“Effect of Capital Structure on the Financial Performance of Listed Industrial Goods Companies in Nigeria”

“Effect of Capital Structure on the Financial Performance of Listed Industrial Goods Companies in Nigeria”

Abubakar Abubakar Sajo, Dr. Ahmad Bukola Uthman

Nile University Abuja, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2025.906000246

Received: 22 May 2025; Accepted: 03 June 2025; Published: 09 July 2025

ABSTRACT

The study aims to understand how various elements of capital structure—short-term debt, long-term debt, equity ratio, and debt-to-equity ratio—influence key profitability indicators like Return on Assets (ROA), Return on Equity (ROE), and Return on Capital Employed (ROCE). The research focuses on listed industrial goods companies in Nigeria, a vital sector for the nation’s economy, to gain insights into the financial factors driving their performance and inform optimal capital structure decisions.

Using Ordinary Least Squares (OLS) regression, the study analyzed pooled panel data from 2012 to 2021 for five selected Nigerian industrial goods companies. The findings indicate that while short-term debt, long-term debt, and equity ratio have a positive but statistically insignificant impact on Return on Equity (ROE), the debt-to-equity ratio (DER) shows a negative and statistically significant effect. This means that an increase in the proportion of debt relative to equity is associated with a notable decrease in shareholder returns.

The study concludes that a high debt-to-equity ratio negatively impacts ROE, and cautions against relying solely on debt to boost shareholder returns. It recommends maintaining a balanced capital structure to optimize profitability and create sustainable value in the Nigerian industrial goods sector.

Keywords: Capital Structure, Long Term Debt (LTD), Short Term Debt (STD), Financial Performance, Return on Equity (ROE)

INTRODUCTION

In the contemporary global business landscape, financial performance serves as a paramount indicator of organizational success, reflecting a firm’s capacity to generate profits, enhance shareholder value, and ensure sustainable growth. This is particularly crucial for listed industrial goods firms in Nigeria, given their pivotal role in driving economic expansion and supporting national development (Aggreh, et al., 2022). A key determinant of financial performance is capital structure, the composition of debt and equity financing, which significantly influences a firm’s risk profile. Financial managers strive to establish an optimal capital structure that balances the benefits of debt financing, such as tax deductibility, against the associated financial risks, including increased volatility and potential insolvency, especially during economic downturns (Aggreh, et al., 2022; Abdullah & Tursoy, 2019).

The interplay between capital structure and financial performance has been a subject of extensive scholarly debate (Uremadu & Onuegbu, 2019). While effective capital structure management can enhance financial flexibility, facilitate strategic investments, and ultimately boost shareholder value, suboptimal financing decisions can lead to higher costs of capital, increased financial risk, and diminished competitiveness (Kenn-Ndubuisi, et al., 2019; Nworie et al., 2022). Notably, recent delistings and business closures within the Nigerian Exchange Group (NGX), including prominent firms like GSK and P&G, underscore the potential consequences of inadequate capital structure management (Nigerian Exchange Group Factbook, 2021). These events highlight the urgent need for a comprehensive examination of the factors influencing financial performance in the Nigerian context.

This study aims to address this gap by investigating the moderating effect of the cost of capital on the relationship between capital structure and financial performance of listed firms in Nigeria from 2014 to 2023. Unlike previous research, this study employs a longitudinal analysis using recent secondary data, providing a contemporary perspective on this critical issue. Utilizing return on assets (ROA) as a measure of financial performance, and focusing on short-term and long-term debt as key components of capital structure, this research seeks to provide empirical insights into the dynamics of capital structure management in Nigeria. By incorporating the cost of capital and firm growth as control variables, this study offers a nuanced understanding of the factors influencing financial performance. The findings will contribute to the development of effective financial strategies for Nigerian listed companies, ultimately fostering sustainable economic growth.

Research Hypotheses

H_01: Short term debt (STD) has no significant effect on the return on equity (ROE) of Listed industrial goods companies in Nigeria

H_02: Long term debt (LTD) has no significant effect on the return on equity (ROE) of listed industrial goods companies in Nigeria.

H_03: Equity Ratio (ER) has no significant effect on the return on equity (ROE) of listed industrial goods companies in Nigeria

H_04: Debt ratio (DR) has no significant effect on the return on equity (ROE) of listed industrial goods companies in Nigeria

 H_05: Debt and equity ratio (DER) has no significant effect on the return on equity (ROE) of listed industrial goods companies in Nigeria.

LITERATURE REVIEW

Conceptual Framework

This chapter provides a comprehensive review of the theoretical and empirical literature pertinent to the relationship between capital structure and financial performance, with a specific focus on the moderating role of the cost of capital.

Capital Structure

Capital structure, a fundamental concept in corporate finance, refers to the composition of a firm’s financing, encompassing debt and equity securities. It represents the strategic mix of long-term funding sources, including debt, equity, and potentially preference shares, employed to finance a firm’s operations and growth (Egolum, et al., 2019). The determination of an optimal capital structure is a complex undertaking, influenced by factors such as financial risk tolerance, tax implications, and the cost of capital (Myers, 1984).

Debt financing, characterized by borrowed funds, introduces financial leverage, potentially enhancing returns to shareholders. However, it also imposes fixed interest obligations and increases the risk of financial distress, particularly during economic downturns (Graham, 2000). Equity financing, representing ownership in the firm, provides a buffer against financial adversity, promoting resilience and flexibility. Equity investors participate in the firm’s profitability through dividends and capital appreciation (Myers, 1984). The strategic balance between debt and equity decisions is crucial for optimizing firm performance in dynamic market conditions.

Short-Term Debt

Short-term debt, typically comprising obligations due within one year, reflects a firm’s ability to manage its immediate financial obligations (Smith & Warner, 1979). It is closely associated with working capital management and can significantly impact a firm’s liquidity and profitability (Moyer et al., 2012). Short-term debt, including creditors and accruals, plays a vital role in meeting working capital requirements and supporting operational efficiency (Akinyomi, 2013).

Empirical studies examining the relationship between short-term debt and financial performance have yielded mixed results. While some studies have reported a positive correlation between short-term debt and return on equity (ROE), others have found a negative relationship with return on assets (ROA) (Udisifan, et al., 2021; Avci, 2016; Kenneth & Lateef, 2020). These inconsistencies highlight the context-specific nature of this relationship and the need for further investigation, particularly in developing economies like Nigeria.

Long-Term Debt

Long-term debt, encompassing obligations with maturities exceeding one year, represents a firm’s strategic financing decisions and can significantly influence its risk profile and cost of capital (Myers, 1984). It includes instruments such as mortgages and long-term leases (Akinyomi, 2013). High levels of long-term debt can increase a firm’s financial risk due to fixed interest and principal repayment obligations. However, it also provides access to substantial capital for long-term investments and growth initiatives. The strategic utilization of long-term debt is a critical aspect of capital structure management (Nirajini & Priya, 2013).

Financial Performance

Financial performance reflects a firm’s ability to generate returns from its assets and resources. It is a critical indicator of organizational success and a key concern for various stakeholders, including investors, creditors, and management (Zeitun & Tian, 2007; Tanko & Saman, 2019; Mardones & Cuneo, 2020).

Financial performance can be evaluated using various metrics, including accounting-based measures such as return on assets (ROA), return on equity (ROE), and net profit margin (NPM), as well as market-based measures such as earnings per share (EPS) and dividends per share (DPS) (Nworie & Ofoje, 2022; Nworie & Mba, 2022; Al-Matari, et al., 2014).

Return on Assets (ROA)

Return on assets (ROA) measures a firm’s profitability relative to its total assets, reflecting its efficiency in generating profits from its resources (Lopes & Alencar, 2010). ROA is a widely used metric for assessing a firm’s operational and financial performance and is considered a key indicator of financial health. It is calculated as:

ROA=Total Assets Net Income

Firm Growth

Firm growth represents the expansion of a firm’s operations and resources over time, encompassing various dimensions such as sales, assets, and market share (Gupta, et al., 2013). Firm growth can be measured using quantitative indicators such as revenue growth, asset growth, and employment growth, as well as qualitative factors such as market position and innovation. A firm’s growth strategy plays a crucial role in its long-term success and sustainability.

Theoretical Framework

This study is anchored on the pecking order theory because it provides a realistic framework for understanding firms’ financing behavior, especially in contexts characterized by information asymmetry and market imperfections. It aims to offer an alternative view to the static trade-off theory, highlighting the dynamic nature of financing decisions and the importance of internal funds (Myers, 1984; Jibran, et al., 2012). The theory’s emphasis on retained earnings as the primary source of financing, followed by debt and then equity, aligns with the observed financing patterns of many firms.

Trade-Off Theory

The trade-off theory, originating from the seminal work of Modigliani and Miller (1958), posits that firms optimize their capital structure by balancing the benefits and costs associated with debt financing. This theory suggests that firms strive to achieve an optimal debt-to-equity ratio by weighing the tax advantages of debt against the potential costs of financial distress, including bankruptcy and agency costs (Dell’Ariccia et al., 2012).

The core tenet of the trade-off theory is that as a firm increases its debt levels, the marginal benefits of tax shields diminish while the marginal costs of financial distress escalate. Firms aim to identify the point at which the marginal benefit of additional debt equals its marginal cost, thereby maximizing firm value.

Key assumptions underlying the trade-off theory include:

Debt and Equity as Primary Financing Sources: Firms primarily rely on debt and equity to finance their operations.

Optimal Capital Structure: An optimal capital structure exists that maximizes firm value.

Dividend Policy: The theory often assumes a simplified dividend policy, which may not reflect real-world practices.

Constant Business Risk and Profit Yield: The theory typically assumes a stable business environment, which may not hold true in dynamic markets.

Rational Investors: Investors are assumed to be rational and focused on maximizing returns (Huang, et al., 2014). However, the trade-off theory has been subject to criticism due to its simplifying assumptions. Critics argue that the assumption of constant profit yields and business risks does not align with the realities of fluctuating economic conditions (Muthee, 2010). Furthermore, the assumption of 100% dividend payout is unrealistic, as firms often reinvest a portion of their earnings. Nevertheless, the trade-off theory remains relevant to this study as it provides a framework for understanding the interplay between debt and equity financing and its impact on financial performance. It underscores the importance of balancing the benefits of debt, such as tax shields, against the associated costs, such as increased financial risk.

Pecking Order Theory

The pecking order theory, initially proposed by Donaldson (1961) and later refined by Myers and Majluf (1984), offers an alternative perspective on capital structure decisions. This theory posits that firms follow a hierarchical order when selecting financing sources, prioritizing internal financing over external financing.

According to the pecking order theory, firms prefer to finance investments using retained earnings, followed by debt, and lastly, equity (Adair & Adaskou, 2015). This preference stems from the information asymmetry between managers and external investors, which can lead to adverse selection problems and increased costs of external financing.

Key tenets of the pecking order theory include:

Preference for Internal Financing: Firms prioritize internal funds due to lower transaction costs and information asymmetry advantages (Tolani & Pandya, 2024).

Debt as Second Choice: In the absence of sufficient internal funds, firms opt for debt financing due to its lower information sensitivity compared to equity.

Equity as Last Resort: Equity financing is considered the least preferred option due to its high information sensitivity and potential dilution of existing shareholders’ ownership.

Sequential Funding Choice: Firms follow a “sequential funding choice” when deciding between internal and external finance (Jaisinghani & Kanjilal, 2017; Shubita & Alsawalhah, 2012).

Alignment of Dividends and Growth: Companies attempt to align long-term dividend payout percentages with growth and profitability potential (Gusfriyanto & Sihombing, 2024).

The pecking order theory challenges the notion of an optimal capital structure, suggesting that firms’ financing decisions are driven by information asymmetry and managerial preferences rather than a deliberate trade-off between benefits and costs.

EMPIRICAL REVIEW

Numerous empirical studies have explored the intricate relationship between capital structure and firm profitability across various industries and geographical contexts, yielding diverse findings. Examining the Nigerian banking sector, Adegbola et al. (2020) analyzed the capital structure’s impact on the profitability of eight Nigerian Deposit Money Banks from 2003 to 2018. Employing a descriptive research design and regression analysis on secondary data, their study concluded that indicators measuring capital structure (debt-equity ratio and leverage ratio) and profitability (returns on equity) exhibited a negative relationship. This implies that an improper proportion of debt mixed with equity as financing methods can negatively affect profitability. Also in Nigeria, Udobi-Owoloja et al. (2020) investigated the capital structure and firm profitability in the listed consumer goods sector from 2011 to 2018, using panel regression on data from ten randomly selected firms. Their results showed that Debt to Asset Ratio (DAR) was positively significant on Return On Asset (ROA), while Debt to Equity Ratio (DER) and Liquidity Ratio (LIQ) were not statistically significant. Short Term Debt to Total Asset Ratio (SDTA) displayed a negative connection, Firm Size (FS) had a weak correlation with profit, and Long-Term Debt to Total Asset Ratio (LDTA) did not influence firms’ profitability.

Further local insight is provided by Awuri Horsefall (2022), whose study on Nigerian consumer goods manufacturing firms emphasized that sound capital structure practices are crucial for enhancing profitability and long-term firm value, recommending optimization of capital structure. Olaniyi et al. (2022) also investigated Nigerian manufacturers from 2005-2020, finding that equity capital, total debt, and long-term debt had the potential to positively and significantly influence financial performance (ROE), while short-term debt had a positive but insignificant influence. They also noted that total asset had a positive and significant influence on financial performance.

From the Indonesian context, Suzulia et al. (2020) studied the effect of capital structure, company growth, and inflation on firm value, with profitability as an intervening variable, for manufacturing companies listed on the Indonesian Stock Exchange from 2014 to 2018. Their path analysis revealed that capital structure had a significant effect on firm value and profitability, while company growth and inflation did not significantly affect either. Additionally, profitability itself had a significant effect on firm value. Hastuti and Carolina (2022) further explored capital structure and profitability’s influence on firm value in Indonesian manufacturing companies (2017-2020), with interest rates as a moderator. Their multiple regression analysis indicated that capital structure had no effect on firm value, but return on assets and net profit margin significantly affected firm value. The moderating variable of interest rates, however, could not moderate these relationships. Gultom et al. (2022), focusing on Indonesia’s Non-Cyclical Consumer Sector (2016–2020), found that capital structure (Debt-to-Equity Ratio) had a negative effect on firm value, while profitability (ROE) had a positive effect. They concluded that capital structure and profitability together significantly affected firm value.

In other emerging economies, Dinh and Pham (2020) investigated the capital structure’s effect on the financial performance (ROE) of pharmaceutical enterprises listed on Vietnam’s stock market from 2015 to 2019. Their OLS regression results indicated that financial leverage ratio (LR), long-term asset ratio (LAR), and debt-to-assets ratio (DR) had a positive relationship with firm performance, while self-financing (E/C) negatively affected ROE. Similarly, Huong et al. (2021) examined the impact of capital structure on the profitability of eighteen rubber companies listed on the Vietnam stock exchange (2015–2019). Their findings showed that profitability (ROE) had a positive relationship with the debt-to-asset ratio but a negative relationship with the long-term debt-to-asset ratio. They also noted a positive impact of firm size and revenue growth on profitability.

Studies in the Middle East offer further perspectives. Abdullah and Tursoy (2021), along with Abuamsha and Shumali (2022), examined the impact of debt structure on financial performance (ROA) of 41 non-banking companies listed on the Palestinian Exchange. They concluded that ROA increased when long-term debts were used for financing assets in the insurance, investment, and industrial sectors, but was negatively affected by long-term debt in the service sector. They also found that ROA in insurance and investment sectors was positively impacted by short-term debts, and only industrial companies’ ROA was significantly affected by total debt.

Research from other regions also contributes to the discourse. Ahmed and Bhuyan (2020) examined the capital structure and firm performance (ROA, ROE, operating margin, ROCE) in Australian service sector firms (2009–2019). Their panel regression analysis revealed a significant association between return on equity and leverage levels, indicating that leverage significantly affects firm performance. In Ghana, Bunyaminu et al. (2021) analyzed the impact of financial leverage on the profitability of recapitalized banks (2008-2017). Their findings, based on random and fixed effects estimations, revealed that leverage exerted a significant negative effect on banks’ profits, supporting the pecking order theory, and bank size positively enhanced profitability. Aidoo et al. (2022), focusing on Ghanaian manufacturing companies (2005-2019), found a significant inverse correlation between capital structure and profitability, suggesting that companies might need to minimize the debt component to increase profitability.

In Ethiopia, Ayalew (2021) investigated capital structure and profitability of private banks using panel data from 16 banks. His study, relying on descriptive and inferential statistics, aimed to identify the effect of financial leverage and control variables on profitability. Hossain et al. (2022) investigated the relationship between capital structure and profitability of food industry companies listed in Dhaka Stock Exchange, Bangladesh. Their panel data estimation (OLS, FEM, REM) showed that short-term leverage had a significant negative impact on ROA (OLS) and a strong positive impact on ROE (REM), but long-term debt did not show significant effects on firm profitability.

Examining the telecom industry, Moustapha and Benziane (2022) studied the impact of capital structure on profitability (ROA, ROE) in the United States from 2012 to 2020. Their pooled panel regression analysis of 421 firm-year observations revealed that the ratio of Total Liabilities to Total Assets (TLsTAs) and Total Equity to Total Assets (TETAs) had a significant impact on ROA, but no impact on ROE. Finally, Songjarean (2022) studied the relationship between capital structure (debt-to-asset ratio, debt-to-equity ratio) and profitability of non-financial companies listed on the Stock Exchange of Thailand (SET 50 index) from 2018 to 2020. The quantitative research, using descriptive and inferential statistical analysis, concluded that capital structure is related to the profitability of companies listed on the Stock Exchange of Thailand. In Hong Kong, Olaniyi et al. (2022) examined the impact of capital structure (total debt ratio, later long-term debt ratio) on firm performance (ROA) for 202 cross-sections from 2014 to 2018. Their findings on the impact of capital structure on performance proved inconclusive, with the long-term debt ratio showing a small negative effect. They highlighted the importance of considering cultural, political, and institutional differences.

RESEARCH METHODOLOGY

This chapter details the methodological approach employed to investigate the effect of capital structure on the financial performance of listed industrial goods companies in Nigeria. It outlines the research design, data sources, population and sampling technique, and the methods of data analysis utilized in this study.

Research Design

This study adopted an “ex-post facto” research design. This design was appropriate because it examines relationships between variables after the events have occurred, meaning the researcher does not manipulate the independent variables. Instead, it focuses on analyzing the impact of pre-existing capital structures on subsequent profitability outcomes, consistent with the nature of financial data analysis (Kerlinger & Lee, 2000).

Data Sources and Population

The study relied on secondary data extracted from the publicly available annual reports and financial statements of listed industrial goods companies in Nigeria. The data covered a ten-year period, specifically from 2012 to 2021. The target population for this research comprised all twenty-one (21) industrial goods companies officially listed on the Nigerian Stock Exchange (now Nigerian Exchange Group, NGX) as of March 31, 2022.

Sample and Sampling Technique

A non-probability purposive (convenience) sampling technique was employed to select the study’s sample. Due to the critical requirement for consistent and complete financial data across the entire study period, five (5) paint manufacturing companies were specifically chosen from the broader industrial goods sector. These companies include: Meyer Nigeria Plc., Premier Paints Nigeria Plc., Berger Paints Nigeria Plc., Cap Nigeria Plc., and Portland Paints Nigeria Plc. This selection ensured that all sampled firms had uninterrupted financial reporting for the entire 2012-2021 period and exhibited similar operational scales in terms of turnover and asset bases, enhancing data comparability. While this approach allows for in-depth analysis of key players within this specific sub-sector, it is important to acknowledge that it may limit the direct generalizability of the findings to the entire Nigerian industrial goods sector.

METHOD OF DATA ANALYSIS

The study utilized pooled panel data analysis for its econometric estimation. This method was selected because it effectively combines time-series data (2012-2021) for each of the five selected companies, allowing for a robust examination of the relationship between capital structure and profitability while accounting for both firm-specific and time-invariant characteristics (Baltagi, 2008). The Ordinary Least Squares (OLS) regression method was primarily employed for the econometric estimations. OLS is a widely recognized statistical technique, valued for its ability to provide Best Linear Unbiased Estimates (BLUE) under specified statistical assumptions (Gujarati & Porter, 2009).

Prior to the regression analysis, descriptive statistics were used to summarize and present the key characteristics and distributions of all variables. Subsequently, multiple regression analysis was conducted using E-Views 9.0 statistical software (or specify STATA 14.0 if that was the final software used in your results section for consistency) to assess the individual and combined effects of the independent capital structure variables (short-term debt ratio, long-term debt ratio, equity ratio, debt ratio, and debt-equity ratio) and the control variables (firm growth, firm size, and firm age) on the dependent variable, Return on Equity (ROE). Panel diagnostic tests (e.g., Breusch-Pagan LM test, Hausman test) were also performed to determine the most appropriate panel data model specification (Pooled OLS, Fixed Effects, or Random Effects) for robust analysis.

Model Specification and Variable Measurement

The multiple regression model used is:

ROEit​=β0​+β1​STDit​+β2​LTDit​+β3​ERit​+β4​DRit​+β5​DERit​+β6​GWTHit​+β7​SZit​+β8​AGEit​+ϵit​

Where:

• ROEit​ = Return on Equity for company i at time t
• STDit​ = Short-Term Debt Ratio (Current Liabilities / Total Assets)
• LTDit​ = Long-Term Debt Ratio (Long-Term Debt / Total Assets)
• ERit​ = Equity Ratio (Shareholders’ Equity / Total Assets)
• DRit​ = Debt Ratio (Total Debt / Total Assets)
• DERit​ = Debt-Equity Ratio (Total Debt / Total Equity)
• GWTHit​ = Growth (year-on-year change in revenue)
• SZit​ = Size (natural logarithm of Total Assets)
• AGEit​ = Age (number of years since listing on the NSE)
• β0​ = Intercept
• β1​−β8​ = Coefficients for the independent and control variables
• ϵit​ = Error term

Decision Rule

To determine the statistical significance of the estimated coefficients, the study will rely on the t-statistic and its corresponding p-value. A coefficient will be considered statistically significant if its p-value is less than the chosen significance level of 0.05. If the p-value is less than 0.05, the null hypothesis (of no significant effect) will be rejected, and the alternative hypothesis (of a significant effect) will be accepted. Conversely, if the p-value is greater than 0.05, the null hypothesis will be accepted, indicating an insignificant effect of the independent variable on profitability.

RESULT AND DISCUSSIONS

Descriptive Statistics Descriptive statistics of the variables were carried out to show the nature and behavior of the data using mean, standard deviation, minimum and maximum. The analysis is presented in table 2:

Descriptive Statistics Result

Table 4.9 presents the result of the descriptive statistics of the variables where the minimum, maximum, mean and standard deviations of the data are fully captured. Table 4.9 shows the descriptive statistics of the variables. The table shows the mean, standard deviation, minimum and maximum values of all the variables of the study from the year 2012 to 2021. The total observations of the study are 50 derived from ten years data and five companies.

Table 4.9: Descriptive Statistics of the Variables

Source: STATA output 14.0 based on data collected (2012-2021)

Note: ROE = Return on Equity; LTD = Long-Term Debt, STD = Short-Term Debt, ER = Equity Ratio, DER = Debt to Equity Ratio, FSIZE = Firm Size and FGRT = Firm Growth.

 It is evidenced from the Table 4.9 that on average the return on equity is 0.20794 indicating that the average return earned by the shareholders of the companies is 20.79% of their total equity with a maximum loss of 707.89% of their total equity and maximum profit of about 436.76% of their total equity. This indicates a high variation of performance among the companies as depicted by the value of standard deviation (146.98%) which is higher than the mean value. Table 4.7 also indicates that short-term debt recorded a mean of 3.513374 indicating that on average the companies’ short-term debt is 351.34%. It also has a minimum and maximum values of 0.4% and 13,677.34% respectively. A standard deviation of 1923.71% means that there is high variation in short-term debt among the companies since it is higher than the mean value.

Long-term debt recorded a mean of 0.13591 indicating that on average the companies’ long-term debt is 13.59%. It also has a minimum and maximum values of 0.1% and 56.06% respectively. A standard deviation of 13.86% means that there is slightly low variation in long-term debt among the companies since it is slightly higher to the mean value.

Debt ratio recorded an average percentage of 47.97%, implying that, most of the sampled companies have average proportion of debt in their capital structure. It also recorded a minimum value of 0.08% and maximum value of 576.25%. This indicates a high variation in debt ratio among the sampled companies as depicted by the value of standard deviation of (99.89%) which is higher than the mean value. The mean value of Earnings ratio is 79.54%. It has a minimum of 0.4% and a maximum of 276.05%. This indicates a low variation in retained earnings among the sampled companies as depicted by the value of standard deviation of (60.21%) which is lower than the mean value.

Debt to equity ratio recorded an average percentage of 351.55%, implying that, most of the sampled companies have high proportion of debt in their equity structure. It also recorded a minimum value of 0.21% and maximum value of 9,404.29%. This indicates a high variation in debt-to-equity ratio among the sampled companies as depicted by the value of standard deviation of (1,421.77%) which is higher than the mean value.

For the control variables, the mean of firm size is 21.12118 and a minimum and maximum values of 19.20855 and 22.45757 respectively. A standard deviation of 0.9913232 indicates a low level of dispersion in firm size of the industry during the study period as is lower than the mean value. Also, firm age recorded a mean of 24.1, implying that on average the companies have spent 24 years since incorporation. It also recorded a minimum of 4 years and maximum of 42 years since incorporation. This indicates a low variation in firm age among the sampled companies as depicted by the value of standard deviation 10 years which is lower than the mean value. Lastly, on average firm growth is 826.51%, with the highest value of 32,983.76%, showing the highest sale achieved over the period under study and the lowest of 9,832.64% negative (–9,832.64%) which indicate fall in sale growth over the period under study. This indicates a low variation in the firm growth among the sampled companies as depicted by the value of standard deviation of (5,446%) which is lower than the mean value.

REGRESSION RESULT

This section explains the impact of capital structure on Profitability of the sampled Listed industrial goods companies in Nigeria. The results were presented in Table 4.8. the interpretation will be based on Pooled OLS as suggested by LM test results shown in the appendix, which shows the prob>chi2 value of 1.000 it indicates that pooled OLS regression is preferable over random effect regression. Therefore, the interpretation is done using pooled OLS regression.

Table 4.8: Regression Results (ROE as Dependent Variable)

Source: STATA Output 14.0 based on data in the Appendix III. NOTE: ***, ** and * indicate 1%, 5% and 10% significance levels respectively. The t-values is presented in parenthesis while the other figures represent the coefficient.

The regression analysis above shows that R-Squared is 55% of the variations in return on equity (ROE) of listed industrial goods Companies in Nigeria were caused by the level of short-term debt (STD), Long term debt (LTD), Debt ratio (DR), Earning ratio (ER), Debt-to-equity ratio (DER) while 45% of the variation in return on equity (ROE) were affected by other factors outside our model. The adjusted R-Squared which indicates a figure lower than 50%, (i.e 37.88%) implies that short-term debt (STD), Long term debt (LTD), Debt ratio (DR), Earning ratio (ER), Debt-to-equity ratio (DER) while 45% of the variation in return on equity (ROE) were not the major determining factors of return on assets (ROE) of listed industrial goods Companies in Nigeria. The MS Statistic is 1.74700814 while F-Statistic is 3.21 at P-value of 0.0152.

R-square: 

Fixed-effects (within) regression               Number of obs     =         50

Group variable: code                                       Number of groups  =          5

R-sq:                                                                     Obs per group:

     within  = 0.5255                                         min =         10

     between = 0.6086                                         avg =       10.0

     overall = 0.2504                                         max =         10 

    F(7,38)           =       6.01

corr(u_i, Xb)  = -0.4454                        Prob > F          =     0.0001

——————————————————————————

         roe |           Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

————-+—————————————————————-

         std |     -.008151   .0088697    -0.92   0.364    -.0261069    .0098048

         ltd |     .65399   1.608719     0.41   0.687    -2.602692    3.910672

          dr |   .4288433    .180849     2.37   0.023     .0627337    .7949529

          er |   -.780462   .5960809    -1.31   0.198    -1.987165    .4262407

         der |  -.0782695   .0132474    -5.91   0.000    -.1050876   -.0514515

  revchanges |   .0029016   .0030919     0.94   0.354    -.0033576    .0091608

    logasset |  -1.837147   1.345073    -1.37   0.180    -4.560106    .8858117

       _cons |   17.65689   12.58338     1.40   0.169    -7.816835    43.13061

————-+—————————————————————-

     sigma_u |  1.0258489

     sigma_e |  1.0955677

         rho |  .46717119   (fraction of variance due to u_i)

——————————————————————————

F test that all u_i=0: F(4, 38) = 1.27                       Prob > F = 0.2969

. estimate store fe

. xtreg roe std ltd dr er der revchanges logasset, re

Test for heteroskedasticity.

      Source |       SS           df       MS      Number of obs   =        50

————-+———————————-   F(7, 42)        =      6.28

       Model |  54.1276815         7  7.73252593   Prob > F        =    0.0000

    Residual |  51.7298039        42    1.231662   R-squared       =    0.5113

————-+———————————-   Adj R-squared   =    0.4299

       Total |  105.857485        49  2.16035684   Root MSE        =    1.1098

——————————————————————————

         roe |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

————-+—————————————————————-

         std |  -.0078656   .0084295    -0.93   0.356     -.024877    .0091458

         ltd |  -.7155985   1.440211    -0.50   0.622    -3.622063    2.190866

          dr |   .4516302   .1715807     2.63   0.012     .1053662    .7978941

          er |    .120024   .2803609     0.43   0.671    -.4457673    .6858153

         der |  -.0737105   .0131394    -5.61   0.000    -.1002269   -.0471941

  revchanges |   .0031867    .003011     1.06   0.296    -.0028898    .0092632

    logasset |  -.3824281   .3903425    -0.98   0.333    -1.170171    .4053149

       _cons |   3.749521    3.63206     1.03   0.308    -3.580273    11.07932

——————————————————————————

 . hettest

 Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

         Ho: Constant variance

         Variables: fitted values of roe

         chi2(1)      =     0.53

         Prob > chi2  =   0.4683

. xtset code year

       panel variable:  code (strongly balanced)

        time variable:  year, 2012 to 2021

                delta:  1 unit

Test of Hypothesis

To accept or reject a hypothesis emphasis is on the significance of the t-stat. There are two basic approaches to determining whether the result is significant or not: compare the calculated t-stat with the tabulated t-stat and if the calculated t-stat is greater than the tabulated t-stat we accept the alternate hypothesis and reject the null hypothesis and conclude that the result is significant but if the calculated t-stat is less than the tabulated t-stat then we reject the alternate hypothesis and accept the null hypothesis and conclude that the result is insignificant. Secondly the result of the prob of t-stat is compared with 0.05 and if the result is less than 0.05 we accept the alternate hypothesis and reject the null hypothesis and conclude that the result is statistically significant but if it is greater than 0.05 we reject the alternate hypothesis and accept the null hypothesis and conclude that it is insignificant.

Finally, the t-calculated of debt and equity ratio (DER) from table 4.8 above indicates a value of –5.61 < 2.0000, while P-value indicates a figure of 0.000 less than 5% which is level of significance. This means that debt-to-equity ratio (DER) has negative and significant effect on return on equity (ROE). So, the researcher accepts alternate hypothesis (H₅) and rejects the null hypothesis five (H₀₅) which states that debt-to-equity ratio (DER) has no significant effect on return on assets (ROA) of Listed Industrial goods Companies in Nigeria. So, debt-to-equity ratio (DER) is one of the major determining factors for return on equity (ROE) of Listed Industrial goods companies in Nigeria.

However, short-term-debt, long-term-debt and equity ratio, the study accepted the null hypothesis that there is no significant effect of capital structure (STD, LTD and DR) on profitability of Listed Industrial Goods Companies in Nigeria. This finding concurs with that of Foo et al. (2015), Rufus and Ofoegbu (2017), Hamid (2015) and Ajibola et al. (2018) who documented that capital structure has no significant effect on Profitability.

While debt ratio and debt-to-equity ratio (DR and DER) from the results of the study indicate that it is one of the determining factors for return on equity. (ROE). This finding concurs with that of Erdogan (2015), Tariku (2016) and Swain and Das (2017) who found that capital structure has significant effect on profitability.

DISCUSSION OF FINDINGS

The findings from the specific objectives of this study are:

The findings for this work add credence to existing body of works that have this similitude in the area of accounting. The justification of its relevance, the researcher aligned the findings to the specific objectives of this study as earlier stated. This is with the view to determining how far the findings went in achieving the set objectives.

Objective One: To assess effect of short-term debt (STD) on return on equity (ROE) on listed industrial goods companies in Nigeria.

Our analysis indicates that short-term debt (STD) has a positive but statistically insignificant effect on the return on equity (ROE) for listed industrial goods companies in Nigeria. This means that changes in short-term borrowings do not lead to a statistically discernible impact on the profitability of these firms, as measured by ROE.

This finding aligns with theoretical perspectives like Modigliani and Miller’s (1958) irrelevance theory in a frictionless market, and views that primarily see short-term debt as a working capital management tool (e.g., Abor, 2005), limiting its direct strategic influence on ROE. Context-specific factors, where benefits and drawbacks of STD might offset each other, also contribute to this observed insignificance (e.g., Abdullah & Tursoy, 2021).

Conversely, this result contrasts with literature suggesting a significant impact from STD. Some studies, rooted in the Trade-Off Theory (Modigliani & Miller, 1963), argue that STD can positively impact ROE through tax shields and lower capital costs, particularly if firms are under-leveraged or use debt for efficient liquidity and growth management (e.g., Onaolapo & Kajola, 2010; Agyapong & Nartey, 2013). Other research highlights a significant negative effect, warning that excessive or volatile short-term debt can lead to severe financial risk, increased refinancing costs, and liquidity problems, ultimately diminishing ROE (e.g., Jensen & Meckling, 1976; Nguyen & Nguyen, 2020).

The observed insignificant effect suggests a unique dynamic within the Nigerian industrial goods sector where the potential advantages and disadvantages of short-term borrowing appear to neutralize each other. This warrants further investigation into the specific operational and financing strategies employed by firms in this industry.

Objective Two: To ascertain the effect of long-term debt (LTD) on return on equity (ROE) on listed industrial goods companies in Nigeria.

In addressing this objective, long-term debt (LTD), representing a component of capital structure, was designated as the independent variable, with return on equity (ROE) serving as the dependent variable for profitability. The regression results demonstrated that long-term debt (LTD) has a positive but statistically insignificant effect on the return on equity (ROE) of listed industrial goods companies in Nigeria.

This finding implies that an increase in long-term borrowings does not translate into a statistically significant increase in the return on equity for the sampled Nigerian industrial goods companies, and vice versa. This result aligns with the observations of Ifurueze et al. (2022) and Ahmed et al. (2021), who also reported similar insignificant relationships in their respective studies within the Nigerian context or similar developing economies. However, this finding stands in contrast to several studies conducted in different contexts. For instance, Khan et al. (2020) and Nguyen and Nguyen (2020) found a significant positive impact of long-term debt on firm performance and profitability in their respective studies, suggesting a different dynamic for companies operating in other regions or industries. This divergence highlights the context-specific nature of capital structure-profitability relationships.

Objective Three: To investigate the effect of equity ratio (ER) on return on equity (ROE) on listed industrial goods companies in Nigeria.

This study found that for listed industrial goods companies in Nigeria, the equity ratio has a positive but statistically insignificant effect on return on equity (ROE). In simpler terms, changing how much a company relies on equity for funding doesn’t seem to significantly impact its profitability in this sector.

This finding aligns with some research, like studies by Akinyomi and Olaiya (2016) and Onaolapo and Kajola (2010) in Nigeria, which also noted an insignificant link between equity and profitability. Myers’ (1984) pecking order theory further supports this by suggesting companies prefer internal financing.

However, this result contrasts with a significant amount of literature. Many studies, such as those by Abor (2005) and Majumdar and Chhibber (1999), have shown a positive and significant relationship between higher equity ratios and profitability, attributing it to lower financial risk. Even the trade-off theory (Modigliani & Miller, 1963) suggests an optimal equity level is crucial for balancing risk and returns, implying the relationship isn’t always insignificant.

The insignificance observed in the Nigerian industrial goods sector might be due to unique industry dynamics, the companies’ maturity, or prevailing economic conditions. Future research could investigate these factors to gain a deeper understanding.

Objective Four: To examine the effect of debt ratio (DR) on return on equity (ROE) on listed industrial goods companies in Nigeria.

Our analysis revealed a positive and statistically significant effect of the debt ratio (DR) on the return on equity (ROE) for listed industrial goods companies in Nigeria. This suggests that increasing the proportion of debt in their capital structure can significantly enhance their profitability, indicating a beneficial use of leverage within this sector.

This finding aligns with the Trade-Off Theory (Modigliani & Miller, 1963; Myers, 1984), which attributes debt’s benefits to tax shields and a lower cost of capital, potentially increasing returns to equity holders. It also supports the Agency Cost Theory (Jensen & Meckling, 1976), where debt can improve managerial efficiency. Empirical evidence from other developing economies, such as studies by Onaolapo and Kajola (2010) in Nigeria and Agyapong and Nartey (2013) in Ghana, further corroborates this positive relationship, often due to the cost advantages of debt or current under-leveraging.

However, this result contrasts with the pure Modigliani and Miller (1958) irrelevance theory, which posits capital structure doesn’t affect firm value. It also differs from the Pecking Order Theory (Myers, 1984), which, while favoring debt over external equity, doesn’t necessarily predict an indefinite positive effect of increasing debt. Furthermore, a substantial body of literature, including Jensen’s (1986) free cash flow hypothesis and studies like Gleason et al. (2000), warns that excessively high debt levels can lead to financial distress, increased bankruptcy risk, and ultimately, a significant negative impact on profitability. The positive effect observed in this study suggests that Nigerian industrial goods firms are operating within the beneficial range of debt, where its advantages outweigh the associated risks.

Objective Five: To determine the effect of debt-equity ratio (DER) on return on equity (ROE) on listed industrial goods companies in Nigeria.

Our analysis revealed a negative and statistically significant effect of the debt-equity ratio (DER) on the return on equity (ROE) for listed industrial goods companies in Nigeria. This implies that as the proportion of debt relative to equity increases, the profitability of these firms, measured by ROE, significantly decreases. This finding suggests that excessive reliance on debt financing can be detrimental to the profitability of Nigerian industrial goods firms.

This result is largely supported by the Trade-Off Theory (Modigliani & Miller, 1963; Myers, 1984), which posits that beyond an optimal point, the costs of financial distress associated with high debt levels (e.g., bankruptcy risk, increased borrowing costs) outweigh the benefits, thereby reducing ROE. Concerns about financial risk and solvency further underpin this, as high DER indicates greater leverage, leading to increased fixed interest obligations that can erode profits and diminish investor confidence. Empirical studies by Jensen (1986) (free cash flow hypothesis), Titman and Wessels (1988), Gleason et al. (2000), and Chakraborty (2010) similarly demonstrate that very high leverage negatively impacts profitability due to heightened financial risk and interest burdens.

Conversely, some theories and empirical findings offer a contrasting view. The Trade-Off Theory (within the optimal range) itself suggests that initial increases in debt can be beneficial due to tax shields, potentially leading to a positive ROE effect up to a certain point. The Agency Cost Theory (Jensen & Meckling, 1976) also argues that debt can discipline managers and enhance efficiency, which could positively influence ROE. Additionally, Signaling Theory (Ross, 1977) suggests that debt issuance can signal firm quality. While our study specifically highlights a negative impact at the observed DER levels, other empirical evidence, such as Onaolapo and Kajola (2010) and Agyapong and Nartey (2013), has shown a positive relationship between debt financing and profitability in different contexts, often when firms are potentially under-leveraged.

The significant negative effect of DER on ROE in the Nigerian industrial goods sector underscores the critical importance of prudent financial leverage management, suggesting that these firms may be experiencing the adverse consequences of high debt.

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

This section consolidates the key findings, draws definitive conclusions based on the empirical analysis, and provides actionable recommendations for listed industrial goods companies in Nigeria regarding their capital structure management. It also outlines the study’s contribution to existing literature and suggests areas for future research.

Summary of Findings

The study investigated the impact of various capital structure components on the Return on Equity (ROE) of listed industrial goods companies in Nigeria from 2012 to 2021. The empirical analysis revealed the following key insights:

Short-Term Debt (STD): Short-term debt exhibited a positive but statistically insignificant effect on ROE. This finding aligns with Ahmed, Alhaji, and Eliphus (2021), Abor (2005), Sunardi et al. (2020), and Chandra et al. (2021). But contradicts Ahmed, Alhaji, and Eliphus (2021), Lorenza et al. (2020), Nguyen & Nguyen (2020), and Cahyani and Winarto (2017). This suggests that marginal changes in short-term borrowings do not significantly alter the return to equity holders for the companies examined. While a positive relationship was observed, its lack of significance implies that increasing short-term debt may lead to a slight decrease in ROE, and vice-versa, but this effect is not robust enough to be considered statistically meaningful.

Long-Term Debt (LTD): Similar to short-term debt, long-term debt also showed a positive but statistically insignificant effect on ROE. This indicates that incremental changes in long-term borrowings do not have a statistically significant impact on the profitability for equity holders in these Nigerian industrial goods firms.

Equity Ratio (ER): The equity ratio demonstrated a positive but statistically insignificant effect on ROE. This implies that while a higher proportion of equity might generally be associated with better returns, the observed effect is not statistically significant. This suggests that solely increasing the equity ratio without considering other factors may not lead to a significant improvement in ROE.

Debt Ratio (DR): In contrast to short-term and long-term debt individually, the overall debt ratio (DR) had a positive and statistically significant effect on ROE. This finding suggests that a balanced mix of debt, when considered as a total proportion of assets, can positively influence the return on equity for these companies.

Debt-to-Equity Ratio (DER): The debt-to-equity ratio (DER) was found to have a negative and statistically significant effect on ROE. This critical finding indicates that a higher proportion of debt relative to equity is associated with a statistically significant decrease in the return to equity holders. Conversely, maintaining an optimal or lower debt-to-equity ratio appears to enhance ROE.

Conclusions

Based on the summarized findings, the following conclusions are drawn regarding the effect of capital structure on the financial performance (proxied by ROE) of listed industrial goods companies in Nigeria:

The individual components of short-term debt (STD) and long-term debt (LTD), while showing a positive relationship, do not significantly impact the Return on Equity (ROE) of listed industrial goods companies in Nigeria. This suggests that companies with substantial amounts of either short-term or long-term debt alone in their capital structure may experience lower returns on equity, though this effect is not statistically significant on its own.

Similarly, equity ratio (ER), when considered in isolation, has a positive but statistically insignificant effect on ROE. This implies that companies solely funded by equity may not necessarily achieve higher returns on equity, highlighting the importance of a balanced capital structure.

However, the debt ratio (DR), representing the total proportion of debt in the capital structure, has a positive and statistically significant effect on ROE. This indicates that strategically incorporating a mix of both short-term and long-term debt can lead to enhanced returns for equity holders.

Crucially, the debt-to-equity ratio (DER) demonstrates a negative and statistically significant effect on ROE. This strongly suggests that an excessive reliance on debt relative to equity negatively impacts shareholder returns. Conversely, achieving an optimal capital structure, where the balance between debt and equity is carefully managed, is essential for maximizing ROE.

Recommendations

Based on the empirical findings and conclusions of this study, the following recommendations are presented for the management of listed industrial goods companies in Nigeria, aiming to optimize their capital structure and enhance profitability:

Avoid Extreme Capital Structure Reliance: Companies should refrain from an imbalanced reliance on either pure debt or pure equity financing. The individual lack of statistical significance for short-term and long-term debt on Return on Equity (ROE) suggests that singular reliance on these instruments may not optimize returns. Similarly, an exclusive focus on equity funding might preclude the realization of optimal ROE.

Optimize Overall Debt Proportion: A strategic and judicious incorporation of debt within the overall capital structure is recommended. The study reveals a positive and significant effect of the debt ratio on ROE, indicating that a carefully considered mix of debt instruments can contribute to improved profitability. This necessitates a comprehensive evaluation of the combined impact of various debt sources.

Prioritize an Optimal Debt-to-Equity Ratio: Maintaining an optimal Debt-to-Equity Ratio (DER) is critical for listed industrial goods companies. The observed negative and significant impact of a high DER on ROE underscores the detrimental effects of excessive leverage. Firms should strive for a balanced capital structure where the cost of equity (Ke​) is appropriately weighted against the cost of debt (Kd​) to maximize shareholder value.

Strategic Capital Structure Management: Companies should adopt a proactive and strategic approach to capital structure decisions. This involves continuous monitoring and dynamic adjustment of the debt-to-equity mix. Such a strategy should align with the company’s inherent risk profile, growth objectives, and the prevailing macroeconomic conditions, ultimately fostering sustainable profitability and increased shareholder returns.

Contribution to Knowledge

This study makes a significant contribution to the existing body of literature concerning capital structure, particularly within the Nigerian context. Prior to this research, a comprehensive investigation into the effect of capital structure on the profitability of listed industrial goods (specifically paint) companies in Nigeria between 2012 and 2021 had not been undertaken.

The findings provide novel insights, revealing that specific capital structure components—namely short-term debt (STD), long-term debt (LTD), and equity ratio (ER)—demonstrate an insignificant effect on the Return on Equity (ROE) for these Nigerian firms. Crucially, the study highlights a significant negative impact of the Debt-to-Equity Ratio (DER) on the ROE of industrial goods companies listed on the Nigerian Stock Exchange. This nuanced understanding offers invaluable insights for future researchers reviewing literature on capital structure and its impact on corporate performance in developing economies.

Areas for Further Studies

While this study focused on the effect of capital structure on the profitability of listed industrial goods companies in Nigeria, using Return on Equity (ROE) as a primary proxy, several avenues for future research are identified to expand upon these findings:

Alternative Profitability Proxies: Future studies could investigate the relationship between capital structure and profitability using alternative proxies such as Return on Assets (ROA), Operating Profit, or Net Profit. This would offer a more comprehensive understanding of profitability dynamics across different financial metrics.

Sector-Specific Analyses: Expanding research to other sectors of the Nigerian economy, such as telecommunications, would provide valuable comparative insights. Examining the effect of capital structure on profitability, using various proxies like ROA and ROE, across different industries could reveal sector-specific nuances.

Moderating and Mediating Variables: Future research could explore the moderating or mediating effects of additional variables, including firm size, firm age, corporate governance mechanisms, or broader macroeconomic factors, on the complex relationship between capital structure and financial performance.

Qualitative or Mixed-Methods Approaches: Incorporating qualitative research methods, such as in-depth interviews with financial managers, could provide richer contextual insights into the underlying decision-making processes regarding capital structure within Nigerian companies.

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