MINISTRY OF EDUCATION AND TRAINING HO CHI MINH UNIVERSITY OF BANKING GRADUATION THESIS DETERMINANTS OF CAPITAL STRUCTURE OF THE RETAIL BUSINESS ENTERPRISES LISTED ON VIETNAM’S STOCK MARKET Major Finan[.]
INTRODUCTION
REASONS FOR CHOOSING THE TOPIC
An effective capital structure is crucial for a company's success, enabling financial managers to optimize capital proportions based on current events This strategic approach supports sustainable growth while ensuring the company remains agile in addressing liquidity needs Additionally, banks analyze a company's liability distribution to refine their lending policies, thereby enhancing their business opportunities.
Understanding capital structure is crucial for investors, as it significantly influences a company's success By analyzing how capital structure evolves and its interplay with various economic factors, investors can enhance their evaluations of a company Capital structure adjustments do not occur instantly following economic shifts, leading to scenarios where a company's existing liability proportions may become suboptimal For instance, firms heavily reliant on debt may benefit from low interest rates through tax shields, but rising inflation and increased interest rates can adversely affect these companies, particularly those with high debt ratios This study aims to develop a model that elucidates the relationship between capital structure and economic factors, enabling financial managers and investors to make informed decisions based on anticipated company responses to economic changes.
Numerous studies have explored the capital structure of companies, significantly influenced by Modigliani and Miller’s foundational theory, which examines the effects of capital structure on firm value and average cost of capital Additionally, research by Huang and Song (2002) analyzed data from 1,000 listed enterprises in China from 1994 to 2000, demonstrating that varying levels of leverage—categorized as short-term or long-term—can create distinct relationships with other economic factors.
In their 2019 study, researchers examined the determinants of capital structure among 74 Vietnamese listed construction firms from 2014 to 2018 Similarly, Dinh and Pham (2020) analyzed data from 30 pharmaceutical companies listed on the Vietnam Stock Exchange during the period of 2015-2019 While some studies address the overall capital structure of various enterprises, others focus on specific industries, often neglecting the retail sector, despite retail revenues reaching significant levels.
5000 billion Viet Nam thousand Dong of our country revenue per year (General Statistics Office of Vietnam, 2018-2022).
In 2022, Vietnam's retail sales and consumable services surged by 19.8% compared to the previous year, with 2023 showing a 6.5% increase in the first half, reaching 3,016.8 billion VND This growth reflects the retail industry's upward trend, particularly fueled by the rise of e-commerce during challenging times when many businesses adapted by partnering with online distribution channels to maintain supply during quarantine The shift to online shopping has accelerated sales growth due to its convenience, even amidst economic difficulties The retail sector's potential for recovery is promising, as it requires a high capital turnover ratio, relying heavily on short-term debt for operations Effective management of asset and liability maturity is crucial for retail businesses, highlighting the importance of capital structure management in sustaining growth.
Therefore, in order to support the business activities of companies working in the retail business field, the author has chosen the topic: “DETERMINANTS
The graduation thesis titled "Capital Structure of Retail Business Enterprises Listed on Vietnam’s Stock Market" aims to enhance understanding of effective capital structure management for retail companies It provides valuable insights that can help strengthen the financial framework of these enterprises, ultimately contributing to their growth and sustainability in the competitive market.
RESEARCH OBJECTIVES
The general objectives of the research are to study the determinants of capital structure of the retail business enterprises listed on Vietnam’s in the period of 2018-
To achieve the general objectives, the thesis has to solve the following specific objectives:
Firstly, identifying the factors that affect capital structure of retail business enterprises listed on Viet Nam’s stock market
Secondly, analyzing the influence of the determinants of capital structure of the retail business enterprises listed on Vietnam’s stock market
Thirdly, giving suggestion related to the company’s capital structure determinants.
RESEARCH QUESTIONS
To achieve the following specific objectives, the thesis has to solve the following specific questions:
First question: What are the explained variables for the capital structure of the company?
Second question: How do these factors affect the determinants of capital structure of the retail business enterprises listed on Vietnam’s stock market?
Third question: What advice can be given according to the result of the forecast?
SUBJECT AND AREA OF RESEARCH
The subject of the thesis are capital structure and factors affecting the capital structure of the retail business enterprises listed on Vietnam’s stock market
Research space : The study uses data from 38 retail companies, which are listed on the Vietnam’s stock market
The research spans from January 2018 to December 2022, providing a robust five-year dataset for analysis This timeframe is chosen under the assumption that business activities typically endure for a duration of five years.
METHODOLOGY
The quantitative method analyzes past data to explore the relationships between dependent and independent variables, as well as the interactions among independent variables.
The regression analysis employs Pooled OLS, Fixed Effect, and Random Effect models to estimate panel data, highlighting key data characteristics These models are practical tools for forecasting future values, enhancing predictive accuracy.
To determine the efficiency of the model for practical application, tests for multicollinearity, variance, and heteroskedasticity are conducted, including the Likelihood Ratio test and the Hausman test.
CONTRIBUTION OF THE THESIS
This thesis aims to identify the determinants of company capital structure, enhancing the understanding of this critical subject Through various tests, it uncovers key variables that influence changes in capital structure, reinforcing existing theories and providing valuable insights for analyzing the capital structures of other businesses.
This thesis explores the relationship between a company's capital structure and various economic factors through data analysis By understanding this connection, investors can enhance their investment decisions, financial managers can refine their capital allocation strategies in response to current economic conditions, and bankers can anticipate business behavior to inform their lending policies.
STRUCTURE OF THE RESEARCH
In addition to the introduction, conclusion, table of contents and list of references, the thesis consists of 5 chapters:
Chapter 1 identifies the research subject, which are the determinants of capital structure of the retail business enterprises listed on Vietnam’s stock market The chapter also covers the reasons for choosing the topic, research objectives, research questions, subject and area of research, research methods, research contribution and the thesis structure in detail
Chapter 2 Theoretical background and literature review
Chapter 2 presents the relevant concepts of the research topic, which includes (1) the concept of capital structure; meaning of capital structure in business, the measurement of capital structure; (2) theoretical background and the determinants of capital structures based on the theories that were established in the past; (3) previous empirical studies in the field, which consist of both foreign and domestic research Chapter 2 covers the basis knowledge related to the research subject by referring the previous research and theories, the chapter also states the dependent and independent variables which applied to assess the determinants of capital structure of the retail business enterprises listed on Vietnam’s stock market
Chapter 3 indicates the order of steps of the research process in detail, which involves mentioning the data collection method and data processing method Accordingly, the chapter aims to describe the chosen variables and the data calculation steps in building the regression model by using the panel data, which calculated from the raw data in enterprise’s financial statements
Chapter 4 Research result and discussion
Chapter 4 aims to utilize findings from Chapter 3 to identify and measure the variables influencing the capital structure of retail enterprises listed on Vietnam's stock market It explores the relationships among independent variables through various quantitative research methods The author employs a dataset derived from company financial statements to conduct several quantitative analyses, including descriptive statistics, correlation coefficient analysis, multicollinearity tests, serial correlation tests, and heteroskedasticity tests To enhance model efficiency and address potential defects, the Feasible Generalized Least Squares (FGLS) method is applied, forming a crucial part of the thesis results.
Chapter 5 presents the conclusions on the determinants of capital structure for retail businesses listed on Vietnam's stock market, based on research findings, theoretical frameworks, and empirical studies It also offers recommendations derived from these results Additionally, the author addresses minor limitations of the thesis and suggests directions for future research.
LITERATURE REVIEW
OVERVIEW OF CAPITAL STRUCTURE
According to Hindi and Shama'a (1989), capital structure consists of all the debt and equity of the enterprise or in other words, capital structure is all the liabilities and shareholder equity that company has used to finance for its investment whether it is long-term or short-term investment The other authors define a firm's capital structure as a mix of debt and equity used to finance production and business activities (Damodaran, 2014) As defined by Ross et al
(2008), the capital structure of a firm, also known as financial leverage, is the combination of the use of debt capital and equity in a certain ratio to finance business activities
The author defines capital structure similarly to other researchers, viewing it as the balance between debt and equity in a company's liabilities This thesis focuses on the capital structure of retail businesses listed on Vietnam's stock market, specifically represented by the ratio of total debt to equity, which reflects the company's financial leverage.
2.1.2 Meaning of capital structure in business
A company's success heavily relies on its capital structure, specifically the balance between debt and equity Efficient capital utilization enhances operational mobilization, allowing businesses to address their capital needs seamlessly Conversely, an inappropriate capital structure can expose a company to significant financial risks Financial leverage is a key index commonly employed by financial managers to effectively manage capital structure.
Financial leverage measures the ratio of total debt to total equity, providing companies with a flexible capital source to meet production and operational needs Utilizing debt can also offer tax benefits through the tax shield effect from interest payments However, a high debt ratio may result in significant interest costs, particularly in a high-interest-rate environment, potentially jeopardizing the company's viability Conversely, a higher equity proportion eliminates the obligation for interest payments, replacing them with dividend obligations to shareholders, which can enhance the company's credibility by demonstrating public investment Nonetheless, a high equity ratio diminishes the tax shield effect and may lead to ownership dispersion, creating pressure on management and potentially impacting the company's strategic direction.
2.1.3 Measurement of enterprise’s capital structure
Capital structure reflects a company's financing policy by balancing funds from various capital sources to fulfill its operational and production needs Analyzing and measuring an optimal capital structure is crucial for effective business activities Managers can utilize several financial indices, such as debt ratio and financial leverage, to monitor changes in capital structure over time.
Debt ratio = Total Liabilities/Total Liabilities and Shareholder Equity
Debt ratio indicates the percentage of debt in the total capital that a company uses, which also means the percentage of assets that is formed by debt
Financial leverage = Total Liabilities/Total Shareholder Equity
High financial leverage indicates a significant reliance on debt within a company's overall capital structure While this leverage can enhance purchasing power and enable businesses to meet capital requirements effectively, it also increases financial risk In adverse economic conditions, such heightened risk can lead to severe repercussions for the company's operations.
THEORETICAL BACKGROUND OF CAPITAL STRUCTURE
Durand (1952) highlighted that an enterprise's value is influenced by its capital structure, noting that the cost of debt is typically lower than the cost of equity due to tax benefits, which results in a decrease in the weighted average cost of capital (WACC) as debt levels rise This suggests the existence of an optimal capital structure that maximizes enterprise value by balancing debt and equity to minimize WACC However, increased debt also heightens financial and default risks To address these concerns, Modigliani and Miller's Theory was introduced in 1958, providing further insights into capital structure dynamics (Brigham & Houston, 2009).
2.2.2 Modigliani and Miller's theory (M&M theory)
The Modigliani and Miller theory, commonly referred to as the M&M theory, is a cornerstone of financial theory, established by Franco Modigliani and Merton Miller in 1958 This theory examines how a company's value is influenced by its capital structure in both tax and non-tax contexts.
In a tax-free environment, the Modigliani and Miller theory posits that a perfect market—characterized by the absence of taxes, transaction fees, and bankruptcy costs, along with symmetric information—results in a company's value remaining unaffected by its financial leverage This implies that the distribution of capital between debt and equity does not alter the company's value, which is solely determined by its tangible assets Consequently, there is no optimal capital structure or tax shield under this hypothesis However, this proposition is limited in practical application, as it relies on the unrealistic assumption of a perfect and tax-free market.
The impact of tax, transaction fees, asymmetric information, and bankruptcy costs suggests that leveraged companies possess a higher value than their unleveraged counterparts due to the tax shield, as established by Modigliani and Miller (1963) They highlighted that the value difference stems from the present value of the tax shield, with findings indicating that an increasing debt ratio can elevate a company's value despite the associated financial risks and bankruptcy costs This theory posits that maintaining efficiency is best achieved through a high proportion of debt to leverage the tax shield, implying no optimal capital structure exists However, numerous companies have thrived without significant debt, challenging this theory and paving the way for the development of the trade-off theory.
The trade-off theory, introduced by Kraus and Litzenberger in 1973, highlights the balance between the advantages of debt, such as tax shields from interest, and the associated costs, including financial distress and agency costs, leading to the concept of optimal capital structure This theory posits that there is a specific point in a firm's capital structure distribution that maximizes the benefits of debt utilization However, if a company borrows excessively beyond this optimal debt ratio, the resulting financial distress and agency costs can diminish the firm's value.
Myers (2001) suggests that an increasing debt ratio can cause financial distress costs to escalate more rapidly than the benefits of tax shields, ultimately diminishing a company's value The theory indicates that firms with substantial tangible assets and taxable income typically exhibit higher debt ratios Additionally, larger firms with significant liquidity tend to have more debt than equity Furthermore, it is advised that profitable businesses leverage debt to reduce taxable income, while companies with high growth potential should limit borrowing to mitigate the risk of financial crises.
Like the M&M theory, the trade-off theory fails to account for the success of numerous companies that effectively operate with minimal debt This limitation paved the way for the development of the pecking order theory.
Pecking order theory, introduced by Gordon Donaldson in 1961 and further developed by Myers and Majluf in 1984, posits that information asymmetry is absent, implying that investors and company insiders possess equal knowledge about the company's information However, in reality, insiders often hold more information than market participants, leading to disparities in information among those interested in the company.
Myers and Majluf (1984) highlight that asymmetric information influences capital structure, leading to misvalued stock prices in the market Myers (1984) notes that firms tend to issue shares for capital when their stock is perceived as overvalued, while borrowing becomes a preferred option when the company is undervalued Additionally, the level of financial distress plays a crucial role; high financial distress decreases the debt ratio in a firm's capital structure, whereas low financial distress enables the firm to leverage debt for substantial growth.
The theory of capital structure emphasizes the pecking order in which companies choose their financing sources, favoring internal cash flow over external options When a firm's capital requirements surpass its available resources, it resorts to external financing, selecting options based on increasing costs associated with asymmetric information The accompanying figure illustrates the hierarchy of capital sources in financial decision-making.
Figure 2.1 Pecking order of capital
According to the pecking order theory, companies with high endogenous cash flow prefer to utilize internal capital and debt over issuing shares for public capital raising When endogenous cash flow is inadequate, firms turn to external sources, resulting in an increased ratio of debt or equity This theory significantly highlights the impact of cash flow on a firm's capital structure.
Agency costs theory, introduced by Jensen and Meckling in 1976, highlights the conflicts that arise when the interests of managers (agents) diverge from those of owners (principals) This misalignment can lead to actions that may harm the company's performance or hinder its growth trajectory To mitigate these conflicts, agency costs serve as compensation for managers, incentivizing them to align their actions with the owners' objectives Additionally, the theory identifies agency costs of debt and equity, which reflect the dynamics between creditors, shareholders, and managers.
The theory suggests that as share issuance rises, the conflict of interest between managers and shareholders intensifies, leading to increased agency costs of equity These costs arise when managerial decisions fail to enhance shareholder value, encompassing expenses related to owner oversight, compliance costs for managers, and the loss of utility stemming from discrepancies between managerial actions and the owners' utility-maximizing goals (Fama, 1980).
The agency cost of debt arises from the conflict of interest between creditors and managers, where managers may increase profits through leverage without sharing gains with creditors Conversely, if the company fails or declares bankruptcy, creditors face additional burdens As the debt ratio increases, managers tend to be more cautious in their business operations, leading to improved efficiency However, a higher debt ratio also heightens risks for creditors Consequently, rising debt levels are often accompanied by increasing interest rates Currently, the agency cost of debt encompasses the opportunity cost associated with managerial decisions, the costs incurred by creditors to monitor managers, and the compensation required to mitigate the risks of business defaults.
DETERMINANTS OF A COMPANY’S CAPITAL STRUCTURE
Trade-off theory concludes that larger firms with significant tangible assets and taxable income typically exhibit a higher debt ratio compared to smaller firms Additionally, large firms with high liquidity tend to have more debt relative to equity The low agency cost of debt in these firms is attributed to their easier access to credit markets, as they are often viewed as more creditworthy Furthermore, large companies prefer using debt to leverage tax shields for growth Overall, this study suggests that a company's size positively influences its financial leverage, a finding that
(2006), Rashid and Akin (2020) and the results of domestic study such as Dinh and Pham (2020) Regarding the arguments stated above, the study has the following hypothesis for the research
H1: Company’s size (SIZE) has positive impact on the financial leverage
Company’s size is measured by the logarithm of total assets of the company
According to trade-off theory, as outlined by Myers (2001), larger firms tend to exhibit a positive correlation with financial leverage, as they generally maintain higher liquidity and utilize more debt compared to equity In contrast, pecking order theory posits that companies with substantial total assets prefer to finance their operations through internal capital and debt instead of issuing new shares to attract public investment The author supports the hypothesis that a firm's size positively influences its debt usage, aligning with findings from previous studies by Dinh and Pham (2020), Huang and Song (2006), and Rashid and Akin (2020).
The profitability of a company is a key indicator of its efficiency, and extensive research has explored the connection between financial leverage and profitability However, findings from these studies often vary significantly.
The Trade-off theory suggests that the tax-shield effect enables companies to benefit from debt financing, leading to substantial business growth Consequently, the theory concludes that a company's profitability is positively correlated with its financial leverage.
According to pecking order theory proposed by Myer (1984), profitable companies typically minimize public share issuance to avoid ownership disparity and prioritize internal cash flow over external funding when addressing capital needs Consequently, this theory concludes that a company's profitability is inversely related to its financial leverage Based on these insights, the study formulates the following research hypothesis.
H2: Profitability of a company (ROA) has negative impact on the financial leverage
The profitability of a company is assessed using the return on assets ratio, revealing varying conclusions regarding the relationship between capital structure and profits While the trade-off theory suggests a positive link between profitability and financial leverage, the pecking order theory, as proposed by Myer (1984), indicates a negative relationship Despite these differing perspectives, the author supports the hypothesis of a negative impact of profitability on capital structure, aligning with findings from studies by Almuaither and Marzouk (2019) and Rashid and Akin (2020).
Agency cost theory suggests that as the debt ratio increases, the agency cost of debt also rises due to the transfer of risk However, a high proportion of tangible assets in a company serves as a reliable means to repay debt, effectively reducing agency costs This enables firms with significant tangible assets to enhance their borrowing capacity and leverage tax benefits from interest payments to support operations Furthermore, research by Huang and Song (2006) demonstrates a positive relationship between fixed assets and financial leverage, reinforcing the consensus that a company's tangibility is positively correlated with its financial leverage usage Based on these insights, the study proposes the following hypothesis.
H3: Tangibility of a company (TANG) has positive impact on the financial leverage
The tangibility of a company, determined by the fixed assets to total assets ratio, is positively linked to its capital structure According to agency cost theory, firms with a higher proportion of tangible assets possess greater borrowing capacity, allowing them to leverage tax shields from interest to enhance business operations This leads to an increased debt usage ratio in such companies Additionally, research by Huang and Song (2006) supports the positive correlation between fixed assets and financial leverage.
Growth opportunities of a company ( GROWTH )
The growth opportunities indicator serves as a key metric for assessing the development trends of a company's business activities, calculated based on revenue growth rates Previous research has shown an ambiguous relationship between growth opportunities and capital structure, similar to findings related to profitability indicators.
According to Myers (1984) in the agency cost theory, high-growth companies prefer equity financing over debt financing due to the tendency of highly leveraged firms to allocate most of their cash flow gains to meet interest obligations, benefiting creditors more than shareholders Consequently, companies with promising projects are inclined to finance them through shareholder equity, suggesting an inverse relationship between growth opportunities and financial leverage.
Pecking order theory suggests that companies with strong growth potential often seek debt financing to expand their business activities Based on this theory, the study proposes the following research hypothesis.
H4: Growth opportunities (GROWTH) has positive impact on the financial leverage
Growth opportunities are assessed through a company's sales growth rate Past research has shown an ambiguous relationship between growth opportunities and capital structure According to agency cost theory, Myers (1984) posits that high-growth companies prefer equity financing over debt, suggesting an inverse relationship between growth opportunities and financial leverage Conversely, pecking order theory indicates that companies with strong growth prospects often utilize higher financial leverage to expand their operations Additionally, Almuaither and Marzouk (2019) and Rashid and Akin (2020) have identified a positive relationship between growth opportunities and capital structure, leading the author to adopt this hypothesis for the study.
Tax payments of a company ( TAX )
Taxation plays a crucial role in shaping a company's capital structure, as highlighted by Modigliani and Miller's theory and the trade-off theory These theories suggest a positive correlation between a firm's tax payments and its financial leverage Specifically, the trade-off theory indicates that companies with significant tangible assets and taxable income typically maintain higher debt ratios compared to others Empirical studies conducted by Vo support these findings.
Research by Almuaither and Marzouk (2019) indicates a positive relationship between tax rates and the utilization of debt leverage Based on these findings, the study proposes a hypothesis for further investigation.
H5: Tax payments of a company (TAX) has positive impact on the financial leverage
Modigliani and Miller's theory, along with the trade-off theory, suggests a positive correlation between a company's tax payments and its financial leverage Empirical research by Vo (2017) and Almuaither and Marzouk (2019) supports this connection, indicating that higher tax rates are associated with increased debt leverage Consequently, the author formulated a hypothesis based on this premise to explore the research topic further.
Non-debt tax shield of a company ( NDTS )
PREVIOUS RESEARCH IN THE FIELD
Huang and Song (2006) conducted a study on the capital structure of over 1,000 Chinese listed companies from 1994 to 2000, utilizing OLS regression analysis Their findings revealed a positive relationship between financial leverage and factors such as firm size, non-debt tax shields, and fixed assets Conversely, profitability and earnings volatility were found to negatively impact financial leverage Additionally, the study indicated that debt leverage varies across different industries.
Chang et al (2009) utilized structural equation modeling (SEM) to investigate the determinants of capital structure choice, employing a Multiple Indicators and Multiple Causes (MIMIC) model on data from 1988 to 2003 Their findings provided more compelling insights than those of Titman and Wessels (1988) The study identified growth, measured by the market-to-book assets and market-to-book equity ratios, as the most significant determinant of capital structure, followed by profitability, assessed through operating income relative to total assets or total sales Notably, the relationship between growth and capital structure varied based on the measurement used; a negative correlation emerged with the market-to-book assets ratio, while a positive correlation was observed with the market-to-equity ratio Similarly, the analysis revealed contrasting effects of profitability on capital structure, with a negative influence when operating income was divided by total assets and a positive relationship when measured against total sales Additionally, the research highlighted an inverse relationship between the collateral value of assets and debt ratios, as well as between uniqueness and financial leverage, positioning collateral value as the second most crucial factor in capital structure decision-making, following profitability.
M'ng, Rahman, and Sannacy (2017) studied the factors influencing the capital structure of public companies listed on Bursa Malaysia, Singapore Stock Exchange, and Thailand Stock Exchange from 2004 to 2013 Their research identified key determinants such as profitability, firm size, asset tangibility, depreciation relative to total assets, inflation, and lagged leverage Correlation tests revealed no significant multicollinearity among the independent variables across the three countries Utilizing the OLS method with fixed effect panel data regression, the study confirmed that the chosen independent variables effectively explained the variability in leverage ratios, as indicated by a high R² value The findings showed a negative relationship between capital structure and both profitability and depreciation to total assets, consistent across all three markets, while a positive relationship was observed for firm size, asset tangibility, inflation, and lagged leverage.
Almuaither and Marzouk (2019) investigated the determinants of capital structure among FTSE 100 companies in the UK for the year 2016, utilizing OLS estimation with six independent variables: company size, profitability, tangibility, growth opportunities, tax, and volatility, along with four industry classification dummy variables, while financial leverage served as the dependent variable Their findings indicated a positive relationship between company size and leverage, as well as between tax and leverage, although these results were statistically insignificant Conversely, the study identified profitability, tangible asset levels, growth opportunities, and volatility as determinants negatively correlated with debt leverage, with the negative relationships of tangible assets and volatility also lacking statistical significance.
Rashid and Akin (2020) examined the factors influencing capital structure in GCC countries, including Bahrain, Kuwait, Qatar, Oman, Saudi Arabia, and the United Arab Emirates, using a sample of 329 non-financial firms from 2009 to 2017 Their research employed regression models to analyze determinants of capital structure at both country and regional levels The study found that firm size, asset tangibility, and growth opportunities positively impact leverage, while factors such as profitability, age, financial constraints, liquidity, and government ownership negatively affect it Additionally, they identified weak evidence for a positive correlation between leverage and operating risks Despite the unique institutional environments of GCC countries, the researchers concluded that the determinants of financing decisions align with those in other developing nations.
Bhattacharjee and Dash (2021) conducted an analysis using pooled regression (OLS) and panel regression (GLS fixed-effects and random-effects) to identify the determinants of capital structure in the Indian cement sector, examining data from twenty-five companies between 2003 and 2011 Key independent variables included the collateralizable value of assets, non-debt tax shield, size, profitability, and growth opportunities The study revealed a significant influence of collateralizable asset value and profitability on financing decisions, indicating that while collateralizable asset value positively correlates with capital structure, profitability has a negative impact.
Doan (2010) conducted a path analysis to examine the determinants of capital structure and financial performance, utilizing raw data from the financial statements of 428 companies listed on the Vietnam stock exchange The study identified key determinants of capital structure, including business efficiency, business risk, asset structure, and company size Findings revealed that the debt ratio of listed enterprises in Vietnam exhibited an inverse relationship with profitability, business risk, and asset structure, while showing a positive correlation with company size.
Vo (2017) conducted the GMM estimation and regression model with the sample data from market data and financial statement of public firms listed on the
Between 2006 and 2015, the Ho Chi Minh City stock exchange analyzed various factors affecting capital structure, excluding financial companies and banks due to their unique business nature The independent variables examined included growth, tangibility, profitability, firm size, and liquidity The findings revealed that the relationship between these determinants and capital structure varied based on the type of leverage considered Specifically, for long-term leverage, all suggested variables positively correlated with capital structure, although some coefficients were insignificant In contrast, for short-term leverage, all variables except growth exhibited an inverse relationship.
Dinh and Pham (2020) conducted a study examining the impact of capital structure on the financial performance of 30 Vietnamese pharmaceutical companies listed on the Vietnam Stock Exchange from 2015 to 2019 Utilizing ordinary least squares (OLS) regression, the research assessed the relationship between capital structure and financial performance, with return on equity (ROE) as the dependent variable Key independent variables included self-financing ratio, financial leverage, long-term assets proportion, debt-to-asset ratio, company size, fixed asset ratio, and growth rate The findings revealed a positive correlation between financial performance and financial leverage, long-term asset ratio, debt-to-assets ratio, company size, fixed asset ratio, and growth rate, while self-financing showed a negative relationship with ROE.
Tran (2022) conducted a study on the factors influencing the capital structure of steel industry enterprises listed on the Ho Chi Minh Stock Exchange, utilizing a regression model to analyze the relationship between capital structure and various economic factors The research examined financial data from nine Vietnamese steel companies over a decade, from 2010 to 2019, with financial leverage as the dependent variable Key independent variables included firm size, liquidity, growth rate, corporate income tax, fixed assets, tangibility, and product-specific characteristics The findings revealed a negative relationship between enterprise size and financial leverage, while liquidity, growth rate, and tangibility significantly impacted the debt ratio However, corporate income tax and product-specific characteristics showed no correlation with capital structure.
A review of existing studies reveals that the findings regarding the determinants of capital structure in Vietnam are inconsistently significant Consequently, there is a pressing need for further research to clarify and refine these determinants, particularly within the retail industry.
The following table focuses on sythesizing and summarizing the previous studies related to the research subject that this thesis aimed to explain.
Table 2.2 Summary of previous studies
Authors Research topic Data Research method Research result
The determinants of capital structure:
1000 Chinese listed companies in the period of 1994-2000
OLS regression Firm size, non-debt tax shield and fixed assets had positive connection with financial leverage
Profitability and earning volatility had negative connection with financial leverage
Determinants of capital structure choice: A structural equation modeling approach
Refined indicators of companies in the period of 1988-2003
Structural equation modeling (SEM), Multiple Indicators and Multiple Causes (MIMIC) model
Growth is identified as the most influential factor affecting capital structure A negative relationship was observed between the market-to-book ratio and capital structure, whereas a positive relationship emerged when growth was measured using the market-to-equity ratio.
The study revealed that profitability exhibited a negative impact when assessed as operating income relative to total assets Conversely, a positive influence was observed when profitability was evaluated using operating income in relation to total sales.
The determinants of capital structure:
Evidence from public listed companies in Malaysia, Singapore and Thailand
Public listed companies on Bursa Malaysia, Singapore Stock Exchange and Thailand Stock Exchange from 2004-
OLS method with fixed effect panel data regression
Negative relationship with capital structure are founded in the profitability and depreciation to total assets, the conclusion was made the same for all three countries
Positive relation are founded in factors like firm size, tangibility of assets, inflation and leverage lagged one year, this result was also consistent for the three countries
Determinants of Capital Structure: Evidence from the UK
OLS estimation Factors that had positive relationship with financial leverage are company size and tax
For the negative relationship, there were profitability, level of tangible assets, growth opportunities, volatility
Factors affecting the capital structure: new evidence from GCC countries
329 non-financial firms for the period between 2009 and
Size, tangibility and gowth opportunities have positive impacts on leverage, while profitability, age, financial constraints, liquidity, and government ownership affect the leverage negatively
They also propose weak evidence for a positive relationship between leverage and operating risks
Determinants of Capital Structure in the Indian Cement Sector
25 companies from the cement industry, over the study period 2003-2011
Pooled regression (OLS) and panel regression (GLS fixed-effects and random-effects) modeling
Collateralizable value of assets was considered to be positively related with capital structure while profitability provide negative impact
Doan (2010) Các nhân tố ảnh hưởng đến cấu trúc tài chính và hiệu quả tài chính: tiếp cận theo phương pháp phân tích đường dẫn
Raw data from financial statements of
428 enterprises listed on the Viet Nam Stock Exchange
Debt ratio of listed enterprises in Viet Nam had inverse relationship with profitability, business risk and asset structure while holding a positive connection with the enterprise size
Vo (2016) Determinants of capital structure in emerging markets: Evidence from
Market data and financial statement of public firms listed on
GMM estimation and Regression model
The independent variables that the author suggested are growth, tangibility, profitability, firm size and liquidity
Vietnam the Ho Chi Minh City stock exchange for the period from 2006 to
For the long-term leverage, all the dependent variables that the author had suggest had positive relationship with capital structure although there are few coefficients had insignificant result
For the short-term leverage, except for growth, all the remaining variables had inverse relationship with short-term leverage
The Effect of Capital Structure on Financial Performance of
30 pharmaceutical enterprises listed on Viet Nam’ Stock Exchange from 2015 to 2019
Firm performance had positive relationship with financial leverage ratio, long-term asset ratio, debt-to- assets ratio, company size, fixed asset ratio and growth rate
Negative relationship with firm’s return on equity (ROE) involved the participation of self-financing
Tran (2022) Factors affecting capital structure of steel industry enterprises listed at Ho Chi Minh Stock
Data from financial statements of nine Vietnamese steel companies listed on the Ho Chi Minh Stock Exchange in the period of 10 years, from 2010 to 2019
The regression analysis reveals that enterprise size negatively impacts financial leverage, while liquidity, growth rate, and tangibility significantly affect the debt ratio Additionally, there is no observed relationship between corporate income tax and product-specific characteristics with capital structure.
Chapter 2 presents the relevant concepts of the research topic, which includes (1) the concept of capital structure; meaning of capital structure in business, the measurement of capital structure; (2) theoretical background and the determinants of capital structures based on the theories that were established in the past; (3) previous empirical studies in the field, which consist of both foreign and domestic research Chapter 2 covers the basis knowledge related to the research subject by referring the previous research and theories, the chapter also states the dependent and independent variables which applied to assess the determinants of capital structure of the retail business enterprises listed on Vietnam’s stock market According to the theories and empirical studies from all over the world, the independent variables that use to explain for the changes of capital structure are (1) Company size (SIZE); (2) Profitability (ROA); (3) Tangibility (TANG); (4) Growth opportunity (GROWTH); (5) Tax payments of a company (TAX); (6) Non debt tax shield (NDTS); (7) Liquidity of the company (LIQUID); (8) Uniqueness of the business (UNI).
RESEARCH METHODOLOGY
RESEARCH PROCESS
The research process is tailored to meet specific objectives, focusing on capital structure Initially, the author reviews foundational theories and prior empirical studies to establish the research direction and formulate hypotheses Data collection involves analyzing financial statements from 38 retail enterprises listed on Vietnam’s stock market, sourced from SSI Securities Corporation Subsequently, the data is processed using Stata17 software to conduct descriptive analysis, correlation analysis, and regression models, including Pooled OLS, FEM, and REM After testing for multicollinearity, autocorrelation, and heteroskedasticity, the optimal regression model is selected The findings elucidate the relationship between various factors and capital structure, leading to recommendations aimed at enhancing capital structure management for companies.
Step 1: Identification of a research problem
The author’s review of previous research on enterprise capital structure reveals inconsistent conclusions, with particular emphasis on the retail industry According to the General Statistics Office of Vietnam, retail revenue ranged from 4,000 to 5,000 billion Vietnamese Dong between 2018 and 2022, highlighting its significance in understanding business dynamics This underscores the necessity of conducting research to explore the behavioral patterns of businesses within this vital sector.
Step 2: Theoretical background and literature review to build research hypothesis and research model
The author reviews theoretical frameworks and previous studies to establish a research pathway, formulate hypotheses, and create a model with explanatory variables related to capital structure The research employs regression analysis to explore the relationships between the subject and the explanatory variables, utilizing Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM) to address model deficiencies Additionally, the Feasible Generalized Least Squares (FGLS) method is applied to eliminate any remaining flaws Quantitative analysis is conducted using Stata software.
The research analyzed data from 38 retail companies listed on Vietnam's stock market, covering the period from January 2018 to December 2022 to ensure a robust sample for the analysis.
The author employs Stata for quantitative analysis, conducting descriptive analysis, correlation assessments, and tests for multicollinearity and heteroskedasticity The study utilizes regression models, including Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM), to analyze panel data effectively To address identified issues, the Feasible Generalized Least Squares (FGLS) method is applied, ensuring robust results throughout the research.
The FGLS method was employed to develop a regression model that illustrates the relationship between capital structure and various economic factors This analysis will focus on the influence and statistical significance of each independent variable, as indicated by their coefficients in the model.
Step 6 involves stating the conclusion of the research, which will cover the overall research process and the achievement of the research along with providing suggestion on capital management based on the regression result
The report will include the detail information about how the research is constructed, which is the detail process from literature review to making suggestion based on the research result
Figure 3.1 Summary of research process
RESEARCH MODEL
To analyze the impact of various factors on capital structure, the author employed the Ordinary Least Squares (OLS) estimation method This technique facilitates optimal model estimation by minimizing the sum of squared residuals, ensuring the inclusion of sufficient variables for accurate analysis.
Overall regression model for panel data:
Theoretical background and literature review
: Intercept/Constant of the regression model
: Coefficient of variable of the independent variable
: Error value between actual value and estimated value
This thesis investigates the relationship between capital structure and various economic factors, drawing on relevant theories and previous research The author selects key variables from past studies to ensure results align with real-world scenarios and to assess their impact on the retail business Key insights are derived from the research conducted by Almuaither and Marzouk (2019), Rashid and Akin (2020), and Bhattacharjee and Dash (2021).
In their research, Chang et al (2009), Almuaither and Marzouk (2019), and Rashid and Akin (2020) utilized financial leverage to represent capital structure Following this precedent, the author also adopted financial leverage for their study While various methods exist to calculate financial leverage, such as the debt-to-asset, debt-to-capital, and debt-to-equity ratios, most researchers prefer the debt-to-asset ratio, as evidenced by Rashid and Akin (2020) and Almuaither and Marzouk (2019) To offer a fresh perspective, the author chose to employ the debt-to-equity ratio for analyzing capital structure data.
Determinants of capital structure are critical factors influencing financial leverage, as highlighted by Almuaither and Marzouk (2019), who identified six key elements: company size, profitability, tangibility, growth opportunities, tax, and volatility In contrast, Rashid and Akin (2020) expanded the framework by proposing additional independent variables, including age, financial constraints, liquidity, and government ownership, alongside size, tangibility, growth opportunities, and profitability This divergence in perspectives underscores the complexity of capital structure determinants in financial analysis.
Research has shown that factors such as the collateralizable value of assets, non-debt tax shields, company size, profitability, and growth opportunities significantly influence financial leverage Many studies agree on key independent variables, including company size, profitability, tangibility, growth opportunities, tax ratio, non-debt tax shield, and liquidity Additionally, Titman and Wessels (1988) highlighted the impact of business uniqueness on capital structure, alongside factors like business longevity, interest expenses, and business risk Due to data limitations, the author has selected eight independent variables for further analysis: company size (SIZE), profitability (ROA), tangibility (TANG), and growth opportunities (GROWTH).
(5) Tax payments of a company (TAX); (6) Non-Debt Tax Shield (NDTS); (7) Liquidity (LIQID); (8) Uniqueness (UNI)
With eight independent variables and the dependent variable we have the overall regression model as below:
: Leverage of firm i at time t and is measured by the debt-to-equity ratio
: Size of company i at time t and is measured by the logarithm of total assets of company i at time t
: Profitability of a company i at time t and is measured by the Earning after tax to total assets of firm i at time t
: Tangibility of a company i at time t and is measured by the Fixed assets to total assets of firm i at time t
: Growth opportunities of a company i at time t and is measured by the growth rate of sale at time t of company i
: Tax payments of a company i at time t and is measured by the tax to earnings before interest and tax (EBIT) ratio
: Non-debt tax shield of company i at time t and is measured by the depreciation to total assets ratio
: Liquidity of company i at time t and is measured by the current assets to current liabilities ratio
: Uniqueness of company i at time t and is measured by the selling expense to sales ratio
: The constant component of the regression model
: Coefficient of the independent variables, which are used to indicate the influence of independent variables on the dependent variable.
RESEARCH METHODOLOGY
This research employs both qualitative and quantitative methods The qualitative approach includes a literature review to formulate hypotheses and clarify the study's variables In contrast, the quantitative method focuses on estimating regression models, utilizing techniques such as Pooled Ordinary Least Squares (OLS), Fixed Effects Model (FEM), and Random Effects Model (REM).
Step 1: Data collection, descriptive analysis and correlation analysis
Data was gathered from the financial statements of 38 retail companies listed on Vietnam's stock market, covering the period from January 2018 to December 2022 This information was sourced from the SSI Securities Corporation website.
Upon completing the data collection process, the author proceeded to calculate key financial indexes based on suggested variables, including the debt-to-equity ratio to assess financial leverage and the logarithm of total assets to determine company size.
Descriptive analysis is performed in order to indicate specific characteristic of the data panel such as mean, median, standard deviation, min value, max value
Correlation analysis examines the relationship between specific variables, offering a comprehensive understanding of how these variables impact capital structure prior to a detailed regression model analysis.
Step 2: Pooled OLS regression model and model test
The Pooled OLS model is initially utilized due to its simplicity The model testing encompasses assessments for multicollinearity, autocorrelation, and heteroskedasticity to evaluate its suitability.
Multicollinearity indicates a state when there is relationship within the independent variables, which means there is one or more independent variables that are strongly correlated with each other
The multicollinearity test employs two main methods: the correlation matrix and the variance inflation factor (VIF) While the correlation matrix is less commonly used, VIF is the preferred method for assessing multicollinearity in a model VIF results are interpreted based on specific thresholds: a VIF greater than 10 indicates the presence of multicollinearity, values between 2 and 10 suggest emerging multicollinearity, and a VIF below 2 confirms the absence of multicollinearity (Gujarati, 2003).
Autocorrelation, also known as serial correlation, occurs when a model's variables are strongly correlated with their lagged values from the past In this study, the Wooldridge test is utilized to assess autocorrelation in panel data The findings are interpreted based on the p-value; a p-value below 0.05 indicates that the null hypothesis can be rejected, signifying the presence of autocorrelation in the model Conversely, a p-value above 0.05 suggests that the null hypothesis cannot be rejected, indicating that autocorrelation is not present in the model.
Heteroskedasticity is a condition where the variance of residuals changes over time, leading to inaccurate model estimations and potentially indicating missing important independent variables The presence of heteroskedasticity can be assessed using White's test in Stata, which provides a p-value for interpretation A p-value less than 0.05 suggests the rejection of the null hypothesis, indicating homoskedasticity in the model, while a p-value greater than 0.05 implies that the null hypothesis cannot be rejected, suggesting the presence of unrestricted heteroskedasticity.
Step 3: Run F-test and Hausman test to choose between Pooled OLS, FEM and REM
H0: The Pooled OLS model is suitable
H1: Fixed effect model (FEM) is suitable
If p-value is less than 0.05, the null hypothesis can be denied, which means the Fixed effect model is more suitable On the other hand, if p-value is more than
0.05, we cannot deny null hypothesis, thus the Pooled OLS model is more suitable
H0: Random effect model (REM) is suitable
H1: Fixed effect model (FEM) is suitable
When the p-value is less than 0.05, it indicates that the null hypothesis can be rejected, suggesting that the Random Effect Model is the more appropriate choice Conversely, a p-value greater than 0.05 means the null hypothesis cannot be rejected, making the Fixed Effect Model the better option.
Step 4: Conduct multicollinearity test, auto correlation test, heteroskedasticity test for the new model
Following the Hausman test results, the appropriate model—either Fixed Effect or Random Effect—will be selected for further testing Subsequently, multicollinearity, autocorrelation, and heteroskedasticity tests will be performed, mirroring the process outlined in step 2 If the model exhibits issues with multicollinearity, autocorrelation, or unrestricted heteroskedasticity, step 5 will be implemented to address these deficiencies.
Step 5: Feasible generalized least squares (FGLS) estimation is used to solve the defects of the model
Feasible generalized least squares (FGLS) utilizes the ordinary least squares (OLS) method to account for heteroskedasticity and autocorrelation The errors derived from the model are used to construct the variance or covariance matrix of these errors This matrix is essential for estimating the coefficients of independent variables, effectively addressing issues of autocorrelation and heteroskedasticity The resulting coefficients will reveal the extent to which the proposed determinants influence capital structure.