The report's primary goal is to examine how capital structure affects the value of 76 listed real estate businesses listed on the Vietnamese stock market from 2017 to 2021, generalizing
INTRODUCTION
Research motivation
Real estate development significantly impacts various industries, driving job creation and economic growth However, unsuccessful investments in residential real estate pose risks to businesses, commercial banks, and the financial system, contributing to broader economic challenges Structural weaknesses in real estate investment have been pivotal in triggering market crises, as evidenced by the East Asian currency crisis of 1997–98 and the Global Financial Crisis of 2007–2008, both of which highlighted deficiencies in policy and market management.
The corporate bond market plays a crucial role in funding investments in the real estate sector, complementing the stock market It helps mitigate risks associated with significant currency and term fluctuations on balance sheets, which can lead to financial instability, as seen during the East Asian monetary crisis In Vietnam, inadequate risk assessment and management, particularly regarding the economic impacts of the Russia-Ukraine War, heighten the pressure on real estate companies to meet debt obligations and increase liquidity risks for distribution agents committed to repurchasing bonds This situation is further exacerbated by the government's tightening of regulations on real estate bond issuance.
Maximizing business or shareholder value should be the ultimate objective of all financial actions One of the crucial choices in business financial management is the choice
Businesses can secure funding from various sources to support their operations The capital structure of a company indicates how its financing is organized, combining borrowed capital and equity in specific proportions to facilitate business activities, as noted by Stephen A Ross, Randolph W Westerfield, and Bradford D Jordan (1997).
(2005), "capital structure is the combination of debt and equity of the firm" Ahmad et al
Capital structure refers to the ratio of debt to equity used by a business to finance its production and operational activities It represents the balance between borrowed funds and owners' equity in an enterprise's financial framework.
Maximizing enterprise value is the primary goal for company managers Various metrics, including Tobin's Q, the market price-to-book value ratio, economic value added (EVA), and market capitalization, are essential for evaluating a company's worth.
Analyzing the impact of capital structure on a company's value is crucial for managers to formulate risk management strategies, assess bankruptcy risks, and increase overall enterprise value As capital structure influences enterprise value, managerial decision-making and policy implementation evolve over time Furthermore, stakeholders involved in business operations can gain valuable insights from evaluating how capital structure affects enterprise value.
Between 2017 and 2021, the capital structure of real estate enterprises in Vietnam revealed a significant reliance on loans, including both bank loans and bond issuances Data from Finnpro indicates that 14% of the capital structure is sourced from bank loans, while 17% is derived from bonds.
Over the past five years, the capital structure has been significantly influenced by various factors, with more than half of the capital sourced from loans, particularly through business cooperation contracts The Covid-19 pandemic has notably impacted capital ratios, alongside legal challenges that have hindered project progress Consequently, access to investment capital has become limited, necessitating that government support institutions align more closely with the overall socio-economic conditions of the country, resulting in stricter regulations than in the past.
The capital structure of real estate businesses is increasingly problematic due to rising input and capital costs driven by inflation and interest rates Inflation, influenced by escalating commodity prices and geopolitical tensions, is expected to continue rising Real estate developers face significant cost pressures, particularly from steel, which constitutes 15% to 20% of total project expenditures Since April 2019, steel prices have surged by 46%, leading to an average equipment cost increase of nearly 7% This has resulted in a notable decline in apartment output and a reduced sales-to-inventory ratio Additionally, the government has tightened lending requirements, complicating cash flow for the real estate sector due to stricter bank credit policies and recent regulatory changes.
The driving force behind the aforesaid macro factors is also the reason why the author carries a quantitative research to dig deep
The report's primary goal is to examine how capital structure affects the value of
From 2017 to 2021, 76 real estate companies were listed on the Vietnamese stock market, highlighting the significant influence of capital structure on the stock prices of these firms This analysis serves as a scientific basis for making informed and strategic financial decisions in the real estate sector.
Research objectives and questions
The thesis focuses on two main issues including:
- Applying some theoretical foundations of capital structure
- Research on the factors affecting the capital structure of real estate stocks
To solve the problem of capital structure, this essay will focus on answering two main questions:
- What are the main factors affecting the capital structure of real estate enterprises listed on the Vietnamese stock market?
- What are recommendations for a corporation to deal with capital structure problems?
The research scales
The paper serves to clarify the factors affecting capital structure of Vietnamese real estate stocks The author uses data of 76 real estate enterprises in Vietnam in the period 2017-
2021 to examine the impact of capital structure on profitability and proposed hypotheses.
Synopsis of Chapters
The study uses both traditional methods such as statistical, descriptive and quantitative research methods
In this section, the author will give an overview of the research problem, along with questions related to the research topic
This article examines three key theories of capital structure, providing a comparative analysis and critique of each Additionally, it highlights seven significant factors that influence the capital structure within the real estate sector, drawing insights from prior research.
This section provides an overview of the Vietnam real estate market, highlighting its key characteristics The author analyzes the factors influencing the capital structure of this industry, emphasizing the relevance of the current macro and microeconomic context Additionally, the chapter outlines the data collection methods and the econometric techniques employed in the study.
The author will analyze the effects of the relationships among the variables in the quantitative model, focusing on their impact on the capital structure of real estate enterprises Additionally, the analysis will address any potential defects in the model and summarize the key factors influencing capital structure.
Chapter 5 Conclusions, discussion and limitation
The author presents a summary of the aggregated results and offers recommendations for decentralization by businesses, securities commissions, and government entities Furthermore, the author acknowledges the limitations identified in the research within this thesis.
LITERATURE REVIEW
Theoretical framework
The modern capital structure theory is significantly influenced by the research of Nobel laureates Franco Modigliani and Merton Miller, particularly their M&M theory established in 1958 This foundational theory of corporate finance analyzes the impact of capital structure under two scenarios: the absence of corporate income tax in 1958 and the presence of it today (1963) Modigliani and Miller's assumptions include that investors expect identical cash flows from investments, capital markets are ideal with no transaction costs, taxes, or bankruptcy-related expenses, and all investors have access to the same information Additionally, investors can borrow at the risk-free interest rate, there are no agency costs as agents align with owners' goals, and capital and investment decisions are made independently.
The theory suggests that without corporate income tax, a firm's value remains unchanged regardless of its capital structure, provided future cash flow projections and risks are constant Essentially, a business's value is the same whether it uses debt or not However, when corporate income tax is introduced, the value of a firm that utilizes debt exceeds that of a firm without debt, with the difference being the product of the debt's value and the corporate income tax rate Additionally, borrowing money incurs interest payments that increase operational costs and reduce revenue.
13 business will pay less income tax To sum up, utilizing debt will assist boost a company's value
From M&M theory, much work has been done by omitting the assumptions M&M has made The trade-off theory of capital structure was proposed by Kraus and Litzenberger
(1973) and developed by Myers (1984) According to Kraus and Litzenberger (1973),
Optimal financial leverage represents the balance between the tax advantages of using debt and the potential costs associated with bankruptcy As noted by Myers (1984), firms adhering to the trade-off theory of capital structure aim to achieve a specific debt-to-value ratio, which they adjust over time This target ratio is established by weighing the benefits of debt against the risks of bankruptcy.
The trade-off theory of capital structure is a fundamental concept that enhances the understanding of capital structure decisions, competing notably with the pecking order theory Rooted in the Modigliani and Miller (M&M) theory, it explains why firms often utilize a mix of debt and equity financing This theory posits that businesses aim to balance marginal costs and benefits when determining their capital structure According to M&M's 1963 tax model, a firm's value increases with higher debt levels, peaking when fully financed by debt Ross (2002) suggests that debt serves as a mechanism to signal the firm's value, with debt replacing equity up to the firm's maximum value Myers (1977, 1984) further asserts that firms following the trade-off theory will establish a target debt ratio, leading to a self-adjusting capital structure.
14 adjust to that target level The target debt ratio is determined by balancing the benefits of the tax shield with the costs of bankruptcy
Determining bankruptcy costs is complex, as identified by Breadley et al (1984), who categorized them into three types: direct administrative costs from third parties upon dissolution, costs related to reopening the company, and the loss of tax credits The observation that firms with low financial leverage can still perform well challenges the equilibrium theory, particularly since increasing debt can paradoxically help maximize profits at equilibrium This discrepancy highlights the need for the development of pecking order theory to better explain these phenomena.
Businesses cannot rely solely on debt for financing due to the costs associated with bankruptcy and financial difficulties, which encompass both direct and indirect expenses According to Mackie-Mason (1990), firms with low tax rates, such as those carrying forward tax losses, are more inclined to issue equity securities rather than bonds The study supports the capital structure trade-off theory, indicating that debt is beneficial for tax-paying businesses Additionally, the findings align with Miller's (1977) equilibrium, where the low capital gains tax rate neutralizes the value of a firm's tax shield, leading to higher returns for investors.
In scenarios where the tax rate on loan interest is 15% lower than that on equity income, companies with lower tax rates are likely to utilize equity financing Consequently, the conclusions drawn by Mackie-Mason (1990) regarding the significant impact of tax shields on the market value of firms or their debt ratios, as suggested by trade-off theories, cannot be substantiated.
According to Donaldson (1961), utilizing a company's retained earnings is a more effective method for capital growth than issuing additional shares This perspective is supported by Myers and Majluf (1984), who expanded on Donaldson's findings to develop the pecking order theory.
According to Myers and Majluf (1984), financial costs increase due to asymmetric information, as business managers possess more knowledge about their companies than outside investors Consequently, every decision made by management affects the company's overall health The preferred funding option is to utilize retained earnings for promising initiatives that yield high returns If retained earnings are insufficient, management opts for loans with fixed interest rates typically lower than the project's return rate, thereby avoiding profit sharing with new owners Equity financing is only considered when the company's stock is valued above its actual market worth.
This approach has its drawbacks, primarily due to the tax benefits that lead most businesses to borrow money to some extent However, the amount of borrowed funds is limited by costs related to raising debt, such as bankruptcy and agency fees Consequently, most businesses utilize a combination of debt and equity The target debt ratio reflects the average debt ratio, considering both equity and debt.
To effectively mobilize and utilize debt, businesses maintain a reserve debt capacity due to information asymmetry This allows them to borrow for investments when needed, avoiding the issuance of shares at a loss Consequently, the preferred debt ratio is usually lower than that suggested by the trade-off theory.
The agency cost theory considers agency costs as in Jensen & Mecking's (1976) study when analyzing how firms make capital decisions
While most managers theoretically agree with the owner's goal of maximizing wealth, they often prioritize their own job security and benefits This concern leads them to avoid taking risks that could jeopardize the business and their personal financial stability Consequently, this cautious approach results in profits that fall short of the maximum potential.
A management compensation mechanism aligned with stock price maximization is a widely recognized and effective solution to the agency problem, designed to motivate management to act in the best interests of owners Additionally, attractive remuneration packages enable organizations to compete for and attract top managerial talent.
Jensen and Meckling (1976) argue that an effective capital structure can reduce agency costs by incentivizing managers to prioritize the company's interests A higher debt-to-equity ratio (D/E) can diminish owners' agency expenses and enhance firm value by influencing managerial behavior, such as reducing salaries and limiting managerial power.
17 compensation This puts pressure on managers to find a way to manage cash flow better so they can compensate shareholders.
Empirical Findings
The capital structure represents the blend of a firm's debt and equity, which is essential for financing its production and business activities According to Horne et al (2005), the decisions made regarding this mix are critical, as highlighted by Damodaran (2001).
Capital structure refers to the relationship between debt and equity in a company's financing, as defined by Ahmad et al (2012) It is a combination of these financial sources that fund production and business activities This perspective is echoed by Ahmad, Pouraghajan, and Malekian (2012), who emphasize that capital structure comprises both debt and equity that form the enterprise's assets Similarly, Nguyen Thanh Cuong (2014) describes a business's capital structure as the blend of debt and equity utilized for its operations.
The authors' concepts of capital structure are largely similar, as it refers to the various forms of capital a company utilizes Specifically, it encompasses the debt to capital ratio that finances production and commercial activities.
According to Roden & Lewellen (1995), there is a correlation between capital structure and business performance for 48 US companies operating between 1981 and
High-profitability businesses tend to utilize more debt, as noted by Hadlock & James (2002) Recent studies in developing countries have also explored this relationship For instance, Majumdar & Chhibber (1999) found a negative correlation between debt usage and corporate profitability in Indian firms Similarly, Salim (2012) identified a negative relationship between debt utilization and the performance of companies listed on the Malaysian Stock Exchange.
Numerous studies demonstrate the significant impact of capital structure on enterprise value Research by Harvey et al (2004) indicates that in firms characterized by high agency costs, an excessive debt investment phenomenon can enhance shareholder value.
In Vietnam, various authors have explored the relationship between capital structure and corporate value A notable study by Do Van Thang and Trinh Quang Thieu (2010) investigated this connection for companies listed on the Ho Chi Minh City Stock Exchange Their OLS regression analysis identified a third-order relationship between enterprise value and capital structure, indicating that the optimal capital structure for businesses is achieved at a debt to equity ratio of 105 percent.
Research by Nguyen Tan Vinh (2011) indicates that the capital structure does not significantly influence the performance or value of companies listed on the Hanoi Stock Exchange (HNX) Additionally, Nguyen Huu Huan et al (2014) identified debt ceilings affecting firm value through their study of the relationship between capital structure and firm value, which included 517 non-financial businesses listed on two stock exchanges in Ho Chi Minh City.
Between 2010 and 2012, the authors utilized Tobin's Q and ROE as metrics to assess enterprise value Their analysis revealed a correlation between capital structure and company value, as indicated by ROE, through threshold regression analysis However, they did not find any specific debt thresholds that significantly influenced the enterprise's worth.
2.2.2 Factors affecting the capital structure
The enterprise growth rate is determined by the growth of total assets, a measure of firm expansion highlighted by Titman and Wessels (1988) Kraus and Litzenberger's (1973) trade-off theory suggests that companies with high debt ratios face increased failure rates and potentially slower growth In contrast, the pecking order theory, explored by Myers and Majluf (1984), indicates that rapidly growing firms require substantial capital for investments, leading them to issue more shares instead of taking on debt to minimize the distribution of benefits between owners and creditors Additionally, Titman and Wessels (1988) note that the variety of future investment opportunities results in higher intermediary costs for fast-growing businesses.
High growth rates can lead to increased financial leverage, as businesses experiencing rapid development often benefit from a favorable lending market and easier access to credit This tendency suggests that such companies are likely to increase their borrowing to sustain their potential for future growth Consequently, the relationship between asset growth rates and debt ratios can be both positive and negative.
Phuong (2014) highlights that in the construction industry, slower growth leads to increased financial challenges, resulting in a higher overall debt ratio, suggesting an inverse relationship between a company's growth potential and its debt levels Conversely, Ha et al (2021) find a positive correlation in the energy sector's capital structure Additionally, Aggarwal and Padhan (2017) reveal a significant negative relationship between the growth rate of total assets and enterprise value in the real estate sector, further emphasizing the complexities of capital structure across different industries.
(2021) concur with the idea that there is a bad association between business growth rates and the capital structure of the real estate sector
The relationship between profitability and financial leverage is significant, as higher profitability ratios reduce the likelihood of bankruptcy, making businesses prioritize their own capital over borrowed funds, which in turn increases financial leverage The trade-off theory suggests that firms are incentivized to borrow more due to the benefits of the tax shield Abor (2005) recommended that firms utilize short-term borrowings, aligning with the pecking order theory, which posits that companies prefer internal capital before considering debt and equity Titman and Wessel (1988) found that, all else being equal, firms with higher profitability tend to have lower financial leverage ratios, a view supported by Chakraborty (2010), who argued that increased profits correlate with reduced debt rates Additionally, Antoniou et al (2008) highlighted a negative relationship between capital structure and profitability.
21 while the findings of other research show that capital structure is positively affected by profitability (Chadha & Shama’s, 2015; Iwarere & Akinyele, 2010)
Consider the relationship between profitability and capital structure of enterprises to industries Research on the capital structure of the cement industry, in the period 2007-
In 2009, Shah et al (2013) built upon the research of Shah and Khan (2007), analyzing data from cement companies listed on the Karachi Stock Exchange in Pakistan, and found a negative relationship between profitability and capital structure In the context of the FMCG industry, profitability is assessed using the ratio of profit after tax to total assets, as noted by Huong (2019), who supports her findings with the research of Myer and Majluf.
Firms tend to prioritize their own capital for reinvestment over external debt, leading to a negative correlation between profitability and financial leverage, while also indicating a positive relationship with the speed of capital structure adjustment In the real estate sector, research by Dang Ngoc Hung et al (2019) reveals a significant positive correlation between return on total assets and enterprise value, highlighting that the profitability of total assets positively influences the value of real estate companies.
The ratio of fixed assets to total firm assets is crucial for assessing a company's financial stability The trade-off hypothesis suggests that a higher fixed asset ratio enhances collateral availability, reducing bankruptcy risk and expanding investment opportunities, ultimately boosting overall value Additionally, pecking order theory indicates that a greater fixed asset to equity ratio minimizes information asymmetry and agency costs, contributing to increased enterprise value.
Research methodology and methods
Introduction Vietnam real estate sector
The real estate market plays a crucial role in the national economy, closely linked to financial, monetary, construction, and material markets Its effective growth and management can attract investment capital and support socioeconomic development, significantly contributing to sustainable rural and urban development while driving the nation towards industrialization and modernization.
The article provides an overview of the real estate industry, highlighting significant challenges that have emerged over time In 2022, the market faced "Rising waves challenge industry growth," as various factors impacted the industry's outlook Key challenges include rising interest rates that influence home buying decisions, increasing material prices that drive up housing costs, and stricter bank loan policies alongside tighter supervision of corporate bond issuance.
There exists 4 phases in the development of real estate market in Vietnam
The underdeveloped economy, vast land resources, and slow urbanization resulted in minimal demand for land from local organizations and individuals, leading to a lack of a formal real estate market, characterized instead by implicit, non-market transactions.
The first real estate wave (1993-1999)
Investors are currently captivated by land and land use rights, with rising demand for homes, residential real estate, and agricultural and commercial land, especially in metropolitan areas, prior to the implementation of the Land Law in 1993 In response to volatile market conditions, the state intervened to curb speculation by enacting Decrees 18 and 87 on land leases Consequently, investors who relied on financial leverage were compelled to liquidate their shares to support the Bank, leading to a market downturn as a wave of stock sales by speculators created an oversupply.
The second real estate wave (2001-2006)
Investors have reacted positively to the policy enabling Vietnamese expatriates to buy homes and the announcement of new land prices, sparking a second wave of land activity in the region Since 2002, state policies have contributed to a temporary freeze in the Vietnamese real estate market, resulting in a capital shift towards the stock market from 2002 to 2006.
The third real estate wave (2007-2008)
High-end apartments and villas have become a focal point in Vietnam's real estate market, particularly during the economic boom from 2003 to 2007, driven by substantial foreign direct investment (FDI) inflows The years 2006-2007 marked a peak for the Vietnam Stock Market, with investors reaping significant profits, which subsequently fueled a surge of wealth into the real estate sector This influx has intensified the demand for luxury properties In response, the government has enacted stringent monetary policies aimed at regulating the market, particularly targeting non-productive credit.
28 contain inflation in the face of the expanding real estate market bubble and the quickly rising inflation rate
3.1.2 Main features of Vietnamese real estate capital structure
Figure 1 Structure of Vietnam's real estate industry.
The distribution of residential real estate businesses is mainly concentrated in the cities:
Ho Chi Minh City leads with 2,086 enterprises, followed by Hanoi with 325, highlighting the significant urbanization rates in these major cities (SSI Research, 2021) The location of a real estate business not only reflects the appeal of the investment environment but also influences investment policy implications, even if the business operates multiple projects across various regions.
Table 1 General credit structure of the real estate industry (unit: trillion VND)
The main source of loans of real estate enterprises Balance as of Dec 31, 2021
Serviced Apartment Retail Real Estate
Bank credit for real estate developers 700
Bank credit for home buyers 1312.9
Source: State Bank of Vietnam 2022
As of March 31, 2022, the outstanding credit for the real estate sector reached 2,240,166 billion VND, reflecting a 7.87% increase from December 31, 2021, and representing 20.23% of total outstanding shared loans The State Bank of Vietnam reported that consumer/self-use credit, primarily for residential real estate, constituted 65.01% of the total credit in the real estate sector, while loans for real estate businesses made up 34.99%.
The State Bank is currently implementing strict controls on credit within the real estate sector, particularly focusing on the real estate business This approach aims to channel capital towards low-cost commercial housing, social housing, and accommodations for young people and workers, addressing the genuine needs of the population With bank credit allocated up to 65% for homebuyers, the primary risk factors are linked to the income and savings of the homebuyer, as well as the prevailing home loan interest rates set by banks.
In 2021, domestic institutions, securities companies, and commercial banks were the primary purchasers of real estate bonds Significant policy changes, such as TT16 for banks and Decree 153 for individual bonds, have broadened access for other institutional investors.
30 investors including insurance companies and changing the form of issuance to Public offering is an important consideration in capital strategy.
Analysis of Vietnamese real estate in 2022
3.2.1 Tightening of credit in the real estate sector and closely monitoring the issuance of corporate bonds
Real estate businesses are likely to encounter challenges in raising capital in the coming quarters, as the State Bank of Vietnam (SBV) has been redirecting credit flows towards manufacturing, services, and agriculture while reducing lending rates for the real estate sector Effective from 2020, Circular 22/2019/TT-NHNN mandates that commercial banks decrease the maximum ratio of short-term funds allocated for medium and long-term loans from 34% in October 2021 to 30% by October 2022 To curb real estate speculation, the SBV has instructed banks to closely monitor credit in this sector and limit funding for high-end real estate investments Additionally, the government is enforcing supervision of the corporate bond market to mitigate risks associated with land use rights issuance and auctions.
3.2.2 Sales revenues boost and slowdown in land fund expansion
In recent years, the real estate industry has experienced a shift, with project distributors intensifying sales efforts while land fund expansion has slowed The market is expected to see a recovery in supply in 2022, as companies prioritize sales to enhance cash flow This trend is evident in the projected significant sales growth for listed real estate firms, such as KDH with a 14-fold increase year-over-year, DXG with a 300% increase, and NLG with a 105% increase, driven by a low base in 2021 and the resumption of projects previously hindered by the Covid-19 pandemic (Finpro, 2022) However, the economy's challenges and stringent government measures regarding bond issuance and regulation continue to impact the sector.
31 capital mobilization channels of the industry, investors may be more cautious in expanding funds on land and may reduce the budget for this activity
Figure 2 Sales of listed real estate companies in 2022
The anticipated growth is contingent upon the lifting of social distancing measures and the full reopening of activities However, in reality, the revenue of most publicly listed real estate companies saw a decline in the first quarter of 2022.
Table 2 Revenue of most listed real estate companies dropped sharply in Q1/22
KDH DXG NLG VHM NVL
Prospects for sales of listed real estate companies to grow sharply in 2022 (percentage)
In the current tight capital environment, Vietnamese investors are collaborating with well-funded partners and foreign developers to advance real estate projects This trend is driven by the need for financial stability, as stricter credit regulations and bond controls are expected to foster long-term growth in the real estate market.
3.2.3 Pressure on home loan interest rates increases in the context of rising deposit rates
As of April 26, 2022, the deposit rates for state-owned banks remained stable, with both 3-month and 12-month term deposit rates unchanged since the end of 2021 In contrast, private banks showed an improvement in their 12-month term deposit performance.
14 and 13 basis points, respectively, from the end of 2021 As a result, there was little change in the typical mortgage interest rate at domestic banks in Q1/22
Deposit rates, currently at historic lows, are expected to rise by 30-50 basis points throughout 2022 due to increased demand for capital mobilization as credit accelerates, rising inflationary pressures in Vietnam, and intensified competition from other investment channels like real estate and securities By the end of 2022, the 12-month term deposit interest rate offered by commercial banks may reach 5.9-6.1% per year, up from the current 5.5-5.7%, although this remains below the pre-pandemic level of 7.0% per year.
In 2022, commercial banks are expected to increase lending rates for standard loans to offset rising deposit rates, particularly in the context of stricter credit controls in the real estate sector Mortgage interest rates for house loans are projected to range from 9.5 percent to 10.0 percent, which remains below the pre-pandemic average of 11 to 11.5 percent annually The author anticipates that house mortgage interest rates will stay low throughout 2022, suggesting that there will be no adverse impact on apartment sales during the year.
Research method
Methodology is a framework of beliefs and guiding principles that aids individuals in discovering, creating, selecting, and applying methods in their practice It serves as a system of principles and perspectives, particularly those related to worldview, that directs the construction of procedures and defines the scope of activities Essentially, methodology embodies the philosophy of techniques, encompassing a structured approach, a user's worldview, and rules for problem-solving to achieve optimal effectiveness.
Scientific research methodology serves as a vital tool for scientists, managers, and practitioners, helping to clarify the nature and activities involved in scientific inquiry It not only aids in the theoretical generalization process but also enhances researchers' understanding of their creative thinking mechanisms and capabilities.
Research philosophy is a crucial element of research technique Saunders et al
Philosophy serves as the foundation of knowledge regarding assumptions and techniques that guide researchers in choosing the most effective methods to achieve their research objectives It encompasses the nature of investigation, assumptions, and knowledge, focusing on a specific approach to knowledge development Addressing this issue is crucial, as researchers may possess varying beliefs about the nature of knowledge and truth, and philosophy helps us understand these differences.
35 beliefs Addressing research philosophy involves comprehending and stating the assumptions and opinions of researchers regarding a phenomenon
Research philosophy is primarily influenced by three key factors: positivism, interpretivism, and realism Realism asserts that reality exists independently of human perception, whereas positivism and interpretivism focus on knowledge gained through ideas, experiences, and discourses.
There are 2 things included in research design: quantitative and qualitative method
Quantitative research is a method for collecting numerical data and exploring theoretical connections from a deductive perspective Its primary goal is to develop and apply mathematical models, theories, or hypotheses related to various phenomena The measurement process is vital, as it links empirical observations to the mathematical representation of quantitative relationships This approach employs statistical analysis to assess the relationships between variables Typically, quantitative research is utilized when the research model is clear and the hypothesis is derived from established theory.
Qualitative research aims to deeply understand human behavior and the factors that influence it, focusing not just on the what, where, and when, but also on the why and how of decision-making This approach often employs small, concentrated samples rather than large ones Traditionally, qualitative methods are seen as providing insights specific to the cases studied, with general conclusions viewed as mere assertions awaiting empirical support.
36 study hypothesis, quantitative approaches might be applied The limitation of qualitative research's scope prevents generalizability of the findings, which is a drawback
Researchers must use caution when using these techniques to prevent their own personal biases from tainting the results.
Data sources and sample selection
This research examines the factors influencing capital structure in the real estate sector from 2017 to 2022, utilizing secondary data The study analyzes data from 76 real estate companies listed on the Vietnamese stock market, encompassing a total of 380 observations over five years, from 2017 to 2021.
Panel data, also known as pooled data, longitudinal data, or cohort analysis, involves combining observations from a cross-section over time, allowing for the examination of variations among individuals, companies, or states This data type enhances the accuracy of econometric estimates and predictions, simplifies statistical calculations, and reveals impacts that may be overlooked in pure time series or cross-sectional data By integrating time series with cross-observations, panel data facilitates the exploration of complex behavioral patterns and reduces bias that could arise from using highly aggregated variables Consequently, the application of panel data in research is both reasonable and beneficial.
Model and variables
The model specification identifies financial leverage as the dependent variable, while the independent variables influencing capital structure include growth, tangible assets, liquidity, profitability, firm size, inventory, earnings per share (EPS), and non-debt tax.
This index shows how much of a business's capital is formed from mobilizing short-term debt
This index shows how much of a business's capital is formed from mobilizing long-term debt
The analysis of factors affecting business performance examines how macro and micro factors influence the effectiveness of business management through data This involves utilizing financial statements, economic data, comparative analytical techniques, and econometric models Business managers rely on this analysis to inform their decisions and strategies, aligning them with the strengths and weaknesses of their enterprise or industry This research specifically focuses on the internal factors within corporations.
The capital structure of the real estate industry is influenced by various factors, notably solvency and liquidity Companies with stronger solvency are better positioned to meet their debt obligations, allowing them to maintain a higher debt ratio, indicating a positive correlation between solvency and capital structure Additionally, firms with more liquid assets can leverage these resources to finance capital expenditures effectively.
H1: There is a negative relationship between liquidity and financial leverage
Larger firms tend to perform better than smaller ones, as supported by studies from Majumar (1997), Papadognas (2007), and Lee, J (2009) This performance advantage is partly due to easier access to loans and external funding for larger organizations Established in the market, these businesses benefit from significant financial resources and have better access to financial markets In the real estate sector, large corporations leverage their financial strength, infrastructure, and prestige to achieve greater profitability compared to their smaller counterparts.
H2: There is a negative relationship between firm size and financial leverage
Tangible fixed assets play a crucial role for enterprises as they serve as collateral for borrowing Creditors often require this collateral due to the challenges in evaluating all risks linked to a business's projects In light of the current bad debt situation, having substantial tangible fixed assets is increasingly important for businesses seeking financial support.
39 a high ratio of tangible fixed assets will find it simpler to obtain financing, especially since the amount of collateral is a key factor in the capacity for corporate lending
As analyzed above related theories, tangible fixed assets are an indispensable factor in evaluating the effectiveness of business activities, affecting the profitability of enterprises, therefore, the author concludes
H3: There is a positive relationship between tangible assets and financial leverage
Previous studies have not addressed the influence of inventory on the capital structure of real estate firms Nonetheless, the author includes this variable in the volumetric model due to observed delays in housing project inventory handovers during the Covid-19 pandemic Financial reports indicate that the prolonged distance caused by the pandemic led to a significant increase in real estate inventories in the third quarter of 2021 Consequently, the author posits a relationship between inventory levels and capital structure.
H4: There is a negative relationship between inventory and financial leverage
Earnings Per Share (EPS) serves as a key indicator of a company's profitability, providing insights into its financial health and aiding investors in making informed stock choices Additionally, EPS facilitates comparisons of business performance among companies within the same industry However, existing research on factors influencing capital structure has not addressed the role of EPS.
40 relationship, therefore, by selecting this variable, it is desirable to see the effect of this variable EPS on the dependent variable
H5: There is a negative relationship between EPS and financial leverage
A study conducted by Oliver, I.I and colleagues (2017) in Nigeria revealed a negative correlation between the growth rate and capital structure of real estate enterprises The research indicates that while asset growth and business profitability are positively linked, long-term asset growth exerts a more significant impact For real estate companies, the effects of total asset growth from new contracts are crucial for evaluating the effectiveness of their operations.
H6: There is a negative relationship between growth and financial leverage
The profitability variable can significantly influence a company's capital structure, exhibiting both positive and negative effects Research by Rajan and Zingales (1995) indicates that firms in the US, Canada, and Japan experience a negative correlation between profitability and financial leverage, whereas German companies demonstrate an opposite trend Additionally, studies on Chinese firms also reveal a negative relationship between profitability and financial leverage.
H7: There is a negative relationship between profitability and financial leverage
The trade-off theory of capital structure suggests that firms with higher tax rates tend to increase their use of debt to benefit from the tax shield provided by interest on borrowed funds Previous research has highlighted the significance of the variable real tax rate in this context.
L Wu, H Yue (2009), G Huang, F.M Song (2006) in China, and Nguyen Thi Thanh Nga
H8: There is a negative relationship between non-debt tax rate and financial leverage.
Methodology
This article builds on prior research to investigate the factors influencing the capital structure of real estate businesses, utilizing the aforementioned variables The author employs a fixed-random effects methodology to execute the regression model To validate the model's diagnostics, VIF testing and the Hausman test will be conducted.
Financial Leverage (FL) = β 0 + β 1 Growth i,t + β 2 Tangible i,t + β 3 Liquidity i,t + β 4 Profitability i,t + β 5 Firmsize i,t + β 6 Inventory i,t + β 7 Nondebttax i,t + β 8 EPS i,t
With β0 is known as a constant variable, βn is a model parameter
LTDA and STDA represents for financial leverage
LTDA stands for long-term debt divided by total asset
STDA stands for short-term debt divided by total asset
GROWTH stands for growth in total asset ratio
TANGIBLEAS stands for tangible assets
CURRENT RATIO stands for liquidity
TOTAL ASSET stands for firm size
EPS stands for earnings per shares
NONDEBTTAX stands for non-debt tax rate
Analysis and finding
Descriptive statistics
Table 3 Summarize dependent and independent variables
The list of secondary data utilized in this dissertation, including variable names, observational data, means, standard deviations, minimum and maximum values, is shown in the table below
Variable OBS Mean Std Dev Min Max
(Source: The author compiled secondary data and summarized STATA 16)
From 2017 to 2021, the average LTDA and STDA values in the Vietnamese real estate market were 0.175 and 0.35, indicating a strong capital structure during this period The mean CURRENT-RATIO of 2.724 suggests a medium level of liquidity, with a maximum value of 21.699 highlighting significant liquidity activities The average total assets across 380 observations stood at 1.26e+07, significantly lower than the maximum of 4.28e+08 For tangible assets, the mean value for 76 companies was approximately 0.323, with the maximum exceeding three times this average Interestingly, real estate companies also maintained inventory, with a minimum of zero Earnings per share (EPS) varied widely from -14353 to 29356, reflecting both negative growth in some firms and high profits in others The average growth rate was positive at 2025.67, indicating overall profitability among businesses Additionally, the average ROA exceeded 4, while the tax shield ratio was around 0.01, further confirming the financial dynamics within the sector.
(Source: The author summarizes from STATA 15 using collected secondary data)
The primary objective of correlation analysis in regression models is to identify multicollinearity among independent variables Gujarati (2004) states that a correlation of at least 80% between two variables indicates potential collinearity issues In this analysis, all independent variable correlations fall below this threshold, except for one notable exception: an 85.15% correlation between the independent variables INV and TOTAL-ASSET Consequently, multicollinearity does not pose a significant concern for my model.
Empirical results
Table 5 Regression analysis for different measurement of dependent variables
Note Robust standard errors *, **, *** show significant at the 10%, 5%, and 1% level respectively SDTA = Short term Debt to Total Asset, Liquidity = Current Assets over
Short-term Debt, Tangible Asset = Fixed Asset plus Inventory over Total Asset, Inventory
Tangible asset inventory Eps Growth ROA Non-debt tax Current ratio 1.000
= Value of inventory, ROA = Return on Asset, Non-debt tax = Depreciation divided by Total Assets , Firm Size = Total Asset the Fixed effect model
(Source: The author summarizes from STATA 15 using collected secondary data)
Relationship between liquidity and financial leverage
Liquidity, measured by the current ratio, exhibits a negative correlation with both short-term and long-term debt ratios Specifically, a 1% increase in liquidity results in a decrease of 0.0198 units in the short-term debt ratio, assuming all other factors remain constant This phenomenon occurs because businesses with substantial liquid assets can reinvest these assets before relying on external funding This perspective contrasts with prevailing research, which suggests that high liquidity enables firms to secure loans for production and operations, thereby enhancing creditor confidence Studies by Hassan S.U and Farouk M.A (2014) and Nguyen Hoang Anh et al (2017) indicate that companies with advanced knowledge and skills tend to achieve higher production levels, further opposing the author's findings.
Relationship between firm size and financial leverage
Firm size (SIZE) exhibits a negative correlation with the debt ratio, indicating that a 1% increase in enterprise size results in a decrease of 8.52e-10 units in the short-term debt ratio, assuming other factors remain constant This finding challenges the trade-off theory, which posits that bankruptcy risk and financial distress costs influence a firm's borrowing capacity Larger enterprises typically face a lower likelihood of bankruptcy and reduced financial distress costs, along with fewer issues related to asymmetric information, leading them to favor debt capital to maximize tax benefits.
According to pecking order theory, real estate enterprises will tend to have more debt The real estate industry is an industry with a long business cycle, requiring a huge
The size of a firm significantly influences its competitive advantage in the real estate market, which requires substantial investment capital (K.C and Reilly, F.K., 2009) Larger firms enjoy benefits such as greater access to capital, warehouses, factories, and enhanced prestige, enabling them to operate more efficiently than smaller firms However, if their management systems are inadequate, large firms may experience detrimental effects on performance Conversely, small enterprises benefit from simpler human resource management and less complex administrative processes Yet, if they struggle to sell products over the long term, their operational efficiency declines while costs rise, leading to increased financial risks and a reduction in overall enterprise value.
Relationship between tangible assets and financial leverage
The debt ratio and short-term debt ratio exhibit an inverse relationship with tangible fixed assets (TANG), with the long-term debt ratio increasing by 0.164 units and the short-term debt ratio by 0.1151 units for each unit increase in TANG, assuming all other factors are constant This aligns with the trade-off theory and pecking order hypothesis, which suggest that fixed assets serve as reliable collateral for debt financing However, from 2017 to 2021, the economic landscape differed from 2010 to 2014, as businesses faced challenges in securing loans despite state support and relaxed bank collateral requirements, including unsecured loans Consequently, research on the capital structure of real estate enterprises in Vietnam during 2010-2014 indicates that the significance of fixed assets in real estate development has diminished, a finding that contrasts with my current research.
48 the author argues that in the last 5 years, tangible assets has played an important role in the capital structure of enterprises
Relationship inventory and financial leverage
An increase in inventory positively influences a firm's capital structure, with a 1% rise in inventory leading to a 2.13e-10 unit increase in the firm's debt structure However, it is important to highlight that the prob>F value indicates the model lacks statistical significance at the 5% level.
Experts suggest that viewing real estate inventories as unsold goods is not a short-term concern Most of the current supply in the real estate market consists of inventory from previous quarters, with both supply and new projects remaining limited and showing no signs of improvement Despite this, demand remains positive, and real estate continues to attract significant interest from customers and investors, even during the epidemic (Linh, 2019).
Relationship between EPS and financial leverage
The analysis reveals a positive correlation between Earnings Per Share (EPS) and the short-term debt ratio of businesses, with a statistically significant model (Prob>F = 0.0000) at the 5% significance level Conversely, the impact of long-term debt on EPS is not significant, which aligns with the limited research available on the relationship between EPS and the capital structure of enterprises.
Relationship between growth and financial leverage
Growth opportunity (GROWTH) has a positive correlation with the debt ratio, indicating that for every unit increase in GROWTH, the short-term debt ratio rises by 0.0144 units, assuming all other factors remain constant This finding aligns with the pecking order theory proposed by Myers and Majluf (1984).
When a business experiences rapid growth, it often requires additional external capital to support development investments, as internal funds may be insufficient This need for external financing primarily affects the long-term debt ratio rather than the short-term debt ratio, which remains stable due to growth opportunities and future investment projects The annual data used in the analysis may not capture immediate impacts on short-term debt Additionally, real estate companies typically possess significant assets such as land and construction projects, which contribute to asset growth This growth is often driven by contracts with partners and clients, along with upfront deposits for real estate construction, leading to increased assets and new initiatives.
Relationship between profitability and financial leverage
The analysis reveals a negative correlation between profitability (ROA) and debt ratio, indicating that a 1-unit increase in ROA leads to a 0.003-unit decrease in the debt ratio, holding other factors constant With a p-value of 0.011, the model demonstrates statistical significance at the 5% level This finding aligns with pecking order theory, suggesting that firms with strong performance and high profitability prefer to finance through internal capital before resorting to external funding to prevent ownership dilution.
Le Phuong Dung et al (2014), Le Thi My Phuong (2017), Biger et al (2008), Onaolapo & Kajola (2010), Le Phuong Dung et al (2014), and Le Thi My Phuong (2017)
50 all reached similar conclusions In contrast, other studies such as Abor (2005), Kouser et al (2011), Devi (2014), and Nguyen Anh Hien (2017) hold the opposite viewpoint
Relationship between non-debt tax rate and financial leverage
The tax rate factor (TAX) does not significantly impact the debt ratio or the short-term debt ratio, as indicated by P-values exceeding 0.05 in both regressions This finding contrasts with some studies suggesting that higher tax rates encourage firms to increase debt usage to benefit from tax shields.
Diagnostic test
The Hausman test is utilized to determine the suitable estimation method between fixed effects and random effects models (Baltagi, 2008) The null hypothesis (H0) posits that there is no correlation between the characteristic error of the objects and the explanatory variables in the model Under the H0 hypothesis, the random effects (RE) estimate is valid, while it is not under the alternative hypothesis Conversely, the fixed effects (FE) estimate remains valid for both the H0 and alternative hypotheses If the null hypothesis is rejected, the fixed effects estimate is deemed more appropriate than the random effects estimate.
Therefore, in this research, the author chooses Hausman model to test the model's suitability to the data:
B=consistant under H0 and Ha; obtained from xtreg B=inconsistent under Ha, efficient under H0, obtained from xtreg Test: H0: difference in coefficient not systematic
(Source: The author summarizes from STATA 15 using collected secondary data) H0: The model chosen is the Fix-effect model
H1: The model chosen is the random-effect model
P-value (Hausman) > 0.05 accepts the hypothesis Ho The model chosen is the random effects model REM
P-value (Hausman) < 0.05 rejects the null hypothesis The model chosen is the fixed-effects model FEM
Pro>chi2 = 0.0000 < 0.05, therefore, fix-effect model is the model chosen in this research
Table 7 Testing multicollinearity by using VIF
(Source: The author summarizes from STATA 15 using collected secondary data)
To determine the presence of multicollinearity among independent variables, the Variance Inflation Factor (VIF) is employed to assess their correlation VIF values start at 1 and have no upper limit; a VIF between 1 and 2 indicates no correlation, while values from 2 to 5 suggest a moderate association that typically does not require corrective measures A VIF exceeding 5 signals a high correlation, leading to unreliable coefficient estimates and uncertain p-values Specifically, if VIF values remain below 10 and the average VIF is under 6, multicollinearity is not significantly impacting regression coefficients (Montgomery, 2007) Additionally, a condition index below 15 further suggests that multicollinearity is unlikely to be an issue in the analysis.
Multicollinearity often arises from poorly designed trials and is primarily based on unchangeable observational data Variables may be selected due to data collection from purely observational studies, leading to flawed choices of independent variables Additionally, insufficient data can further compromise the analysis, as noted by Montgomery and Peck (1982) Other influencing factors also affect the outcomes of the research.
The mean value of the Variance Inflation Factor (VIF) is 1.91, which is below the threshold of 10, indicating that multicollinearity is not present in the regression model This absence of multicollinearity can be attributed to the substantial dataset of 380 samples collected for the study.
White’s test for Ho: homoskedasticity
Cameron & Trivedi’s decomposition of Im-test
(Source: The author summarizes from STATA 15 using collected secondary data)
Heteroskedasticity refers to a statistical condition where the standard error of a variable remains constant over time in a linear regression model This phenomenon can lead to significant problems in Ordinary Least Squares (OLS) regression, as it may produce unbiased estimates but result in biased standard errors Consequently, the inferences drawn from the test may be inaccurate, compromising the reliability of the test results.
As a result, it is unlikely that this issue will arise in regression models This project applies the Breusch-Pagan test, which Breusch and Pagan devised, to identify heteroscedasticity
In this table, P-value is lower than 0.01/0.05 or 0.1, heteroscedasticity occurs
The Wooldridge test is applied in two models The prob>F shows that model 1, model 2, have a sign of autocorrelation
Model 1 Total long-term debt over total asset
Wooldridge test for autocorrelation in panel data H0: no first order autocorrelation
F (1,101) = 12.913 Prob > F = 0.0006 Model 2 Total short-term debt over total asset
Wooldridge test for autocorrelation in panel data
F (1,101) = 20.141 Prob > F = 0.0000 (Source: The author summarizes from STATA 16 using collected secondary data)
The autocorrelation approach is a valuable method for measuring and explaining the internal correlation between data or variables in a statistical model (Hill et al., 2001) Even in the presence of autocorrelation, the Ordinary Least Squares (OLS) estimation remains unbiased and consistent This method is favored for its versatility and ease of use (Drukker, 2003) In this analysis, the Wooldridge test will be conducted using STATA, and a Prob P-value greater than 0.05 indicates no evidence of autocorrelation or serial correlation in the data.
In this case, there doesn’t exists autocorrelation because P-value in 2 models are less than 0.05