Effect of corporate governance on the capital structure on non-financial firms in developing countries: A Qualitative Approach ()
1. Introduction
The study examines how corporate governance influences the capital structure of quoted non-financial in developing countries. Over the years, capital structure studies have remained a largely unresolved puzzle. There is no consensus on how firms choose their debt, equity, or hybrid securities (DeAngelo, 2021). The financial choices concerning the optimum capital structure mix lack unanimity on theoretical underpinnings supporting the financing decision and mix of firms, thereby making capital structure mystifying. However, a capital structure comprises a firm’s financing mix, which depends on contending variables that may affect the firm’s objective, the puzzle set by Miller and Modigliani (Miller & Modigliani, 1961; Modigliani & Miller, 1958) and revisited by scholars (Hossain, 2021) has remained even more puzzling. Understanding capital structure will help make a predictive decision on equity or debt mix supported by a theoretical framework without ambiguity.
A more recent focus of scholars is on the influence of corporate governance in determining the capital structure decision of firms (Akinto, 2021; Ozili, 2021; Ehikioya et al., 2021). Corporate governance entails the combination of board structure or composition, CEO characteristics, board diversity, and age combination of the management team, as well as their actions and inactions (Ozili, 2021). The interrelationship amongst these prevailing variables in the design and execution of policy actions on debt or equity decisions remains increasingly attractive to scholars. Therefore, corporate governance structure and practices are prone to various intervening variables like the age of board members, size, and composition. Thus, a good corporate governance policy is necessary to guide top management in making effective capital structure decisions that will aid in achieving the financial goal of the firm.
In much of the research in recent years on the nexus between corporate governance and capital structure, scholars reviewed the influence of intervening variables of corporate governance on capital structure, precisely gender diversity (Zaid et al., 2020; García & Herrero, 2021); board attributes (Ali et al., 2021a; Ali et al., 2021b); board quality (Gyimah et al., 2021; Nguyen et al., 2021); board composition and characteristics (Ezeani et al., 2022; Grabinska et al., 2021; Lartey et al., 2020); and board ownership structure (Ibrahimy & Aidi, 2021). However, most of the results are inconsistent. The implication is that the relationship between corporate governance and capital structure cannot be generalised.
The study’s main objective was to investigate corporate governance’s effect on capital structure using empirical findings from previous studies from 2011 to 2022. The specific objective was to examine the effect of board size on leverage. Consequently, the research question based on the proxies selected is to what extent does board size influence the leverage of developing countries? Following the introduction above, the rest of the study is arranged using the following structure: the literature review, the methodological approach selected for the study, results, discussion and implications of findings, and conclusion.
2. Literature Review
Corporate governance is the process used to compose the best mix of board members for the governing and managing firms to achieve the organisational goal (Wang & Ramzan, 2020). This composition comprises the board of directors, considered the main players in the firm’s management. Feng et al. (2020) define corporate governance based on the crucial role it plays in the monitoring and guiding of managers to reduce conflicts of interests in decision-making. The study believes corporate governance is a critical mechanism for monitoring the firm’s performance and tools for resolving agency problems.
Corporate governance is also viewed as a mechanism for protecting the interest of all stakeholders (Shahid et al., 2019). The stakeholders include managers, customers, investors, and regulators. Managing stakeholders’ interest helps in mitigating conflicts which could affect the firm’s performance. Good corporate governance attributes are connected to the stakeholder’s behaviour and institutional influence, personal and moral virtues, and structural factors (Steckler & Clark, 2019).
The thematic areas of corporate governance include firm performance, regulatory obligations, and investment decisions (Akinto, 2021). Farah et al. (2021), in their study on corporate governance in the Middle East and North Africa, stated that ownership comprises concentration, family businesses, and State-owned enterprises (SOEs) are common themes of corporate governance. Also, board characteristics like the Chief Executive Officer (CEO) duality, audit committee, financing and capital structure, level of financial development, board size, gender diversity, disclosure and compliance, and corporate social responsibility (CSR) are other attributes of corporate governance.
Studies have identified links to the measurement of corporate governance as ownership structure, managerial and institutional shareholding size, board composition comprising board size, outside directors, Chief Executive Officer (CEO) duality, frequency of board meetings, board experience and gender diversity (Albanez & Schiozer, 2022; Ezeani et al., 2022; Grabinska et al., 2021; Ibrahimy & Aidi, 2021; Thakolwiroj & Sithipolvanichhgul, 2021). Gyimah et al. (2021) measured the quality of corporate governance using the G-Index and E-index.
Board size directly correlates with capital structure (Feng et al., 2020). Wang & Ramzan (2020) categorised the arguments on board size into two schools of thought. The first school argued that the larger the board size, the more efficient firms perform, while the second group noted that small board sizes are more effective for decision-making. Nooitgedagt (2020) reasoned that a bigger board size would do better to reduce the firms’ leverage, but this could result in a more serious agency problem due to control. Supporting the argument, Feng et al. (2020) highlighted that a large board ensures more supervision and monitoring. The cost of managing large board sizes, conflict, and slow decision-making makes the smaller board size more effective. A large board size may create agency problems due to corporate control and ownership (Feng et al., 2020).
In a theoretical argument on the board size, Zaid et al. (2020) stated that agency theory postulates that larger board size has a more significant opportunity to minimise agency costs. The study mentioned that the capital structure philosophy allows creditors to recognise that companies with large board sizes are likely to monitor the firm’s operations and reduce agency conflict effectively. Larger board size will reduce the debt cost, promoting access to financing. On the contrary, boards with smaller sizes are likely to have a more informed opinion than those with a larger size (Thakolwiroj & Sithipolvanichhgul, 2021).
Capital structure is the permutation of equity and debt, which is used to derive the cost of capital (Oino & Ukaegbu, 2015). Giovanni et al. (2020) define capital structure as a fundamental aspect of corporate financial decisions that maximises firm value and minimises capital costs by determining the appropriate proportion of debt and equity to minimise the company’s financial difficulties. Also, Shahar and Manja (2018) define capital structure as the financial decisions regarding the raising of funds from several sources, comprising internal (retained earnings) and external financing (debt and equity). Wrong capital structure decisions will harm the company.
Some factors determine the capital structure decision. These include information asymmetry, cost of distress, profitability, strong financial needs, macroeconomic needs, distance form, and growth opportunities (Haron et al., 2013; Lemma & Negash, 2014). Also, transaction costs, including legal, financial environment, and investment bank fees, may prevent firms from adjusting their target leverage continuously, especially if these costs are prohibitively high (Oino & Ukaegbu, 2015; Öztekin & Flannery, 2012). Traditionally, growth, size, tangibility, profitability, industry median, debt ratio, and expected inflation are also factors that determine capital structure decisions (Bajaj et al., 2020; Bolarinwa & Adegboye, 2020; Frank & Goyal, 2009).
Previous works identified debt-to-equity ratios as measures of capital structure (Danila et al., 2020; Hussain et al., 2020). Dao and Ta (2020) adopted accounting and market-based measures for capital structure studies. The market proxy is measured as the return on assets and return on equity, while the Tobin Q is also measured as market-based proxies. On the other hand, leverage with related measures of short-term, long-term, and total debt leverage of the firms is used to explain capital structure (Bolarinwa & Adegbboye, 2020; García & Herrero, 2021; McGuinness, 2021; Warmana et al., 2020). In addition, Li et al. (2020) measure capital structure using debt finance, which is computed as the total debt ratio. Other scholars like Naseem et al. (2019) and Das et al. (2020) preferred the total debt ratio.
As indicated in Figure 1, the conceptual framework shows the relationship between the independent variable represented by corporate governance, explaining the proxies as board size and the dependent variable of capital structure represented by the debt-to-equity ratio. Figure 1 below shows that an effective corporate governance mechanism represented by board size would influence the firm’s leverage.
Some common capital structure theories include the tradeoff theory, the pecking order theory, and the market timing theory (Baker & Wurger, 2002). They are also signalling and the agency theory (Alan & Litzenber, 1973). These theories tried to explain the puzzle of capital structure, determinants of capital structure, firms’ performance, and the relationship between capital structure and corporate governance. Similarly, some studies that have tried to explain corporate governance to capital are the management-friendly hypothesis, stewardship theory (Donaldson & Davis, 1991), stakeholder theory (Freeman, 2015), resource
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Source: Author’s computation (2022).
Figure 1. Showing the link between corporate governance and capital structure.
dependence theory (Salancik & Pfeffer, 1974) and top echelon theory (Hambrick & Mason, 1984).
The available evidence for the relationship between corporate governance and capital structure has been mixed with inconsistency in the theoretical foundations. The agency theory is an important theory used to explain the nexus between corporate governance and capital structure (Fama, 1972; Jensen & Meckling, 1976). The agency theory states that the principals’ and agents’ interests’ conflict when there is a separation between ownership and control. The conflicts of interest between managers and shareholders as well as between majority and minority shareholders; in this sense, managerial ownership influences the firm’s financing decision (Feng et al., 2020). However, leverage has been identified as one of the common strategies to resolve agency conflicts, in addition to board characteristics of diversity, size, and level of independence (Farooq & Pashayev, 2019).
Although, Anwar and Sun (2015), as cited by Lartey et al. (2020), argued that large firms have higher agency costs relative to small firms and therefore issuing debt is a means of ensuring that managers are monitored by outsiders to reduce agency conflicts contrary to the pecking order theory which contends that large firm size implies high costs associated with information asymmetry, which limits the firm’s ability to access external finance, thus implying a negative firm size-leverage nexus (Myers & Majluf, 1984; Frank & Goyal, 2009). Therefore, the study’s theoretical underpinning is supported by the agency theory.
Ali et al. (2021a) explored the effect of corporate governance, firm age, and top management experience on the firms’ capital structure in Borsa Istanbul, Turkey. The study used a regression model of non-financial listed firms in Pakistan from 2013 to 2017 to analyse the data. The findings reveal that board size is statistically significant and positively affects leverage. They noted that a larger board size suffered from prolonged decision-making and increased conflict, which weakened corporate governance practices and resulted in a higher level of leverage.
In a study to examine the determinants of capital structure and relationships between capital structure and board structure comprising board diversity, board size, and board independence, Elmoursy (2020) reviewed the UK companies listed on the London Stock and Exchange (LSE) from 1999 to 2016 using a panel regression model. The result of the study showed that board size has a significant positive relationship with decisions related to leverage. Similarly, Feng et al. (2020) examined the relationship between corporate governance, ownership structure, and capital structure of Chinese real estate-listed companies from 2014 to 2018. The paper employs panel data of 119 Chinese real estate listed firms using fixed and random effect regression analysis techniques to examine the hypotheses. The results, which align with agency theory, showed that board size positively influences capital structure.
On the contrary, Mwambuli (2018) found a significant negative effect of board size on capital structure decisions after examining board characteristics and their effects on capital structure decisions in developing economies using a balanced panel dataset of 32 non-financial listed firms in the East African region from 2006-to 2015. This finding is supported by Soriya and Kumar (2022) and Ehikioya et al. (2021), that investigated countries of India and Nigeria, respectively, and showed a negative relationship between board size and firm leverage.
El-Habashy (2018) investigated the characteristics of corporate governance that impact the capital structure decisions in listed firms in Egypt. A sample of 240 observations from the most active non-financial companies collected in 2009-2014 was analysed using Multiple regression models (OLS). The result was that the influence of board size on leverage is mixed, given that the board size showed a significant positive association with long-term debt, a significant negative correlation with short-term ratio and an insignificant negative impact on debt-equity ratio and long-term debt assets. The mixed results were also confirmed by Nguyen et al. (2021) and Younas and Kassim (2020).
The studies reviewed have shown that despite using different locations with different time series dates, methods of analysis, and countries, the results remained inconsistent. Therefore, this study will further review recently published articles for 2011 to 2022 to assess if the trend is consistent.
3. Methodology
This study adopted a qualitative approach by reviewing published and high-quality journal articles from reputable databases of google scholar and EBSCOhost research. The search was conducted using the selection criterion of the corporate governance study population from a private sector perspective in developing countries. The advanced search of the EBSCOhost research database and google scholar with keywords “corporate governance and capital structure” plus “board size and book leverage” was used anywhere in the article or the title of the article search criteria with dates from 2011 to 2022. The selection excluded banks and other financial firms. The exclusion of financial firms is due to the regulations and guarded capital structure set by banks and non-financial firms’ regulators. Firms like banking and financial services’ capital structure is highly influenced by regulatory guidelines with a different account and disclosure requirements dictated by the bank and other regulatory agencies (Azegele, 2021).
The focus was also on samples collected in developing countries defined by the World Bank and United Nations Development Agencies. The developed countries were excluded because of the advanced rules and regulations, standardised procedures and strong legal system compared to the developing countries where corporate governance plays a vital role in alleviating agency problems and severe information asymmetry, as legal systems, the rule of law, and investor protection are not as effective as in developed countries (Nguyen et al., 2021). Also, the nature of the governance structure in developing countries compared to developed countries is different. While corporate governance, the rule of law and a strong legal system make most of the policies and actions consistent, most developing countries still struggle with government influence and weak institutional framework. As such, a further study on developing countries and their findings will be more impactful to policymakers. In addition, most corporate governance studies in developing countries are in the early stages (Magrus, 2012) with weak legal environments, lack of knowledge about corporate governance, poor leadership, lack of training among directors and weak investment awareness among investors.
The empirical evidence from previous studies was analysed across different thematic areas but focused on board size and leverage. The results were from the descriptive synthesis of the previous heterogeneous studies concerning the thematic area of interest. The use of verification strategies ensures trustworthiness and rigour during the study (Bello et al., 2022); this led to generalisations made in the study. Finally, the findings were related to existing theories, hence the study’s theoretical significance.
4. Results
This section presents an empirical appraisal of articles that studied the influence of corporate governance on capital structure from 2011 to 2022. The empirical studies were explained using groupings based on the findings from the various samples of 52 articles that met the selection criteria. The groupings are based on the methodology adopted for the study and finding of results that have positive, negative, and mixed relationships between board size and leverage.
Figure 2 shows the result of the findings, with positive results representing 52% of the analysis on the relationship between board size and firm leverage. More than half of the analysis leads to a positive result. The negative relationship represents 31%, while the mixed results represent mixed findings.
Table 1 shows the analysis of the distribution of the results based on the methodology adopted and the findings. The analysis showed that regression analysis was the most utilised estimation model, with 26.92 per cent of the studies adopting the methodology. It also showed that findings of the positive, negative, and mixed relationship between board size and leverage were prevalent, with positive results having six, negative has five and mixed results three. This shows whether there is any relationship with the specific findings from the empirical review of the findings of the various studies.
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Source: Authors computation, 2022.
Figure 2. Findings on the relationship between board size and leverage.
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Table 1. Distribution of methodology adopted and results.
**FsQCA represents Poisson Regression Estimation and Fuzzy Set Qualitative Comparative Analyses; Source: Authors Computation 2022.
Another finding from Table 1 shows that about 25% of the studies used dynamic panel data, which combines pooled OLS, Fixed or Random effects and GMM or GLS estimation techniques. Further analysis indicates that nine findings are positive relationships, one negative and three mixed results. Other findings showed 23.08% of the studies used multiple regression analysis as a technique for estimation, as shown in Table 1 above, making it the third most popular model adopted by scholars during the review period; However, studies with both positive and negative results used multiple regression techniques and non-had mixed results.
Other methods used were studies, as shown in Table 1, the Fixed Effect technique and GMM techniques, both having 3.85% with equal distribution of positive and negative findings only. Several other studies used different methods, with positive and mixed results distributed among them.
5. Discussions and Implications
The analysis reveals different results of the effect of corporate governance on capital structure in developing countries. In most instances, as indicated by the study, corporate governance positively affects capital structure compared to negative or mixed findings. The implication is that more studies have shown that a larger board size tends to influence the leverage choice of the firm. This aligns more with the theoretical underpinning of agency theory.
Over a quarter of the previous studies on the effect of board size on leverage in developing countries used regression analysis as the predominant estimator. A more forth comparative analysis showed that no consistent results were obtained despite the consistency of the model (Balagobe, 2020; Purag & Abdullah, 2016; Uwuigbe, 2014). The implication is that most likely other intervening factors may have control or mediate the outcome, which makes it difficult for the decision to be consistent and generalisable.
The other outcome follows the same pattern of inconsistent results, especially the methodology with at least two or more articles despite the studies being conducted in different locations. For instance, the GMM conducted in the countries of South Africa had negative results (Sewpersadh 2019), and South Korea had a positive outcome (Kamila & Gandakusuma 2021). This assertion was further reinforced by studies that adopted the Fixed effects model (Amin et al., 2022; Ehikioya et al., 2021). This outcome confirms this study’s earlier assertion that intervening factors may have influenced the results, thereby confirming the puzzle surrounding the capital structure theories. Although most studies included control or mediating variables, the results were still inconsistent. This study further demonstrates the importance of intervening variables rather than focusing on only good corporate governance attributes as drivers of predetermined and consistent outcomes.
Also, most of the studies adopted secondary data as an analysis instrument. Only two studies introduced primary data to conduct their investigation. Firstly Shabbir et al. (2020) used the Poisson Regression Estimation and Fuzzy Set Qualitative Comparative Analyses (FsQCA) to conduct their study in China, while Gill and Kohli (2018) used General Linear Model/Cluster Analysis in India. Both studies presented different outcomes, with Shabbir et al. (2020) obtaining negative results and Gill and Kohli (2018) demonstrating a positive relationship. The implication is that the methods adopted for collecting data for analysis do not necessarily lead to similar results.
On the theoretical underpinnings, the findings within the developing countries’ scope did not confirm the assertions of the agency theory, which aligns with the positive relationship that board size influences the effectiveness of capital structure choice. The claim of this study, as shown from empirical reviews of developing countries’ studies, has been inconsistent, with some having positive, negative, or mixed results, thereby disagreeing wholesomely with the agency theory perspectives. However, the study aligns strongly with capital structure theorists who adopted a more theoretically triangulation as a convenient way of explaining the conceptual analysis. Introducing two or more theories will assist in explaining the outcomes and support the study’s findings.
6. Conclusion
This paper reviewed the effect of corporate governance on the capital structure of non-financial firms in developing countries from 2011 to 2022. It discussed the previous studies’ findings and the theoretical implications. The qualitative analysis revealed that studies on the influence of board size on leverage had returned inconsistent results even when similar models were adopted. The positive results showed that 52 per cent of the papers reviewed had positive results, 31 per cent had negative, and 17 per cent returned mixed findings.
Furthermore, the study also revealed that over 12 models were adopted in the various studies that span across the developing countries, with the regression model being the most adopted technique of analysis, followed by panel data analyses and multiple regression analysis, all returning inconsistent outcomes. This implies that the study’s model does not determine the extent to which board size influences the choice of financial leverage of firms.
This study is limited by the inability of the study to link the extent to which intervening variables influenced the previous studies’ outcomes. Though the scholars may have applied different intervening variables, this study did not consider the role of the intervening variables and their direction in the study. In addition, the study did not focus on specific industry characteristics, given that non-financial firms may have all sectors with unique features that might naturally influence the results. Lastly, developing countries’ application of rules or codes of corporate governance may influence the results; even though some may be strong and others weak, the study did not consider the extent of adoption of the codes.
Future studies on the effect of corporate governance on capital structure in developing countries should consider the extent of the intervening variables like firm size, risk, and sector characteristics. Also, future studies could conduct similar qualitative research on the financial services industry.