stability?

What should be the solutions to restrain credit risk and enhance the Vietnamese bank stability?

Object and scope of the research

The object of this research is the factors that affecting bank stability and specifically the impact

of credit risk on the stability of Vietnamese banks

This study employs pooled ordinary least squares (pooled OLS), fixed effects model (FEM), random effects model (REM), and generalized least squares (GLS) to analyze the aforementioned objectives because GLS can correct common flaws in the conventional model such as multicollinearity, heteroscedasticity, and autocorrelation

The research scope is focusing on factors that affect credit risk and the stability of Vietnamese banks Data is gathered from the financial statements of 22 Vietnamese banks, as well as macroeconomic data from ADB indicators in the period of eleven years from 2012 to 2022

II LITERATURE

1 The definition and theory of credit risk

Given that a bank exists not merely to take deposits but also to extend credit, it is always exposed to credit risk As the definition of Timothy W Koch (1995), credit risk is the possible loss of net revenue and the value of credit capital due to non-payment or late payment by customers According to Basel Committee (2006), credit risk is when the loan customer or the counterparty is unable to meet the obligations under the terms agreed upon The risk of loss for

a bank is the obligor's breach of the contract, defined as any substantial breach of the contractual obligation to repay the debt and interest The most important risk that banks have

to deal with is credit risk, and the prosperity of their business relies more heavily on accurately assessing and effectively handling this risk compared to any other risks they face

According to Circular 02/2013/TT-NHNN dated January 21, 2013 of the State Bank of Vietnam Regulations on the classification of assets that have the levels and methods of setting up risk provisions and the use of provisions to handle risks in the operations of credit institutions and foreign bank branches defined that when a bank or a foreign bank branch lends money to a customer, the possibility that the customer will not pay back part or all of the debt as agreed is referred as credit risk

Credit risk, on the other hand, is defined as the degree to which the value of debt instruments and derivatives fluctuates as a result of changes in the underlying credit quality of borrowers and counterparties The major portion of banking risks is covered by credit risk, which is one

of the major causes of the economic downturn and an important indicator of financial vulnerability (Dudian et al., 2008) Empirical studies on the determinants of credit risks are, therefore, essential for a stable economy

The main sources of credit risk are limited institutional capacity, inappropriate credit policies, volatile interest rates, poor management, inappropriate laws, low capital and liquidity levels, direct lending, massive bank licensing, poor loan underwriting, laxity in credit assessment, poor lending practices, government interference, and insufficient central bank supervision (Kithinji, 2010) If the bank lends to debtors about whom it knows little, the credit risk may increase

Moreover, according to Ghosh (2012), there are many causes leading to credit risk, including external and internal causes of the bank Common reasons from commercial banks can include: too easy credit decisions, ineffective credit management, unexpected unexpected events, and stubbornness in not repaying debt stemming from customer side External factors stem from macroeconomic weakness, deterioration of economic conditions and poor development of external markets The negative relationship from macroeconomic conditions affects borrowers,

as it reduces their source of income and increases their likelihood of not being able to repay their debt External factors such as changes in fiscal policy, money supply, import-export

policy, trade restriction policy, or changes in the financial market will also affect a company's credit portfolio bank

The influence of external factors can lead to an economic recession, during the crisis period, the economic activity is slowed down, the volume of products and revenue of enterprises decreases, the demand for goods and services decreases lower service Market fluctuations also affect the decline in the value of banks' credit portfolios On the contrary, in the boom period of the economy, the number of products is created more, the demand for goods and services is higher, and businesses earn more profits Thus, the borrower will easily repay the bank and the risk of default is reduced During a recession, credit risk increases and during a boom, credit risk decreases

Internal factors from the borrower and their business are factors that affect the bank's credit risk Factors such as business risks, financial management, technical process limitations, management experience, poor inventory management are some of the common factors that cause decline in production efficiency and quality product quality, reduces the borrower's income, and increases the probability of default

Besides, the borrower's dishonesty and unethical attitude are also one of the main causes of credit risk

Thus, the causes from external or internal factors, from the borrower's side, affect credit risk

In addition, reasons such as the effectiveness of the legal system, economic and political environment affect the granting of credit

2 The bank stability and its determinant

Financial stability and long-term development have become critical to global social and economic development (Adusei & Elliott, 2015; Ali & Puah, 2018; Dao et al., 2020; Shair et al., 2021; Yin, 2019) In other words, the lack of banking crises is achieved through the stability

of all banks in the banking system or sector (Brunnermeier,M.,et al.,2009) Banking stability

can be characterized in terms of interdependence as the stability of banks that are tied to each other either directly through the interbank deposits market and participation in syndicated loans, or indirectly through lending to shared industries and proprietary transactions (Segoviano & Goodhart, 2009) On the other hand, banks are scrutinized not just by political, legislative, regulatory, and management organizations, but also by customers, who are increasingly concerned about the long-term viability of bank operations Banking stability determinants and their impact on financial system stability differ between nations; consequently, national bank supervisors are interested in learning more about banking stability determinants

The empirical research identifies certain economic, financial, regulatory, and institutional elements that influence banking stability The previous research in Vietnam and throughout the world has all found that internal and external factors have an impact on bank stability According to (Jahn & Kick, 2012), in their examination of the variables defining the stability

of the banking system, defined financial stability’s definition is: "Banking system financial stability is a steady state in which the banking system performs its functions effectively, such

as resource allocation, risk dispersion, and income distribution", thus, the bank's effective operation, or profitability generation, is what ensures banking stability

In this paper, along with analyze the impact of credit risk on bank stability, author also concentrate on the influence of other internal and external factors on bank stability The factors that chosen include bank size, credit risk, solvency, capital structure, and

macroeconomic factors which is GDP and inflation

Bank size

Bank size is a concept that refers to the scale and scope of a bank's operations and activities This factor can be measured by various indicators, such as total assets, total revenue, net income, market capitalization, number of branches, number of employees, and market share Bank size can have different implications for the performance, risk, efficiency, and

competitiveness of banks, as well as for the stability and regulation of the banking system (Lindblom et al., 2014) The too-big-to-fail theory suggests that larger banks pose greater risks to the financial system and the economy due to their interconnectedness, contagion potential, and systemic relevance (Stern & Feldman, 2009) Larger banks may also enjoy implicit or explicit government guarantees and subsidies that reduce their market discipline and incentives to manage risk prudently This may create moral hazard and adverse selection problems that increase the likelihood and severity of banking crises The economies of scale theory suggests that larger banks can benefit from lower average costs and higher profits due

to their ability to exploit scale economies in production, diversification, innovation, and market power Larger banks can also benefit from lower funding costs and higher ratings due

to their perceived safety and systemic importance However, larger banks may also face diseconomies of scale due to increased complexity, bureaucracy, and coordination problems The market power theory suggests that larger banks can influence the structure and conduct

of the banking industry and the financial markets due to their dominant position and

bargaining power Larger banks may also affect the competition and efficiency of the banking sector by creating entry barriers, exploiting market frictions, engaging in anticompetitive practices, or influencing regulatory policies Through the aforementioned theories, bank size can have positive or negative effects on different aspects of banking performance and

stability, depending on various factors, such as bank management, regulation, supervision, competition, and macroeconomic conditions Therefore, it is important for bank size

practitioners and researchers to understand the theory and practice of bank size and to keep abreast of the latest developments and innovations in this field

Capital structure

Turning to the capital structure, this factor refers to the way a company finances its operations and investments by utilizing a combination of equity (shares) and debt (loans, bonds, etc.) It

represents the composition of a company's long-term capital, including the proportion of equity and debt used to fund its activities

Solvency

Solvency is the ability of the banks to meet their long-term financial obligations It reflects the adequacy of the banks’ capital and assets to cover their liabilities One of the indicators of solvency is solvency, which measures the ratio of total equity to total assets A higher

solvency means a higher solvency for the banks, as it implies that they have more equity than assets, or a lower leverage The solvency indicator reflects the bank's solvency causing a series of bank failures

Credit risk

The connection between bank credit risk and bank stability can be understood in the context

of the systemic theory and the diversification of the firm Some theories suggest that credit risk transfer, which is the process of transferring credit risk from one party to another through securitization or credit derivatives, can enhance bank stability by reducing the exposure of banks to credit losses, diversifying their assets, improving their liquidity and lowering their funding costs Other theories argue that credit risk transfer can undermine bank stability by increasing the complexity and opacity of the financial system, creating moral hazard and adverse selection problems, weakening the monitoring and screening incentives of banks, and amplifying systemic risk

GDP

GDP is the total worth of goods and services generated in a country during a specific time period It reflects the country's economic progress and development A higher GDP indicates increased economic activity and income for the country because it implies more goods and services are produced and consumed

3 Empirical review

About the credit risk, this is a factor that directly affects the stability of any bank because credit

is the main activity of the bank and accounts for a large proportion thus, numerous scholars have investigated the influence of credit risk on banks in various aspects According to Yong Tan & Christos Florosb, 2012, the higher the risk of credit, the higher the bad debt that reflects lower bank stability,

Another research of Ogboi and colleagues (2013) about the influence of credit risk management and capital sufficiency on the profitability ratios of Nigerian commercial banks using data from the financial statements of six commercial banks from 2004 to 2009 The panel data model is used to calculate the relationship between loan loss provisions, loans and advances, bad debts, capital sufficiency, and ROA of banks The findings reveal that loan loss provisions, bad debts, and capital adequacy all have a favorable impact on a bank's ROA, with the exception of loans and advances, which have a negative impact on the bank's profitability ratio over the research timescale

Numerous empirical studies have established that bank-specific variables can influence bank's bank According to Adusei (2015), bank stability has traditionally been supported by both bank size assessed by the natural logarithm of total assets or deposits, indicating that the goal of bank size expansion in relation to financial market stability must be pursued Ali and Puah (2018) evaluated the impact of bank size on five Islamic and nineteen banks in Pakistan In the context

of credit risk as assessed by the loans to asset ratio, this has a positive and statistically significant influence on bank stability As a result, a rise in credit risk may result in improved bank stability (Adusei, 2015; Ali & Puah, 2018)

The author Kargi in 2011 investigated how credit risk affects the profitability of Nigerian banks Financial ratios were used to measure bank performance and credit risk, which is collected from the annual reports and accounts of some banks from 2004-2008 The descriptive, correlation and regression methods is used to study the data The result is that credit risk management had a big effect on the profitability of Nigerian banks And another discovery is

that the profitability of banks was negatively related to the levels of loans and advances, performing loans and deposits, which made them more vulnerable to illiquidity and distress

non-In another examination, Zou et al (2014) examined the influence of credit risk management on commercial bank profitability Return on equity (ROE) and return on assets (ROA) are defined

as proxies for profitability in the research model, while bad debt ratio and capital adequacy ratio are specified as proxies for credit risk management From 2007 to 2012, data was collected from 47 of Europe's top commercial banks A multivariate regression model was utilized by the author The findings reveal that the bad debt ratio has a negative and significant influence on European bank profitability, whereas the capital adequacy ratio has no effect on profitability Felix and Claudine (2008) looked into the connection between bank performance and credit risk management Their findings indicated that return on equity (ROE) and return on assets (ROA), both of which measure profitability, were inversely connected to the ratio of non-performing loans to total loan of financial institutions, resulting in a drop in profitability Ahmad and Ariff (2007) investigated the fundamental factors of commercial bank credit risk

on developing market banking systems in comparison to established economies According to the report, regulation is vital for banking systems that offer a variety of products and services; management quality is critical in the circumstances of loan-dominant banks in emerging nations A rise in loan loss provisions is also seen as a strong predictor of prospective credit risk The study also found that credit risk in emerging-market banks is higher than in developed-market banks

Bhattarai (2016) investigated the influence of credit risk on Nepalese commercial banks' profitability ratios A regression model was used to evaluate aggregated data from 14 commercial banks from 2010 to 2015 The regression results reveal that the bad debt ratio has

a negative impact on the bank's profitability ratio, whereas the cost per loan asset has a positive impact Furthermore, while bank size has a favorable effect on the bank's profitability ratio,

there is no statistical evidence that the capital adequacy ratio and cash reserves have an impact

on the bank's profitability ratio

The relationship between credit risk and profits at six commercial banks in Ghana from 2005

to 2009 is investigated by Boahene and colleagues (2012) The author measured credit risk using three variables: bad debt ratio, net charge-off rate, and profit ratio before provisioning/total outstanding debt; the dependent variable is return on equity (ROE) The panel data model regression results show that credit risk has a positive connection with bank performance, indicating that banks in Ghana are extremely profitable while being exposed to significant credit risk

Alshatti (2015) employs a panel data model to examine whether credit risk measurement factors are connected to commercial bank performance (as measured by ROA and ROE) in Jordan The findings indicate that the bad debt/total outstanding debt ratio has a beneficial effect on bank profitability

Nguyen Thanh Dat et al (2021) investigated how credit risk affects the performance of Vietnamese commercial banks Research and survey 30 joint-stock commercial banks in Vietnam from 2007 to 2019 The article employs a regression model with panel data and the Hausman test to select an appropriate estimation method to test the impact of human

resources on the environment and bad debt ratio on commercial bank performance The findings indicate that credit risk indicators have a strong positive impact on bank profitability Furthermore, there is a link between bank size and bank performance The author provides some solutions based on the research findings to restrict the influence of credit risk on the profitability of commercial banks in Vietnam

Over the period 1998-2008, Al-Khouri (2011) examined the impact of a bank's specific risk characteristics as well as the general banking environment on the performance of 43

commercial banks operating in six Gulf Cooperation Council (GCC) nations Using fixed effect regression analysis, the results revealed that credit risk, liquidity risk, and capital risk

are the major factors influencing bank performance when measured by return on assets, while liquidity risk is the only risk influencing profitability when measured by return on equity Beside, Ben-Naceur and Omran (2008) discovered that bank capitalization and credit risk have a positive and significant impact on banks' net interest margin, cost efficiency, and profitability in Middle East and North Africa (MENA) countries from 1989 to 2005 in their attempt to examine the influence of bank regulations, concentration, financial, and

institutional development on commercial banks' margin and profitability In their study, Ahmed, Takeda, and Shawn (1998) discovered that loan loss provision has a considerable favorable influence on non-performing loans As a result, an increase in loan loss provision suggests an increase in credit risk and degradation in loan quality, which has a negative impact on bank performance

Along with the credit risk, bank stability is also influenced by various variables, bank size is one of the factors that greatly affects the stability of the bank Studies in the world showed a two-way correlation of these two factors The positive correlation indicates that large banks will have the advantage of market share, the ability to dominate the market and generate higher revenues It resulted that the stability of these banks is also higher (Martin Cihák & Heiko Hesse, 2008; Luc Laeven, Lev Ratnovski &Hui Tong, 2014; Boyd et al, 2004) Other studies, meanwhile, had found that large-scale banks often ventured into many areas,

including those that were high risk and threatened bank stability (Mirzaei, Moore & Liu, 2013; Fu et al , 2014; Pak & Nurmakhanova, 2013 ) Larger banks can diversify their lending and investment portfolios, develop their network, spend heavily on technology, and maintain

a good reputation and high degree of consumer and investor confidence (Tarek Al-Kayed et al., 2014) As a result, the scale of a bank has a significant and beneficial impact on its profitability Furthermore, by specializing, major banks may lower their input and operational expenses (Gupta & Mahakud, 2020; Nguyen & Nguyen, 2016; Sufian, 2011)

When it comes to bank capital structure, many supposed that better capitalized banks, in particular, experience reduced bankruptcy costs, lowering capital costs and increasing

profitability Recent studies confirm evidence when they examine banks in the Sub-Saharan region from 2000 to 2006 and find that capital structure does not influence bank

effectiveness, whereas profitability has a negative and significant impact on capital structure (Adesina et al., 2015; Sufian & Habibullah, 2009) Amidu (2007) and Adesina et al (2015) examine banks in the Sub-Saharan region and find a negative relationship between bank profitability and capital structure

According to Wassim Rajhi and Slim A Hassairi (2013), the higher the solvency of the bank

is, the safer the bank will be The loss of assets will minimize in banks In other words, the relationship between solvency and bank stability is positive

Most studies on banking stability were considered in a certain macroeconomic environment which refered to the influence of factors representing the economy such as GDP, inflation, exchange rates, government policies These factors were evaluated in two directions: there were good and bad effects on banking stability

Banks are expected to be more stable in stronger growth economies (Nguyen et al 2012) There have been many studies suggesting that GDP growth has a positive impact on bank stability Because GDP growth when the economies are growing well Meanwhile, the income of individuals and households increases, on the one hand, an increase in the income

of individuals and households will promote them to pay off the loan Therefore, stability of banks is maintained (Diaconu and Oanea, 2014; Chen et al, 2017; Djatche 2019; Abuzayed et

al, 2018) Hence, the paper states that the GDP growth rate is positively correlated to bank stability

Inflationary pressures can have a mixed influence on bad debt Higher inflation, on the other hand, can make debt repayment simpler for two reasons The Phillips curve, for example, is related with reduced unemployment rates and, as a result, can diminish the real value of the

loan (Castro, 2013) Inflation, on the other hand, might drive clients to default when their real income falls In countries with variable lending rates, inflation can have a negative impact on the ability of customers to repay loans due to changes in monetary policy aimed at

combatting inflation or interest rate modifications made by lenders to retain profits (Nkusu, 2011) As a result, the link between inflation and bad debt might be either positive or

negative In particular, factors that appeared more in research related to banking activities such as GDP , inflation (Okumus & Artar, 2012; Rahim et al, 2012; Heiko Hesse & Martin Cihák, 2007, Martin Richard Goetz, 2016) The research use two factors which is GDP and Inflation to analyze the impact of macroeconomic on the bank stability

According to the different research results, the article builds research hypothesises on the impact of credit risks as well as other determinants on bank stability below:

H1: Increased credit risk creates banking instability

H2: Relationship of bank size and stability is negative

H3: The capital structure negatively impact on bank profitability

H4 : Solvency is positively correlated with banking stability

H5 : GDP impact positively to banking stability

H6: There is a positive relationship between credit risk and bank profitability

H7: Inflation has the negative impact on bank stability

III THE OVERVIEW OF VIETNAMESE BANK STABILITY IN THE PERIOD FROM

2012 TO 2022

According to a study by Nguyen et al, bank stability in Vietnam was influenced by various factors, such as bank size, credit growth, liquidity ratios, income diversification, loan to total assets ratio, inflation rate, and GDP growth The study used a sample of 22 commercial banks and Bayesian linear regression to analyze the data from 2012 to 2022 The results showed that bank size, credit growth, and liquidity ratios had a positive impact on bank stability,

while income diversification and loan to total assets ratio had a negative impact Inflation rate also had a negative effect on bank stability, while GDP growth had a positive effect

According to another study by Le et al, the COVID-19 pandemic had a negative impact on financial stability in Vietnam, especially in the early stage of the outbreak The study used a sample of daily data from January 23, 2020 to June 30, 2022, and employed the VECM and NARDL models to examine the relationship between the pandemic and financial stability from the perspectives of the interbank market and the stock market The results indicated that the pandemic reduced the interbank lending and borrowing rates, as well as the stock market index, in both short term and long term However, the impact of the pandemic gradually faded over time The study also found an asymmetric relationship between the financial market and the pandemic in both short term and long term

According to a dataset by Tran et al, which consists of key statistics on the activities of 45 Vietnamese banks from 2002 to 2021, the Vietnamese banking system experienced

significant changes and improvements over the years The dataset includes information on deposits, loans, assets, and labor productivity of the banks, as well as some macroeconomic indicators such as GDP growth, inflation rate, exchange rate, and interest rate The dataset can be used for various purposes, such as analyzing the performance, efficiency, profitability, and stability of the banks, as well as examining the impact of macroeconomic factors on the banking sector

The Vietnamese banking sector faced some challenges in 2020 due to the COVID-19

pandemic, such as liquidity pressure, lower credit growth, higher provisioning, and reduced profitability However, the sector also showed resilience and adaptation, thanks to the timely and effective response of the government and the central bank, as well as the strong

fundamentals and business prospects of the banks1

Vietcombank, one of the largest and most reputable banks in Vietnam, achieved impressive results in 2020, despite the adverse impacts of the pandemic The bank reported a total

revenue of VND 132.8 trillion, an increase of 10.3% compared to 2019, and a pre-tax profit

of VND 23.1 trillion, an increase of 12.3% compared to 2019 The bank also maintained a high asset quality, with a non-performing loan ratio of only 0.62%, and a high capital

adequacy ratio of 11.3% Vietcombank also enhanced its brand value, ranking 207th in the Brand Finance Banking 500 list, up from 325th in 2019

The Vietnamese banking sector is expected to recover and grow further in 2021, as the economy rebounds from the pandemic and the demand for credit increases The World Bank projected a credit growth rate of 12% for Vietnam in 2021, higher than the estimated rate of 10.1% in 2020 The sector is also expected to benefit from the ongoing digital transformation, the development of fintech and e-commerce, and the integration into regional and global markets

IV METHODOLOGY

1 Data

This study's analysis gathered financial data from the Finance.vietstock.vn database, as well as the annual report and audited financial statements of 22 Vietnamese commercial banks Commercial banks that provide complete public reporting data in line with the legislation, as well as a credible source of income statements, balance sheets, and other financial and non-financial data With regard to the observation time, the period from

2012 to 2022 will be selected

The data were structured in a panel format to take use of the advantages of estimating with

a larger number of observations or degrees of freedom, thus increasing estimator efficiency Furthermore, panel data analysis enables the management of unobserved time-invariant heterogeneity, such as cultural characteristics or organizational variations, as well as the assessment of the dynamics of individual behaviors, which cannot be computed using cross-sectional data

or REM model has autocorrelation or heteroscedasticity, the FGLS (Feasible Generalized Least Squares) model is used because this model controls autocorrelation and heteroscedasticity The software used is Stata 13.0

2.2 Pooled OLS

Pooled OLS requires a stationary and balanced panel data It has constant coefficients of slopes and intercepts regardless of time and individuals; hence it ignores the individual effects in error term and manipulates the true relationships among dependent and independent variables (Gil-Garcia & Puron-Cid, 2015) The data is pooled, which will later be processed by Ordinary Least Square (OLS) method Wooldridge (2010) suggested that the pooled OLS should only be used if the sample selected for each time period of the data is not the same There are a lot of disadvantages that make pooled OLS biased, most importantly the error terms tend to face serial correlation and

heteroskedasticity (Podesta, 2000) Since the sample in this study is similar across individuals, it is more recommendable to make use of Fixed effect model (FEM) and Random effect model (REM) instead

2.3.Fixed effect model (FEM)

Tackling the limitation of Pooled OLS, the FEM focuses on the differences in individuals because it helps indicate the relationship between outcome and explanatory variables within countries/ companies etc, thus studying the influence of variables which vary throughout time The time-invariant variables such as gender will be excluded due to collinearity (M.Wooldridge, 2010), hence we can study the net impact of independent variables on dependent variables

2.4.Random effect model (REM)

Unlike FEM, REM assumes the random fluctuations among entities hence they are not intercorrelated with neither of the variables Furthermore, REM allows the existence of variables that do not change over time In the FEM, these time-invariant variables are absorbed by intercepts, but they are allowed to appear fully in the REM

In this study, the author will make use of all three methods to run regression analyses; and conduct necessary tests for the robustness of those models, namely Hausman Test for choosing REM and FEM; VIF test for Multicollinearity; LM Test for Heteroskedasticity; Wooldridge Test for Autocorrelation However, only the best completed results will be presented

2.5 FGLS model

When it comes to FGLS, the modeling experience is divided into two stages The model is first estimated using OLS or another consistent (but inefficient) estimator, and the residuals are used to construct a consistent estimator of the errors covariance matrix (to do so, one frequently needs to examine the model adding additional constraints; for example, if the errors follow a time series process, a statistician generally needs some theoretical assumptions on this process to ensure that a consistent estimator is available) Then, using the consistent estimator of the error covariance matrix, GLS concepts can be implemented

Whereas GLS is more efficient than OLS in the presence of heteroscedasticity (sometimes called heteroskedasticity) or autocorrelation, FGLS is not (Baltagi, B H.,2008) The feasible estimator is asymptotically more efficient, providing the errors covariance matrix

is consistently computed, but it can be less efficient than OLS for small to medium-sized samples This is why some authors prefer to employ OLS and reformulate their inferences

by simply taking into account an alternative estimation for the variance of the estimator that is robust to heteroscedasticity or serial autocorrelation Under heteroskedasticity or serial correlation, FGLS is preferable over OLS for large samples (Hansen, Christian B.,2007)

FGLS can be applied to a wide range of data formats, including cross-sectional, time series, panel, and spatial data, where the errors may display varying patterns of correlation FGLS can also manage heteroskedasticity, which means that the variances of the errors differ FGLS is frequently utilized in econometrics and other applied statistics domains

3 Variables

When investigating issues affecting the stability of commercial banks, authors Nicolae Petria (2013), Hasan Ayaydin (2014), and Aremu Mukaila Ayanda (2013) all concluded: Bad debt has an impact on the stability and profitability of commercial banks Starting with the model of the preceding authors, the author constructs a model to investigate the impact

of credit risk on bank stability Using the dependent variables ROE (bank profitability) and ROA (bank stability), credit risk is represented by the variable bad debt ratio (NPL), and the following controllable variables are also included in the model The multivariate regression model employed in this investigation is as follows:

Model 1: ROA = β0 + β1* CSTRUCTURE + β2* SIZE + β3* NPL + β4*

Solvency + β5*GDP + β6*INF+ u