Executive Summary The dissertation investigates the impact of capital structure on firm value of 435 listed firms on two major stock exchanges in Vietnam, HOSE and HNX, as well as three
Introduction
In the first half of 2020, Vietnam's GDP growth was only 1.81%, marking the lowest rate in a decade due to the global impact of the Covid-19 pandemic (GSO of Vietnam, 2020) Despite this, Vietnam's economic performance remained relatively strong compared to major economies like the U.S., EU, and Japan, which experienced negative growth (Lee, 2020) Projections indicate that Vietnam's GDP will recover to 4.1% by the end of 2020, leading Southeast Asia, with expectations of further growth at 6.8% in 2021 (Khoa).
In 2020, key industries such as food and beverage (F&B), construction, and real estate emerged as crucial sectors for the recovery and future growth of the Vietnamese economy.
The food and beverage industry in Vietnam ranks as the second largest production sector in the economy, following retail, and is recognized as a crucial industry with significant growth potential With a predominantly young population and rising income levels, coupled with strong companies and well-known brands, this sector is anticipated to emerge among the top three in Asia in the near future.
In the first seven months of 2020, the Vietnamese food and beverage industry experienced a significant revenue decline of approximately $12.1 billion, equivalent to a 16.6% year-on-year drop, raising concerns about the industry's recovery amid potential future social distancing measures (Thong, 2020) However, the implementation of the EVFTA in August 2020 presents a promising opportunity for revitalization in the sector.
3 opportunity for the F&B industry in Vietnam thanks to tariff liberalization and immediate duty-free for many agricultural products, which include coffee, tea, spices, fruits and nuts (Nguyen, 2020)
In the first half of 2020, the Vietnamese construction and industrial sectors experienced significant growth, contributing 2.98% to overall growth and 73.14% to GDP (GSO of Vietnam, 2020) Despite the moderate impact of the epidemic on the construction industry, 2020 is expected to pose challenges for contractors, particularly small firms with low profit margins, amid increased competitive pressure during the global pandemic (FPT Securities).
Despite facing challenges, the construction industry is expected to experience robust annual growth of around 7.2% over the next decade, as projected by Fitch Solutions This growth is supported by a broader 6.8% increase in the construction sector and a 5.7% rise in infrastructure from 2021 to 2019 The recent economic expansion in Vietnam has led to increased incomes, driving up demand for luxury residential properties in major cities.
The 2020-2021 Vietnamese real estate conference highlighted the sector's significant impact on 35 other industries, including construction, tourism, and finance, with real estate accounting for 65% of collateral in banking While the industry has faced challenges due to Covid-19, such as complex investment procedures, insufficient land availability, and limited transportation infrastructure, the future remains optimistic There is considerable potential in industrial real estate, and banks continue to provide ample financing options.
The rise in government investments and the introduction of four credit products for household and logistics real estate are set to boost the sector (Nhi, 2020) Furthermore, the EVFTA is expected to enhance export activities, thereby attracting foreign investments and increasing demand for industrial properties, including land and ready-built factories (Ly).
2020) The real estate industry is expected to grow in the last 3 months of 2020 in the best case scenario, but more likely to stay quiet until the upcoming years (Nguyen, 2020)
Financing decisions are crucial in corporate finance for maximizing shareholder wealth, serving as a foundation for investment and dividend choices (Arnold, 2013) The ongoing debate regarding the optimal mix of debt and equity remains unresolved (Singh & Bansal, 2016), and research on capital structure and firm value is notably limited in Vietnam (Vo & Ellis, 2017) Most empirical studies focus on listed firms within a single stock exchange or sector, with few comparisons across different sectors This study aims to analyze the impact of capital structure on firm value across various industries, specifically excluding the financial services sector, while also examining the food and beverage, construction, and real estate sectors The findings will be compared to existing theoretical and empirical research, as well as the unique characteristics of the selected industries, providing valuable insights for financial managers, investors, and regulators.
5 creditors in their process of decision-making, as well as academics in making further analysis regarding to impact of capital structure on firm value
The subsequent chapters of the dissertation are structured as follows: Chapter 2 reviews the literature on the theoretical foundations of capital structure and its empirical impact on firm value Chapter 3 outlines the data collection process and methodology, detailing the selected variables, hypotheses, and estimation techniques Chapter 4 presents an analysis of the empirical findings, including hypothesis testing and a discussion of limitations Finally, Chapter 5 concludes the research, summarizing key insights and offering recommendations for related topics.
Literature Review
Theoretical background of capital structure decisions
Before the groundbreaking theoretical research by Modigliani & Miller in the 1950s and 1960s, various approaches explored the relationship between capital structure, the weighted average cost of capital (WACC), and firm value The fundamental assumptions are that WACC represents the total cost of debt and equity, with debt being cheaper than equity, and that future cash flows are perpetual and discounted to present value using WACC to determine firm value Consequently, firm valuation hinges on the debt-equity mix: a lower WACC results in a higher firm value, and vice versa (Arnold, 2013).
In the first scenario, it is assumed that the cost of equity remains constant while the cost of debt decreases as the proportion of debt increases This adjustment leads to a reduction in the Weighted Average Cost of Capital (WACC).
Increasing debt can enhance a firm's value, but when debt levels rise, the cost of equity may also increase proportionately, leading to a constant cost of capital and stable firm value In contrast, while some scenarios suggest that the benefits of debt financing outweigh the increased cost of equity, resulting in a lower weighted average cost of capital (WACC) and higher firm value, other scenarios indicate that rising equity costs can negate these benefits, ultimately decreasing firm value as the cost of capital rises Despite being traditional viewpoints, these scenarios form critical foundations for many subsequent capital structure theories (Arnold, 2013).
Modigliani and Miller's 1958 analysis of capital structure and firm value operates under the ideal conditions of a perfect market, where taxation, transaction costs, financial distress, and agency issues are absent, and information is equally accessible to all market participants They propose three key propositions: first, a firm's value remains unaffected by its capital structure; second, as debt levels increase, the cost of equity rises proportionately, resulting in no change to the weighted average cost of capital (WACC) and, consequently, the firm's value; and third, increasing the gearing ratio exposes the firm to greater financial risks, leading shareholders to demand a risk premium for their investments.
Regardless of a firm's use of financial leverage, the rate of return on its projects and its Weighted Average Cost of Capital (WACC) remain equal When a firm transitions to an all-equity financing structure, the cost of capital remains constant, aligning with the cost of equity, as established by Modigliani and Miller in 1958.
The initial theory of capital structure laid the groundwork for understanding a firm's debt and equity choices, despite its unrealistic assumptions Over time, Modigliani and Miller expanded their theory in 1963 by incorporating taxation effects, highlighting that debt financing offers not only a lower cost compared to equity but also valuable tax shields They argued that as a firm's gearing level increases, the rising cost of equity cannot offset the advantages of debt, leading to a decreased cost of capital and an enhanced firm value Consequently, it suggests that firms should maximize borrowing to leverage financial benefits However, this perspective does not align with real-world scenarios, as the complexities of taxation and other factors influencing capital structure and firm value require further investigation.
Numerous scholars, including Miller (1977), have examined the effects of taxation on capital structure decisions Miller's study highlights that low personal taxes on equity benefit shareholders, leading to increased demands for higher lending interest rates from debt holders.
Increasing the cost of debt diminishes its advantages as a cheaper source of finance, which can negate the benefits of corporate tax reductions Consequently, higher debt levels may lead to an increased cost of equity, elevate the weighted average cost of capital (WACC), and ultimately reduce the firm's value DeAngelo and Masulis (1980) expanded on Miller's (1977) research by examining corporate and personal taxes, revealing the significance of non-debt tax shields, such as accounting depreciation and investment tax credits, as alternatives to debt tax shields They concluded that each firm's optimal capital structure is unique, influenced by the tax effects on debt and equity returns Additionally, Graham (2000) estimated that approximately 9.7% of firm value could benefit from taxation, a figure that is halved when personal tax effects are excluded He noted that financially stable large firms tend to adopt conservative debt strategies, while others may opt for more aggressive approaches, weighing the costs and benefits of financial leverage.
In 1970, Gordon emphasized the need for a theory of financial distress following the collapse of numerous corporations, defining financial distress as a situation where a firm cannot meet its debt obligations due to poor profit generation If unresolved, this distress can lead to bankruptcy Altman (1968) demonstrated that financial ratios are effective in predicting bankruptcy potential, and further evidence from 1984 highlights the importance of understanding bankruptcy costs Regardless of a firm's ability to manage liquidation, these factors remain critical in assessing financial health.
Financial distress and subsequent bankruptcy incur both direct and indirect costs for a business Direct costs typically include legal fees for lawyers and court filings, as well as expenses related to accounting and management In contrast, indirect costs primarily stem from reduced earnings due to operational disruptions.
Uncertainties in business can severely harm the relationships between a firm and its suppliers and customers, leading to employee underperformance As a result, managers often prioritize short-term financial obligations over long-term goals of maximizing shareholder wealth This precarious financial situation makes lenders hesitant to provide debt financing, often resulting in higher return demands due to the firm's poor financial health (Arnold, 2013).
Jensen and Meckling's (1976) research highlights the significance of agency theory in understanding a firm's ownership structure and capital structure They define the agency relationship as a contract between principals and agents, where agents are tasked with acting on behalf of principals However, due to information asymmetry, agents may not always prioritize the principals' best interests To address this challenge, principals incur costs to monitor agent behavior, incentivize them to avoid excessive risks, and protect themselves from any detrimental actions Additionally, discrepancies in decision-making by agents can lead to agency costs that diminish the welfare of principals Jensen (1986) further explored agency theory, emphasizing the control benefits of debt financing.
Using debt to minimize agency costs serves as an alternative to dividends, as it obligates managers to prioritize future payments to debt holders, thereby preventing inefficient spending of free cash flows However, the restrictive covenants imposed by lenders can limit investment flexibility Even when high Net Present Value (NPV) projects are pursued, lenders often demand higher returns to compensate for the increased risk involved (Arnold, 2013).
The trade-off theory, established after the M&M theorems in 1958 and 1963, explains the relationship between capital structure and firm value by considering the impacts of taxes, financial distress, and agency theory It highlights that the costs associated with financial distress and agency issues can surpass the benefits of tax reductions, leading to increased capital costs and diminished firm value Consequently, firms must find a balance between these costs and benefits to achieve an "optimal capital structure," where the weighted average cost of capital (WACC) is minimized, and firm value is maximized (Arnold, 2013) The static trade-off model, which focuses solely on bankruptcy costs, was developed by Kraus & Litzenberger (1973) and Scott (1977), while Myers (1977) and Bradley et al (1984) incorporated both bankruptcy and agency costs However, since these conclusions are based on cross-sectional data applicable only to end-of-period firms, further investigation into a dynamic trade-off model is necessary Fischer et al (1989) explored dynamic capital structure, revealing that adjustments toward the optimal debt ratio differ across firm types, and even minor changes in recapitalization decisions can lead to substantial transaction costs.
Another popular approach in explaining the choice of debt and equity is the pecking-order theory, which was developed by Myers (1984) and his research with
Maljuf's theory challenges both M&M theories and the trade-off model by rejecting the notion of a target capital structure The authors categorize equity capital into internal and external sources, emphasizing that firms prefer retained earnings under a stable dividend policy When additional funds are needed, companies opt for less risky external financing, prioritizing debt issuance over equity This preference stems from agency theory and asymmetric information, where managers have superior knowledge about share valuation Consequently, they are more likely to issue new shares when overvalued and rely on debt when undervalued Investors interpret equity issuance as a negative signal, which can lead to a decline in share prices Ultimately, the findings suggest that managers favor debt over equity for external financing, with unprofitable firms often exhibiting high financial leverage and varying average debt ratios across industries.
Empirical evidence from impact of capital structure on firm value 13
Numerous studies have been conducted since the introduction of financial structure theories to examine the alignment between practical findings and theoretical research, yet the relationship between capital structure and firm value remains a contentious issue While there is an abundance of literature on firm leverage and its impact on value, it is impractical to cover all empirical research comprehensively This dissertation focuses on studies from 2010 to 2020, emphasizing the effect of capital structure on firm value The relationship between capital structure and firm value is complex, reflecting a range of outcomes from significant to insignificant and mixed results in prior empirical investigations.
Empirical evidence from Vietnam indicates a negative significant impact of capital structure on firm value, as demonstrated in the study by Vo & Ellis (2017) involving listed firms on the Ho Chi Minh City Stock Exchange from 2007 to 2013 Utilizing multivariate regression with fixed effects and accumulated stock returns as the firm value indicator, the study found that firm size positively influences firm value, alongside the price-to-book (PB) ratio In contrast, the price-to-earnings (PE) ratio and market risk negatively affect firm value Additionally, Cuong & Canh (2012) analyzed 92 Vietnamese seafood processing firms from 2005 to 2010, revealing that capital structure exerts both positive and negative substantial effects on firm value, characterized by a linear Inverted-U relationship In this context, firm size negatively impacts firm value, while firm growth has a positive effect.
Research by Dang et al (2019) on 214 firms listed on HOSE in Vietnam indicates that financial leverage negatively and significantly affects enterprise value (EV) when assessed using pooled OLS with FEM and REM, but has no significant impact on Tobin’s Q when ROA is employed as a profitability measure instead of ROE The study finds no significant relationship between firm growth and firm value, while ROE shows a positive significance to EV and ROA is positively significant to Tobin’s Q Additionally, firm size positively influences EV but does not have a substantial effect on Tobin’s Q.
As for the empirical evidence on non-Vietnamese firms, there’s also a variety of results in regards to the impact of capital structure on firm value
Research by Cheng & Tzeng (2011) highlights a significant positive impact of financial structure on firm value, analyzing 645 firms on the Taiwan Stock Exchange from 2000 to 2009 using the GMM method Firm value is assessed through the ratio of market value of equity plus book value of debt to net fixed assets While the Z-score, a measure of financial quality, does not significantly affect firm value, it does strengthen the positive correlation between firm leverage and firm value Conversely, high free cash flow per share negatively impacts firm value, with no change in the effects of capital structure Similarly, Gill & Obradovich (2012) found a notable positive relationship between firm leverage and firm value in their study of 333 firms on the New York Stock Exchange from 2009 to 2011, utilizing the OLS method and measuring firm value through Tobin’s Q.
The analysis of 15 firms across the manufacturing and service industries reveals that the relationship between capital structure and firm value remains consistent in both sectors However, the size of the firm, measured by the logarithm of total assets, demonstrates a significant positive impact solely on service firms, while profitability, indicated by ROA, exhibits a similar effect exclusively on manufacturing firms in the U.S Additionally, research by Rizqia & Sumiati (2013) on 15 listed manufacturing companies in Indonesia from 2006 to 2011 provides further empirical evidence of the positive influence of capital structure, firm size, and profitability on Tobin's Q.
The study by Hasbi (2015) analyzed 152 Indonesian microfinance institutions from 2009 to 2014 using panel regressions, revealing consistent results regarding the relationship between dependent and independent variables However, it focused on firm growth, measured by changes in total assets, rather than firm size, with the firm's value defined as the market value of both debt and equity.
A study by Al-Sleha (2020) analyzing 13 mining and extraction firms listed in Jordan from 2010 to 2018 found that firm leverage negatively impacts firm value, though this effect is statistically insignificant In contrast, the size of the firm and the proportion of fixed assets, or asset structure, demonstrate a significant positive influence on firm value.
Cheng et al (2010) conducted a study on 650 Chinese listed firms from 2001 to 2006, revealing that capital structure significantly influences firm value, both positively and negatively This research utilized a panel threshold regression model and variables similar to those employed by Cuong & Canh (2012) in their analysis of Vietnamese firms, with a focus on the impact of firm size.
Research indicates that firm growth does not significantly influence a firm's value The "twin effect" has been validated in other studies, showing a linear relationship Cheng & Tzeng (2014) expanded their earlier work by utilizing pooled OLS with fixed effects and random effects estimations to explore additional contextual variables that interact with capital structure, such as growth opportunities, corporate taxes, non-debt tax shields, and inflation rates Similarly, Aggarwal & Padhan (2017) examined 22 listed hotel firms in India, employing the same methodology and incorporating multiple independent variables, measuring firm value through enterprise value, price-to-book (PB) ratio, and Tobin’s Q.
Singh & Bansal (2016) conducted a study on 58 Indian listed FMCG firms from 2007 to 2016, revealing a significant positive impact of gearing level on enterprise value (EV), while finding a negative and insignificant effect on Tobin’s Q This aligns with the findings of Dang et al (2019) regarding Vietnamese listed firms Additionally, other control variables such as return on assets (ROA) and asset structure showed an insignificant positive influence on both firm value measures.
The relationship between capital structure and firm value yields varying results, reflecting different theoretical perspectives Findings indicate that firms across diverse countries and industries can produce distinct outcomes The choice of methodology and variables contributes to this variability, leading to multiple types of results However, empirical research also reveals gaps that require further investigation.
17 especially in Vietnam where it is stated that published studies on the relations between capital structure and firm value are still limited
There is a notable lack of empirical studies across various Vietnamese industries, with Cuong & Canh (2012) focusing solely on the seafood processing sector Similarly, research by Vo & Ellis (2017) and Dang et al (2019) is limited to a small number of firms listed on the HOSE stock exchange Outside Vietnam, the only significant empirical analysis comes from Gill & Obradovich (2012), which examines two industries collectively Most past studies in Vietnam have relied on ordinary least squares techniques for panel data estimations, while alternative methods such as panel threshold regression and GMM are rarely utilized, appearing only in the works of Cheng et al (2010) and Cheng & Tzeng (2011).
This dissertation uniquely investigates the impact of capital structure on firm value across various industries in Vietnam, distinguishing itself from other studies that focus on the broader context It employs a mix of simple and advanced regression methods, including pooled OLS, FEM, REM, and GMM, to analyze the data The upcoming chapter will outline the research methodology, detailing data collection, variables, hypotheses, and estimation techniques.
Data and Methodology
Data collection
Secondary data for the research are firm-specific indicators from 2012 to
2019 of Vietnamese listed firms from two major stock exchange, HOSE and HNX Total 1,548 companies in Vietnam were found on Bureau Van Dijk’s Osiris and
A total of 435 non-financial firms were chosen for this study due to the unique operational characteristics of financial institutions, which complicate comparative analysis with typical corporations Additionally, the increase in listed firms over the past five years has led to data inconsistencies, as transitions between stock exchanges can result in the loss of historical data, and several financial indicators are missing from the database The balanced panel data comprises 24,360 firm-year observations.
To analyze industry-specific differences among 435 selected firms, three key sectors—food and beverage, construction, and real estate—were identified due to their significance to the Vietnamese economy The limited number of listed companies in other industries rendered them unsuitable for empirical research, potentially skewing results However, discrepancies exist in industry classification, as the GICS and NAICS 2017 codes are utilized in the Bureau Van Dijk’s Osiris database, while Vietnam employs its own VSIC 2018 code A comparison of these classifications reveals that the food and beverage sector comprises 32 listed firms, the construction sector has 56 listed firms, and the real estate sector includes 38 listed firms.
19 of firm-year observations in each industry in balanced panel data is 1,792, 3,136 and 2,128 respectively.
Variables and hypotheses
Firm value can be assessed through various metrics, with enterprise value being a preferred measure in this dissertation due to its frequent use in previous research This approach allows for a comprehensive evaluation of the firm by considering both market and book value Singh & Bansal (2016) and Aggarwal also utilize enterprise value in their analyses, reinforcing its relevance in empirical studies.
& Padhan (2017) and Dang et al (2019): it is calculated by the sum of market capitalization and book value of debt minus cash and cash equivalents
In addition to capital structure, which serves as an explanatory variable for its influence on firm value, seven control variables are considered: firm size, profitability, growth, tangibility, and liquidity Prior empirical studies indicate that these control factors stem from the determinants of capital structure; they not only help explain financial structure behavior but also directly impact firm value The independent variables and alternative hypotheses are outlined as follows.
Capital structure is commonly assessed at year-end through various metrics derived from balance sheets These metrics include the ratio of total debt to total assets (Cheng et al., 2010; Cuong & Canh, 2012; Rizqia & Sumiati, 2013; Dang et al., 2019), the ratio of total debt to total equity (Hasbi, 2015; Singh & Bansal, 2016; Al-Sleha, 2020), and the ratio of total liabilities to total assets (Gill & Obradovich, 2012; Vo & Ellis, 2017) Additionally, alternative indicators of capital structure are also used, such as the total liabilities metric.
In their studies, Cheng & Tzeng (2011, 2014) utilized the ratio of 20 divided by net fixed assets, while Aggarwal & Padhan (2017) analyzed total outside liabilities divided by total net worth This research calculates capital structure by following the methodologies of Gill & Obradovich (2012) and Vo & Ellis (2017), emphasizing that total liabilities provide a more comprehensive measure of financial obligations.
Theoretically, the impact of capital structure on firm value can be positively significant according to the propositions of M&M (1963), signalling theory (Ross,
The trade-off theory suggests that a firm's financial leverage may not be optimal, leading to potential drawbacks, while the pecking-order theory highlights a preference for internal financing.
According to trade-off theory, a firm's financial leverage should not exceed its target level; however, empirical studies have shown varied results, with some indicating a positive and significant relationship (Gill & Obradovich, 2012; Rizqia, 1984).
Research has shown varying results regarding the relationship between capital structure and firm value, with studies indicating negative and significant impacts (Vo & Ellis, 2017), insignificant effects (Al-Sleha, 2020), and mixed findings (Singh & Bansal, 2016; Dang et al., 2019) Consequently, the alternative hypothesis highlights the significance of the relationship rather than the direction of the impact.
H1.1: Capital structure has a significant effect on the value of the firm
Firm size is used in most of empirical studies including Cheng et al (2010), Gill & Obradovich (2012), Cuong & Canh (2012), Rizqia & Sumiati (2013), Aggarwal & Padhan (2017), Vo & Ellis (2017), Dang et al (2019) and Al-Sleha
(2020) It is calculated by natural logarithm of total assets in all of studies mentioned and this research will follow the same calculation Theoretically, a large
Companies with a robust and diverse resource base are better equipped to navigate adverse changes in business operations and financial market shocks, significantly reducing the risk of bankruptcy and protecting their reputation.
1970) In addition, there will be more information available on large corporations, which lower the problem of asymmetric information as well as agency costs (Jensen
Empirical studies have shown mixed results regarding the impact of firm size on firm value, with research by Aggarwal & Padhan (2017) and Dang et al (2019) highlighting both significant and insignificant effects Consequently, the alternative hypothesis focuses solely on the significance of this relationship without addressing the extent of its impact.
H1.2: Firm size has a significant effect on the value of the firm
Firm profitability is also applied in the majority of empirical research including Gill & Obradovich (2012), Cuong & Canh (2012), Rizqia & Sumiati
(2013), Hasbi (2015), Singh & Bansal (2016), Aggarwal & Padhan (2017) and Dang et al (2019) Apart from ROE which is used in Hasbi (2015) and Dang et al
In 2019, most studies utilized Return on Assets (ROA) as a key indicator of a firm's profitability, and this dissertation follows suit However, this research opts to use Earnings Before Interest and Taxes (EBIT) rather than net profits after taxes, as EBIT provides a clearer representation of a company's operational earning power, free from the influences of interest and tax expenses Consequently, ROA is calculated as EBIT divided by total assets.
Increasing profitability ratios enhances a firm's value and reduces the likelihood of bankruptcy and financial distress, as a profitable company generates enough earnings to meet its financial obligations (Gordon, 1970).
22 show mixed results regarding to the impact of firm profitability on firm value: positive and significant (Gill & Obradovich, 2012; Rizqia & Sumiati, 2013; Hasbi,
2015), negative and significant (Aggarwal & Padhan, 2017), significant and insignificant (Dang, et al., 2019) Thus, the alternative hypothesis predicts only the significance in their relationship:
H1.3: Firm profitability has a significant effect on the value of the firm
Firm growth can be effectively measured through proportional changes in sales revenue or total assets over the year, as highlighted in various studies (Cuong & Canh, 2012; Singh & Bansal, 2016; Dang et al., 2019; Aggarwal & Padhan, 2017) While sales revenue is often subject to fluctuations and manipulation, an asset-based approach, as advocated by Aggarwal & Padhan (2017), provides a more stable indicator of growth Additionally, changes in a firm's assets reflect critical investment decisions in corporate finance, making this method particularly relevant for assessing firm expansion.
According to agency theory, firm growth can reduce firm value as managers may prioritize personal benefits over the interests of principals, leading to ineffective project choices (Jensen & Meckling, 1976; Jensen, 1986) However, Aggarwal & Padhan (2017) found that the impact of firm growth on value is both positive and negative, with some effects being insignificant.
23 theoretical and practical research, the alternative hypothesis again states only the significance in their relationship:
H1.4: Firm growth has a significant effect on the value of the firm
Firm tangibility, defined as the ratio of fixed assets to total assets, is a key focus in empirical studies such as those by Singh & Bansal (2016), Aggarwal & Padhan (2017), and Al-Sleha (2020) This research adheres to the established measurement, suggesting that a higher proportion of fixed assets can serve as valuable collateral, enhancing a firm's ability to absorb shocks and mitigate information asymmetry as outlined in agency theory (Jensen & Meckling, 1976; Jensen, 1986) While some studies report a significant relationship between tangibility and firm value (Al-Sleha, 2020), others find insignificant results (Singh & Bansal, 2016), and a mix of outcomes (Aggarwal & Padhan, 2017) Consequently, the alternative hypothesis posits that tangibility significantly impacts firm value.
H1.5: Firm tangibility has a significant effect on the value of the firm
Firm liquidity or current ratio appears in the research of Aggarwal & Padhan
The liquidity ratio, calculated by the proportion of total current assets to total current liabilities, plays a crucial role in a firm's ability to meet short-term financial obligations A high liquidity ratio can enhance a company's chances of fulfilling its financial commitments and minimizing costs associated with financial distress However, research by Aggarwal & Padhan (2017) reveals that the relationship between liquidity and firm value can exhibit both positive and negative effects.
24 alternative hypothesis only state the significance instead of the direction of current ratio’s impact on the value of the firm:
H1.6: Firm liquidity has a significant effect on the value of the firm.
Estimation methods
The estimation methods for this dissertation consists of pooled OLS with
FEM and REM following the research on traditional financial econometrics by
Wooldridge (2013) and Brooks (2014) The combination of methods also employed in the empirical studies of Aggarwal & Padhan (2017) as well as Dang et al (2019)
The GMM estimation method is utilized in this research as an advanced approach for panel data analysis, building on the insights from modern econometrics by Kennedy (2008) and Verbeek (2017) A significant issue identified by both authors in linear regressions is endogeneity, which can result in estimation problems such as measurement errors, reversed cause-and-effect relationships, and bias from omitted variables By employing the GMM estimation method, the model circumvents the need for analytical solutions, avoids specific distributional assumptions, and provides a unified framework for analysis.
The research by Hayakawa (2009) demonstrates that the GMM estimator using orthogonal deviations outperforms first differences, and this approach will be utilized in this dissertation for the dynamic panel data model.
The estimation equations using pooled OLS with FEM and REM method are demonstrated as follow:
+ 𝛽 7 𝐶𝑅 𝑖,𝑡 + 𝜀 𝑖,𝑡 The estimation equations using GMM method are demonstrated as follow:
+ 𝛽 7 𝐶𝑅 𝑖,𝑡 + 𝜀 𝑖,𝑡 The interpretation of variables in equations can be summarized in table 3.1 below:
Table 3.1: The choice of variables
Market Capitalization + Book value of Debt – Cash and cash equivalents
Enterprise value previous year EV t-1
Capital structure LEV Total liabilities / Total assets +/-
Firm size SIZE Ln (Total assets) +/-
Firm profitability ROA Earnings after taxes / Total assets +/-
Firm growth GROW (Total assets year t – Total assets year t-
1) / Total assets year t +/- Firm tangibility TANG Fixed assets / Total assets +/-
Firm liquidity CR Current assets / Current liabilities +/-
Source: Summarization from section 3.2 and 3.3 according to previous research
This chapter analyzes the empirical findings of the study on how capital structure and other factors influence firm value, comparing these results with existing theoretical and practical research The analysis encompasses all industries, with a focused examination of three specific sectors: food and beverage, construction, and real estate.
Results and Discussion
Descriptive statistics and correlation matrix
Table 4.1: Descriptive Statistics – All industries (excluding financial services sector)
Variables ROA GROW TANG CR
Source: Outcomes of data analysis on Eviews
Table 4.1 reveals that enterprise value exhibits the highest standard deviation among all variables across industries, as it is the only metric represented in absolute terms The presence of negative values in minimum enterprise value indicates that a firm's worth can potentially drop below zero By applying logarithmic transformation to total assets, the deviation of firm size from its mean is minimized Additionally, a debt ratio exceeding one-half of total assets signifies substantial losses that cannot be compensated by equity capital A negative minimum Return on Assets (ROA) further implies that a firm has incurred losses due to elevated operating expenses prior to accounting for interest and taxes Furthermore, a firm's growth can manifest in both expansion and contraction, evidenced by the lowest data value being negative Lastly, there exists a diverse asset structure among firms.
The analysis reveals that the maximum and minimum proportions of fixed assets in total assets are 27% Despite the extremes in the current ratio indicating some unusual historical cases, the average suggests that the differences between short-term assets and liabilities are relatively narrow Furthermore, the Jarque-Bera test results for all variables show probability values below the 5% significance level, confirming that the collected data do not follow a normal distribution.
The analysis of selected industries, including food and beverage, construction, and real estate, reveals notable trends in enterprise value, profitability, growth, and financial metrics Specifically, the food and beverage industry exhibits a higher average enterprise value and profitability compared to construction and real estate Additionally, food and beverage firms maintain a lower mean debt ratio Conversely, the construction industry showcases the highest financial leverage ratio, while the real estate sector is characterized by the largest size and current ratio Furthermore, the size of real estate listed firms is the only metric that follows a normal distribution, as indicated by the Jarque-Bera test results exceeding the 5% significance level.
Table 4.2: Correlation Matrix – All industries (excluding financial services sector)
EV LEV SIZE ROA GROW TANG CR
Source: Outcomes of data analysis on Eviews
According to table 4.2, current ratio has the strongest correlation with capital structure which is negative 0.487431 and at the same time, has the weakest
The analysis reveals a positive correlation of 0.005582 between profitability and the combined data across all industries Notably, none of the correlation coefficients exceed 0.8 or fall below -0.8, indicating that the regression models are not significantly affected by collinearity, which could lead to biased estimation results (Brooks, 2014).
The analysis reveals no significant collinearity issues in model estimation, as the independent variables for the food and beverage, construction, and real estate industries show low correlation with one another (see Appendices D, E, and F) Notably, the highest correlation between enterprise value and firm size is observed in the food and beverage (0.580319), construction (0.538233), and real estate (0.780750) sectors Conversely, the weakest correlation in the food and beverage industry is between profitability and tangibility, recorded at -0.010141, a similar trend is noted in the real estate sector with a correlation of -0.011865 In the construction industry, the least correlation exists between the current ratio and firm tangibility at 0.015691.
Estimation results
Table 4.3: Estimation results – All industries (excluding financial services sector)
Pooled OLS FEM REM GMM
Source: Outcomes of data analysis on Eviews
Table 4.4: Estimation results – Food and Beverage industry
Pooled OLS FEM REM GMM
Source: Outcomes of data analysis on Eviews
Table 4.5: Estimation results – Construction industry
Pooled OLS FEM REM GMM
Source: Outcomes of data analysis on Eviews
Table 4.6: Estimation results – Real Estate industry
Pooled OLS FEM REM GMM
Source: Outcomes of data analysis on Eviews
Fixed effects (FEM) and random effects models (REM) are commonly used to address unobserved factors in empirical studies; however, only one method is efficient under specific conditions where regression assumptions remain intact The Hausman test determines the suitability of FEM or REM, requiring unobserved factors to be uncorrelated with explanatory variables for unbiased REM results A p-value below 5% supports the use of the fixed effects model, while an insignificant p-value suggests the random effects model is more appropriate (Wooldridge, 2013) The Chi-square probabilities from the Hausman test for various industries, including food and beverage, construction, and real estate, are 0.0001, 0.0002, 0.0000, and 0.0047, respectively Consequently, the regression model estimations in tables 4.3 to 4.6 should rely on FEM rather than GMM estimation, as summarized in the accompanying table.
Table 4.7: Outline estimation results (FEM and GMM method)
All industries (excluding financial services sector)
Food and Beverage Construction Real Estate
SIZE Positive Positive Positive Positive
Source: Summarization form table 4.3 to table 4.6
Table 4.7 indicates that capital structure and firm liquidity, as measured by the current ratio, have a negative but insignificant impact on firm value across all industries Additionally, while there are contradictory results regarding the growth and tangibility of the firm when analyzed through FEM and GMM, these factors also show insignificant effects on enterprise value In contrast, the size of the firm demonstrates a significant and positive influence on its value.
In the food and beverage industry, a strong and positive correlation exists between capital structure and firm value, as evidenced by GMM estimation Additionally, this relationship extends to the influences of firm profitability, asset tangibility, and liquidity on overall firm value.
The growth of a firm negatively impacts its value, while firm size positively correlates with firm value, as evidenced by both Fixed Effects Model (FEM) and Generalized Method of Moments (GMM) estimations.
In the construction industry, capital structure negatively affects firm value, while firm growth also shows a similar negative impact, confirmed by both FEM and GMM methods Conversely, firm tangibility positively influences firm value, but this is only evident in GMM estimations Although there is an inconsistency regarding the effect of ROA on firm value, neither firm profitability nor liquidity significantly impacts enterprise value Additionally, firm size positively and significantly affects firm value in both FEM and GMM analyses.
In the real estate industry, similar to the construction sector, financial leverage negatively impacts firm value, while both firm size and liquidity play crucial roles in enhancing enterprise value.
The analysis demonstrates that the variable 32 shows a significant positive impact when assessed through both FEM and GMM methods In contrast, firm growth negatively affects firm value according to fixed effects model estimation, while no significant correlation exists between firm profitability and enterprise value.
Hypothesis testing
The regression model analysis indicates that all alternative hypotheses from H1.1 to H1.6 can be both accepted and rejected, as each selected factor influences firm value significantly or insignificantly, with the exception of firm size, which demonstrates a consistent impact.
When all industries are taken into consideration, capital structure has an insignificant effect on firm value and the result is consistent with the work of Singh
Research indicates that financial leverage positively influences firm value in the food and beverage industry, aligning with findings from Cheng & Tzeng (2011), Gill & Obradovich (2012), Rizqia & Sumiati (2013), and Hasbi (2015) This is further supported by Singh & Bansal (2016) and Aggarwal & Padhan (2017), who also utilized enterprise value as a key indicator of firm value Conversely, a significant negative relationship between capital structure and firm value is observed in the construction and real estate sectors, corroborating the studies by Aggarwal & Padhan (2017), Vo & Ellis (2017), and particularly Dang et al (2019).
(2019) employing enterprise value as one of firm value indexes The alternative hypothesis H1.1 is accepted
The positive and significant influence of the size of the firm on firm value in all results is consistent with a majority of previous empirical studies including Gill
& Obradovich (2012), Rizqia & Sumiati (2013), Aggarwal & Padhan (2017), Dang et al (2019) and Al-Sleha (2020) The alternative hypothesis H.1.2 is accepted
Firm profitability significantly influences various industries, particularly the food and beverage sector, aligning with findings from Gill & Obradovich (2012), Rizqia & Sumiati (2013), Hasbi (2015), and Dang et al (2019), thereby supporting the acceptance of alternative hypothesis H1.3 Conversely, the relationship between Return on Assets (ROA) and firm value in the construction and real estate industry remains insignificant, corroborating the research of Singh & Bansal (2016) and Dang et al (2019), leading to the rejection of alternative hypothesis H1.3.
Firm growth does not significantly impact firm value across various industries, aligning with the findings of Cuong & Canh (2012), Aggarwal & Padhan (2017), and Dang et al (2019), leading to the rejection of the alternative hypothesis H1.4 Additionally, firm growth is found to have a negatively insignificant effect in the food and beverage, construction, and real estate sectors, which supports Aggarwal & Padhan (2017) but contradicts their own findings when using a different firm value indicator, as well as the evidence presented by Cheng et al.
(2010) – the alternative hypothesis H1.4 is accepted
The study reveals that firm tangibility has an insignificant overall influence across all industries, leading to the rejection of the alternative hypothesis H1.5 However, a positive and significant relationship between firm tangibility and firm value is observed in the food and beverage and construction sectors, while a negative and significant correlation is found in the real estate industry.
34 estate industry They can be all found the work of Aggarwal & Padhan (2017), partly in the study of Singh & Bansal (2016) on insignificant results and Al-Sleha
(2020) on positive results – the alternative hypothesis H1.5 is accepted
Firm liquidity is proved to be statistically insignificant combining all industries together as well as in construction industry – the alternative hypothesis
The current ratio has a positive and significant impact on firm value in the food and beverage industry, while it shows a negative and significant effect in the real estate sector These findings align with the empirical evidence presented by Aggarwal & Padhan (2017), leading to the acceptance of the alternative hypothesis H1.6.
Analysis and discussion of results
The overall findings align with previous studies in Vietnam and similar international research; however, when analyzed at the industrial level, discrepancies emerge Specifically, the insignificant impact of capital structure on firm value across all Vietnamese industries contradicts earlier empirical evidence, such as the studies conducted by Vo & Ellis (2017) and Dang et al., which reported significant relationships within the same context.
Research by Cheng et al (2010) and Cheng & Tzeng (2011, 2014) highlights the positive and significant impact of financial leverage on firm value within the Vietnamese food and beverage sector This finding aligns with similar studies conducted in the manufacturing industries of the U.S (Gill & Obradovich, 2012) and Indonesia (Rizqia), indicating a consistent trend across different regions.
& Sumiati, 2013), or FMCG (Singh & Bansal, 2016) and hotel industry (Aggarwal
& Padhan, 2017) in India However, the significant influences of debt ratio on the
35 value of the firm are opposite to the findings of Vietnamese construction and real estate industry
Variations in the choice of variables and estimation methods, along with the diverse characteristics of numerous industries, may contribute to the insignificant impact of factors such as capital structure, firm growth, tangibility, and liquidity on firm value This explains the less significant empirical results when analyzing all industries collectively, compared to more pronounced outcomes when examining specific industries, despite differing impacts across various sectors and countries Additionally, the differing economic conditions among nations—where countries like China and the U.S are seen as economic giants, while others like India and Vietnam are emerging markets—further elucidate the discrepancies in how capital structure and other factors affect firm value Furthermore, enterprise value, which encompasses both market and book value, can be influenced by market efficiency and investor behavior, leading to unpredictable stock price movements and inconsistent results with existing theoretical and empirical studies Ultimately, the regression model estimation results can be interpreted through established theoretical frameworks and the unique business characteristics of each industry.
There’s an insignificant impact of capital structure on firm value considering all industries as a whole, but it is noted that the work of Modigliani & Miller (1958)
The irrelevancy theory, as proposed by M&M, is often criticized for its unrealistic assumptions in real-world scenarios, where factors like taxes, transaction costs, financial distress costs, agency costs, and information asymmetry are prevalent Consequently, an increase in gearing levels results in a proportional rise in the cost of equity, while the overall cost of capital and firm value remain unchanged.
In Chapter 2, subsequent studies systematically dismantled the initial assumptions of capital structure theory, revealing how various factors influence the cost of debt and equity in response to changes in capital structure These findings indicate that such elements significantly affect a firm's value, challenging the relevance of Modigliani and Miller's 1958 theory, which inadequately explains the weak relationship between firm leverage and value.
The food and beverage industry demonstrates a strong positive relationship between capital structure and firm value, aligning with the principles established by Modigliani & Miller (1963) and the trade-off theory proposed by Kraus & Litzenberger (1973).
Research by Myers (1977), Bradley et al (1984), and others highlights that an increase in debt financing can serve as a positive signal for a firm's future, enhancing tax benefits and lowering debt costs However, if financial distress and agency costs outweigh these advantages, the overall cost of capital may decrease, thereby increasing the firm's value Conversely, the significant negative relationship between financial leverage and enterprise value supports the pecking-order theory proposed by Myers (1984) and Myers & Maljuf (1984), indicating that debt issuance may not always be favorable.
When raising capital, firms must prioritize their capital structure, as previous studies by Cheng et al (2010) and Cuong & Canh (2012) indicate that the relationship between capital structure and firm value can be non-linear, highlighting the existence of an optimal capital structure for maximizing firm value The average debt ratio in the food and beverage industry is 47.73%, which is significantly lower than the 65.54% and 53.28% observed in the construction and real estate sectors, respectively This suggests that listed food and beverage firms may not have achieved their ideal capital structure, while the financial leverage in the construction and real estate industries may have surpassed optimal levels.
The size of a firm significantly enhances its value across various estimation methods, including pooled OLS, fixed and random effects, and GMM This positive relationship is consistent across multiple industries, such as food and beverage, construction, and real estate, reinforcing the financial distress theory proposed by Gordon.
According to agency theory by Jensen & Meckling (1976) and Jensen (1986), larger firms possess advantages that help lower costs, reduce debt expenses, and enhance their overall value However, in the construction and real estate industry, the benefits of firm size do not sufficiently counterbalance the costs of debt, as capital structure continues to exert a negative and significant impact on firm value.
The profitability across various industries, particularly in the food and beverage sector, supports Gordon's financial distress theory (1970), which posits that having a reliable income stream can mitigate financial distress and lower bankruptcy costs Nevertheless, the relationship between firm profitability and financial stability remains complex.
The construction and real estate industry exhibits a minimal impact on enterprise value, largely attributed to substantial debt financing that leads to increased interest expenses and diminished earnings quality Statistical analysis reveals that the average returns on total assets for listed construction and real estate firms are approximately 3.5% and 2.83%, respectively, significantly lower than the overall industry average of 6.59% and the 9.17% average for listed food and beverage companies.
Research indicates that, when analyzing various industries collectively, firm growth negatively and insignificantly impacts firm value in specific sectors such as food and beverage, construction, and real estate This phenomenon may be attributed to agency theory as proposed by Jensen and Meckling.
Conflicts between managers and owners, as well as issues with debtors, can lead to ineffective decision-making in corporate finance, resulting in increased costs and reduced firm value (Myers, 1984) In the construction and real estate sectors, agency costs may outweigh the benefits of debt expenses, negatively impacting enterprise value Conversely, the food and beverage industry experiences a positive effect from capital structure on enterprise value.
The tangible assets of firms significantly enhance their value in both the food and beverage and construction industries This supports the agency theory proposed by Jensen & Meckling (1976) and Jensen (1986), highlighting that substantial fixed assets can offer numerous benefits, especially in terms of debt financing, by mitigating asymmetric information.
Limitations of estimation
Despite the numerous advantages of GMM estimation highlighted in the previous chapter, it faces challenges related to weak instruments, as discussed in the research by Kennedy (2008) and Verbeek.
The Sargan test is utilized to assess the correlation between over-identifying instruments and residuals The J-statistics probability values for various industries, including food and beverage, construction, and real estate, are 0.182590, 0.129120, 0.352314, and 0.413236, respectively All these values exceed the 5% significance level, indicating that the regression models employing the GMM method are not misspecified.
The Pooled OLS method, similar to other multiple linear regression techniques, relies on specific assumptions for optimal regression model estimations, including collinearity, auto-correlation, normality, and heteroscedasticity The correlation coefficients among independent variables range from -0.8 to 0.8, indicating that multi-collinearity is not a significant concern for the regression models utilizing data from selected and all industries However, the Durbin-Watson ratios for the pooled OLS method, as well as fixed and random effects, reveal values that are not close to 2, suggesting the presence of serial correlation issues Furthermore, the residuals from the pooled OLS method violate assumptions, as evidenced by the probability values from the Jarque-Bera tests.
The analysis reveals that the error term across various industries, including food and beverage, construction, and real estate, is not normally distributed, with significant p-values at a 5% confidence level Notably, the real estate industry's period test shows a p-value of 0.0811, while all other likelihood ratio probability values in both cross-section and period tests are 0.0000, indicating heteroscedasticity in most error variances To address this issue, a robust estimation method will be utilized, adjusting standard errors to accommodate the presence of heteroscedastic residuals, as outlined in the following tables (Brooks, 2014).
Table 4.8: Robust estimation results – All industries
Source: Outcomes of data analysis on Eviews
Table 4.9: Robust estimation results – Food and Beverage industry
Source: Outcomes of data analysis on Eviews
Table 4.10: Robust estimation results – Construction industry
Source: Outcomes of data analysis on Eviews
Table 4.11: Robust estimation results – Real Estate industry
Source: Outcomes of data analysis on Eviews
Table 4.8 reveals that robust standard errors amplify the negative effect of firm growth on firm value in the fixed effects model, shifting from insignificant to significant across all industries when compared to table 4.3 Despite the Hausman test supporting the fixed effects model, the overall influence of independent variables on the dependent variable significantly diminishes Table 4.9 indicates that in the food and beverage industry, no significant relationships are identified using both fixed effects and random effects models, with only firm size showing a significant impact in the pooled OLS analysis In the construction industry, as shown in table 4.10, the fixed effects model maintains an insignificant relationship between capital structure and firm performance.
The analysis reveals that firm size significantly influences enterprise value, particularly in the real estate and food and beverage industries However, other factors exhibit no substantial correlation with enterprise value Notably, the GMM estimation method consistently yields more significant results than alternative methods, proving to be an unbiased estimator Therefore, GMM is deemed the most appropriate approach for examining the impact of capital structure and additional factors on firm value.
Summary, Conclusions and Recommendations
Summary and conclusions
This research analyzes the influence of capital structure on firm value, specifically focusing on Vietnamese listed companies on HOSE and HNX from 2012 to 2019 It incorporates control variables such as firm size, profitability, growth, tangibility, and liquidity, utilizing pooled OLS, fixed effects, random effects models, and the GMM method Additionally, the study categorizes firms into three groups to explore industry-specific differences The application of the GMM method and the examination of multiple industries is novel in the context of Vietnam and is seldom found in global empirical studies regarding the relationship between capital structure and firm value.
The findings indicate that after confirming the Fixed Effects Model (FEM) as the most suitable among the chosen Ordinary Least Squares (OLS) techniques, the results, when combined with Generalized Method of Moments (GMM) estimation, reveal both significant and insignificant effects that vary across industries When analyzing all non-financial listed firms collectively, the impact of capital structure and other control variables is found to be less significant compared to the results observed in specific sectors such as food and beverage, construction, and real estate.
The impact of capital structure on firm value varies across industries; it is insignificant for all listed firms but positively significant in the food and beverage sector, while negatively significant in construction and real estate Firm size consistently shows a positive and significant influence on firm value across all industries and specific sectors Additionally, firm profitability positively affects firm value for all industries and within the food and beverage sector, though its impact is insignificant in construction and real estate The relationship between firm growth and value is generally insignificant across all firms but is negative and significant in selected industries Firm tangibility's connection to firm value is insignificant overall, yet it is positive and significant in the food and beverage and construction industries, while negatively significant in real estate Lastly, firm liquidity has an insignificant effect on firm value across all industries and construction, but it is positively significant in the food and beverage sector and negatively significant in real estate.
The research reveals that the overall findings align closely with previous empirical evidence from Vietnam, the U.S., and various Asian countries; however, notable differences emerge when the research scope is more narrowly defined.
For a more precise comparison, it is essential to analyze data at the industrial level rather than the national level, as economic conditions vary significantly between countries Additionally, the divergent findings can be attributed to earlier theoretical studies and the unique characteristics of businesses within different industries, which have often been neglected in past empirical research both in Vietnam and globally.
Due to the limitations of Ordinary Least Squares (OLS) methods, the Generalized Method of Moments (GMM) has emerged as the most effective estimation technique for analyzing the relationship between firm value and its determinants This research offers valuable insights into capital structure and firm value, providing essential information that can aid financial managers, investors, policy-makers, lenders, and scholars in their decision-making processes and future research endeavors.
Recommendations
To maximize firm value and enhance shareholder wealth, financial managers should prioritize factors such as capital structure, firm size, profitability, growth, tangibility, and liquidity However, this research indicates that the impact of these factors on firm value varies across different industries, necessitating tailored strategies and decisions that align with specific industry dynamics.
For instance, an increase in financial leverage can be a good decision to improve the value of the firm in food and beverage industry, but it could create an
Listed construction and real estate firms are currently facing adverse effects due to excessive borrowing While larger firms often benefit from the correlation between total assets and firm value, growth in total assets does not necessarily enhance value, particularly in the F&B, construction, and real estate sectors Achieving a high profit ratio is essential, but it must be accompanied by quality earnings to truly enhance firm value Additionally, the balance of fixed assets in total assets presents a trade-off, offering long-term earnings potential and risk mitigation while also introducing higher fixed costs and business risks Although maintaining liquidity is crucial in the short term, an excessively high current ratio can lead to inefficiencies, as too many illiquid assets like inventories or surplus cash can hinder sustainable productivity and ultimately decrease firm value.
Previous empirical studies have highlighted significant relationships between capital structure and various factors across different sectors, including manufacturing, services, FMCG, hotels, and mining For instance, a business plan aimed at increasing financial leverage, firm size, and profitability can enhance the firm value in manufacturing, akin to trends observed in the food and beverage industry However, it is crucial to recognize that the research contexts differ due to variations in countries and time periods, which may affect the applicability of the findings Consequently, these results should be carefully examined before being used to guide financial managers.
Management should utilize industry average figures as benchmarks for adjusting capital structure and other significant factors impacting firm value, such as profitability and current ratio However, caution and flexibility are essential, as production capacity varies across businesses, and overly ambitious financial strategies may harm future performance For instance, while the food and beverage industry's average debt ratio is 47.73%, firms must assess their earnings capacity to meet financial obligations with increased leverage Conversely, the construction and real estate industries, with average debt ratios of 65.54% and 53.28% respectively, may have exceeded their optimal capital structures, but increased financial leverage could still enhance future performance through necessary business expansion.
Investors should conduct thorough analyses to develop effective investment strategies and make informed decisions Fundamental analysis is crucial for stock selection, helping to identify whether companies are undervalued or overvalued, and it includes a detailed examination of financial statements By assessing the impact of various factors, such as capital structure and other control elements on firm value, investors can enhance their evaluation of the strategies and decisions made by financial managers over the years to boost firm value.
An announcement regarding additional borrowing in the coming years may lead to a decline in the value of publicly listed construction and real estate firms, which are already burdened with significant debt Consequently, an increase in returns on total assets may not be viewed positively if the underlying earnings generation, such as EBIT, remains low due to high interest expenses These financial outcomes can impact the expected dividends for investors and shareholders, while fluctuations in share prices based on financial performance can also affect the potential for capital gains for investors.
Despite the completion of financial examinations, there is no assurance that all financial statements are free from manipulation Investors must remain cautious, as empirical results may lack reliability, necessitating a thorough review of financial reports, particularly when there are unexplained changes in accounting policies or financial outcomes Additionally, factors such as market efficiency and the rationale behind investment decisions can lead to unusual fluctuations in share prices, causing discrepancies between market capitalization and changes in capital structure Consequently, investors face challenges in achieving accurate results for their strategies and decisions.
Policy-makers should enhance the clarity and quality of information disclosure, as this study and others indicate that most data used for empirical analysis is derived from financial statements.
Firms often manipulate financial statements to achieve various management goals, such as inflating revenues and minimizing expenses to impress investors and enhance profits Conversely, they may reverse these tactics for tax avoidance purposes Such creative accounting and earnings management significantly impact the accuracy of empirical findings, particularly concerning capital structure and its influence on firm value Additionally, companies may engage in market manipulation to artificially boost share prices, despite experiencing prolonged periods of poor financial performance accompanied by unusual gains.
Regulators must critically examine and establish suitable regulations to enhance the quality of financial and non-financial information, as well as the integrity of financial markets Vietnam's accounting system is in the early stages of adopting international accounting standards, which presents an opportunity for Vietnamese firms and international investors to benefit from fair value and increased information transparency amid globalization Furthermore, it is essential to strengthen the legal framework for supervision and penalties for individuals and institutions to mitigate share price manipulation issues.
While the firm's value may not be the primary concern for creditors, it is important to recognize that the control variables in this study significantly influence capital structure Therefore, creditors should consider these factors from a different perspective, examining how they impact capital decisions.
Creditors can assess a firm's capacity to meet its financial obligations based on significant results, influencing their lending decisions However, it is crucial to approach empirical findings with caution, as similar results may arise from differing economic conditions and business characteristics Therefore, conducting comparative research across countries and industries is essential for lenders to make informed decisions.
Last but not least, it is suggested for scholars to continue to have further investigation in regards to the relationship between capital structure and firm value
Future research should expand to include non-listed firms from various industries and countries, taking into account the negative impacts of global epidemics, particularly when analyzing data from the latter quarters of 2020 While many independent and dependent variables have been thoroughly examined, there are still several factors that may have been overlooked and warrant further investigation Additionally, the interpretation of empirical findings needs to be revisited, as there is a lack of studies addressing the relationship between capital structure and firm value, making it challenging to reconcile results that conflict with prior research.
Aggarwal, D & Padhan, P C (2017) Impact of Capital Structure on Firm Value:
Theoretical Economics Letters, Volume 7, pp 982-1000
Al-Sleha, Z A F (2020) Impact of Financial Leverage, Size and Assets Structure on Firm International Business Research, 13(1), pp 109-120
Altman, E I (1968) Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy The Journal of Finance, 23(4), pp 589-609
Altman, E I (1984) A Further Empirical Investigation of the Bankruptcy Cost Question The Journal of Finance, 39(4), pp 1067-1088
Arnold, G (2013) Corporate Financial Management 5th ed London: Pearson Education Limited
Baker, M & Wurgler, J (2002) Market Timing and Capital Structure The Journal of Finance, 57(1), pp 1-32
Bradley, M., Jarrell, G A & Kim, E H (1984) On the Existence of an Optimal Capital Structure: Theory and Evidence The Journal of Finance, 39(3), pp 857-
Brooks, C (2014) Introductory Econometrics for Finance 3rd ed New York: Cambridge University Press
Cheng, M.-C & Tzeng, Z.-C (2011) The Effect of Leverage on Firm Value and How The Firm Financial Quality Influence on This Effect World Journal of Management, 3(2), pp 30-53
Cheng, M.-C & Tzeng, Z.-C (2014) Effect of Leverage on Firm Market Value and How Contextual Variables Influence this Relationship Review of Pacific Basin
Financial Markets and Policies, 17(1), pp 1-63
Cheng, Y.-S., Liu, Y.-P & Chien, C.-Y (2010) Capital structure and firm value in China: A panel threshold regression analysis African Journal of Business Management, 4(12), pp 2500-2507
Cuong, N T & Canh, N T (2012) The Effect of Capital Structure on Firm Value for Vietnam’s Seafood Processing Enterprises International Research Journal of Finance and Economics , Issue 89, pp 222-223
Dang, H N., Vu, V T T., Ngo, X T & Hoang, H T V (2019) Study the Impact of Growth, Firm Size, Capital Structure, and Profitability on Enterprise Value:
Evidence of Enterprises in Vietnam Journal of Corporate Accounting & Finance, Volume 30, pp 146-162
DeAngelo, H & Masulis, R W (1980) Optimal capital structure under corporate and personal taxation Journal of Financial Economics, 8(1), pp 3-29
Fischer, E O., Heinkel, R & Zechner, J (1989) Dynamic Capital Structure Choice: Theory and Tests The Journal of Finance, 44(1), pp 19-40
FPT Securities (2020) BÁO CÁO CẬP NHẬT NGÀNH XÂY DỰNG, Ha Noi: FPT Securities
Gill, A & Obradovich, J D (2012) The Impact of Corporate Governance and Financial Leverage on the Value of American Firms International Research Journal of Finance and Economics, Issue 91, pp 1-14
Gordon, M J (1970) Towards a Theory of Financial Distress The Journal of Finance, 26(2), pp 347-356
Graham, J R (2000) How Big Are the Tax Benefits of Debt? The Journal of Finance, 55(5), pp 1901-1941
GSO of Vietnam (2020) Socio-economic situation in the second quarter and the first 6 beginning months of 2020 [Online]
Available at: https://www.gso.gov.vn/default_en.aspx?tabidb2&idmid=&ItemID663 [Accessed 07 July 2020]
Hasbi, H (2015) Islamic Microfinance Insitution: The Capital Structure, Growth, Performance and Value of Firm in Indonesia The Procedia - Social and Behavioral
Hayakawa, K (2009) First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models?: A Simulation Study Economics Bulletin, 29(3), pp 2008-2017
Jensen, M C (1986) Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers The American Economic Review, 76(2), pp 323-329
Jensen, M C & Meckling, W H., 1976 Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure Journal of Financial Economics, 3(4), pp 305-360
Kennedy, P (2008) A Guide To Econometrics 6th ed Malden: Blackwell Publishing Ltd
Khoa, D (2020) Vietnam poised for highest GDP growth in Southeast Asia
Available at: https://e.vnexpress.net/news/business/data-speaks/vietnam-poised- for-highest-gdp-growth-in-southeast-asia-4118031.html
Kraus, A & Litzenberger, R H (1973) A State-Preference Model of Optimal Financial Leverage The Journal of Finance, 28(4), pp 911-922
Lee, C (2020) Vietnam GDP increased by 1.81% in the first six months of 2020 [Online]
Available at: https://vietnamtimes.org.vn/vietnam-gdp-increased-by-181-in-the- first-six-months-of-2020-21792.html
Ly, T (2020) EVFTA expected to give a lift to real estate sector [Online] Available at: https://vietnamnews.vn/economy/business-beat/749190/evfta- expected-to-give-a-lift-to-real-estate-sector.html
Miller, M H (1977) Debt and Taxes The Journal of Finance, 32(2), pp 261-275
Modigliani, F & Miller, M H (1958) The Cost of Capital, Corporation Finance and the Theory of Investment The American Economic Review, 48(3), pp 261-297
Modigliani, F & Miller, M H (1963) Corporate Income Taxes and the Cost of Capital: A Correction The American Economic Review, 53(3), pp 433-443
Myers, S C (1977) Determinants of corporate borrowing Journal of Financial Economics, 5(2), pp 147-175
Myers, S C (1984) The Capital Structure Puzzle The Journal of Finance, 34(3), pp 575-592
Myers, S C & Maljuf, N S (1984) Corporate financing and investment decisions when firms have information that investors do not have Journal of Financial Economics , 13(2), pp 187-221
Ngoc, T (2020) Vietnam construction sector forecast to grow over 7% over next decade: Fitch [Online]
Available at: http://hanoitimes.vn/vietnam-building-construction-sector-forecast- to-grow-over-7-over-next-decade-fitch-312049.html
Nguyen, J (2020) Despite Economic Slowdown, Vietnam Banks on Domestic
Tourism and Real Estate [Online]
Available at: https://www.vietnam-briefing.com/news/despite-economic- slowdown-vietnam-banks-domestic-tourism-real- estate.html/?hilite=%27real%27%2C%27estate%27
Nguyen, T (2020) Timing for EVFTA ratification could not be better for Vietnam and EU: HSBC [Online]
Available at: http://hanoitimes.vn/timing-for-evfta-ratification-could-not-be- better-for-vietnam-and-eu-hsbc-313017.html
Cuối năm 2020, thị trường bất động sản đang đứng trước ngã rẽ quan trọng, với nhiều câu hỏi về khả năng phục hồi hay rơi vào tình trạng suy thoái Những yếu tố kinh tế và chính sách ảnh hưởng đến sự phát triển của ngành này đang được xem xét kỹ lưỡng Các chuyên gia nhận định rằng, mặc dù có những thách thức lớn, nhưng vẫn tồn tại cơ hội để thị trường phục hồi nếu có sự hỗ trợ hợp lý từ chính phủ và các nhà đầu tư.
Nieuwsbericht (2019) Vietnam Food & Beverage industry [Online]
Available at: https://www.agroberichtenbuitenland.nl/actueel/nieuws/2019/08/01/vietnam-food- -beverage-industry
Rizqia, D A & Sumiati, S A (2013) Effect of Managerial Ownership, Financial Leverage, Profitability, Firm Size, and Investment Opportunity on Dividend Policy and Firm Value Research Journal of Finance and Accounting , 4(11), pp 120-130
Ross, S A (1977) The Determination of Financial Structure: The Incentive- Signalling Approach The Bell Journal of Economics, 8(1), pp 23-40
Scott, J H (1977) Bankruptcy, Secured Debt, and Optimal Capital Structure The
Singh, A K & Bansal, P (2016) Impact of financial leverage on firm's performance and valuation: a panel data analysis Indian Journal of Accounting,
Thong, V (2020) Food industry considers survival plans as Covid-19 spreads
Available at: https://e.vnexpress.net/news/business/industries/food-industry- considers-survival-plans-as-covid-19-spreads-4138452.html
VCCI (2017) EVFTA VÀ NGÀNH SẢN XUẤT THỰC PHẨM, ÐỒ UỐNG VIỆT NAM, Ha Noi: VCCI
Verbeek, M (2017) A Guide to Modern Econometrics 5th ed New Jersey: John Wiley & Sons, Inc
Vo, X V & Ellis, C (2017) An empirical investigation of capital structure and firm value in Vietnam Finance Research Letters, Volume 22, pp 90-94
Wooldridge, J M (2013) Introductory Econometrics 6th ed Boston: Cengage Learning
Appendix A: Descriptive Statistics – Food and Beverage industry
Variables ROA GROW TANG CR
Source: Outcomes of data analysis on Eviews
Appendix B: Descriptive Statistics – Construction industry
Variables ROA GROW TANG CR
Source: Outcomes of data analysis on Eviews
Appendix C: Descriptive Statistics – Real Estate industry
Variables ROA GROW TANG CR
Source: Outcomes of data analysis on Eviews