Capital Structure and Financial Performance of Manufacturing Companies in Nepal

ABSTRACT


INTRODUCTION
Capital Structure (CS) is a mix of long-term sources of financing for the corporation.The CS decision is one of the crucial domains in corporate finance and draws more attention in the finance literature.Saad [1] stated capital structure is the financial framework of a firm's debt and equity.In other words, CS is a combination of equity, debt, and hybrid securities a company uses to manage its assets.Thus, CS is a mix of debts, preferred stock, and equity a company uses.A sound CS is a debatable and critical decision for any business that ultimately increases the profitability and value of the company.The company can use various available sources of financing to raise capital and fulfill its financing requirements.The firm can raise its capital by issuing common equity or debt or preferred stock or composition of them, increasing its efficiency, profitability, and market value.Thus, the optimal CS (capital structure) decision is essential to make sound financing decisions about how a firm finances from various sources to minimize its overall cost of capital for the smooth operation of business activities by efficiently utilizing various resources for shareholders' wealth maximization.
Modigliani and Miller (MM) introduced contemporary capital structure theory in 1958.Modigliani and Miller [2] revealed capital structure irrelevant theory and argued that a firm's value is irrelevance with capital structure when asset earnings and future investment opportunities remain constant.MM theory assumes a lack of taxes, bankruptcy expenses (costs), and asymmetric information.The market should be more efficient and perfect, and a company's value should not be affected by financing decisions, whether the company's capital is from equity debt or a combination of them.Financial leverage does not affect the size of operating income and business risks, and the interest cost of debt does not affect the company's value.MM's theory argues that any composition of debt and equity does not affect the company's total value.Division of CS into equity and debt is unimportant, and it does not matter.Capital structure changes do not affect a firm's values.If two firms are identical, then the total values of the two firms must be the same.If not, arbitrage will occur, driving equal values of the two firms.
Modigliani and Miller [3] revised theory of capital structure based on earlier preposition with the incorporation of tax benefits.In this proposition, MM argued that interest on debt tax-exempted expense means the firm can make tax shield benefits using more debt, accelerating firm value.The firm's cost of funds (capital) decreases due to corporate taxes with more use of debt in its capital structure.The value of a levered company equals the combined value of an unlevered company and the tax shield.MM argued there are no bankruptcy costs.However, in practice, the larger the use of debt, the higher the bankruptcy costs, which affect the firm's value, resulting in difficulties in meeting obligations of interest and principal payments in time.Finally, it may lead to the liquidation of the firm.Thus, the value of the levered firm should be determined by incorporating both tax shield and bankruptcy costs.
The MM theory is broadly accepted in modern theories of CS, and most researchers still use the MM hypothesis in empirical analysis of CS.The trade-off theory of CS suggests that the best capital structure balances tax advantages (tax shield) and the value of bankruptcy costs in the use of debt financing [4], [5].This theory argues that optimal CS is formulated with the interaction of competitive forces and intends to maximize tax advantages by more effectively applying debt financing.Bankruptcy expenses (costs) create pressure on financing decisions.[6] developed agency costs (AC) theory and explored the nature of agency costs arising from both debt and equity in a firm.The study scrutinized the conflicting interests between owners and managers and between owners and creditors, significantly influencing the firm's financial structure.Thus, these factors must be carefully considered when determining the optimum capital structure decision.The pecking order (PO) theory is another hypothesis of capital structure developed by Myers and Majluf [7].PO theory states that a company does not necessarily require a specific target debt ratio.The company prefers to use more retained earnings (internal equity) as prime financing sources.If there are insufficient retained earnings, the firm raises funds from debt (less risky sources); if both retained earnings and debt capital are inadequate, the firm finally raises funds from external equity financing (highly risky source).In these theoretical debates, an issue may arise in determining new funding from debt or equity financing to maintain the optimal CS (capital structure).

Jensen and Meckling
The trade-off (TO) theory of CS argues the optimal CS of a company is formulated based on market imperfections (taxes, agency costs, financial distress costs, etc.).Taxes, bankruptcy, and AC (agency costs) influence financial leverage.This theory argues that optimal CS is the best debt-equity mix, formulated with the trading-off of debt benefits against its costs [8].In other words, the optimum capital structure can be formulated by considering corporation tax, bankrupt costs, and agency costs.
The information asymmetry hypothesis of CS assumes managers may have information about the firm's characteristics, such as investment opportunities and return streams, but may not have information on common investors.In real life, some financing behaviors are inconsistent with the TO (trade-off) theory of CS (capital structure).Myers and Majluf [7] and Myers [9] observed internal and external funds are used hierarchically.Myers [9] Developed the pecking order hypothesis and argued firms prioritize internal financing over external equity financing.At first, retained earnings (internal funds) should be used; when internal funds are depleted, debt financing is used; if the issue of more debt is not possible, the company can issue shares to use external equity capital.More profitable companies should use small debt and more internal equity capital because more profitable companies can use more internal equity funds (retained earnings).Pinegar and Wilbrich [10] argued managers prefer a financing hierarchy to maintain the target debt-equity ratio.Other researchers supported the pecking order hypothesis and supported the existence of the significance of information asymmetric [11], [12], [13], [14], [15].
Previous empirical studies on capital structure have been administered to analyze the relationship between CS and financial performance.Several theoretical and empirical literature studies have shown the theoretical controversy on CS and financial performance.Most of the research on CS is based on data from developed countries.Myers and Majluf [7] stated companies prefer to finance from retained earnings (internal equity) and use debt only when internal equity is insufficient.Thus, it is expected that there is a contrary relationship between CS and financial performance.Jensen [16] and Williamson [17] revealed that capital structure and corporate performance are positively related.Rajan and Zingales [12] used data from the G-7 countries and observed the inverse effect of financial leverage or CS on the firm's economic performance.
In investigating the relationship of culture and CS with financial performance, Gleason et al. [18] analyzed the inter-relationship of culture, CS, and performance by obtaining data from retailers in European countries.The result reveals CS differs as the different cultures of retailers strengthen with the inclusion of control variables that influence the CS of the firms.In addition, the result concludes the performance of retailers is not affected by cultural influence and CS.
Booth et al. [13] administered research work using data from developing economies and revealed a positive association between a corporation's earnings (performance) and CS.Pandey [14] used data from Malaysia and observed a negative relationship between CS and a firm's financial performance (profitability), which supports the pecking order hypothesis.Bevan et al. [19] used data from the UK and observed a significant negative relation between capital structure and a firm's financial performance or profitability.
An analysis of the effect of CS on the profitability of listed companies in Ghana revealed short-term debt to assets is significantly positively related to ROE [20].The study's findings indicate that firms with higher earnings levels can use relatively more short-term debt financing in their business, which means short-term debt would be the best alternative financing source.Further, the findings show an adverse influence of long-term debt to assets on financial performance in terms of ROE.Finally, the result shows debt to assets has a positive association with ROE, which implies a direct relation between total debt and financial performance in business firms.
Coleman [21] investigated the influencing role of capital structure in the financial performance of microfinance and revealed a positive association of CS with a firm's performance, which indicates the positive influencing power of debt (financial leverage) in explaining a firm's financial performance.CS plays a significant negative role in determining a firm's financial performance (both in accounting and market measures) [22].
In an analysis of the influence of CS (capital structure) and operational risk on financial profitability, Chen et al. [23] researched using factor and path analysis was administered, and it revealed that a firm's CS does not influence its value.Still, a relationship exists between operational risk and CS and firm profitability.CS has an inverse association with profitability, which indicates that the use of more equity (less use of reserve-to-liability) ratio results in a higher financial performance (profitability) level of the firm.This finding concludes CS is inversely associated with operational risk and has a similar association of operational risk with a firm's financial performance.
Azeez et al. [24] analyzed the impact of CS's choice of equity or debt on US firms' financial performance using inferential techniques (multiple regression models) to investigate the role of CS in determining the level of corporate financial performance and revealed mixed results.The study shows that a higher level of gearing of leverage has a significant negative influence on financial performance in terms of ROE (return on assets).In the study of the impact of CS on listed companies' financial performance in Roman, Vatavu [25] applied a cross-section regression technique and observed that companies can accelerate their financial performance when they can use higher level equity only and debt is avoided.The result of the study shows a preference for the use of debt.Firms use equity capital only when facing more business risk and having financial difficulties using more debt capital.The study concludes that debt (financial leverage) has a significant negative role in explaining corporate financial performance.
Pradhan and Pokharel [26] examined factors determining a bank's performance using pooled cross-sectional data and revealed that the capital structure and size of the firm negatively influence ROA.In contrast, credit risk has a positive impact on ROA.Capital structure (debt to assets, short-term debt to assets, long-term debt to assets) has an inverse effect on EPS, showing that an increase in debt decreases EPS.Furthermore, the result confirms short-term and long-term financial leverages are negatively related to banks' net interest margin (NIM).Finally, the result concludes that bank size and credit risk are key factors determining financial performance, and using more leverage negatively influences financial performance in Nepalese commercial banks.
In the examination of the effect of CS on financial performance, Nasimi [27] examined the relationship of CS with financial performance and reported the negative influence of debt-equity on ROA (return on assets) and a significant positive impact on ROE (return on equity).Moreover, the result of the study confirms a significant positive influence of interest coverage on financial performance in terms of ROCI, ROE, and ROA.The study's insights conclude optimum CS needs to be formulated and maintained to accelerate the company's financial performance.Semuel and Widjojo [28] analyzed the relation of a firm's CS with its financial performance and revealed a significant positive role of CS in explaining the financial performance of firms.
In an examination of CS and the performance of the companies, Kalyani and Mathur [29] used data from seven Indian firms.Correlation and regression results show the significant role of sales, operating leverage, and asset growth in explaining the financial performance of companies.Basit and Irwan [30] investigated the effect of CS on the economic performance of Malaysian companies using descriptive and regression analysis and revealed several insights.Firstly, the result shows the inverse relationship between debt-equity on both ROA and ROE.Secondly, the debt ratio observes a weak effect on ROA but a significant positive influence on ROE.Furthermore, the result demonstrates that debt-to-equity adversely affects EPS.In the investigation of CS and its influences on the financial performance of companies in the pharmaceutical sector, Ghayas and Akhter [31] observed debt to assets positively impacts financial performance, and long-term debt to assets has an inverse nexus with ROE measures as economic performance.
Jaishi and Poudel [32] investigated the relationship of a firm's CS with financial performance based on annual data of listed non-financial companies for the study period 2005-2018.They observed that most efficient firms use less and less financial leverage.This study concludes that companies using higher leverage are less efficient.Bhattarai [33] reported a significant effect of CS on insurance companies' FP (financial performance) in Nepal.Companies with more debt in their capital structure can have better financial performance [34].In the analysis of the impact of CS on financial performance, Ali and Faisal [35] revealed that using more debt in CS reduces the cost of capital and contributes to financial performance growth.Firms' Capital structure significantly influences their financial performance in the Nepalese context [36].
Olaoye and Adesina [37] investigated how the capital structure of manufacturing companies influenced their financial performance and revealed an insignificant inverse effect of debt to equity on ROA, a significant positive influence on ROE, and no impact on net profit margin.Therefore, companies should focus on determining the optimal capital mix (structure) for enhanced financial performance in manufacturing firms.
In examining CS's effect on firms' financial performance, Anozie et al. [38] applied the ex-post facto method to analyze secondary data for the period 2011-2020 and revealed long-term debt has a significant role in ROA and short-term debt to assets as well.Debt-equity both have a positive but insignificant influence on financial performance.The result suggests reducing companies' long-term debt to maximize their financial performance.Bashyal and Bhandari [39] investigated the impact of CS (capital mix) on financial performance by applying pooled OLS, REM (random effect models), and FEM (fixed effect models) with the application of both descriptive and causality designs and reported debt ratio has significant negative and equity to assets has substantial positive impact on firms' financial performance.Still, the size of firms has a positive but insignificant influence on firms' financial performance.
Previous empirical studies investigating the relationship between CS and financial performance show inconclusive results.The Nepalese capital market is still in the premature development stage, and many firms are not listed in NEPSE.In this prospect, it is important to explore the influencing power of CS in explaining firms, financial performance.Therefore, the present study examines the impact of firms' capital structure on economic performance in Nepalese manufacturing companies.
Research Objectives: This study intends to investigate how CS affects the financial performance of manufacturing companies in Nepal.The following sections are outlined: Section two discusses the research methodology.Section three presents the analysis of results and subsequent discussion.Finally, section four concludes the results and the study's implications.

METHOD
This research employs both descriptive and causal-comparative research designs.The descriptive analysis explores the relationship between CS and financial performance in Nepalese manufacturing companies.In addition, the causal-comparative research design is implemented to assess how different aspects of capital structure (such as long-term debt to total capital, debt to total asset, debt to common equity, and long-term debt to common equity) influence the financial performance (net profit margin and return on capital) in Nepalese manufacturing companies.
This paper has used secondary panel data from annual reports published by SEBON (Security Board of Nepal) and sample companies' financial statements covering 15 years of data for 2008-2022.All the manufacturing and processing companies listed in NEPSE till mid-July 2022 are regarded as the population of this research.The total number of listed companies till mid-July was 234; 19 companies are listed and working as manufacturing and processing companies, and 15 listed manufacturing and processing companies are used as the sample of this research.In this study, a total of 195 observations have been used to investigate the relationship and to examine the impact of CS on the financial performance (FP) of manufacturing companies in Nepal.
This study applies Pearson's correlation analysis to explore the relationship between CS and FP.Furthermore, it utilizes pooled ordinary least square regression models to investigate how CS affects the FP of manufacturing companies in Nepal.The data collected is processed and analyzed using SPSS software (version 20) and MS Excel.This paper employs regression analysis along with t-statistics, F-statistics, Adjusted R2 to scrutinize the impact of CS on the financial performance of manufacturing companies in Nepal.
This paper uses return on capital (ROC) and net profit margin (NPM) to measure financial performance; both are independent variables.ROC is net income to the total capital of firms.NPM is the net income to sales ratio of sample manufacturing companies.The ROC is the percentage of net income on total capital employed.Theoretical and empirical literature confirms several factors that influence firms' financial performance.This study employs debt to assets (DA), debt to common equity (DCE), long-term debt to common equity (LDCE), and long-term debt to capital (LDC) as predictor (explanatory or independent) variables.
This paper uses regression models to examine the impact of explanatory variables and how they influence financial performance in the manufacturing sector of Nepal, which are stated as follows: ROC indicates the return on capital, NPM represents net profit margin, DA stands for debt to total assets, DCE is debt to common equity, LDCE indicates long-term debt to common equity, LDC stands for long-term debt to total capital, β0 represents the coefficient of the constant term, β1, β2, β3, β4 are regression coefficients of explanatory (predictor) variables, and ɛt indicates error terms.

RESULTS AND DISCUSSION
This section analyses the associations between capital structure and its factors affecting corporate performance.This study uses correlation analysis to investigate the relationship between variables.Regression analysis based on a causality research design is used to examine the impact of CS on the financial performance of manufacturing companies in Nepal.

Analysis of the Relationship of Variables
This study used various capital structures (DA, DCE, LDCE, & LDC) to analyze their relationship with the FP of manufacturing companies in Nepal.Table 1 exhibits Pearson's correlation coefficients of variables that measure the relationship between CS and the financial performance of manufacturing companies in Nepal.The correlation coefficient results are substantial, and using various debts in CS reduces financial performance in Nepalese manufacturing firms.

Analysis of the Impact of Capital Structure on Financial Performance
This research employs regression models to examine the impact of explanatory variables on financial performance (FP).Table 2 exhibits regression results as pre-specified equations to explain the influence of capital structure on FP measured by the return on capital of manufacturing companies in Nepal.Table 2 presents regression results.The regression coefficient shows the statistically significant positive impact of DCE on ROC at 1%, which indicates the usage of more debt in capital structure that intends to increase financial performance in Nepalese manufacturing companies.In addition, regression coefficients show that DA, LDCE, and LDC hurt ROC.Results are statistically significant and are consistent with the output (findings) of Rajan and Zingales [12], Booth et al. [13], and Chen [15], which implies that DA, LDCE, and LDC have strong explanatory power of financial performance in Nepalese manufacturing firms.Therefore, Nepalese manufacturing companies must reduce DA, LDCE, and LDC to maximize economic performance.On the contrary, the result of this paper is inconsistent with the prior findings of Coleman [21], who observed a direct (positive) relationship between CS and the financial performance of the companies.
Adjusted R 2 stands for coefficient of determinants of multiple regression models, which is 0.437.This implies predicting the capacity of explanatory variables used in models is 43.7 percent to explain financial performance as return on capital employed in manufacturing firms.The f-statistic of regression models is 14.463, significant at a 1% level (P-value < 0.01).This implies regression models applied in the estimation of return on capital employed as financial performance with selected explanatory variables have the fitness of tests of the overall models of this study.Table 3 of this paper presents estimated regression results on financial performance measured by net profit margin (NPM).The regression coefficient shows the statistically significant positive effect of DCE on NPM at 1%, which indicates more debt use in the firm's CS (capital structure) intends to increase the financial performance of Nepalese manufacturing companies.In addition, regression coefficients show that DA, LDCE, and LDC negatively impact NPM and are statistically significant.These results are consistent with the outcomes of Rajan and Zingales [12] and Booth et al. [13], which implies that DA, LDCE, and LDC have a powerful explaining capacity of financial performance as NPM in Nepalese manufacturing companies.Therefore, Nepalese manufacturing companies must reduce DA, LDCE, and LDC to accelerate financial performance.The research findings contradict the prior result of Coleman [21], who revealed a direct association between CS financial performances of manufacturing companies in Nepal.
Adjusted R 2 stands for coefficient of determinants of multiple regression models, which is 0.397.This implies that the predicting capacity of explanatory variables used in regression models is 39.7 percent to explain financial performance as net profit margin in Nepalese manufacturing companies.F-statistic of the regression models is 12.964, which is significant at 1% (P-value < 0.01).This result implies that the regression models applied in the estimation of net profit margin as financial performance with the various selected explanatory variables have the fitness of tests of the overall models.

Table 1 demonstrates
Pearson's correlation coefficient of pairs of financial performance and explanatory variables.Correlation results indicate that ROC and NPM are positively related to debt to common equity (DCE) and statistically significant at a 5 percent level.Both ROC and NPM are negatively associated with DA, LDCE, and LDC.

Table 2 .
Regression Results Return on Capital with Explanatory Variables.

Table 3 .
Regression Results Net Profit Margin with Explanatory Variables.Regression coefficient estimation based on data obtained from SEBON (2008-2022).Net profit margin is a dependent variable, and DA, DCE, LDCE, and LDC are explanatory variables.P-values <0.01 and Pvalues <0.05 indicate that regression results are significant at 1% and 5%, respectively.The regression coefficients, standard errors, t-statistics, F-statistics, and Adjusted R2 are also reported.