DOI QR코드

DOI QR Code

Capital Structure of Malaysian Companies: Are They Different During the COVID-19 Pandemic?

  • Received : 2021.12.15
  • Accepted : 2022.03.17
  • Published : 2022.04.30

Abstract

This study examined the level of capital structure and its determinants of publicly traded companies in Malaysia before and after the COVID-19 pandemic. The data for this study was examined using Python Programming Language and time-series financial data from 2,784 quarterly observations in 2019 and 2020. The maximum debt is larger before the COVID-19 period, according to the findings. During the COVID-19 period, short-term debts and total debts have both decreased slightly. However, long-term debts have increased marginally. As a result, this research demonstrates that the capital structure has changed slightly during the COVID-19 period. The findings imply that independent of the capital structure proxies, tangibility, liquidity, and business size had an impact on capital structure in both periods. It was found that profitability had a significant impact on total debts both before and after the COVID-19 crisis. While higher-profit enterprises appear to have lesser short-term debts before the COVID-19 periods, they are also more likely to have lower long-term debts during the COVID-19 periods. Even though growing companies tend to have higher short-term debts and thus total debts during those periods, longterm debts are unaffected by potential growth.

Keywords

1. Introduction

The outbreak of the COVID-19 pandemic has come as a rude awakening in modern history since mankind was unprepared for the virus’s consequences. As of September 14, 2021, the virus had infected 226, 322, 754 people worldwide and claimed the deaths of 4, 656, 323 people (WorldOMeter, 2021). In the past, devastating pandemics such as the Spanish flu, which lasted over a year, the H1N1 outbreak or swine flu from 2009 to 2010, and Middle East respiratory syndrome (MERS) in 2012 have swept the world, but they were not as quickly contagious as COVID-19. Unlike COVID-19, the virus eventually died out when the affected persons died, and the community developed immunity to it.

Governments around the world impose movement control orders (MCOs) to prevent the spread of COVID-19, which results in business closures as community health deteriorates, affecting employment, cash flows, supply chain disruptions, changes in consumer demand, and eventually revenue and income contraction (Donthu & Gustafsson, 2020). MCO prevents people from engaging with one another, resulting in social estrangement and the emergence of a new working and social norm. When business, employment, or even school resumes from home, the use of information technology and equipment expands. As a result of the increased use of technology, consumer demand is projected to evolve. Being at home also means spending more time learning new hobbies, skills and starting a new business, all of which could lead to new markets for new items (Donthu & Gustafsson, 2020).

Due to the MCO, which has been in effect since March 18, 2020, public-listed firms in Malaysia are not exempt from a sluggish economic slowdown. The MCO had an impact on a number of industries, including tourism and transportation, such as hotels and airlines. It’s because citizens aren’t allowed to travel across borders for work or pleasure to prevent the COVID-19 virus from spreading (Becker et al., 2020; Che Omar et al., 2020) while vaccinations are developed and ready to be provided to the public.

The economic downturn caused by the COVID-19 pandemic outbreak is by far the worst since the global recession in 1930 (Shen et al., 2020). The Malaysian government quickly closed the borders and urged the citizens to stay home by implementing the MCO. The MCO has caused companies failure to sustain profitability as most business activities could not be carried out except for essential businesses like health care and food supply companies (Md Shah et al., 2020). This has resulted in companies turning to additional debts as sources in financing the business activities to stay afloat (IMF, 2020).

According to reports, global debt reached above 230 percent of GDP in 2018, owing primarily to an increase in debt financing among emerging and developing countries (Koh et al., 2020). China’s manufacturing industry shrank by 13.5 percent in the first quarter of 2020, while European countries are providing debt relief to corporations to assist them to avoid bankruptcy. Central banks around the world are assisting local banks in easing lending and borrowing terms to help businesses stay afloat (Becker et al., 2020). A certain amount of debt can be beneficial to the economy by increasing public consumption and corporate investment. Unfortunately, a high level of debt will expose the companies to have greater liquidity risks as they will be more vulnerable to economic and financial risks shocks. Hence, companies may need to restructure their financing positions through leverage.

Literature has provided empirical evidence of various aspects of capital structure, including capital structure determinants (Saif-Alyousfi et al., 2020; Vo, 2017), corporate governance and capital structure (Feng et al., 2020; Zaid et al., 2020), capital structure, and firm performance (Ahmed & Afza, 2019; Ali & Faisal, 2020; Ayaz et al., 2021; Islam & Iqbal, 2022; Mathur et al., 2021), capital structure during the financial crisis (Danso et al., 2020; Khalfan & Wendt, 2020; Morri & Artegiani, 2015). However, most of the literature uses data from developed countries without considering the impact of a pandemic outbreak. Since research on the impact of the COVID-19 pandemic is still scarce, empirical research must be carried out to analyze whether the capital structure in developing countries differs in response to the COVID-19 pandemic, particularly in the Malaysian context. Thus, this study looks at how public listed companies in Malaysia structured their capital before and during the COVID-19 pandemic. Prior studies suggest that several determinants may influence capital structure. Following studies such as Chaklader and Padmapriya (2021), Pathak and Chandani (2021), Vo (2017), Zaid et al. (2020), and Zaman et al. (2021), this study explores the impact of tangibility, profitability, liquidity, growth and firm size on the capital structure of Malaysian public listed companies particularly before and during COVID-19 pandemic outbreak.

This research contributes to the body of knowledge about Malaysia’s capital structure before and during the COVID-19 pandemic epidemic. Other researchers may be inspired to do a new study in the future with a comparable or different depth, scope, and area. This research could also aid in the recovery of businesses once the pandemic has passed. The comparison analysis may provide greater insight into how the COVID-19 pandemic outbreak affects the companies. This study may also benefit current and potential capital providers by providing information on Malaysia’s capital structure, which may be useful in their investment decision making process.

2. Literature Review

2.1. Capital Structure Theories

The trade-off theory and the pecking theory are two popular capital structure ideas. The ideal capital structure is achieved by balancing the tax benefits and associated bankruptcy costs, according to trade-off theory (Modigliani & Miller, 1963). The trade-off between the revenue of the debt issuance cost (Fischer et al., 1989) and the tax shield benefits determines the level of leverage (Jensen & Meckling, 1976). According to Baxter (1967), increasing debt financing beyond the optimal level could lead to increased bankruptcy risk and capital structure expenses. As a result, capital structure is said to be determined by balancing the benefits and costs of debt (Bradley et al., 1983; Sheikh & Qureshi, 2017).

Pecking order theory, on the other hand, does not place a premium on the optimal capital structure. Rather, it focuses on the efficiency with which corporations manage their capital structure. The disparities in debt ratios are suggested by this idea (Moradi & Paulet, 2019; Shyam- Sunder & Myers, 1999). Because internal funding will be the most important source of funding, debt issuance is used when internal funding is insufficient (Pathak & Chandani, 2021). The plan is to use debt financing to cover the anticipated funding shortfall (Huang & Ye, 2021). Due to asymmetry in information about the firm’s value, debt may be favored overstock. As a result, corporations should participate in a series of hierarchical financing preferences, according to the pecking order idea (Myers & Majluf, 1984).

2.2. COVID-19 and Capital Structure

After the COVID-19 pandemic breakout, the OECD (2020) expects a disruption in economic activity and macroeconomics, including a global recession, as a result of lockdown enforcement in many countries around the world. It was demonstrated that a number of countries, including Japan and the United States, approved huge fiscal packages to revive their weak economies, with Japan and the United States each approving USD1.7 trillion and USD3 trillion for the first nine months of 2020, respectively. The Malaysian government also released economic stimulus measures and recovery plans of RM295 billion in 2020, according to the Central Bank of Malaysia (BNM), to boost the economy’s resilience amid the COVID-19 pandemic. In addition, the government promised an extra RM10 billion in funding for additional support, mostly for individuals and small and medium-sized businesses (SMEs).

During an economic slump, Trinh and Phuong (2016) identified three significant effects on the economy. To begin with, product supply is drastically reduced when demand power decreases. Second, the reduction in foreign direct investment has had an indirect impact on domestic business funds. Finally, the financial market has been severely impacted by the halting of investment activity and the change in interest rates. As a result, several governments have applied the same instrument techniques used during the financial crisis to the current economic crisis brought by the COVID-19 pandemic (Quéré & Weder, 2020). Examples include a specific award for the afflicted company, temporary layoff assistance, and temporary credit guarantees to ensure that the bank can meet the enterprises’ liquidity needs during the COVID-19 pandemic.

Many firms, particularly those with significant leverage, may face financial distress as a result of COVID-19’s negative influence on their financial health (Huang & Ye, 2021). Because low-leverage and profitable businesses have easier access to debt funding, they are assumed to have greater financial flexibility. Companies will be exposed to increased risk as their reliance on debt financing grows. A shortage of cash flows in such companies may lead to a liquidity crisis. As a result, the COVID-19 pandemic has prompted businesses to restructure their capital structure.

2.3. Capital Structure and its Determinants

Strong financial assistance has a significant impact on a company’s growth and long-term sustainability. Equity and debt financing are two common types of business funding. During the period 2008–2019, East Asian companies received roughly 70% of all equity and loan financing (Abraham et al., 2020). Several companies are forced to adjust their paradigms on how to supervise their business operations and financial structure as a result of the negative impact of the COVID-19 pandemic (Rizvi et al., 2020). Debt financing is regarded to be a necessary component of corporate finance, and capital structure is one of the most important factors to consider when assessing a company’s financial health. Capital structure can also be exploited as a foundation for investment policy (Muradoğlu & Sivaprasad, 2009). Companies are inclined to have debt financing because of tax shields benefit (Danso et al., 2020). Too much reliance on debts financing may expose companies to a higher risk of repayment default. It is also claimed that high leverage companies may allocate higher profits and cash flows to ensure they do not default on their debt payments (Abraham et al., 2020). Shortage of cash or inability to pay its obligations may have resulted from inefficient debt management or financial obligations. Consequently, companies may need to restructure their financial compositions as a continuous predicament may result in financial distress, eventually leading to business failure. Therefore, the capital structure must be properly strategized to ensure companies’ performance and positions are not detrimentally affected.

Empirical studies on non-financial companies have investigated the firm-specific factors that influence capital structure. Frank and Goyal (2009) have identified that asset tangibility, firm profitability, and firm size have a more significant influence on capital structure. The availability of assets may influence the accessibility to more debt financing (Dakua, 2018; Khan et al., 2021). In addition, the profitability level of a company may influence leverage either favorably or unfavorably (Dakua, 2018; Khan et al., 2021). Leverage is also influenced by the firm size (Vo, 2017), and the companies’ preference over the types of debts depends on the firm size. Other factors such as liquidity and growth may also influence capital structure (Dakua, 2018; Deesomsak et al., 2004). Hence, following previous literature, this study focuses on the determinants of capital structure, namely tangibility, profitability, liquidity, growth, and size.

2.4. Development of Hypothesis

2.4.1. Profitability and Capital Structure

In line with trade-off theory, profitable companies are expected to have higher leverage levels due to better debt serving capabilities (Pathak & Chandani, 2021) and tax shields benefits (Khémiri & Noubbigh, 2018). Thus, these companies are likely to have high debts obligations. Studies such as Chaklader and Padmapriya (2021), Dakua (2018), Frank and Goyal (2009), and Gunardi et al. (2020) conclude that profitability is positively associated with leverage. However, pecking order theory assumes that profitable companies are anticipated to have higher retained earnings, using their internal funds to finance their operations. Since debt payment is mandatory, the use of debts financing will decrease the available cash for managerial use. Hence, profitability and leverage are negatively associated. This view is supported by Fama and French (2002), Kaloudis et al. (2020), Khoa and Thai (2021), Moradi and Paulet (2019), Nguyen and Duong (2022) as well as Saif-Alyousfi et al. (2020). Therefore, in line with prior literature, the first hypothesis is proposed:

H1: Profitability has a significant influence on capital structure.

2.4.2. Tangibility and Capital Structure

Both trade-off and pecking order theories support the view that the accessibility of tangible assets influences capital structure. Trade-off theory assumes that companies with more tangible assets tend to have a higher level of leverage since the assets can be used as collateral to obtain debt financing effortlessly (Titman &, 1988; Sbeti & Moosa, 2012). Studies done by Chaklader and Padmapriya (2021), Kaloudis et al. (2020), Nguyen et al. (2021), Pathak and Chandani (2021), and Saif-Alyousfi et al. (2020), provide evidence that there is a positive relationship between tangibility and capital structure. Pecking order theory postulates that higher fixed assets will result in lower debt financing (Booth et al., 2001). Empirical evidence suggests that tangibility has an inverse relationship with capital structure (Dakua, 2018; Khoa & Thai, 2021; Nguyen & Duong, 2022; Yusuf et al., 2015) as firms with higher tangible assets have higher tangible Wessels ability to generate internal funds using these assets. However, Gunardi et al. (2020) suggest that physical assets do not influence capital structure. Consequently, the second hypothesis in this study is postulated as follows:

H2: Tangibility has a significant influence on capital structure.

2.4.3. Growth and Capital Structure

Growth has an inverse relationship with capital struc- ture, according to both trade-off and pecking order theories. Chaklader and Chawla (2016) suggested that enterprises with high growth potential would prefer internal funding due to lower distress costs, which is consistent with trade-off theory. According to the pecking order theory, growing companies have lesser leverage because the debt disciplinary function reduces self-interested management. Growth, on the other hand, has a positive impact on capital structure, according to Nguyen and Duong (2022) and Pathak and Chandani (2021). High-growth companies that have exhausted their internal resources are compelled to rely on debt funding (Michaelas et al., 1999). Therefore, the third hypothesis is suggested as follows:

H3: Growth has a significant influence on capital structure.

2.4.4. Liquidity and Capital Structure

According to the trade-off theory, companies with high liquidity are more likely to use high debt financing since they have lower liquidity risks and can meet their obligations (Saif-Alyousfi et al., 2020; Vo, 2017). As a result, there is a positive relationship between liquidity and capital structure. Bukair (2019), Chaklader and Padmapriya (2021), Dakua (2018), and Gunardi et al. (2020) supported this hypothesis. According to the pecking order theory, because highly liquid companies use their internal funds to support their investments (Khémiri & Noubbigh, 2018), liquidity and capital structure have a negative relationship. Companies with lower liquidity may rely more on debt financing. Consequently, these companies experience higher leverage and lower current assets. Thus, the fourth hypothesis in this study is as follows:

H4: Liquidity has a significant influence on capital structure.

2.4.5. Size and Capital Structure

Several studies, including Correia et al. (2015), Kaloudis et al. (2020), Nguyen and Duong (2022), and Pathak and Chandani (2021), suggested that size and capital structure are related. The finding endorses the trade-off theory, which states that due to high business diversification, larger companies are more likely to rely on debt funding. Hence, pecking order theory proposes that capital structure is inversely related to size. Chaklader and Padmapriya (2021) and Saif-Alyousfi et al. (2020) supported this theory. Due to information asymmetry, larger companies are assumed to have the ability to raise their funds through equity (Panda & Nanda, 2020). Hence, the fifth hypothesis of this study is proposed as follows:

H5: Size has a significant influence on capital structure.

3. Methodology

3.1. Sample Selection and Data Collection

In conducting this study, secondary data was used to collect the necessary information. The data was collected through Refinitiv Eikon published by Thomson Reuters. Before analyzing the data, this study eliminated the sample of financial institutions, incomplete information, missing data, and outliers. The dataset comprises 2, 784 quarter observations from the period 2019 until 2021. It is based on 348 public listed companies in Malaysia using eight-quarters of the financial data.

3.2. Variables

This study adopted the variables used by previous literature. Following Shahzad et al. (2021), the dependent variable of the study is the capital structure which is measured by total debts (TD), long-term debts (LTD), and short-term debts (STD). The independent variables used in the study are tangibility, profitability, liquidity, growth, and size. A description of all variables is shown in Table 1.

Table 1: Variables and Variable Measurement

OTGHEU_2022_v9n4_239_t0001.png 이미지

The data was analyzed using Python Pandas Programming tools, which is unique to this study. The process of extracting data from Excel documents is known as file extraction. The data in the excel file in this study is in a sequential or structured format. For this study, number extraction was performed on the companies excel files collected by Refinitiv Eikon. Hence, the Pandas Python library will be used because it can extract data from Excel files that are sequential or arranged in a specific way.

This library also has the capacity to generate, decrypt, and combine Excel files. The Python Pandas programming language will be used to carry out the extraction operation. Pandas is data manipulation and analysis software library created for the Python computer language. The code will be run on Jupyter Notebook, and the regression equations for this study’s objective have been constructed as follows:

\(\begin{aligned} \mathrm{STD}_{i t}=& \beta_{0}+\beta_{1} \mathrm{PROF}_{i t}+\beta_{2} \mathrm{TANG}_{i t}+\beta_{3} \mathrm{GROWTH}_{i t} \\ &+\beta_{4} \mathrm{LIQ}_{i t}+\beta_{5} \mathrm{SIZE}_{i t}+\epsilon_{i t} \end{aligned}\)       (1)

\(\begin{aligned} \mathrm{LTD}_{i t}=& \beta_{0}+\beta_{1} \mathrm{PROF}_{i t}+\beta_{2} \mathrm{TANG}_{i t}+\beta_{3} \mathrm{GROWTH}_{i t} \\ &+\beta_{4} \mathrm{LIQ}_{i t}+\beta_{5} \mathrm{SIZE}_{i t}+\epsilon_{i t} \end{aligned}\)       (2)

\(\begin{aligned} \mathrm{TD}_{i t}=& \beta_{0}+\beta_{1} \mathrm{PROF}_{i t}+\beta_{2} \mathrm{TANG}_{i t}+\beta_{3} \mathrm{GROWTH}_{i t} \\ &+\beta_{4} \mathrm{LIQ}_{i t}+\beta_{5} \mathrm{SIZE}_{i t}+\epsilon_{i t} \end{aligned}\)       (3)

Whereby:

STD = Short-term debts ratio

LTD = Long-term debts ratio

TD = Total debts

PROF = Profitability ratio

TANG = Tangibility ratio

GROWTH = Growth ratio

LIQ = Liquidity

SIZE = Firm Size

€ = Error term

4. Results and Discussion

Table 2 shows a summary of descriptive statistics. The standard deviation of the capital structure was extremely high before and during the COVID-19 epidemic. For the time being, it signifies that the fluctuation in capital structure is modest. The capital structure proxies used in this analysis were short-term debt over total assets, long-term debt over total assets, and total debt over total assets. Therefore, some businesses are debt-free, with a debt-to-equity ratio of zero. Furthermore, the maximum debt is higher before the COVID-19 pandemic than during the COVID-19 pandemic period for all forms of capital structures.

Table 2: Summary of Descriptive Statistics

OTGHEU_2022_v9n4_239_t0002.png 이미지

In general, the mean value of profitability, tangibility, sales growth, liquidity, and size ratio is higher during the COVID-19 pandemic period than before the COVID-19 pandemic period. In the case of growth, representing current year total sales minus previous year total sales over previous year total sales, it implies high fluctuation before and during the COVID-19 pandemic. It indicates that companies grew better during the COVID-19 pandemic period. In other words, after COVID-19 occurred, companies can continue and show signs of growth in a short period.

The correlation values among variables are shown in Tables 3 and 4. Table 3 depicts the relationships between variables before the COVID-19 pandemic, whereas Table 4 depicts the correlations between variables during the COVID-19 pandemic epidemic. The association between the variables is generally in an opposite direction, especially before and during the COVID-19 pandemic outbreak. Before the COVID-19 period, tangibility and growth were on the upswing. However, it exhibits a negative direction association during the COVID-19 period. Aside from that, profitability has a negative relationship with short-term debt (STD) and total debt (TD) following the COVID-19 period; however, there was no notable trend before the COVID-19 period. We first identify the variables’ heterogeneity and multicollinearity before moving on to the regression analysis. Its purpose is to ensure that the variables are not multicollinear. As a result, Tables 2 and 3 show that the greatest correlation for long-term debt (LTD) and total debt (TD) before and during the COVID-19 pandemic period is 0.695 and 0.714, respectively. Because the value is less than 9, it shows that there is no multicollinearity.

Table 3: Correlations Between Variables Before COVID-19 Period

OTGHEU_2022_v9n4_239_t0003.png 이미지

Table 4: Correlations Between Variables During COVID-19 Period

OTGHEU_2022_v9n4_239_t0004.png 이미지

Notes: Tables 3 and 4 present the correlations amongst variables employed in the analysis. STD is short-term debt over total assets, LTD is long-term debt over total assets. TD is total debt over total assets, PROF is profitability measured by ROE, TANG is tangibility, GROWTH is sales growth, LIQ is liquidity measured by the current ratio and Size of the companies.

Short-term debt, long-term debt, and total debt scaled over total assets were all regressed. When the independent factors were regressed across the three different dependent variables, we examined them to see if they behaved differently. Table 5 summarizes the findings.

Table 5 shows the regression findings for the factors affecting the capital structure, which are proxied by long term debt, short-term debt, and total debt over total assets. Overall, the findings of our capital structure research in Malaysian enterprises are quite promising. The coefficients are statistically significant at the 1%, 5%, and 10% levels, according to the data in Table 5. Short-term debt and total debt over total assets have greater R-squared values than long-term debt over total assets. Furthermore, for long-term debt and overall debt, R-squared during the COVID-19 pandemic period is larger than R-squared before the COVID-19 pandemic period. However, when compared to before the COVID-19 epidemic, short-term debt-adjusted R-squared was somewhat lower during the COVID-19 period. Furthermore, the variables chosen in this analysis may explain more than 32% of the variation in leverage in Malaysian enterprises throughout the COVID-19 period for short-term debt and overall debt. Most explanatory variables are statistically significant at the 1% level in these models, and they are well-fitted.

Table 5: Capital Structure Regression Analysis

OTGHEU_2022_v9n4_239_t0005.png 이미지

Notes: Standard coefficients are presented (p-values in parentheses) ***, ** and * are significant at 1%, 5% and 10% respectively.

Short-term debt before the COVID-19 period, long term debt after the COVID-19 period, and total debt before and throughout the COVID-19 period all have a negative connection with profitability expressed by return on equity (ROE). According to the pecking order idea, companies that make a lot of money shouldn’t borrow more money to fund their projects. (Khémiri & Noubbigh, 2018) These companies are retaining their internal funds. As a result, the findings of this study are consistent with the pecking order theory, which states that companies with high profits will borrow less for short-term debt before COVID-19. Profitable enterprises will borrow less for long-term debt after the COVID-19 period. They avoid obtaining long-term debt because of the economic slump in COVID-19; in the interim, companies are using their own funds to fund their activities and projects. This result also implies that a profitable company is not compelled to raise funds through the sale of shares (Pathak & Chandani, 2021).

This finding is in line with those of Danso et al. (2020), Saif-Alyousfi et al. (2020), and Yazdanfar and Öhman (2015), who discovered that profitability is negatively associated with capital structure. Hypothesis 1 is confirmed in this case, suggesting that profitability has a large impact on capital structure for short-term debt before the COVID-19 period, long-term debt after the COVID-19 period, and total debt. The second independent variable is the tangibility ratio representing fixed assets over total assets. Based on Table 5, shows that tangibility has various kinds of significant effects on capital structure. The result reveals that long-term debt positively influences tangibility before and during the COVID-19 pandemic period. Therefore, companies were using tangibility assets as collateral to increase their long term debt regardless of the period. Supported by Chaklader and Padmapriya (2021), Danso et al. (2020), and Kyissima et al. (2020), tangibility has a positively significant influence on long-term debt. However, surprisingly, short-term debt and total debt over total assets negatively influence before and during the COVID-19 pandemic period. It is supported by Haron et al. (2020), who also found that short-term debt (STD) and total debt (TD) have a negative relationship with tangibility.

Furthermore, Vo (2017) found that tangibility has a direct association with long-term debt and an inverse relationship with short-term debt. This research emphasizes the fact that organizations with more tangible assets as collateral can borrow more long-term obligations. Tangibility assets are worth more than intangible assets in the event of bankruptcy (Huang & Ritter, 2009; Yazdanfar & Öhman, 2015). Hence, Hypothesis 2 holds true: tangibility has a significant impact on capital structure. Given the loan structure’s stability and flexibility, Malaysian businesses are likely to be forced to use tangibility assets as collateral for long-term debt.

Before the COVID-19 period, the growth ratio had a positive association with short-term debt and total debt. According to Danso et al. (2020), high-growth enterprises demand additional funding to fund their projects and operations. As a result, enterprises will use short-term loans to enhance their finance before the COVID-19 period. However, Md-Rus et al. (2020) and Moradi and Paulet (2019) found a significant negative relationship between company growth and leverage in their analyses, contradicting these findings. As a result, Hypothesis 3 is examined, which states that expansion has a significant impact on capital structure with short-term debt and overall debt before the COVID-19 pandemic period.

Finally, the capital structure of a corporation is positively correlated with its size: short-term debt, long-term debt, and total debt over total assets. It shows that large companies used short- and long-term debt to fund their investments and activities before and throughout the COVID-19 pandemic. Furthermore, our findings support the trade-off argument that larger businesses are more stable and less likely to fail (Danso et al., 2020; Frank & Goyal, 2009; Khémiri & Noubbigh, 2018; Matemilola et al., 2014; Vo, 2017). As a result, Hypothesis 5 is supported, claiming that size has a major impact on capital structure in terms of short-term debt, long-term debt, and overall debt, independent of the time period preceding or following the COVID-19 pandemic. Furthermore, these findings are consistent with the pecking order theory, which suggests that corporations should use internally generated funds rather than borrowing to increase their debt. Hypothesis 4 is examined, suggesting that the impact of liquidity on capital structure is highly important with short-term debt, long-term debt, and overall debt, regardless of the time period before or after the COVID-19 pandemic.

Finally, the capital structure of a corporation is positively correlated with its size: short-term debt, long-term debt, and total debt over total assets. It shows that large companies used short- and long-term debt to fund their investments and activities before and throughout the COVID-19 pandemic. Furthermore, our findings support the trade-off argument that larger businesses are more stable and less likely to fail (Danso et al., 2020; Frank & Goyal, 2009; Khémiri & Noubbigh, 2018; Matemilola et al., 2014; Vo, 2017). As a result, Hypothesis 5 is supported, claiming that size has a major impact on capital structure in terms of short-term debt, long-term debt, and overall debt, independent of the time period preceding or following the COVID-19 pandemic.

5. Conclusion

Companies have been forced to change their business strategies in response to the COVID-19 pandemic, to be more robust in an uncertain commercial environment. Companies may finance their activities through extra indebtedness due to the difficulty of maintaining their activity. Debt financing is one of the most important factors to consider, and it will have an impact on the companies’ long-term sustainability. As a result, the goal of this research is to evaluate the financial structure of Malaysian enterprises before and after the COVID-19 pandemic, as well as to look into the firm specific features that may influence the capital structure. The outcomes of this analysis imply that during the COVID-19 period, the capital structure shifts slightly.

The analysis reveals some intriguing facts, such as the fact that short-term and long-term debts have different firm specific features. Even if high-profit enterprises have fewer short-term debts before the COVID-19 pandemic, they have smaller long-term debts during the COVID-19 period. While access to tangible assets has a negative impact on both short and long-term obligations, it has a beneficial impact on long-term debts. Growing enterprises are more likely to have bigger short-term debts before entering the COVID-19 phase, while long-term debts are unaffected by potential growth. Debt financing is used less often by high-liquid enterprises, while debt financing is used more often by more renowned companies.

Future research may focus on specific industries, as the influence of the COVID-19 pandemic outbreak on business changes for each area, while this study is centered on companies listed on Bursa Malaysia regardless of their sectors. Other variables may be examined to determine the impact of COVID-19 on a company’s overall financial health. Despite its flaws, this study adds to the limited literature on the impact of the COVID-19 pandemic outbreak, particularly in the setting of Malaysia. The findings help management understand the factors that influence the capital structure and capital sources while making investment decisions. 

References

  1. Abraham, F., Cortina Lorente, J. J., & Schmukler, S. (2020). Growth of global corporate debt: Main facts and policy challenges. SSRN Journal, 9, 99. https://doi.org/10.2139/ssrn.3690997
  2. Ahmed, N., & Afza, T. (2019). Capital structure, competitive intensity and firm performance: Evidence from Pakistan. Journal of Advances in Management Research, 16(5), 796-813. https://doi.org/10.1108/JAMR-02-2019-0018
  3. Ali, A., & Faisal, S. (2020). Capital structure and financial performance: A case of Saudi Petrochemical industry. Journal of Asian Finance, Economics, and Business, 7(7), 105-112. https://doi.org/10.13106/jafeb.2020.vol7.no7.105
  4. Ayaz, M., Mohamed Zabri, S., & Ahmad, K. (2021). An empirical investigation on the impact of capital structure on firm performance: Evidence from Malaysia. Managerial Finance, 47(8), 1107-1127. https://doi.org/10.1108/MF-11-2019-0586
  5. Baxter, N. D. (1967). Leverage, risk of ruin, and the cost of capital. Journal of Finance, 22(3), 395-403. https://doi.org/10.1111/j.1540-6261.1967.tb02975.x
  6. Becker, B., Hege, U., & Mella-Barral, P. (2020). Corporate debt burdens threaten economic recovery after COVID-19: Planning for debt restructuring should start now. https://voxeu.org/article/corporate-debt-burdens-threaten-economic-recoveryafter-covid-19
  7. Booth, L., Aivazian, V., Demirguc-Kunt, A., & Maksimovic, V. (2001). Capital structures in developing countries. Journal of Finance, 56(1), 87-130. https://doi.org/10.1111/0022-1082.00320
  8. Bradley, M., Jarrell, G. A., & Kim, E. H. (1984). On the existence of an optimal capital structure: Theory and evidence. Journal of Finance, 39(3), 857-878. https://doi.org/10.1111/j.1540-6261.1984.tb03680.x
  9. Bukair, A. A. A. (2019). Factors influencing Islamic banks' capital structure in developing economies. Journal of Islamic Accounting and Business Research, 10(1), 2-20. https://doi.org/10.1108/JIABR-02-2014-0008
  10. Chaklader, B., & Chawla, D. (2016). A Study of determinants of capital structure through panel data analysis of firms listed in NSE CNX 500. Vision, 20(4), 267-277. https://doi.org/10.1177/0972262916668700
  11. Chaklader, B., & Padmapriya, B. (2021). Impact of cash surplus on firm's capital structure: Validation of pecking order theory. Managerial Finance, 47(12), 1801-1816. https://doi.org/10.1108/MF-08-2020-0417
  12. Che Omar, A. R., Ishak, S., & Jusoh, M. A. (2020). The impact of COVID-19 movement control order on SMEs' businesses and survival strategies. Malaysian Journal of Society and Space, 16(2), 139-150. https://doi.org/10.17576/geo-2020-1602-11
  13. Correia, A., Cerqueira, A., & Brandao, E. (2015). Determinants of corporate capital structure: Evidence from non-financial listed French firms (FEP Working Papers 566). Portugal: Universidade do Porto, Faculdade de Economia do Porto. http://wps.fep.up.pt/wps/wp566.pdf
  14. Dakua, S. (2019). Effect of determinants on financial leverage in the Indian steel industry: A study on capital structure. International Journal of Finance and Economics, 24(1), 427-436. https://doi.org/10.1002/ijfe.1671
  15. Danso, A., Lartey, T. A., Gyimah, D., & Adu-Ameyaw, E. (2021). Leverage and performance: Do size and crisis matter? Managerial Finance, 47(5), 635-655. https://doi.org/10.1108/MF-10-2019-0522
  16. Deesomsak, R., Paudyal, K., & Pescetto, G. (2004). The determinants of capital structure: Evidence from the Asia Pacific region. Journal of Multinational Financial Management, 14(4-5), 387-405. https://doi.org/10.1016/j.mulfin.2004.03.001
  17. Donthu, N., & Gustafsson, A. (2020). Effects of COVID-19 on business and research. Journal of Business Research, 117, 284-289. https://doi.org/10.1016/j.jbusres.2020.06.008
  18. Fama, E. F., & French, K. R. (2002). Testing trade-off and pecking order predictions about dividends and debt. Review of Financial Studies, 15(1), 1-33. https://doi.org/10.1093/rfs/15.1.1
  19. Feng, Y., Hassan, A., & Elamer, A. A. (2020). Corporate governance, ownership structure and capital structure: Evidence from Chinese real estate listed companies. International Journal of Accounting and Information Management, 28(4), 759-783. https://doi.org/10.1108/IJAIM-04-2020-0042
  20. Fischer, E. O., Heinkel, R., & Zechner, J. (1989). Dynamic capital structure choice: Theory and tests. Journal of Finance, 44(1), 19-40. https://doi.org/10.1111/j.1540-6261.1989.tb02402.x
  21. Frank, M. Z., & Goyal, V. K. (2009). Capital structure decisions: Which factors are reliably important? Financial Management, 38(1), 1-37. https://doi.org/10.1111/j.1755-053X.2009.01026.x
  22. Gunardi, A., Firmansyah, E. A., Widyaningsih, I. U., & Rossi, M. (2020). Capital structure determinants of construction firms: Does firm size moderate the results? Montenegrin Journal of Economics, 16(2), 93-100. https://doi.org/10.14254/1800-5845/2020.16-2.7
  23. Haron, R. (2014). Capital structure inconclusiveness: Evidence from Malaysia, Thailand, and Singapore. International Journal of Managerial Finance, 10(1), 23-38. https://doi.org/10.1108/IJMF-03-2012-0025
  24. Haron, R., Norman, N. M., Abdullah Othman, A. H., Husin, Md., M., & Sharofiddin, A. (2020). The influence of firm, industry, and concentrated ownership on dynamic capital structure decisions in emerging markets. Journal of Asia Business Studies, 16, 1-21. https://doi.org/10.1108/JABS-04-2019-0109
  25. Huang, H., & Ye, Y. (2021). Rethinking capital structure decision and corporate social responsibility in response to COVID-19. Accounting and Finance, 61(3), 4757-4788. https://doi.org/10.1111/acfi.12740
  26. Huang, R., & Ritter, J. R. (2009). Testing theories of capital structure and estimating the speed of adjustment. Journal of Financial and Quantitative Analysis, 44(2), 237-271. https://doi.org/10.1017/S0022109009090152
  27. International Monetary Foundation (IMF). (2020). Debt management responses to the pandemic, IMF COVID-19 special series. https://www.imf.org/~/media/Files/Publications/covid19-special-notes/en-special-series-on-covid-19-debtmanagement-responses-to-the-pandemic.ashx?la=en
  28. Islam, Z., & Iqbal, M. M. (2022). The relationship between capital structure and firm performance: New evidence from Pakistan. Journal of Asian Finance, Economics, and Business, 9(2), 81-92. https://doi.org/10.13106/jafeb.2022.vol9.no2.0081
  29. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs, and ownership structure. Journal of Financial Economics, 3(4), 305-360. https://doi.org/10.1016/0304-405X(76)90026-X
  30. Kaloudis, A., Tsolis, D., & Koutsobinas, T. (2020). Capital structure determinants and speed of adjustment in the US (including cultural industries): A quantile regression approach. 11th International Conference on Information, Intelligence, Systems, and Applications, IISA 2020, Pireaus, 15-17 July 2020 (pp. 98-109). Manhattan, NY: IEEE. https://doi.org/10.1109/IISA50023.2020.9284413
  31. Khalfan, T., & Wendt, S. (2019). The impact of the financial and economic crisis on leverage: The case of Icelandic private firms. International Journal of Managerial Finance, 16(3), 297-315. https://doi.org/10.1108/IJMF-01-2019-0019
  32. Khan, S., Bashir, U., & Islam, M. S. (2021). Determinants of capital structure of banks: Evidence from the Kingdom of Saudi Arabia. International Journal of Islamic and Middle Eastern Finance and Management, 14(2), 268-285. https://doi.org/10.1108/IMEFM-04-2019-0135
  33. Khemiri, W., & Noubbigh, H. (2018). Determinants of capital structure: Evidence from sub-Saharan African firms. Quarterly Review of Economics and Finance, 70, 150-159. https://doi.org/10.1016/j.qref.2018.04.010
  34. Khoa, B. T., & Thai, D. T. (2021). Capital structure and tradeoff theory: Evidence from Vietnam. Journal of Asian Finance, Economics, and Business, 8(1), 45-52. https://doi.org/10.13106/jafeb.2021.vol8.no1.045
  35. Koh, W. C., Kose, M. A., Nagle, P. S. O., Ohnsorge, F., & Sugawara, N. (2020). Debt and financial crises. SSRN Journal, 20, 70. https://doi.org/10.2139/ssrn.3535970
  36. Kyissima, K. H., Xue, G. Z., Yapatake Kossele, T. P., & Abeid, A. R. (2019). Analysis of capital structure stability of listed firms in China. China Finance Review International, 10(2), 213-228. https://doi.org/10.1108/CFRI-05-2018-0044
  37. Matemilola, B. T., Bany-Ariffin, A. N., & Annuar, Md. (2014). Debt and cash flow relationship in pecking order theory of corporate financing: Dynamic panel evidence. The Empirical Economics Letters, 13, 618-623. https://www.academia.edu/28503055/Debt_and_Cash_flow_Relationship_in_POT_of_Corporate_Financing_Dynamic_Panel_Evidence_Debt_and_Cash_flow_Relationship_in_Pecking_Order_Theory_of_Corporate_Financing_Dynamic_Panel_Evidence
  38. Mathur, N., Tiwari, S. C., Sita Ramaiah, T., & Mathur, H. (2021). Capital structure, competitive intensity and firm performance: An analysis of Indian pharmaceutical companies. Managerial Finance, 47(9), 1357-1382. https://doi.org/10.1108/MF-01-2020-0009
  39. Md-Rus, R., Mohd, K. N., Mohd Taib, H., & Shahar, H. K. (2020). Determinants of capital structure: Evidence from Malaysian firms. Asia-Pacific Journal of Business Administration, 12(3/4), 283-326. https://doi.org/10.1108/APJBA-09-2019-0202
  40. Md Shah, A. U., Safri, S. N. A., Thevadas, R., Noordin, N. K., Abd Rahman, A., Sekawi, Z., Ideris, A., & Sultan, M. T. H. (2020). The COVID-19 outbreak in Malaysia: Actions taken by the Malaysian government. International Journal of Infectious Diseases, 97, 108-116. https://doi.org/10.1016/j.ijid.2020.05.093
  41. Michaelas, N., Chittenden, F., & Poutziouris, P. (1999). Financial policy and capital structure choice in U.K. SMEs: Empirical evidence from company panel data. Small Business Economics, 12(2), 113-130. https://doi.org/10.1023/A:1008010724051
  42. Modigliani, F., & Miller, M. H. (1963). Income taxes and the cost of capital. American Economic Review, 53(3), 433-443. https://www.jstor.org/stable/1809167
  43. Moradi, A., & Paulet, E. (2019). The firm-specific determinants of capital structure-An empirical analysis of firms before and during the Euro crisis. Research in International Business and Finance, 47, 150-161. https://doi.org/10.1016/j.ribaf.2018.07.007
  44. Morri, G., & Artegiani, A. (2015). The effects of the global financial crisis on the capital structure of EPRA/NAREIT Europe index companies. Journal of European Real Estate Research, 8(1), 3-23. https://doi.org/10.1108/JERER-04-2014-0017
  45. Muradoglu, Y. G., & Sivaprasad, S. (2012). Using firm-level leverage as an investment strategy. Journal of Forecasting, 31(3), 260-279. https://doi.org/10.1002/for.1221
  46. Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187-221. https://doi.org/10.1016/0304-405X(84)90023-0
  47. Nguyen, T. G., Nguyen, L., & Nguyen, T. D. (2021). Capital structure and its determinants: Evidence from Vietnam. Journal of Asian Finance, Economics, and Business, 8(10), 1-10. https://doi.org/10.11214/jafeb.2021.vol8.no10.10
  48. Nguyen, V. D., & Duong, Q. N. (2022). The impact of foreign ownership on capital structure: Empirical evidence from listed firms in Vietnam. Journal of Asian Finance, Economics, and Business, 9(2), 363-370. https://doi.org/10.11141/jafeb.2022.vol9.no2.363
  49. Organization for Economic Co-Operation and Development (OECD). (2020). Issue Note 2. Insolvency and debt overhang following the COVID-19 outbreak: Assessment of risks and policy responses. https://www.oecd-ilibrary.org/economics/insolvency-and-debt-overhang-followingthe-covid-19-outbreak-assessment-of-risks-and-policyresponses_747a8226-en
  50. Panda, A. K., & Nanda, S. (2020). Determinants of capital structure; a sector-level analysis for Indian manufacturing firms. International Journal of Productivity and Performance Management, 69(5), 1033-1060. https://doi.org/10.1108/IJPPM-12-2018-0451
  51. Pathak, M., & Chandani, A. (2021). The nexus between capital structure and firm-specific factors: Evidence from Indian companies. Journal of Economic and Administrative Sciences, ahead-of-p(ahead-of-print), ahead-of(ahead-of). https://doi.org/10.1108/JEAS-02-2021-0028
  52. Purohit, H., & Khanna, S. (2012). Determinants of capital structure in the Indian manufacturing sector. Asia-Pacific Journal of Management Research and Innovation, 8(3), 265-269. https://doi.org/10.1177/2319510X1200800306
  53. Quere, A. B., & Weder, B. (2020). Europe in the time of COVID-19. https://voxeu.org/article/europe-time-covid-19-new-crash-testand-new-opportunity
  54. Rizvi, S. K. A., Mirza, N., Naqvi, B., & Rahat, B. (2020). COVID-19 and asset management in EU: A preliminary assessment of performance and investment styles. Journal of Asset Management, 21(4), 281-291. https://doi.org/10.1057/s41260-020-00172-3
  55. Saif-Alyousfi, A. Y. H., Md-Rus, R., Taufil-Mohd, K. N., Mohd Taib, H., & Shahar, H. K. (2020). Determinants of capital structure: Evidence from Malaysian firms. Asia-Pacific Journal of Business Administration, 12(3/4), 283-326. https://doi.org/10.1108/APJBA-09-2019-0202
  56. Sbeti, W. M., & Moosa, I. (2012). Firm-specific factors as determinants of capital structure in the absence of taxes. Applied Financial Economics, 22(3), 209-213. https://doi.org/10.1080/09603107.2011.610738
  57. Shahzad, A., Azeem, M., Nazir, M. S., Vo, X. V., & Linh, N. T. M. (2021). The determinants of capital structure: Evidence from SAARC countries. International Journal of Finance and Economics, 26(4), 6471-6487. https://doi.org/10.1002/ijfe.2132
  58. Sheikh, N. A., & Qureshi, M. A. (2017). Determinants of capital structure of Islamic and conventional commercial banks: Evidence from Pakistan. International Journal of Islamic and Middle Eastern Finance and Management, 10(1), 24-41. https://doi.org/10.1108/IMEFM-10-2015-0119
  59. Shen, H., Fu, M., Pan, H., Yu, Z., & Chen, Y. (2020). The impact of the COVID-19 pandemic on firm performance. Emerging Markets Finance and Trade, 56(10), 2213-2230. https://doi.org/10.1080/1540496X.2020.1785863
  60. Shyam-Sunder, L., & C. Myers, S. (1999). Testing static tradeoff against pecking order models of capital structure. Journal of Financial Economics, 51(2), 219-244. https://doi.org/10.1016/S0304-405X(98)00051-8
  61. Titman, S., & Wessels, R. (1988). The determinants of capital structure choice. Journal of Finance, 43(1), 1-19. https://doi.org/10.1111/j.1540-6261.1988.tb02585.x
  62. Trinh, T. H., & Phuong, N. T. (2016). Effects of the financial crisis on the capital structure of listed firms in Vietnam. International Journal of Financial Research, 7(1), 66-74. https://doi.org/10.5430/ijfr.v7n1p66
  63. Vo, X. V. (2017). Determinants of capital structure in emerging markets: Evidence from Vietnam. Research in International Business and Finance, 40, 105-113. https://doi.org/10.1016/j.ribaf.2016.12.001
  64. WorldOMeter. (2021). Coronavirus. https://www.worldometers.info/coronavirus/
  65. Yadav, I. S., Pahi, D., & Gangakhedkar, R. (2022). The nexus between firm size, growth, and profitability: New panel data evidence from Asia-Pacific market. European Journal of Management and Business Economics, 31(1), 115-140. https://doi.org/10.1108/EJMBE-03-2021-0077
  66. Yazdanfar, D., & Ohman, P. (2015). Debt financing and firm performance: An empirical study based on Swedish data. Journal of Risk Finance, 16(1), 102-118. https://doi.org/10.1108/JRF-06-2014-0085
  67. Yusuf, A. N., Al-Attar, A. M., & Al-Shattarat, H. K. (2015) Empirical Evidence on Capital Structure Determinants in Jordan. International Journal of Business and Management, 10(5), 134-152. http://doi.org/10.5539/ijbm.v10n5p134
  68. Zaid, A. A. M., Wang, M., T. F. Abuhijleh, S., Issa, A., W. A. Saleh, M., & Ali, F. (2020). Corporate governance practices and capital structure decisions: The moderating effect of gender diversity. Corporate Governance, 20(5), 939-964. https://doi.org/10.1108/CG-11-2019-0343
  69. Zaman, Q. U., Akhter, W., Abdul-Majid, M., Hassan, S. I. U., & Anwar, M. F. (2021). Does bank affiliation affect firm capital structure? Evidence from a financial crisis. Journal of Economic and Administrative Sciences, ahead-of-p(ahead-ofprint), ahead-of(ahead-of). https://doi.org/10.1108/JEAS-11-2020-0193