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 in response to market events This approach supports steady company growth and ensures liquidity to meet financial needs Additionally, banks can analyze a company's liability distribution to refine their lending policies, maximizing business opportunities.
Understanding capital structure is crucial for investors, as it significantly influences a company's success and its interaction with various economic factors Changes in capital structure do not occur instantly following economic events, which can lead to challenges for companies if their current debt levels become unsustainable For instance, businesses that heavily rely on debt during low-interest periods benefit from tax shields, but they may struggle when inflation prompts interest rate hikes, resulting in increased costs for floating-rate loans 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, with foundational theories such as Modigliani and Miller’s, which highlight the influence of capital structure on firm value and average cost of capital Research by Huang and Song (2002) analyzed data from 1,000 listed enterprises in China between 1994 and 2000, demonstrating that varying levels of leverage—categorized into short-term and long-term—result in distinct relationships with other economic factors Additionally, domestic research has contributed valuable insights into this area.
In their 2019 study, researchers examined the capital structure determinants of 74 Vietnamese listed construction firms from 2014 to 2018 Similarly, Dinh and Pham (2020) analyzed data from 30 pharmaceutical companies listed on Vietnam's Stock Exchange between 2015 and 2019 While some studies address the capital structure of various industries, others overlook the retail sector, despite retail revenue being a significant contributor, accounting for 4000.
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 service revenue surged by 19.8% compared to the previous year, with a 6.5% increase in the first half of 2023, reaching 3016.8 billion VND This growth reflects a positive trend in the retail industry, bolstered by the rise of e-commerce, especially during the pandemic when many businesses adapted to online channels to maintain supply during quarantine The shift to online shopping has not only accelerated sales but also changed consumer habits, making shopping more convenient Despite economic challenges, the retail sector shows promising potential for growth as the economy stabilizes Additionally, the retail industry is characterized by a high capital turnover ratio, heavily relying on short-term debt, which underscores the importance of effective capital structure management for sustaining growth and addressing asset-liability maturity concerns.
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 This research provides valuable insights that can assist in optimizing financial strategies within the retail sector in Vietnam.
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 covers data from January 2018 to December 2022, ensuring a comprehensive analysis over a five-year period, based on the assumption that companies' business activities typically span five years.
METHODOLOGY
The quantitative method analyzes past data to explore the relationships between dependent and independent variables, as well as interactions among independent variables.
The regression analysis employs Pooled OLS, Fixed Effect, and Random Effect models to estimate relationships using panel data These models highlight essential data characteristics and are effective for forecasting future values.
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 applicable to the analysis of capital structures in other businesses.
This thesis explores the relationship between a company's capital structure and various economic factors, derived from data analysis By understanding these connections, investors can enhance their investment decisions, financial managers can tailor their capital distribution strategies to current economic conditions, and bankers can forecast corporate 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 leverage the findings from Chapter 3 to identify and measure the variables influencing the capital structure of retail businesses listed on Vietnam's stock market It explores the relationships among independent variables through various quantitative research methods By analyzing a dataset derived from company financial statements, the author conducts 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 employed, forming a crucial part of the thesis results.
Chapter 5 presents the conclusions regarding the determinants of capital structure in retail businesses listed on Vietnam's stock market, drawing from research findings, theoretical frameworks, and relevant empirical studies It also offers recommendations based on these insights Additionally, the author discusses the minor limitations of the thesis and suggests directions for future research.
LITERATURE REVIEW
OVERVIEW OF CAPITAL STRUCTURE
Capital structure refers to the combination of debt and equity that a company utilizes to finance its investments, encompassing both long-term and short-term liabilities and shareholder equity (Hindi & Shama'a, 1989) It is fundamentally a blend of debt and equity that supports a firm's production and business activities (Damodaran, 2014; 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 within a company's liabilities This thesis focuses on the capital structure of retail businesses listed on Vietnam’s stock market, specifically analyzing the ratio of total debt to equity, which represents the company's financial leverage.
2.1.2 Meaning of capital structure in business
The success of a company heavily relies on the effective management of its capital structure, particularly the balance between debt and equity Efficient capital utilization enhances operational mobilization, allowing businesses to address capital needs seamlessly Conversely, an inappropriate capital structure can expose a company to significant financial risks Financial leverage is a key metric commonly employed by financial managers to navigate capital structure management effectively.
Financial leverage measures the ratio of total debt to total equity, providing businesses with flexible capital to meet production and operational needs Utilizing debt can also offer tax benefits through interest deductions, but a high debt ratio may result in significant interest payments, particularly in a high-interest-rate environment, potentially jeopardizing the company's viability Conversely, a higher equity proportion means no obligation for interest payments, but companies must pay dividends to shareholders, which can signal trustworthiness to investors due to strong public funding However, a high equity ratio may diminish tax advantages and create ownership dispersion, leading to increased pressure on management and potentially altering the company's strategic direction.
2.1.3 Measurement of enterprise’s capital structure
Capital structure reflects a company's financing strategy, encompassing the methods used to raise funds to support production and business operations Assessing and analyzing an optimal capital structure is crucial for effective business management Various financial metrics, such as debt ratio and financial leverage, enable managers to track 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 total capital structure While this leverage enhances purchasing power and enables businesses to meet capital requirements effectively, it also increases financial risk In adverse economic conditions, such elevated leverage can result in severe repercussions for the company's operations.
THEORETICAL BACKGROUND OF CAPITAL STRUCTURE
Durand (1952) highlighted that a company'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 leads to a decrease in the weighted average cost of capital (WACC) as debt increases This suggests the existence of an optimal capital structure that maximizes enterprise value by balancing debt and equity to achieve the lowest WACC However, it is also important to recognize that increasing debt heightens financial and default risks To address these concerns, Modigliani and Miller's Theory was introduced in 1958, providing further insights and addressing gaps in existing research (Brigham & Houston, 2009).
2.2.2 Modigliani and Miller's theory (M&M theory)
The Modigliani and Miller theory, commonly known as the M&M theory, is a pivotal concept in finance, introduced by Franco Modigliani and Merton Miller in 1958 This theory examines how the value of a company is influenced by its capital structure, considering both tax and non-tax environments.
In a tax-free environment, the theory posits that a perfect market exists, characterized by the absence of taxes, transaction fees, bankruptcy costs, and symmetric information (Modigliani and Miller, 1958) This hypothesis suggests that a company's value remains unchanged regardless of its financial leverage, indicating that the distribution of capital between debt and equity does not impact the company's overall worth Consequently, a company's value is solely determined by its real assets rather than its financing methods, implying there is no optimal capital structure or tax shield in this idealized scenario However, this proposition has significant limitations, as it is based on the unrealistic assumption of a perfect, tax-free market that does not exist in practice.
According to Modigliani and Miller (1963), leveraged companies possess a higher value than unleveraged ones due to the tax shield, which represents the present value of tax benefits associated with debt Their research indicates that increasing the debt ratio can enhance a company's value, despite the accompanying rise in financial risks and bankruptcy costs The theory suggests that maintaining efficiency involves utilizing a high proportion of debt to capitalize on the tax shield, indicating that no optimal capital structure exists However, many successful companies thrive 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 within a company's capital structure that enables firms to maximize the benefits of debt financing However, if a company over-leverages itself beyond this optimal debt ratio, it risks incurring financial distress and agency costs, ultimately diminishing its overall value.
Myers (2001) posits that an increasing debt ratio can cause financial distress costs to escalate more rapidly than the advantages of tax shields, ultimately diminishing a company's value The theory indicates that firms with substantial tangible assets and taxable income are likely to maintain higher debt ratios Additionally, larger firms with significant liquidity tend to favor debt over equity Furthermore, the theory suggests that profitable companies should leverage debt to reduce taxable income, while firms with high growth potential should limit borrowing to mitigate the risk of financial crises.
The trade-off theory, like the M&M theory, fails to account for the success of many companies that utilize 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, suggesting that both investors and company insiders possess the same knowledge about the firm However, in reality, insiders often have more information than market participants, leading to a significant disparity in information among stakeholders interested in the company.
Myers and Majluf (1984) highlight that asymmetric information influences capital structure, leading to misvaluation of stock prices in the market Myers (1984) suggests that firms are more inclined to issue shares for capital when their stock is perceived as overvalued, whereas borrowing becomes the preferred option when the company is undervalued Additionally, the cost of financial distress plays a crucial role; high financial distress diminishes the debt ratio within a firm's capital structure, while low financial distress enables the firm to leverage debt for substantial growth.
The pecking order theory suggests that companies prefer to finance their operations using internal cash flow before resorting to external sources of capital When a firm's capital needs surpass its internal financial capacity, it turns to external funding options, selecting them based on increasing costs associated with asymmetric information This hierarchy of financing sources reflects the firm's strategy in managing its capital structure effectively.
Figure 2.1 Pecking order of capital
The pecking order theory suggests that companies with strong endogenous cash flow prefer to utilize internal funds and debt instead of issuing shares for public capital When endogenous cash flow falls short, firms seek external capital, leading to an increased reliance on debt or equity This theory significantly highlights the influence 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 agent (manager) and the owner are not the same individual This divergence can lead to situations where a manager's interests may conflict with those of the owner, potentially harming the company's performance and growth trajectory To mitigate these conflicts, agency costs serve as compensation for managers, aligning their actions with the principal's objectives The theory also distinguishes between agency costs of debt and agency costs of equity, which reflect the dynamics among creditors, shareholders, and managers.
The theory highlights that as share issuance rises, the conflict of interest between managers and shareholders intensifies When managerial decisions fail to enhance shareholder value, agency costs of equity emerge These costs encompass the expenses owners incur to monitor managers, compliance costs associated with managerial actions, and the reduction in utility resulting from discrepancies between managers' decisions and the owners' goal of maximizing utility (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 goes bankrupt, creditors face significant losses As the debt ratio increases, managers tend to exercise greater caution in capital utilization, leading to more efficient company operations However, a rising debt ratio also heightens risks for creditors Consequently, as debt levels rise, interest rates tend to increase as well 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 for the risks of business defaults.
DETERMINANTS OF A COMPANY’S CAPITAL STRUCTURE
Trade-off theory suggests that larger firms with significant tangible assets and taxable income typically exhibit higher debt ratios compared to smaller firms Additionally, large firms with substantial liquidity are observed to have a preference for debt over equity This trend is attributed to lower agency costs of debt, as these firms enjoy easier access to credit markets due to their creditworthiness Furthermore, large firms leverage debt to capitalize on tax shields, promoting business growth Consequently, the study posits that a company's size positively influences its financial leverage, aligning with findings from global research, such as that of Huang and Song.
(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, larger firms tend to exhibit a positive correlation with financial leverage, as highlighted by Myers (2001), indicating that firms with greater size and liquidity typically utilize more debt than equity Conversely, pecking order theory posits that companies with substantial total assets prefer to leverage internal capital and debt over public equity issuance for raising funds 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 numerous studies have explored the connection between financial leverage and profitability However, the findings from these studies often yield varying results.
The Trade-off theory suggests that tax shields enable companies to leverage debt for substantial business growth Consequently, the theory concludes that a company's profitability is positively correlated with its financial leverage.
Pecking order theory, as proposed by Myer (1984), suggests that profitable companies prefer to 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 arguments, the study presents the following research hypothesis.
H2: Profitability of a company (ROA) has negative impact on the financial leverage
The profitability of a company is assessed through the return on assets ratio Research indicates varying conclusions regarding the relationship between capital structure and profits The trade-off theory suggests a positive correlation between profitability and financial leverage, while the pecking order theory, as proposed by Myer (1984), indicates a negative relationship Despite these differing perspectives, the author supports the hypothesis that profitability negatively impacts capital structure, aligning with findings from studies by Almuaither and Marzouk (2019) and Rashid and Akin (2020).
Agency cost theory posits that the agency cost of debt rises with an increasing debt ratio due to heightened risk transfer However, a high proportion of tangible assets in a company serves as collateral, effectively reducing the agency cost of debt This enables firms with substantial tangible assets to enhance their borrowing capacity and leverage tax shields from interest payments to support operations Additionally, research by Huang and Song (2006) confirms a positive relationship between fixed assets and financial leverage, reinforcing the consensus that a company's tangibility positively correlates with its financial leverage utilization Based on these findings, the study proposes the following hypothesis for further research.
H3: Tangibility of a company (TANG) has positive impact on the financial leverage
The tangibility of a company, determined by the ratio of fixed assets to total assets, is positively linked to its capital structure According to agency cost theory, firms with a higher proportion of tangible assets possess greater borrowing capacity, enabling them to leverage tax shields from interest payments to enhance operational support This leads to an increased debt usage ratio in such companies Additionally, research by Huang and Song (2006) reinforces 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 a company's business development trends, calculated through the revenue growth rate of enterprises Past research has shown an ambiguous relationship between growth opportunities and capital structure, paralleling findings related to profitability indicators.
According to agency cost theory, as proposed by Myers (1984), high growth companies prefer equity financing over debt financing due to the constraints imposed by financial leverage Companies with significant debt often allocate a substantial portion of their cash flow to meet interest obligations, benefiting creditors more than shareholders Consequently, firms with promising investment opportunities are inclined to utilize shareholder equity for project financing, suggesting an inverse relationship between growth opportunities and a company's financial leverage.
Pecking order theory suggests that companies with strong growth potential prefer debt financing to expand their business activities Based on this premise, the research is guided by the following 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 unclear relationship between growth opportunities and capital structure According to Myers (1984) in agency cost theory, high-growth companies typically prefer equity financing over debt, suggesting an inverse relationship between growth opportunities and financial leverage Conversely, pecking order theory posits that companies with strong growth prospects may utilize higher financial leverage to expand their operations Additionally, studies by Almuaither and Marzouk (2019) and Rashid and Akin (2020) indicate a positive relationship between growth opportunities and capital structure, prompting the author to adopt this hypothesis for further investigation.
Tax payments of a company ( TAX )
Tax considerations play a crucial role in determining a company's capital structure According to Modigliani and Miller's theory, as well as the trade-off theory, there is a positive correlation between a company's tax payments and its financial leverage The trade-off theory suggests that firms with substantial tangible assets and taxable income typically exhibit higher debt ratios compared to others.
Almuaither and Marzouk (2019) demonstrated a positive relationship between tax rates and the utilization of debt leverage Based on this evidence, the study proposes a hypothesis for further investigation.
H5: Tax payments of a company (TAX) has positive impact on the financial leverage
Both Modigliani and Miller's theory, along with the trade-off theory, suggest a positive correlation between a company's tax payments and its financial leverage Empirical research conducted by Vo (2017) and Almuaither and Marzouk (2019) further supports this connection, indicating that higher tax rates are associated with increased debt leverage Consequently, the author formulated a hypothesis to explore this relationship in the research study.
Non-debt tax shield of a company ( NDTS )
PREVIOUS RESEARCH IN THE FIELD
Huang and Song (2006) conducted a study on the capital structure determinants 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 identified as negatively correlated with financial leverage Additionally, the study indicated that debt leverage varies across different industries.
Chang et al (2009) explored the determinants of capital structure choice using structural equation modeling (SEM) and the Multiple Indicators and Multiple Causes (MIMIC) model, yielding more robust findings than Titman and Wessels (1988) Their research identified growth, measured by market-to-book assets and market-to-book equity ratios, as the most significant determinant of capital structure, followed by profitability, assessed through the ratio of operating income to total assets or total sales Notably, different measurement approaches led to varying conclusions; a negative relationship was observed between growth and capital structure when using the market-to-book assets ratio, whereas a positive relationship emerged with the market-to-equity ratio Similarly, profitability showed a negative influence when calculated as operating income divided by total assets, but a positive relationship was found when measured against total sales Additionally, the study indicated an inverse relationship between the collateral value of assets and debt ratios, as well as between uniqueness and financial leverage, with collateral value ranked second in importance for capital structure decisions, following profitability.
M'ng, Rahman, and Sannacy (2017) examined the determinants of capital structure in public listed companies across 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 issues among the independent variables Utilizing the OLS method with fixed effect panel data regression, the study acknowledged the heterogeneity of the sample firms The high R² value indicated that the selected independent variables effectively explained the variability in leverage ratios across the three countries Notably, a negative relationship with capital structure was observed for profitability and depreciation to total assets, while a positive relationship was found for firm size, asset tangibility, inflation, and lagged leverage, consistent across all three nations.
Almuaither and Marzouk (2019) investigated the determinants of capital structure using a sample of FTSE 100 companies from the UK in 2016, employing OLS estimation with six independent variables: company size, profitability, tangibility, growth opportunities, tax, and volatility, alongside four industry classification dummy variables The study found a positive relationship between company size and leverage, as well as between tax and leverage, although these results were statistically insignificant Conversely, profitability, tangibility, growth opportunities, and volatility were identified as negatively related to debt leverage, with the negative connections for tangible assets and volatility also lacking statistical significance.
Rashid and Akin (2020) investigated 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 analysis employed regression models at both country and regional levels to identify key determinants of capital structure and any differences observed The study revealed that firm size, tangibility, and growth opportunities positively affect leverage, while profitability, age, financial constraints, liquidity, and government ownership negatively impact it Additionally, they found weak evidence for a positive correlation between leverage and operating risks Despite the unique institutional environment of GCC countries, the study concluded that the determinants of financing decisions align with those observed 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 collateralizable value of assets, non-debt tax shield, company size, profitability, and growth opportunities The study confirmed previous findings, revealing a significant impact of collateralizable assets and profitability on financing decisions, with collateralizable value positively influencing capital structure, while profitability exerted a negative effect.
In a study conducted by Doan (2010), the determinants of capital structure and financial performance were analyzed using path analysis, utilizing raw data from the financial statements of 428 enterprises listed on the Vietnam Stock Exchange The research identified key factors influencing capital structure, including business efficiency, business risk, asset structure, and company size The findings revealed an inverse relationship between the debt ratio of listed enterprises in Vietnam and profitability, business risk, and asset structure, while indicating 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 influencing capital structure, excluding financial companies and banks The study identified independent variables such as growth, tangibility, profitability, firm size, and liquidity Results indicated that these determinants have a variable relationship with capital structure, differing between short-term and long-term leverage Specifically, for long-term leverage, all suggested variables exhibited a positive relationship, despite some coefficients being insignificant Conversely, for short-term leverage, only growth maintained a positive relationship, while the other variables showed an inverse correlation.
Dinh and Pham (2020) conducted a study examining the impact of capital structure on the financial performance of 30 pharmaceutical companies listed on the Vietnam Stock Exchange from 2015 to 2019, utilizing least squares regression (OLS) to analyze the data The research identified the return on equity (ROE) as the dependent variable, while 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 firm performance and financial leverage, long-term asset ratio, debt-to-assets ratio, company size, fixed asset ratio, and growth rate, whereas self-financing exhibited 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 sample comprised financial data from nine Vietnamese steel companies over a ten-year period, from 2010 to 2019 Financial leverage served as the dependent variable, while 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, with liquidity, growth rate, and tangibility significantly affecting the debt ratio Conversely, corporate income tax and product-specific characteristics showed no correlation with capital structure.
A review of prior studies indicates that the findings regarding the determinants of capital structure in Vietnam are inconsistently significant Consequently, additional research is essential to clarify 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 significant factor influencing capital structure A negative relationship between the market-to-book ratio and capital structure was observed, whereas a positive relationship emerged when growth was assessed using the market-to-equity ratio.
The analysis revealed a similar trend in profitability, indicating a negative impact when operating income is assessed relative to total assets Conversely, a positive effect was observed when operating income is evaluated 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 achieve 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 The data is then 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 model is selected The findings from the regression models 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 existing research on enterprises' capital structure adjustments reveals inconsistencies in conclusions, particularly highlighting the retail industry’s prominence Data from the General Statistics Office of Vietnam indicates that retail revenue ranged from 4,000 to 5,000 billion Vietnamese Dong between 2018 and 2022, underscoring its significance in the economy This emphasizes the importance of understanding business behavior within this sector and justifies the need for further research.
Step 2: Theoretical background and literature review to build research hypothesis and research model
The author conducts a comprehensive review of theoretical frameworks and previous studies to establish a research pathway, formulate hypotheses, and create a model that identifies explanatory variables related to capital structure Utilizing a regression model, the study examines the relationships between the research subject and the explanatory variables To enhance model accuracy, the analysis employs Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM), alongside the Feasible Generalized Least Squares (FGLS) method to rectify any identified deficiencies The quantitative analysis is performed 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 analysis.
The author employs quantitative analysis using Stata to conduct descriptive analysis, correlation analysis, and tests for multicollinearity and heteroskedasticity The study utilizes regression models including Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM), culminating in the application of the Feasible Generalized Least Squares (FGLS) method to address identified issues.
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 investigate the impact of various factors on capital structure, the author employed the Ordinary Least Squares (OLS) estimation method This approach enables optimal model estimation by minimizing the sum of squared residuals, ensuring that the model incorporates 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 prior research The author selects key variables from past studies to ensure consistency with real-world outcomes and to analyze their impact on the retail sector Notably, the research builds on the findings of Almuaither and Marzouk (2019), Rashid and Akin (2020), and Bhattacharjee and Dash (2021).
In their studies, Chang et al (2009), Almuaither and Marzouk (2019), and Rashid and Akin (2020) utilized financial leverage to represent capital structure, prompting the author to adopt a similar approach While financial leverage can be calculated using various methods such as the debt-to-asset ratio, debt-to-capital ratio, or debt-to-equity ratio, most researchers favor the debt-to-asset ratio, as highlighted in Rashid and Akin (2020) and Almuaither and Marzouk (2019) To offer a fresh perspective, the author has chosen to employ the debt-to-equity ratio for analyzing capital structure data.
According to Almuaither and Marzouk (2019), the determinants of capital structure include six key factors: company size, profitability, tangibility, growth opportunities, tax, and volatility In contrast, Rashid and Akin (2020) identified different independent variables influencing financial leverage, such as size, tangibility, growth opportunities, profitability, age, financial constraints, liquidity, and government ownership.
In 2021, it was discovered that various factors, including the collateralizable value of assets, non-debt tax shield, company size, profitability, and growth opportunities, significantly influence financial leverage Researchers commonly agree on key independent variables for such studies, namely 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, along with longevity, interest expenses, and business risk Due to data limitations, the author has synthesized previous research findings and selected eight independent variables for the study: (1) Company Size (SIZE); (2) Profitability (ROA); (3) Tangibility (TANG); and (4) 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 study variables, while the quantitative approach utilizes regression model estimation, incorporating Pooled OLS, Fixed Effects Model (FEM), and Random Effects Model (REM).
Step 1: Data collection, descriptive analysis and correlation analysis
The study analyzes raw data from the financial statements of 38 retail enterprises listed on Vietnam's stock market, covering the period from January 2018 to December 2022 This data was sourced from the website of SSI Securities Corporation.
Upon completing the data collection process, the author proceeded to calculate key financial indexes, including the debt-to-equity ratio to assess financial leverage and the logarithm of total assets to evaluate 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 insights into 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 evaluation encompasses tests for multicollinearity, autocorrelation, and heteroskedasticity to assess the model's appropriateness.
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 primary 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 The interpretation of VIF results is straightforward: a VIF value greater than 10 indicates a significant multicollinearity problem, values between 2 and 10 suggest emerging signs of multicollinearity, and a VIF less than 2 confirms the absence of multicollinearity in the model (Gujarati, 2003).
Autocorrelation, also known as serial correlation, occurs when a model's variables are strongly correlated with their past values This study employs the Wooldridge test to assess autocorrelation in panel data The results are interpreted based on the p-value: a p-value less than 0.05 indicates that the null hypothesis can be rejected, signifying the presence of autocorrelation in the model Conversely, a p-value greater than 0.05 suggests that the null hypothesis cannot be rejected, indicating the absence of autocorrelation.
Heteroskedasticity refers to the situation where the variance of residuals varies over time, leading to inaccurate model estimations and potential omission of significant independent variables The results of a heteroskedasticity test, typically analyzed through White's test in Stata software, are determined by the p-value A p-value less than 0.05 indicates that the null hypothesis can be rejected, suggesting the presence of homoskedasticity in the model Conversely, a p-value greater than 0.05 means the null hypothesis cannot be rejected, indicating unrestricted heteroskedasticity within the model.
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
A p-value less than 0.05 indicates that the null hypothesis can be rejected, suggesting that the Random Effects Model is more appropriate Conversely, a p-value greater than 0.05 means the null hypothesis cannot be rejected, making the Fixed Effects Model the better choice.
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 analysis Subsequently, tests for multicollinearity, autocorrelation, and heteroskedasticity will be conducted, similar to the procedures in step 2 If any issues with multicollinearity, autocorrelation, or unrestricted heteroskedasticity persist, step 5 will be implemented to address these problems.
Step 5: Feasible generalized least squares (FGLS) estimation is used to solve the defects of the model
Feasible Generalized Least Squares (FGLS) builds upon the Ordinary Least Squares (OLS) method to address issues of heteroskedasticity and autocorrelation By extracting errors from the model, FGLS constructs a variance or covariance matrix of these errors, which is then used to estimate the coefficients of independent variables This approach effectively resolves problems related to autocorrelation and heteroskedasticity Ultimately, the resulting coefficients reveal the degree of influence that the identified determinants have on capital structure.