Impacts of capital structure on the performance of listed companies in vietnam

The study titled “Impacts of Capital Structure on the Performance of Listed Companies in Vietnam” explores how capital structure, comprising debt and equity, influences firm performance

INTRODUCTION

Background and Rationale

The capital structure of a company is a complex and often debated topic globally, primarily due to its significant impact on profitability and overall performance Also referred to as financial leverage, capital structure encompasses various elements that influence a business's financial health and operational effectiveness (Watson & Head, 2007).

The debt-to-equity ratio reflects the balance between a company's debt and equity used to finance asset creation, significantly impacting managerial behavior and financial decision-making By analyzing financial ratios like the debt-to-equity ratio, also referred to as the long-term loan-to-equity ratio or the long-term loan-to-total capital employed ratio, one can assess an organization's capital structure Additionally, this ratio can encompass both short-term and long-term loans, which is particularly relevant for companies managing extended overdrafts.

The capital structure of a company is vital for its financial stability and long-term growth, representing the debt-equity mix used for funding operations and investments An optimized capital structure enables businesses to leverage the tax benefits of debt while mitigating the risks associated with excessive borrowing In emerging economies like Vietnam, where capital is limited, an appropriate capital structure is crucial for enhancing liquidity, reducing costs, and boosting profitability Research on capital structure is essential for organizations to comprehend how financing decisions impact performance and to identify the optimal debt-equity balance that maximizes shareholder value and financial flexibility.

Examining the components of capital structure and their impact on profitability, market valuation, and risk exposure enables companies to make strategic financing decisions that support growth and competitiveness This research is essential not only for businesses but also for investors, banks, and policymakers, as it aids in the development of sustainable financing policies By understanding capital structure, investors can evaluate risk-return profiles, while banks can tailor loans and investments to support businesses effectively Additionally, capital structure analysis enhances business performance and sustainability, particularly for Vietnamese companies navigating market volatility and economic shifts, ultimately fostering resilience.

Vietnamese companies can significantly benefit from this research on capital structure optimization, which analyzes the balance between debt and equity funding to enhance firm performance Understanding the ideal finance mix is crucial for maximizing profits and mitigating debt risks in emerging markets like Vietnam The study reveals the impact of inflation, GDP, and interest rates on firm performance, enabling debt-dependent companies to grasp how external economic conditions influence their finances and anticipate market changes This knowledge enhances the competitiveness of Vietnamese SMEs by optimizing loan management and business size, fostering domestic and international success Additionally, the research supports sustainable growth in capital-intensive industries such as manufacturing and real estate, emphasizing the importance of rigorous financial planning Ultimately, these insights empower Vietnamese enterprises to refine their financial strategies, navigate economic challenges, and thrive in a competitive landscape.

In 2016, Thanh identified a significant relationship between capital structure and firm performance, though results may vary based on economic context, financial recording methods, and research methodologies The socio-political and financial-banking frameworks of Vietnam influence its stock market, making it essential to explore how capital structure affects firm performance to enhance capital structure theory Vietnamese studies provide valuable context-specific insights that global research may overlook, particularly as firms navigate unique challenges and opportunities during Vietnam's transition to a market-oriented economy Understanding the role of capital structure in this environment is crucial for developing effective market strategies Research by Nguyen and Ramachandran (2006) and Pham and Nguyen (2013) highlights how Vietnamese companies adapt their capital structures in response to economic growth, regulatory changes, and market dynamics, ensuring that financial solutions are both theoretically sound and practically applicable in Vietnam.

Research on capital structure reveals its significant impact on firm performance, both globally and within Vietnam Vietnamese studies adapt international theories to enhance their relevance and reliability, while also contributing diverse perspectives to the global discourse This interplay enriches the understanding of capital structure's role in business success.

Research Objectives

The thesis addressed these research goals.:

- To make an in-depth literature review on capital structure

- To analyze the impact of capital structure factors on the performance of listed companies in Vietnam

- To make implications for management to enhance the performance of listed companies in Vietnam

Research Questions

Accordingly, the thesis is to answer the following research questions:

- What are theories and concepts on capital structure applied in the study?

- How do capital structure factors affect the performance of listed companies in Vietnam?

- Which implications for management should be made to enhance the performance of listed companies in Vietnam?

Research Structure

This study aims to explore how capital structure influences the performance of companies listed on the Vietnamese stock market from 2012 to 2021, providing valuable insights for identifying an optimal capital structure that enhances firm performance.

Chapter 2: Literature review and research model

LITERATURE REVIEW AND RESEARCH MODEL

Theories on Capital Structure and Firm Performance

Capital structure refers to the mix of debt and equity that companies utilize to finance their long-term operations, as defined by Khan and Jain (1997) and Demirguc-Kunt et al (2019) It is assessed by subtracting short-term liabilities from total assets, with capital serving as a source of long-term financing According to Watson and Head (2007), a company's capital structure illustrates the ratio of its liabilities relative to its equity Various financial metrics, such as the debt-to-equity ratio and the long-term loan-to-equity ratio, can be employed to evaluate capital structure, which ultimately reflects the performance distribution between shareholders and creditors Additionally, the assessment may involve the book or market values of assets, liabilities, and equity The distinction between long-term and short-term loans significantly influences a firm's total debt, with liabilities playing a crucial role in this calculation Ross et al (2013) characterize capital structure as the management of debt and equity, emphasizing the importance of determining the appropriate securities to issue before seeking external financing The total debt/equity ratio, which incorporates both short-term and long-term loans, is commonly utilized in capital structure analysis.

To achieve an optimal capital structure, corporations must strategically coordinate their funding sources, as highlighted by Watson and Head (2007) and Davidson (2018) This ideal structure allows firms to minimize their cost of capital and maximize asset value for owners Key to this process is identifying the optimal level of existing debt while considering various market factors such as taxation, financial constraints, agency costs, and asymmetric information that influence capital structure decisions.

The debt-to-total assets ratio is a vital metric for assessing an organization's capital structure, indicating the percentage of assets financed through borrowed capital By calculating this ratio—either by summing all debts or dividing total loans by their maturities—organizations can gain insights into their reliance on borrowed funds This ratio can be derived from three types of debt: total debt, long-term loans, and short-term loans A lower debt-to-total assets ratio signifies financial independence from creditors, reinforcing the notion that a reduced reliance on debt correlates with greater financial stability.

To better understand how companies finance their internal operations, the debt-to-equity ratio serves as a valuable tool by comparing the two primary types of capital: debt and equity This ratio provides insight into the company's capital structure, indicating the proportion of funding sourced from liabilities, which may include total loans, long-term loans, or short-term loans Additionally, the debt-to-assets ratio offers a similar representation, allowing for various analyses of a company's financial health.

Corporate performance can be evaluated through various financial metrics, including Tobin’s Q, revenue growth, profitability, earnings per share (EPS), and the market value to book value ratio, as noted by Venkatraman and Ramanujam (1986) Additional measures such as brand recognition, market share, product quality, marketing efficiency, and production value also play a significant role in assessing a company's performance Scholars like Phillips and Sipahioglu (2004), Thanh (2016), Mihail and Micu (2021), and Ali et al (2022) emphasize return on assets (ROA) as a crucial indicator of corporate success.

In 2023, Nguyen emphasized the significance of return on equity (ROE) as a key metric for evaluating both individual and corporate success Previous studies by Jiraporn and Liu (2008) and Vo (2017) explored the impact of stock market prices on Tobin’s Q indicator This research aims to analyze company performance through the lenses of return on assets (ROA), return on equity (ROE), and Tobin’s Q.

Divide net return after taxes by total assets to calculate ROA:

Return on Assets (ROA) is a crucial financial metric that evaluates a company's profit generated per dollar of assets after taxes, reflecting its overall profitability and operational efficiency Unlike Return on Equity, ROA encompasses all assets, including those financed by debt and investors, providing a comprehensive view of how effectively a company utilizes its assets to generate income This indicator allows stakeholders to assess the company's ability to manage its resources efficiently, highlighting its financial performance independent of its capital structure (Phillips & Sipahioglu, 2004; Wong et al.).

(2021), a higher ROA means the corporation can make more from its assets Thus, it indicates profitability and productivity

Divide the net return after taxes by the company’s total equity to calculate ROE:

Return on equity (ROE) is a vital financial metric that indicates how effectively a company generates profit from each dollar of stock after taxes It reflects the operational health of a business, assessing how well it manages and utilizes invested assets to deliver shareholder returns A high ROE signifies strong corporate governance and profitability, while a decline below prevailing interest rates may deter shareholder investment As noted by Ebaid (2009) and Yang et al (2010), ROE serves as a critical indicator for evaluating a company's overall performance and managerial effectiveness.

For the purpose of calculating Tobin’s Q, the formula is the capitalization of common stock, debt, and preferred stock divided by book value of total assets, as follows:

𝑇𝑜𝑏𝑖𝑛 ′ 𝑠 𝑄 = Field Value of the Business

Book Value of the Business

Determining the market value of debt can be challenging due to the variety of debt types, maturities, and interest rates available to firms Brainard and Tobin (1968) emphasized that common stock capitalization significantly influences corporate performance, allowing for the substitution of market values of debt and preferred stock with book value or total liabilities Tobin's Q is calculated by dividing a firm's market value by its book value, reflecting that market capitalization is influenced by both current and future earnings A higher Tobin's Q indicates greater business potential and growth opportunities, with values above one suggesting returns on equity exceed expectations, while values below one indicate a shortfall in return relative to market demands, as noted by Jiraporn and Liu (2008).

Theories on Impact/Effect of Capital Structure on Firms’ Performance

The concept of agency costs, introduced by Berle and Means in 1932 and further developed by Jensen and Meckling in 1976, highlights conflicts of interest among shareholders, managers, and creditors that may lead managers to prioritize personal gains over corporate performance To mitigate these conflicts, Harris and Raviv (1991) proposed using debt as a tool to monitor and incentivize board performance, recognizing the correlation between debt ratios and financial distress As a company's financial health declines, the risk of bankruptcy increases, motivating management to enhance their performance to protect their jobs and reputations Ultimately, agency cost theory supports the strategic use of debt to align managerial interests with those of shareholders, thereby improving overall business performance and reducing agency costs.

Durand (1952) introduced the concept of capital structure, highlighting that debt is typically "cheaper" than equity, allowing corporations with higher debt levels to reduce their average cost of capital and enhance performance As the debt-to-equity ratio increases, the return on equity is expected to improve due to the lower cost of debt However, Durand also noted that a higher debt-to-total capital ratio may lead to increased debt costs and heightened bankruptcy risk Therefore, the impact of capital structure on a company's performance depends on finding the right balance between the advantages of debt and equity Companies should aim for an optimal capital structure that minimizes the average cost of capital while maximizing performance.

This research highlights that it does not reach definitive conclusions about the ideal capital structure for businesses, as the optimal configuration varies significantly based on numerous factors unique to each company.

2.2.3 The Theory of Modigliani and Miller

In 1958, Modigliani and Miller introduced the idea that shareholders of highly indebted firms tend to invest in companies with lower debt to mitigate risk, as they perceive higher debt levels as more risky Their key finding was that a company's overall performance is not influenced by its debt ratio However, a subsequent study in 1963 indicated that capital structure and firm performance are influenced by capital costs Additionally, the interest expenses on business debt are tax-deductible, providing tax shields that allow corporations to reduce their tax liabilities, thereby enhancing performance Modigliani and Miller's pioneering work established the foundation for capital structure theories.

The capital structure trade-off, introduced by Kraus and Litzenberger in 1973 and further elaborated by Myers and Majluf in 1984, posits that an optimal capital structure enhances business performance while mitigating financial stress This hypothesis suggests that companies can leverage borrowing until the tax advantages surpass the associated financial risks Typically, firms experience minimal financial distress at standard debt levels, benefiting from borrowing However, as debt levels increase, so does the risk of bankruptcy, potentially harming overall performance The trade-off theory elucidates the variations in capital structures among enterprises, asserting that firms strive to identify the ideal financial framework that aligns with their performance objectives and risk appetite.

According to the pecking order theory, which was first forward by Myers and Majluf in

Since 1984, businesses have favored internal financing over external sources, prioritizing retained earnings for investments and resorting to external finance only when necessary Companies typically follow a hierarchy of financing, starting with borrowing, then issuing bonds, and finally offering shares While the pecking order hypothesis does not dismiss earlier theories regarding tax shields and debt limits, it highlights the significance of the sequence in which companies utilize various financing sources Generally, successful companies maintain lower debt levels, not due to a specific ideal debt ratio but because they can rely on their own funds Conversely, companies with poor performance often incur high debt levels, as they lack sufficient internal funding and must seek external finance to sustain operations Thus, an organization's debt ratio reflects its accumulated need for external cash driven by success and diverse financial requirements.

Research on the Impact of Capital Structure on Firm Performance

Extensive research worldwide has explored the impact of capital structure on company performance, revealing inconsistencies due to variations in sample sizes, business types, and geographic regions This study categorizes the findings into three groups: those indicating a positive effect of capital structure on performance, those suggesting a negative impact, and those concluding that capital structure does not significantly influence a company's success.

Numerous studies have demonstrated that capital structure significantly influences a company's success Research indicates that firms can capitalize on growth opportunities without diluting equity by effectively utilizing debt, leading to increased profitability For instance, Chowdhury and Chowdhury (2010) found that the capital structure of Bangladeshi companies directly impacted their financial success Similarly, Sivathaasan et al (2013) revealed that in Sri Lankan industrial enterprises listed on the Colombian Stock Exchange, capital structure was the sole determinant of improved profitability, with factors like firm size and asset structure showing no effect.

Research indicates that capital structure-related solvency ratios have a significant impact on profitability, as demonstrated in a study of Pakistani chemical industries (2014) Further supporting this, Aggarwal and Padhan (2017) found that organization size, liquidity, and leverage are key predictors of success in Indian hospitality firms Additionally, Nenu et al (2018) identified a strong correlation between leverage, firm size, and share price volatility in Romanian businesses Subsequent studies by Ayuba et al (2019), Khan et al (2021), and Jin and Xu reinforce these findings.

In 2022, research indicated that an improved capital structure through debt can enhance business performance, suggesting that effective management of debt can lead to increased growth and profitability The investigation by Hirdinis (2019) revealed that while a firm's financial structure influences its performance, its size can have a detrimental effect, with surprising findings that profitability had little impact on performance In Malaysia, Ramli et al (2019) identified a mediating relationship between leverage and financial performance, a trend not observed in Indonesia, highlighting the importance of a country's financial environment These findings align with established financial theories, such as the Trade-Off Theory, which emphasizes the need for companies to balance the advantages of debt, like tax benefits, against potential downsides, such as financial distress, to optimize performance.

Numerous studies indicate that financial structures can adversely impact business success, particularly highlighting that high levels of debt can hinder growth and profitability Elevated debt increases financial risk, leading to higher borrowing costs and decreased investment opportunities Research by Masulis (1983) and Singh and Faircloth (2005) demonstrates that significant borrowing levels can deter future investments, ultimately affecting a company's performance and growth potential Additionally, findings from Owolabi and Obida (2012), Liargovas and Skandalis (2008), and Lazaridis and Tryfonidis (2006) reveal that while larger businesses often experience higher profitability, excessive debt ratios can detrimentally influence organizational performance.

Research indicates that financial ratios and capital structure can adversely impact a company's operational performance, while factors such as company size and GDP growth tend to enhance profitability Studies by Dawar (2014), Seetanah et al (2014), and Zeitun and Haq (2015) support the notion that high levels of debt can lead to financial challenges, ultimately diminishing performance Additionally, Dang et al (2019) highlight that long-term loans hinder profit maximization and suggest that excessive reliance on such borrowing restricts a company's potential for future earnings The Pecking Order Theory further posits that businesses prefer using internal funds for financing operations over incurring debt due to the associated high interest rates and costs.

Research indicates that a company's financing structure does not significantly impact its success Debt is not necessarily a crucial factor in determining the success of a business or organization Additionally, capital structure can vary based on the business environment, industry, and various other influences, as demonstrated by Phillips and Sipahioglu.

Research has shown that the capital structure of companies may have minimal impact on their returns A study by Jiraporn and Liu (2008) involving 1,900 publicly traded US firms from 1990 to 2004 revealed that financial structure does not significantly influence performance Similarly, Ebaid (2009) found comparable results in his analysis of Egyptian firms, suggesting that financial structure is not the primary determinant of corporate performance Modigliani and Miller’s Irrelevance Theory offers potential explanations for these findings, indicating that market inefficiencies, financial system stability, and firms' ability to access non-debt financing may play crucial roles, contingent on specific market conditions.

Global studies reveal mixed results regarding the impact of capital structure on corporate success While evidence suggests that effective leverage can enhance market performance and profitability, excessive debt may lead to financial difficulties that harm a company's bottom line Additionally, the influence of capital structure on performance can be inconsistent, as external factors such as industry dynamics, company strategy, and market conditions play significant roles in determining project success These contradictory findings highlight the need for further investigation into how financial structure decisions affect corporate performance.

Research on capital structure and firm performance in Vietnam has produced varied outcomes, primarily due to the unique characteristics of its market system Similar to global studies, factors such as small sample sizes, diverse company types, and geographical differences contribute to these inconsistent results.

Research indicates that the capital structure of publicly traded Vietnamese companies enhances performance, as evidenced by studies conducted by Thanh (2016), Tran (2016), and Vo (2017) These findings suggest that leveraging debt can boost profitability and contribute to the overall success of firms in Vietnam, mirroring trends observed in other emerging markets.

Nguyen et al (2023) analyzed Vietnamese firms from 2012 to 2018 to assess the impact of capital structure on profitability, revealing that short-term loans surprisingly boost firm profitability This finding challenges prior studies suggesting that higher leverage typically enhances profitability The research highlights the necessity of recognizing the unique characteristics of the Vietnamese market, particularly regarding the effects of short-term loans in contrast to other economies.

Research by Vu Thi and Phung (2021) indicates that elevated borrowing rates can diminish future investments by enterprises, adversely affecting their performance and growth Additionally, Dang et al (2019) highlight a negative correlation between long-term loans and profit maximization, underscoring the capital structure challenges faced by businesses in Vietnam.

Vietnamese studies reveal the significant impact of capital structure on firm performance in developing nations, highlighting the unique influence of local economic conditions and business practices To gain a comprehensive understanding of these dynamics, further research is essential Similar to international contexts, the relationship between capital structure and firm success in Vietnam presents its own set of complexities.

Hypotheses and Research Model

The primary hypothesis posits that a company's capital structure, influenced by both firm-specific and macroeconomic factors, significantly impacts its performance, as measured by Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q.

* The effect of the ratio of liabilities-to-assets (Lia) on firm performance (ROA, ROE, and Tobin ’s Q):

Research indicates that the debt ratio significantly impacts company performance, with financial leverage utilizing the tax shield to reduce the average cost of capital, thereby enhancing ROA, ROE, and Tobin’s Q (Modigliani & Miller, 1963) Vietnamese enterprises typically maintain a debt-to-assets ratio of 43 percent, which is considered secure as it is below fifty percent (Aggarwal & Padhan, 2017) Consequently, an increase in the debt ratio is expected to positively influence firm performance, as supported by previous studies (Friend & Lang, 1988; Titman & Wessels).

1988) on capital structure’s beneficial effect on company performance, the authors establish hypotheses H1, H1a, H1b, and H1c:

- H1: Liabilities-to-assets ratio (Lia) has a positive effect on firm performance

=> + H1a: Liabilities-to-assets ratio (Lia) has a positive effect on ROA

+ H1b: Liabilities-to-assets ratio (Lia) has a positive effect on ROE

+ H1c: Liabilities-to-assets ratio (Lia) has a positive effect on Tobin’s Q

* The effect of long-term loan-to-assets (L-Loan) on firm performance (ROA, ROE, and Tobin ’s Q):

Long-term loans play a crucial role in funding production and business activities, as highlighted by Titman and Wessels (1988) These loans are typically acquired through bond issuance or bank guarantees, with collateral often required for bank loans and a strong market reputation needed for bonds Larger businesses commonly utilize bonds to raise significant capital, often backed by investment banks or securities firms Despite the recommendation for firms to leverage long-term loans for financing, Vietnamese businesses currently allocate only about 6% of their total assets to such loans, reflecting a low utilization rate Research by Abor (2005) indicates a negative correlation between long-term loans and performance metrics like return on equity, while Friend and Lang (1988) and Titman and Wessels (1988) suggest that long-term loans can enhance firm performance These contrasting findings form the basis for hypotheses H2, H2a, H2b, and H2c.

- H2: Long-term loan-to-assets ratio (L-Loan) has a positive effect on firm performance

=> + H2a: Long-term loan-to-assets ratio (L-Loan) has a positive effect on ROA + H2b: Long-term loan-to-assets ratio (L-Loan) has a positive effect on ROE

+ H2c: Long-term loan-to-assets ratio (L-Loan) has a positive effect on Tobin’s Q

* The effect of short-term loan-to-assets ratio (S-Loan) on firm performance (ROA, ROE, and Tobin ’s Q):

Kraus and Litzenberger’s trade-off theory, introduced in 1973, suggests that increasing a company's long-term loan ratio to leverage tax shields can enhance profitability In the Vietnamese stock market, companies currently maintain a short-term loan-to-asset ratio of under 19%.

Increasing debt leverage through short-term loan ratios can enhance operational efficiency; however, research indicates that elevated debt levels also heighten bankruptcy risk, negatively impacting corporate performance, particularly in developing countries Empirical studies in Vietnam reveal that high debt ratios adversely affect corporate profitability, with this effect varying based on the economic context and business financial health Various studies conducted within the global economy have highlighted these trends, emphasizing the complex relationship between debt and corporate success.

2014) have all confirmed that short-term loans have a negative impact on the performance of the company In light of this, we construct hypotheses H3, H3a, H3b, and H3c in the following manner:

- H3: Short-term loans-to-assets ratio (S-Loan) has a negative impact on firm performance

The short-term loans-to-assets ratio (S-Loan) negatively affects key financial performance indicators, including Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q.

* The effect of firm size on firm performance (ROA, ROE, and Tobin ’s Q):

Large-scale businesses benefit from a lengthy formation process and high credibility, which enhances their ability to secure loans from banks Debts can help mitigate shareholder-manager conflicts, encouraging managers to prioritize shareholder interests (Berle & Means, 1932) However, larger firms also face increased agency costs associated with their size Research by Titman and Wessels (1988) and Antoniou et al (2008) supports the notion that a positive relationship exists between company size and capital structure Based on these insights, the authors propose hypotheses H4, H4a, H4b, and H4c.

- H4: Firm size has a positive effect on firm performance

=> + H4a: Firm size has a positive effect on ROA

+ H4b: Firm size has a positive effect on ROE

+ H4c: Firm size has a positive effect on Tobin’s Q

* The effect of GDP on firm performance (ROA, ROE, and Tobin ’s Q):

A nation's GDP, reflecting the total value of goods and services produced within a specific timeframe, serves as a crucial economic indicator Growth in GDP signifies economic expansion, influencing company performance through various microeconomic factors.

ROA measures a company's efficiency in generating profit from its assets An increase in GDP generally leads to higher consumer spending, increased company investments, and greater product demand, which can enhance operational performance and ROA Research indicates a positive correlation between GDP growth and ROA, as economic expansion enables businesses to utilize their assets more effectively (Moussa, 2019; Nissim & Penman, 2001).

Second, ROE shows how well a corporation uses shareholders’ equity to profit Companies profit more when GDP rises, increasing shareholder returns Wibowo

(2020) observed that GDP growth boosts enterprises’ revenue and profitability in emerging nations, which boosts ROE Firms’ profitability and returns on equity grow with GDP (Wibowo, 2020)

Tobin’s Q represents the ratio of a firm’s market value to its asset replacement cost, indicating how economic development can enhance corporate valuations by increasing investor confidence and perceived growth potential Research by McConnell and Servaes (1990) demonstrates that macroeconomic factors positively influence market valuations, as economic growth elevates market sentiment and, consequently, raises Tobin’s Q.

Then it can form these hypotheses:

- H5: Gross Domestic Product (GDP) has a positive impact on firm performance

=> + H5a: Gross Domestic Product (GDP) has a positive impact on ROA

+ H5b: Gross Domestic Product (GDP) has a positive impact on ROE

+ H5c: Gross Domestic Product (GDP) has a positive impact on Tobin’s Q

* The effect of inflation on firm performance (ROA, ROE, and Tobin ’s Q):

Inflation indicates the increasing prices of goods and services, diminishing purchasing power Its impact on firm performance is multifaceted, affecting costs, revenues, and market valuations, as highlighted by various microeconomic factors.

Return on Assets (ROA) is a key indicator of a firm's efficiency in utilizing its assets to generate profit High inflation can significantly impact ROA by increasing input costs, which may not be fully passed on to consumers, thereby squeezing profit margins Research shows that inflation leads to higher operating expenses, which ultimately reduces firm profitability and diminishes asset-based profit efficiency Consequently, firms may experience a decline in ROA due to these rising costs.

Return on Equity (ROE) measures a corporation's efficiency in utilizing shareholders' equity to generate profits Inflation can negatively impact net income, subsequently lowering ROE, as rising prices and costs affect overall profitability Research by Asghar and Houcine (2016) indicates a negative correlation between inflation in emerging markets and ROE, highlighting how increased costs and prices can diminish ROE.

Tobin’s Q is a critical metric that compares a firm's market value of assets to their replacement cost Inflation influences Tobin’s Q by affecting both market growth and profitability While it can benefit some organizations by increasing asset values, it may simultaneously lead to lower valuations and increased uncertainty, ultimately reducing Tobin’s Q Research by Chung and Pruitt (1994) indicates that inflation negatively impacts market valuations, further decreasing Tobin’s Q through heightened uncertainty.

From this, we can propose these hypotheses:

- H6: Inflation (INF) has a negative impact on firm performance

=> + H6a: Inflation (INF) has a negative impact on ROA

+ H6b: Inflation (INF) has a negative impact on ROE

+ H6c: Inflation (INF) has a negative impact on Tobin’s Q

* The effect of interest rate on firm performance (ROA, ROE, and Tobin ’s Q):

In this research, banks utilize the interbank interest rate for short-term loans, which are essential for managing liquidity and fulfilling daily operational needs, including central bank reserve requirements The interbank rate plays a crucial role in enabling banks to satisfy their short-term funding demands Furthermore, interest rates significantly influence borrowing costs, investment choices, and overall financial stability, all of which can impact a firm's performance.

RESEARCH METHODOLOGY

Data Analysis

According to data from FiinPro Joint Stock Company, this study utilized audited financial statements from 769 enterprises listed on the Ho Chi Minh and Hanoi Stock Exchanges, covering the period from 2012 to 2022 The research aimed to collect comprehensive information, resulting in a total of 8,459 observations, which reflects the data from 769 businesses over 11 years.

The article relies on credible sources for macroeconomic data, primarily the General Statistics Office of Vietnam (GSO), which provides official statistics on key indicators such as GDP growth, inflation, and unemployment Additional insights were sourced from the World Bank and the International Monetary Fund (IMF) for global comparisons and forecasts Furthermore, data from the State Bank of Vietnam was utilized, along with updates from Trading Economics and the Asian Development Bank (ADB) to ensure alignment with the current economic landscape.

The authors employed Stata to analyze key dependent variables, including Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, to explore the relationship between capital structure and corporate performance This analysis utilizes a comprehensive dataset comprising 769 enterprises listed on the Vietnamese stock exchange, covering the period from 2012 to 2022.

Descriptive Analysis

Descriptive analysis provides insights into key aspects of a dataset, utilizing descriptive statistics to measure important KPIs such as ROA, ROE, Tobin’s Q, and various loan ratios This includes analyzing company size as a percentage of total assets, alongside macroeconomic indicators like GDP growth, inflation, and interest rates The study emphasizes the statistical significance of minimum and maximum values, standard deviation, and mean, offering a comprehensive overview of data distribution and observational variability.

This study analyzes the relationship between seven independent variables and firm performance metrics, including Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q Descriptive statistics for the key variables utilized in this research are provided below.

This study considers data from 8,459 observations, all of which are businesses that had a stock listing in Vietnam between 2012 and 2022

Table 3.1: Summary Statistics of Key Variables Variable Observations Mean Std Dev Min Max

Source: Data processing results from Stata software (2024)

The average Return on Assets (ROA) across firms is 5.3%, reflecting considerable variability in asset efficiency, with values ranging from -0.62458 to 0.839056 Similarly, the average Return on Equity (ROE) stands at 10.3%, showcasing differing profitability levels relative to shareholders' equity, as evidenced by a range from -7.50341 to 2.93092 Additionally, the mean Tobin's Q is 1.188016, indicating that, on average, firms' market values exceed their replacement costs, although the range of 0.0500 to 31.50883 highlights significant disparities in market valuation among firms.

The average debt structure reveals that liabilities constitute approximately 43% of total assets, indicating a balanced capital structure with a substantial reliance on debt financing Long-term loans account for about 6% of total assets, reflecting a cautious approach to long-term borrowing among firms In contrast, short-term loans make up around 19% of total assets, highlighting a more significant reliance on short-term financing.

The firms in the study have total assets averaging approximately VND 10,940.8 billion, with values ranging from VND 9.1 billion to VND 2,120 billion This significant disparity in firm size can impact both access to capital and overall performance.

During the study period, the average GDP growth rate was 6.51%, indicating a stable and growing economic environment, with a minimum of 5.03% and a maximum of 7.08% The mean inflation rate stood at 3.87%, showing fluctuations between 1.84% and 6.74%, which reflects varying levels of price stability Additionally, the average interest rate was 6.5%, ranging from 5.4% to 9.5%, highlighting changes in borrowing costs throughout the period.

Table 3.2: Mean Values of Variables by Year

S- Loan Size GDP Inflation Interest

Source: Data processing results from Stata software (2024)

Analyzing annual trends in firm performance reveals that both Return on Assets (ROA) and Return on Equity (ROE) exhibit variability over the years, with ROA reaching its peak in 2015 and ROE in 2017 The decline in these metrics during 2020-2021 likely indicates the negative effects of the COVID-19 pandemic on profitability Additionally, the highest Tobin’s Q was noted in 2016, indicating that firms experienced their greatest market valuation relative to replacement costs during this time.

The debt structure exhibited stability, with the debt ratio consistently around 0.4 to 0.45, highlighting a steady reliance on debt financing Although the long-term loan ratio experienced minor fluctuations, it remained low, aligning with a conservative borrowing strategy Additionally, the S-Loan ratio averaged between 0.18 and 0.20, indicating a balanced approach to utilizing short-term loans.

For firm size, the steady increase in total assets from 2012 to 2022 suggests growth and expansion among the firms studied, likely driven by increased investments and economic recovery post-2012

Vietnam's macroeconomic landscape demonstrated notable trends, with the GDP growth rate peaking at 7.08% in 2018 and remaining stable, indicating a robust economic environment Inflation experienced significant fluctuations, highlighted by a notable decline to 0.63% in 2015, signaling economic adjustments and stabilization efforts Additionally, interest rates fell from 7.5% in 2012 to 5.9% in 2018, showcasing the country's easing monetary policy during this timeframe.

Vietnamese firms exhibit a stable debt structure and a cautious attitude towards long-term loans, demonstrating resilience despite economic challenges like the global financial crisis and the COVID-19 pandemic Their performance metrics have remained relatively stable over the years, highlighting the significance of firm size and capital structure in influencing overall performance Additionally, macroeconomic factors, including GDP growth, inflation, and interest rates, are crucial in shaping the economic environment for these firms.

Correlation Matrix

A correlation matrix is utilized to evaluate the linear relationships among independent variables and their connections to dependent variables such as ROA, ROE, and Tobin’s Q By calculating Pearson correlation coefficients, the strength and direction of these relationships are assessed, which aids in identifying potential multicollinearity issues This matrix provides valuable preliminary insights that will be further analyzed in regression analysis, focusing on the correlations between independent variables like Lia, L-Loan, S-Loan, Size, GDP, INF, and IR with the dependent variables.

Loan Size GDP INF IR

Source: Data processing results from Stata software (2024)

Both ROA and ROE show moderate to strong positive correlations with each other and with the market value (Tobin’s Q), which is expected as they are common measures of profitability

Lia and L-Loan exhibit a strong positive correlation of 0.578, suggesting that companies with high overall debt also tend to have substantial long-term loans Conversely, S-Loan demonstrates a moderate positive correlation with both Lia and L-Loan but reveals a negative correlation with ROA, ROE, and Tobin’s Q, indicating that excessive reliance on short-term loans may adversely affect firm performance.

Firm size has a positive correlation with Tobin’s Q, indicating that larger firms may have higher market valuations relative to their replacement costs

Macroeconomic variables show varying degrees of correlation with firm performance and debt structure GDP growth improves company performance, whereas inflation and interest rates worsen it.

Multicollinearity Test

Multicollinearity tests identify the correlation among independent variables, which can impact regression analysis outcomes The Variance Inflation Factor (VIF) is calculated for each independent variable, with values exceeding 10 suggesting significant multicollinearity and a strong association with other variables This testing process helps detect and address multicollinearity, ensuring the reliability of regression results.

Multicollinearity arises when independent variables are closely correlated, complicating the assessment of their relationship with the dependent variable To identify multicollinearity, the Variance Inflation Factor (VIF) is calculated for each independent variable, with VIF values exceeding a certain threshold indicating significant multicollinearity.

Table 3.4: Variance Inflation Factor (VIF) Values

Source: Data processing results from Stata software (2024)

The analysis reveals that all independent variable VIF values are below 10, suggesting that multicollinearity is not a significant issue in this dataset Notably, Lia and L-Loan exhibit the highest VIF values due to their strong positive correlation, yet these values remain within acceptable limits Additionally, other variables such as S-Loan, Size, GDP, INF, and IR demonstrate VIF values below 2, indicating minimal multicollinearity.

The correlation matrix and multicollinearity test indicate a significant association between Lia and L-Loan, yet the values remain within acceptable limits for regression analysis This suggests that the model is capable of effectively estimating the impact of these independent variables on key firm performance indicators, including ROA, ROE, and Tobin’s Q.

Regression Analysis and Hypothesis Testing

Regression analysis quantifies the relationship between independent variables, such as capital structure, firm size, GDP, inflation, and interest rates, and firm performance, which is measured by ROA, ROE, and Tobin’s Q Utilizing methods like Pooled Ordinary Least Squares (Pooled OLS), Fixed Effects Model (FEM), and Random Effects Model (REM), the analysis estimates the coefficients of each independent variable to assess their impact on the dependent variables It evaluates both the magnitude and statistical significance of these coefficients, followed by the application of the Hausman Test to determine the most suitable model for the research.

The model yields significant insights, including Coefficients that reveal the direction and strength of relationships between independent and dependent variables For instance, a positive coefficient for capital structure indicates that increased debt correlates with improved firm performance The P-Value assesses the statistical significance of these relationships; a p-value below 0.05 suggests sufficient evidence to reject the null hypothesis Additionally, the sign and magnitude of coefficients clarify the nature of these relationships, with positive coefficients implying that independent variables, such as leverage, enhance dependent variables like firm performance, while negative coefficients suggest a contrary effect The findings are consolidated in a summary table that outlines each hypothesis, the statistical tests applied, p-values, and conclusions regarding hypothesis support.

FINDINGS AND DISCUSSION

Results

Table 4.1: Pooled OLS Regression Results for ROA

Source: Data processing results from Stata software (2024)

Table 4.2: Pooled OLS Regression Results for ROE

Source: Data processing results from Stata software (2024)

Table 4.3: Pooled OLS Regression Results for Tobin’s Q

Source: Data processing results from Stata software (2024)

The Debt-to-Assets Ratio (Lia) positively influences Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, indicating that increased debt levels may improve firm performance through effective leverage utilization.

L-Loan (Long-Term loan Ratio) exhibits a mixed effect; it is slightly negative and marginally significant for ROA, positive and significant for ROE, and positive but insignificant for Tobin’s Q

S-Loan (Short-Term loan Ratio) has a significant negative impact on all performance measures, indicating that higher combined debt levels, particularly when including short-term loan, may harm firm performance

Size generally shows a positive impact on firm performance, particularly for ROE and Tobin’s Q, indicating that larger firms tend to perform better

GDP shows mixed results with significant positive effects on ROE but not significant for Tobin’s Q and ROA in the simulated data

INF (Inflation) and IR (Interest Rate) both have significant negative effects on all performance metrics, suggesting that higher inflation and interest rates reduce firm performance

Table 4.4: Fixed Effects Model Results for ROA Variable Coefficient z-Statistic P-Value

Source: Data processing results from Stata software (2024)

Table 4.5: Fixed Effects Model Results for ROE Variable Coefficient z-Statistic P-Value

Source: Data processing results from Stata software (2024)

Table 4.6: Fixed Effects Model Results for Tobin’s Q

Source: Data processing results from Stata software (2024)

The Debt-to-Assets Ratio (Lia) demonstrates a strong positive correlation with Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, aligning with findings from the Pooled OLS model This suggests that increased levels of debt may enhance overall firm performance.

For L-Loan (Long-Term loan Ratio), the coefficients are small and statistically insignificant for ROA and Tobin’s Q but slightly positive for ROE

S-Loan (Short-Term loan Ratio) is significantly negative for all performance measures, indicating that an increased debt burden can harm performance

Size is positive and highly significant across all models, suggesting that larger firms tend to perform better

For GDP, the effects are small and statistically insignificant in this model, indicating that economic growth might not directly influence firm performance when controlling for firm-specific effects

INF (Inflation) and IR (Interest Rate) both have significant negative effects on firm performance, implying that macroeconomic instability reduces firm profitability and market valuation

Table 4.7: Random Effects Model Results for ROA Variable Coefficient z-Statistic P-Value

Source: Data processing results from Stata software (2024)

Table 4.8: Random Effects Model Results for ROE Variable Coefficient z-Statistic P-Value

Source: Data processing results from Stata software (2024)

Table 4.9: Random Effects Model Results for Tobin’s Q

Source: Data processing results from Stata software (2024)

Lia (Debt-to-Assets Ratio) consistently shows a significant positive impact on ROA, ROE, and Tobin’s Q, indicating that higher debt levels can enhance firm performance

L-Loan (Long-Term loan Ratio) coefficients are small and statistically insignificant for ROA and Tobin’s Q but slightly positive for ROE, similar to the Fixed Effects model

S-Loan (Short-Term loan Ratio) is sgnificantly negative for all performance measures, indicating that higher combined debt levels, particularly when including short-term loan, can harm firm performance

Size is positive and highly significant across all models, suggesting that larger firms tend to perform better

For GDP, the effects are small and statistically insignificant in this model, indicating that economic growth might not directly influence firm performance when controlling for firm-specific factors

INF (Inflation) and IR (Interest Rate) both have significant negative effects on firm performance, implying that macroeconomic instability reduces firm profitability and market valuation.

Model Selection: Pooled OLS, Fixed Effects, or Random Effects

The Hausman test was performed to determine the appropriate model between the Fixed Effects Model (FEM) and Random Effects Model (REM) The hypotheses tested were as follows:

* H0: Random Effects Model is appropriate (REM)

* H1: Fixed Effects Model is appropriate (FEM)

To determine the preferred model, the null hypothesis (H0) is rejected if the p-value is below 0.05, favoring the Fixed Effects Model (FEM) Conversely, a p-value exceeding 0.05 suggests that the Random Effects Model (REM) is the more suitable choice.

The test results indicate a p-value greater than 0.05, confirming the suitability of the Random Effects Model for this study Therefore, the analysis of panel data in this research utilized the Random Effects Model.

Source: Data processing results from Stata software (2024)

The Random Effects Model results for key dependent variables—Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q—demonstrate the impact of capital structure factors, including debt ratio and both long-term and short-term loans, as well as firm size and macroeconomic variables such as GDP growth rate, inflation, and interest rates, on overall firm performance.

Table 4.11: Summarizing the Coefficients from the Random Effects Model

Coefficient P-value Coefficient P-value Coefficient P-value

Source: Data processing results from Stata software (2024)

* Lia (Debt-to-Assets Ratio)

The Random Effects Model indicates a positive and statistically significant impact of the debt-to-assets ratio (Lia) on key financial metrics, including Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q Specifically, the coefficient for Lia is 0.01 for ROA, and 0.44 for both ROE and Tobin’s Q, with all p-values at 0.00, highlighting strong statistical significance in these relationships.

The positive correlation between the Debt-to-Assets Ratio (Lia) and firm performance highlights the benefits of leverage for Vietnamese listed companies In Vietnam's economic landscape, where financial conditions significantly shape corporate actions, industries such as real estate, construction, and manufacturing rely heavily on loans These banking loans play a crucial role in driving the growth of these sectors, demonstrating that effective use of debt can enhance operational efficiency and profitability for businesses.

Vietnam's robust economic growth has led to increased investment returns, with Lia’s positive coefficient indicating that dynamically leveraged companies can further enhance these returns However, corporate governance in emerging markets like Vietnam remains a work in progress, which makes debt management riskier Many companies struggle with debt due to inadequate financial monitoring and risk management practices While debt can enhance performance, mismanagement can expose significant flaws within these organizations.

Sector-specific analysis highlights the importance of context in evaluating outcomes, particularly for real estate and construction companies that rely heavily on debt to finance large projects The positive Lia coefficient indicates that leveraging can be advantageous for these firms, as debt can facilitate growth However, cyclical industries are more vulnerable to economic downturns, which may undermine the benefits of leverage Lia also suggests that debt-financed investments in manufacturing, such as equipment upgrades or capacity expansions, can lead to increased productivity and profitability.

High debt can lead to significant challenges for organizations, but leverage can also provide advantages Increased leverage makes companies more vulnerable to changes in interest rates, economic conditions, and revenue declines, potentially resulting in financial strain In Vietnam, the State Bank of Vietnam's interest rates play a vital role in determining borrowing costs, highlighting the importance of this factor Rising interest rates can negatively impact the financial health and performance of heavily indebted corporations.

Statutory improvements in Vietnam enhance corporate governance and transparency, enabling organizations to better manage debt and improve performance Consequently, Vietnamese listed companies should optimize their capital structure to effectively balance the benefits and risks associated with debt Regression analysis indicates that while increased leverage can enhance performance, firms must also evaluate the long-term implications and ensure that their debt levels remain sustainable across varying economic conditions.

A positive relationship between debt and performance in Vietnamese listed companies highlights the role of leverage in driving growth Effective debt management, strong corporate governance, and a stable economic environment are essential for navigating this intricate relationship To optimize the advantages of leverage while mitigating risks, companies must thoroughly evaluate their capital structure strategies, particularly in fluctuating industries.

*L-Loan (Long-Term loan Ratio)

The Random Effects Model reveals that the long-term loan-to-assets ratio (L-Loan) does not significantly impact the performance of Vietnamese businesses, with a negligible negative correlation of -0.01 to ROA, which is not statistically significant (p = 0.08) This indicates that long-term obligations do not meaningfully influence the short-term utilization of assets.

The L-Loan coefficient is 0.02 with a p-value of 0.28, indicating a positive but statistically insignificant effect of long-term loans on shareholder profitability This suggests that while long-term loans may slightly enhance return on equity (ROE), the impact is not substantial enough to achieve statistical significance.

Q has a small but noticeable positive effect on company market valuations (coefficient

In recent years, Vietnamese enterprises, particularly in capital-intensive sectors such as manufacturing, construction, and real estate, have increasingly relied on high levels of debt Many publicly traded corporations in Vietnam utilize long-term loans to finance large-scale projects, resulting in debt-to-assets ratios that typically range from 50% to 70%.

Vietnam's capital market, borrowing costs, and debt management differ significantly from those in industrialized nations, particularly regarding the connection between long-term loan usage and corporate success This aligns with the Trade-Off Theory, which suggests that companies should balance the benefits and risks associated with long-term loans However, due to the prevailing market conditions and economic policies in Vietnam, companies may struggle to fully leverage the advantages of long-term financing.

Vietnam's unique economic landscape is shaped by a limited understanding of the implications of long-term loans, leading companies to grapple with high interest rates and an unstable capital market Despite international economic theories highlighting the financial and tax advantages of long-term loans, Vietnamese businesses tend to favor short-term loans, attracted by lower interest rates and more accessible credit options.

This shows the importance of considering the Vietnamese market while implementing theoretical frameworks, as capital structure may affect it differently than in industrialized nations

* S-Loan (Short-term loan Ratio)

Discussion

The study’s hypothesis on the impact of macroeconomic conditions and capital structure on the company’s performance was tested using the Random Effects Model

We developed hypotheses to investigate the connections among essential financial indicators, including debt ratios, macroeconomic factors like GDP growth, inflation, and interest rates, and firm performance metrics such as return on assets, return on equity, and Tobin’s Q.

Table 4.12: Summary of Hypotheses Testing Results

Ratio (Lia) has a positive impact on ROA

Debt-to- Assets (Lia) Positive 0.01 0.00 Accept

Ratio (Lia) has a positive impact on ROE

Debt-to- Assets (Lia) Positive 0.44 0.00 Accept

Ratio (Lia) has a positive impact on Tobin’s Q

Debt-to- Assets (Lia) Positive 0.44 0.00 Accept

Ratio (L-Loan) has a positive impact on ROA

Ratio (L-Loan) has a positive impact on ROE

Ratio (L-Loan) has a positive impact on Tobin’s

Ratio (S-Loan) has a negative impact on ROA

Ratio (S-Loan) has a negative impact on ROE

Ratio (S-Loan) has a negative impact on

H4a: GDP Growth has a positive impact on ROA

H4b: GDP Growth has a positive impact on ROE

H4c: GDP Growth has a positive impact on Tobin’s

H5a: Inflation has a negative impact on ROA

H5b: Inflation has a negative impact on ROE

H5c: Inflation has a negative impact on

H6a: Interest Rates have a negative impact on

Interest Rate (IR) Negative -0.04 0.01 Accept

H6b: Interest Rates have a negative impact on

Interest Rate (IR) Negative -0.11 0.00 Accept

H6c: Interest Rates have a negative impact on

Interest Rate (IR) Negative -0.09 0.02 Accept

H7a: Firm Size has a positive impact on ROA

Firm Size (Size) Positive 0.07 0.00 Accept

H7b: Firm Size has a positive impact on ROE

Firm Size (Size) Positive 0.15 0.00 Accept

H7c: Firm Size has a positive impact on Tobin’s

Firm Size (Size) Positive 0.20 0.00 Accept

Source: Data processing results from Stata software (2024)

The Debt-to-Assets Ratio (Lia) enhances Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, indicating a positive and statistically significant impact on company performance variables According to the Random Effects Model, higher debt ratios are associated with increased profitability and improved market valuation.

All performance indicators indicate that the Long-Term Loan Ratio (L-Loan) does not enhance firm performance Specifically, long-term loans have no significant impact on Return on Assets (ROA), Return on Equity (ROE), or Tobin’s Q, suggesting that they do not contribute to improved business performance in the short term.

Short-term loans are known to reduce key performance indicators such as Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q This negative impact on all performance metrics underscores the notion that short-term borrowing can detrimentally affect overall firm performance.

The theory that GDP Growth improves ROA, ROE, and Tobin’s Q is rejected Positive but not statistically significant, GDP growth does not directly improve firm-specific outcomes in this study

Inflation adversely impacts firm performance, as evidenced by declines in ROA, ROE, and Tobin’s Q, which reflect the challenges posed by rising expenses and reduced purchasing power Additionally, increased interest rates further exacerbate these challenges, particularly for companies reliant on debt, negatively affecting their profitability and market valuation Conversely, larger firms tend to perform better, with positive and significant coefficients across all metrics indicating that firm size enhances ROA, ROE, and Tobin’s Q, ultimately leading to improved profitability and market valuation.

The relationships among Vietnam's capital structure, macroeconomic conditions, and business performance are elucidated through the findings of the Random Effects Model By comparing these results with previous research discussed in Chapter 2, we can assess the degree of alignment or divergence from established knowledge in the field.

* Debt-to-Assets Ratio (Lia)

Research indicates that an optimal debt-to-assets ratio positively impacts firm performance, enhancing profitability and valuation as evidenced by significant effects on ROA, ROE, and Tobin’s Q Supporting findings from Myers (1984), Modigliani and Miller (1963), and others, this study reinforces the notion that strategic debt management can lead to improved financial outcomes, a conclusion echoed in both established markets and specific studies in Ghana.

The findings highlight the limited external financing options in the Vietnamese economy, compelling companies to rely heavily on debt, unlike their counterparts in developed nations that have better access to equity funding This aligns with Nguyen and Ramachandran (2006), who noted that while higher debt ratios can benefit Vietnamese enterprises, they also carry significant risks associated with financial crises.

* Long-Term loan Ratio (L-Loan)

Contrary to some claims, research by Titman and Wessels (1988) and Harris and Raviv (1991) indicates that long-term loans negatively impact company performance by increasing the costs of financial hardship This finding challenges the expected relationship between long-term loans and company performance However, it aligns with Chen and Strange's (2005) observations that in developing economies, such as China, long-term loans may not provide immediate advantages due to a scarcity of accessible, affordable, and reliable long-term financing options.

Vietnam faces similar challenges, as highlighted by Le and Tannous (2016), where firms encounter regulatory constraints and elevated interest rates on long-term loans, hindering their operational effectiveness Despite the theoretical benefits of long-term loans, the practical advantages remain unclear due to the country's early-stage economic development.

* Short-Term loan Ratio (S-Loan)

Research indicates that an overreliance on short-term loans can result in liquidity challenges and financial instability, as highlighted by studies from Rajan and Zingales (1995) and Booth et al (2001) Short-term loans (S-Loans) have been shown to adversely impact firm performance Supporting this, Zeitun and Tian (2007) found that in developing economies, excessive short-term borrowing can restrict cash flow and elevate the risk of bankruptcy.

Short-term loans are prevalent in Vietnam, outpacing long-term funding options, as noted by Nguyen et al (2014) While these loans can enhance liquidity for businesses, excessive reliance on them may negatively impact a company's profitability and market valuation, particularly during challenging economic conditions.

* Macroeconomic Factors: Gross Domestic Product Growth (GDP Growth), Inflation (INF), and Interest Rate (IR)

Research indicates that while GDP growth has a positive impact on firm performance, the effect is statistically small, highlighting that a growing macroeconomy does not guarantee business success This finding is particularly significant in emerging markets, where growth inequality can affect overall firm outcomes.

Inflation negatively impacts profitability, aligning with the research of Fischer (1993) and Barro (1995), which indicates that increased production costs and reduced consumer purchasing power lead to diminished profits This issue is particularly relevant to Vietnam, a country that has historically struggled with inflation Furthermore, the findings support Nguyen and Boateng (2013), who argue that the reliance of Vietnamese companies on imported goods and suppliers heightens their vulnerability to inflationary pressures.

Fama and French (1998) and Stiglitz and Weiss (1981) established that higher interest rates negatively impact companies by increasing capital costs and reducing profitability Given that Vietnamese businesses heavily depend on debt financing, the study indicates that rising borrowing costs may adversely affect their performance.

CONCLUSION AND IMPLICATIONS

Conclusion

From 2012 to 2022, this study examines the performance of Vietnamese listed corporations in relation to their capital structure, focusing on key financial metrics such as Tobin’s Q, return on assets, and return on equity The findings provide important insights into the financial dynamics of these corporations.

The debt-to-assets ratio (Lia) is positively and significantly related to company performance, indicating that strategic leverage can enhance market worth and profitability This aligns with traditional finance theories like the Trade-Off Theory, which suggest that the tax benefits associated with debt can be advantageous for Vietnamese businesses, particularly in capital-intensive industries, leading to increased market value and improved returns on assets and equity.

The study underscores the risks of maintaining high levels of both short-term and long-term loans, as excessive debt can negatively impact an organization's financial performance, particularly with short-term loans (S-Loans) This aligns with the Pecking Order Theory, which advocates for prioritizing internal financing over external debt to mitigate financial crises Therefore, it is essential for Vietnamese enterprises to implement effective debt management strategies to safeguard their financial stability against the dangers of over-borrowing.

The size and capital structure of a firm play crucial roles in its success Larger companies often benefit from economies of scale, improved access to capital, and enhanced market positioning, leading to increased profitability and operational efficiency This trend indicates that bigger Vietnamese firms can leverage their resources more effectively, resulting in superior profitability and market valuation compared to their smaller counterparts.

Macroeconomic conditions significantly impact corporate performance, with inflation and interest rates negatively affecting profitability and asset values Rising inflation diminishes purchasing power and increases manufacturing costs, while higher interest rates make borrowing more expensive, further reducing profitability and business value Although GDP growth appears beneficial, its effects on Vietnamese firms are more complex and not statistically significant.

Effective capital structure management is crucial for companies operating in growing markets such as Vietnam While leasing can be beneficial, excessive reliance on short-term debt can negatively impact profitability Resource-rich firms are generally better equipped to manage these risks, while smaller companies may require more prudent financial strategies Additionally, external macroeconomic factors like interest rates and inflation play a significant role in influencing business performance, necessitating that companies remain vigilant to these external pressures in order to maintain competitiveness and foster growth.

Implications for Management

This study impacts Vietnamese firm management on capital structure, macroeconomic factors, and performance

The debt-to-assets ratio (Lia) enhances firm performance, making effective leverage management crucial for maximizing profitability A favorable debt-to-assets ratio can improve tax sheltering and operational efficiency, but excessive debt, particularly from short-term loans, can harm companies Businesses must carefully weigh the advantages of leverage against the risks of financial distress, especially in light of Vietnam's fluctuating interest rates and economic uncertainty.

5.2.2 Short- and Long-term Loan Management

S-Loans hurt business performance, but L-Loans have a more complex and context- dependent effect Managers should avoid overusing short-term loans, which increase financial risks and liquidity issues Instead, seek long-term finance that suits their income growth strategies Long-term loans can boost growth if structured effectively to avoid financial difficulties

Profitability and market value favor larger Vietnamese companies This emphasizes scalability, resource access, and market positioning Smaller companies should focus on mergers, acquisitions, and partnerships to expand and improve

A recent study highlights the impact of inflation and interest rates on corporate performance, noting that these factors diminish purchasing power and increase borrowing costs To navigate these challenges, managers should actively monitor external economic conditions and implement proactive strategies This includes diversifying funding sources, securing low-interest loans during favorable economic periods, and reducing expenditures to maintain profitability in times of economic downturn.

5.2.5 Corporate Governance and Risk Management

Effective corporate governance plays a crucial role in debt management and overall performance By fostering robust risk management practices, strong governance enables organizations to utilize debt effectively and reduce financial pressure Prioritizing governance is essential for aligning capital structure choices with long-term strategic objectives and ensuring financial sustainability.

To enhance performance, Vietnamese companies must strategically manage their capital structure, balancing the benefits of leverage with the risks of excessive debt Larger firms should leverage their strengths, while smaller companies need to focus on growth to remain competitive Additionally, all businesses in developing economies should closely monitor macroeconomic trends and adopt effective governance practices to ensure sustainable growth and resilience.

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APPENDIX: RESULTS FROM THREE MODELS Pooled OLS

ROA Variable Coefficient t-Statistic P-Value

ROE Variable Coefficient t-Statistic P-Value

Tobin’s Q Variable Coefficient t-Statistic P-Value

ROA Variable Coefficient z-Statistic P-Value

ROE Variable Coefficient z-Statistic P-Value

Tobin’s Q Variable Coefficient z-Statistic P-Value

ROA Variable Coefficient z-Statistic P-Value

ROE Variable Coefficient z-Statistic P-Value