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 Indian Journal of Finance and Banking; Vol. 1, No. 2; 2017 

                                                         ISSN 2574-6081  E-ISSN 2574-609X 

 Published by Centre for Research on Islamic Banking & Finance and Business 

 

1 
 

 

Effects of Capital Structure and Board Structure on Corporate 

Performance of Selected Firms in Nigeria
 
 

Henry Waleru Akani1 

Kenn-Ndubuisi Juliet Ifechi1 

 
1Department of Banking and Finance, Rivers State University, Nkpolu - Port Harcourt, Rivers State, Nigeria 

Correspondence: Henry Waleru Akani, Department of Banking and Finance, Rivers State University, Nkpolu - 

Port Harcourt, Rivers State, Nigeria, Email: henryakani@yahoo.com 

 

Received: October 14, 2017        Accepted: October 28, 2017     Online Published: November 01, 2017  

 

Abstract 

This paper seeks to examine the effect of capital structure and board structure on firm performance in Nigeria 

using secondary data consisting of forty listed companies on the Nigerian Stock Exchange (NSE) within the 

period of 2008 to 2016. Data were merged and pooled for analysis, the unit root test; co -integration, granger 

causality test, and regression were done accordingly. The paper established that there exists a significant 

negative relationship between capital structures (DER), a significant relationship between board size and a 

negative but not significant relationship between board duality and performance (ROA & ROE) in Nigeria 

respectively.
 

 

Keywords: Capital Structure, Board Size, Board Duality. 

 

1. Introduction 

Generally speaking, the issue of capital structure and board structure (under the corporate governance) are 

salient areas in corporate finance that are essential for the maximization of shareholders returns, wealth 

maximization, smooth running of firms operation and even the ability of firms to survive amidst competitions.  

Capital is a very crucial ingredient to the existence of any organization because of its direct relation to business 

continuity and its effect on the ability of the firm to deal with its competitors.  Claessens (2003) argued that 

better corporate frameworks benefit firms through greater access to financing, lower cost of capital, better 

performance and more favorable treatment of all stakeholders. The position has been stated that a weak board 

structure does not only lead to poor firm performance but also risky financing patterns. Invariable, the stronger 

the bond structure of any organization, the better the financing pattern of the firms. 
 

The modern theory of the capital structure originated from the path-breaking contribution of Modigliani and 

Miller in 1958, famous for the irrelevance theory, since then other theories have emerged and they include; the 

trade-off theory that deals with the balancing of costs and benefits, the pecking order theory that deals with 

disparity of information and resolved by an order of preference with respect to sources of finance, the agency 

cost theory of capital structure which states that an optimal capital structure will be determined by minimizing 

the costs arising from conflicts between the parties involved. Agency costs play an important role in financing 

decisions due to the conflict that may exist between shareholders, debt holders and management which brings to 



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the fore the importance of corporate governance. 

Directors of companies are regarded as a group of senior officers, who primarily formulate policies, manage, 

control and authorize company's affair which means that they are in charge of the financing decision of their 

corporation.  In summary, a director is the member of a group that directs the affairs of the company (Nnyeruka 

and Ohaka 2006). The directors can either be inside directors who are employees, officers, major shareholders 

or people connected to the company, they can also be outside directors of the board who are not otherwise 

employed by or engaged with the company and does not represent any of its stakeholders but bring outside 

experience and perspective to the board, keeping a watchful eye on the insider directors and help in resolving 

disputes between inside directors, or between shareholders and the board. Agency theory argues that due to the 

separation of ownership and control in modern organizations which creates information asymmetry between 

corporate owners and managers, the latter are likely to exploit the amount and quality of the information they 

have to their advantage by engaging in self-serving ventures that are "injurious" to the interest of the former. 

One of the primary duties of the board of directors is to serve as the monitoring agent for shareholders to check 

the behavior of corporate managers (Fleischer et al., 1988; and Waldo, 1985).
 

Effective board structure and capital structure will lead to proper and efficient practice in the administration of 

business entities. This will ultimately lead to the reduction in the incidence of corporate failures, poor internal 

control system, poor corporate structure, indiscipline both on the part of management and workers. Poorly 

governed corporations do not only pose a risk to themselves, they do to others and could indeed pull down 

capital market since they are less profitably, have more bankruptcy risks, lower valuations and pay out less to 

their shareholders.
 

Recent literature on the board of directors is basically empirical and focuses on the size of the board (Jensen, 

(1993); Yermack, (1996); Fernándezet al., (1997); Huther, (1997); Eisenberg et al., (1998) its composition and 

independence (Baysinger and Butler, (1985; Hermalin and Weisbach, (1991); Weisbach, (1988); Rosenstein and 

Wyatt, (1997); Bhagat and Black, (1998);  

Much of the public debate on board structure has centered on the pressure for a smaller board size. It is argued 

that although larger board size helps in the facilitation of key board functions, there comes a point when larger 

boards suffer from coordination and communication problems and hence board effectiveness (and firm 

performance) declines (Lipton and Lorsch, (1992); and Jensen, (1993).  

The importance of independent non- executive directors in the composition of a board is to effectively monitor 

the managers and reduce agency cost (Choe and Lee (2003). However, an available theory is scanty on the 

determinants of optimal board composition (Weisbach, (2002). The question, therefore, is "does the composition 

of the board of directors influence the firm performance or does firm performance influence the composition of 

the board of directors? (Davidson & Rowe, (2004).
 

The interest in board research is sustained by such issues as the important governance oversight role that boards 

are expected to play, their negligence to the roles and their association with high-profile corporate failures. 

There is a long tradition of research arguing to what extent the board of director’s composition and size 

influence their company’s performance (Hermalin and Weisbach, (2003); Dalton et al.,(1998).  

Existing literature on the relationship between the board composition, board size, and firm performance reflects 

mixed results. 
 

Despite the interest and numerous studies on corporate boards, empirical results display a remarkable lack of 

consensus. There have been different views with conflicting results (Zajac and Westphal, (1996). Apart from the 

above, the findings of the studies have been controversial and inconducive as some reports positive effects, other 



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reports negative in the time period and methodologies giving the need for further study.
 

Therefore, this study is a contribution to the ongoing debate on the examination of the effects of firms' capital 

structure and board structure on corporate performance. It will also contribute to the existing body of knowledge 

using Nigerian data to investigate the likely effects of capital structure and board structure on firm performance 

in Nigeria.
 

In analyzing this study, the following null hypotheses were formulated: 

H01:  There is no positive relationship between a firm’s capital structure and its performance in Nigeria. 

H02:  There is no significant relationship between board size and corporate performance of firms in Nigeria. 

H03:  There is no significant relationship between the board composition and corporate performance of firms 

in Nigeria. 

2. Theoretical Reflections 

There are two broad schools of thought that gave birth to capital structure. 

The first school of thought is the relevance theory of capital structure which comprises of the net income 

approach and the traditional view. They postulated that the cost of capital is determined by the composition of 

the capital structure of a firm. This suggests that there exist an optimal capital structure that occurs at the point 

where the cost of capital is at its minimal thereby contributing to the market value of a firm. The net income 

approach is based on the assumption that the equity and debt capitalization rates remain constant with changes 

in leverage. If the debt capitalization rate is lower than the equity capitalization rate, with the introduction of 

more debt, shareholders earnings are increased and firm value in effect lowering the cost of capital. 

The tradition view postulates that the mixture of debt and equity can increase firm value by the reduction in the 

weighted average cost of capital to a certain limit of financial leverage. 

The second school of thought is the irrelevance theory of capital structure that includes the Modigliani and 

miller theory which is based on the assumption that in a perfect market, the composition of firm financing mix 

does not affect the cost of capital thereby making the capital structure composition irrelevant in the valuation of 

a firm. Modigliani and Miller (1958) argue that the capital structure of a firm is irrelevant to its market valuation 

based on some assumptions applicable in an ideal market. 
 

Capital structure theories originated from the path-breaking contribution of Modigliani and Miller in 1958, 

famous for the irrelevance theory. They were of the opinion that in a world of perfect capital market and no 

taxes, a firm’s financial structure will not influence its cost of capital.  

Since then, numerous theories and research works have been developed and they include the pecking order 

theory of capital structure as introduced by Donaldson (1961). It is based on the assertion that managers have 

more information about their firms than investors. This disparity of information is resolved by an order of 

preference with respect to sources of finance. According to Myers (1984), due to adverse selection, firms prefer 

internal finance to external finance, when outside funds are necessary, firms prefer debt to equity because of 

lower information costs associated with debt issues.   
 

Secondly, the static trade-off theory of capital structure contrary to the pecking order states that optimal capital 

structure is obtained where the net tax advantage of debt financing balances leverage-related costs such as 

financial distress and bankruptcy, holding firm's assets and investment decisions constant (Baxter, 1967 and 

Altman, 1984) signifying a cost-benefit structure. 
 

Thirdly, the agency theory initially put forward by Berle and Means (1932) and then Jensen and Meckling 

(1976), agency conflicts arise from the possible divergence of interests between shareholders (principals) and 

managers (agents) of firms and also when there is a risk of default, The risk of default may create what Myers 



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(1977) referred to as an "underinvestment" or "debt overhang" problem. In this case, the debt will have a 

negative effect on the value of the firm. They stated that an optimal capital structure will be determined by 

minimizing the costs arising from conflicts between the parties involved. 
 

2.1 Empirical Reflection on Capital Structure and Firm Performance 

Ibrahim and SayedEbaid (2009) pointed out that capital structure decision has a weak-to-no impact on firm’s 

performance. 

Babatunde et al (2014) tried to study the relationship between capital structure and profitability of conglomerate, 

consumer goods, and financial services firms quoted in Nigeria Stock exchange using the Return on Asset (ROA) 

and Return on Equity (ROE) as performance proxies. In addition, debt-equity ratio (DER) and debt asset ratio 

(DAR) were used as capital structure proxies. The results showed an insignificant relationship between return on 

equity (ROE) and DAR, significant relationship in almost all firms between return on equity and debt to equity. 

In the financial firms, there is a negative significant relationship between return on equity and debt to assets 

ratio, the conglomerate firms, there is also a negative relationship between return on assets (ROA) and debt to 

equity ratio however not significant.
 

Mohammed and Jaafer (2012) The study tried to extend Abor’s (2005) and Gill et al, (2011) finding regarding 

the effect of capital structure on profitability of the industrial companies listed on Ammon stock exchange using 

39 companies from 2004 – 2009. The result reveals a significantly negative relation between debt and 

profitability. 

Anthony et al (2010) investigated the relationship between capital structure and profitability of listed 

non-financial firms in Ghana, covering a seven-year period (2002-2008). Ratios such as return on assets, return 

on equity and net profit margin was used as indicators for determining the profitability of the firm. Short-term 

debt, long-term debt, and total debt ratios were also used as indicators for leverage of the firms. The correlation 

and regression results showed a significantly negative association between leverage and profitability.
 

Abor (2005) evaluated the relationship of the profitability with a capital structure for firms listed on the Ghana 

Stock Exchange. He found a positive relation for short-term debt to total assets and return on equity because of 

low-interest rates. However, a negative relation exists between long-term financing and equity returns, as the 

long-term debt was more expensive in that market. The relation among total debt and profitability is positive 

because of the larger proportion of short-term financing in total debt. He suggested that profitable firms are 

largely dependent on debt as a major source of financing.
 

Albert, Michael, and Daniel (2013) studied the relationship between capital structure and profitability of listed 

firms in Ghana during the five year period from 2005 to 2009 using Regression analysis. Similar to Abor (2005) 

study, the results revealed that, there is a statistically significant positive relationship between profitability and 

short-term debt and a significantly negative relationship between profitability and long-term debt. However, the 

results revealed a statistically negative relationship between profitability and total debt contrary to Abor (2005) 

study. 
 

Akintoye (2008) studied the sensitivity of performance to the capital structure on selected food and beverage 

companies in Nigeria. The result shows that performance indicators to turnover (Earnings before Interest and 

Taxes, Earnings per Share and Dividend Per Share) and the measures of leverage (Degree of Operating 

Leverage, Degree of Financial Leverage and Dividend Per Share) are significantly sensitive. 
 

Zeitun and Tian (2007), supports  the relationship between capital structure and firm performance from the 

agency perspective and also supports a negative relationship using 167 Jordanian companies over fifteen year 

period (1989-2003), found that a firm’s capital structure has a significant negative impact on the firm’s 



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performance indicators, in both the accounting and market measures.  

Majumdar and Chhibber (1997) and Rao, M-Yahyaee, and Syed (2007) also confirm the negative relationship 

between capital structure and performance. Their results further suggest that liquidity, age, and capital intensity 

have significant influences on financial performance.
 

Capon et al. (1990), who suggested that out of the 149 relationships, reported using debt as the independent 

variable and firm performance as the dependent variable, 90 reported a negative relationship. 

Numerous other studies supports a negative relationship Kester(1986), Friend and Lang(1988), Titman and 

Wessels (1988), Harris and Raviv(1990), Shah (1994), Rajan and Zingales(1995), Wald (1999), Booth et al. 

(2001) and Fama and French (2002). While others found the relationship to be positive like Roden and Lewellen 

(1995), Champion (1999), Ghosh et al. (2000), Hadlock and James (2002) and Berger and Bonaccorsi di Patti 

(2006). 

2.2 Board Structure 

Tricker (1994) noted that board structure distinguishes between those directors who hold management positions 

in the company and those who do not. Hence with management positions are referred to as insider directors in 

the United States or executive directors in the United Kingdom and Australia. The top person on the board is the 

chairman. He could be an executive or a non-executive of the company. If the Chief Executive Officer (CEO) 

happens to be a director on the board, then he is an executive director.
 

Agency theory argues that due to the separation of ownership and control in modern organizations which creates 

information asymmetry between corporate owners and managers, the latter are likely to exploit the amount and 

quality of the information they have to their advantage by engaging in self-serving ventures that are injurious to 

the interest of the former. One of the primary duties of the board of directors is to serve as the monitoring agent 

for shareholders to check the behavior of corporate managers (Fleischer et al., 1988; and Waldo, 1985). 

Therefore, having an insider-dominated board of directors is likely to exacerbate the situation as the board’s role 

as a monitoring agent of shareholders will be curtailed, paving way for managers to harm shareholders’ wealth. 

Consequently, agency theory argues that effective boards will consist of outside directors. 

2.3 Empirical Reflections On Board Structure and Firm Performance 

Arosa et al. (2010) find that the presence of independent directors on the board of a non-listed family firm has a 

positive effect on performance when the firm is run by the first generation. However, no effect on performance 

is seen when the firm is run by the second and subsequent generations. 

Andres and Vallelado (2008) concluded that a large board size should be preferred to a small size because of the 

possibility of specialization for more effective monitoring and advising functions. 

Bonn, Yokishawa, and Phan (2004) tried to compare the effects of board structure on firm performance between 

Japanese and Australian firms, they found that board size and performance was negatively correlated for 

Japanese firms but no relationship between the two variables for its Australian counterpart was found. However, 

contrary to the Japanese firms the ratios of outside directors and female directors to total board numbers have a 

positive impact in the Australian sample. 
 

Hermalin and Weisbach (2003) concluded that although the empirical literature does not infer a relationship 

between board composition and firm performance, board size is negatively related to corporate performance. 

(Barnhart, et al., 1994). 

Vafeas (2000) reported that firms with the smallest board are better informed about the earnings of the firm and 

thus can be regarded as having better monitoring abilities.  

Forbes & Milliken (1999) suggested that although large boards may increase the quality of decision-making 



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since they offer a broader array of perspectives, their size may hinder the ability to reach a consensus. 

Yermack (1996) found that profitability and financial efficiency ratios decrease as a board’s size increases. 

Jensen (1993) argued that the preference for smaller board size stems from the technological and organizational 

change which ultimately leads to cost-cutting and downsizing.
 

Contrary to the above findings, a positive impact on performance was recorded with larger board size by Mak 

and Li (2001) and Adams and Mehran (2005); Adam and Mehran (2005) found a positive relationship between 

board size and performance (measured by Tobin’s Q) in the U.S banking industry.  

Pearce and Zahra, (1992); Rosenstein and Wyatt, (1990); Schellenger et al., (1989) also reported a positive 

relationship between outside director representation and firm performance.  

Studies by Chaganti et al. (1985); Daily and Dalton (1992), (1993); and Zahra and Stanton (1988) have found no 

relationship between board composition and firm performance.  

3. Research Methodology 

Secondary data consisting of the forty listed companies on the Nigerian Stock Exchange (NSE) within the 

period of 2008 to 2016.Data are analyzed based on time series - cross-section data. They are merged and pooled 

for analysis using Regression.
 

Information relating to firm capital structure (Debt to equity ratio); Board size (Number of directors on the 

board); Board Duality (Proportion of outside directors sitting on the board);  

4. Model Specification 

The econometric model used in the study is given as: 

Y= β0 + β1Xit + Kit             (1) 

Where Y is the dependent variable. β0 is the intercept (it gives the value of Y when X is zero), β1 is the slope 

measuring the rate of change in Y for a unit change in X and the coefficient of the explanatory variables 

(corporate governance mechanisms) in the study, Xit is the explanatory variable and Edit is the error term, 

mathematically; 

Transforming equ. (1 and 2) into a testable form, we obtain the following regression equations; 

CORPERF = β0 + β 1CS + β 2BS + E2t                   (2) 

Where CORPERF = Corporate performance which represents the dependent variable.
 

CS = Capital structure and BS = Board structure are the independent variables. 

E2t = Error term 

β1 and β2 are the coefficients of the explanatory variables respectively. 

In this study, our corporate dependent variable performance will be proxied by Return on Assets (ROA) and 

Return on Equity (ROE) while Capital Structure (CS) is composed of Debt to Equity Ratio (DER); others are: 

ROA  =  β0 + β1DER + β2Bsize + β3Bcomp + E3t       (3) 

ROE  =  β0 + β1DER + β2Bsize + β3Bcomp + E3t        (4) 

Where  

Return on equity (ROE) =  Profit after tax (PAT)/Total equity shares in issue 

Return on asset (ROA)    =  Profit after tax (PAT)/Turnover 

Debt to Equity ratio (DER)  =  Total debt / Total equity 

Board size (Bsize)=  Natural logarithm of the total number of members of the board of directors. 

Board Duality (Bcomp) = Proportion of outside or non-executive directors sitting on the board. 

For performance evaluation firms employ both financial and non-financial performance criteria.  

ROA and ROE were chosen because they are important accounting-based and widely accepted measures of 



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financial performance.  

5. Results and Discussion of Findings 

5.1 Descriptive Statistics 

The table1 shows the descriptive statistics of all the variables used in the study.The Descriptive procedure 

displays a summary statistics for several variables in a single table and calculates standardized values.  Here, 

the sample consists of 40 quoted companies on the Nigeria stock exchange. The following items were applied, 

mean, minimum, maximum, standard deviation, sum, kurtosis and skewness with their probabilities.
 

A critical examination of the descriptive statistics for the dependent and explanatory variables reveals that all the 

variables have a positive mean and the average ROA of the sampled firms is about 28%, while that of the ROE 

is about 15%. The results indicate that on the average, for every N100 worth of total assets of the firms, N28 

was earned as profit after tax, while N15 was earned as after-tax profit on every N100 equity share issued. 

The average of debt to equity ratio is 5.03; while the average of Board size of 40 firms used in the study is 10 

ranging from the minimum of 6 and the maximum of 16 which shows that the size of a board varies 

substantially among companies. The average of board composition is 0.59 showing that only 59 percent of the 

board members are independent respectively with a minimum value of 25percent and a maximum value of 

85percent. Also, the probabilities values of Return on Assets and Return on Equity are significant at 5% 

confidence level meaning that there is a positive and significant relationship between capital structure, bond 

structure and corporate performance of firms in Nigeria. 

Table 1 

 BCOMP BSIZE ROA DER ROE 

 Mean  0.585750  10.32500  0.275947  5.032775  0.146598 

 Median  0.560000  10.00000  0.220000  0.434000  0.110200 

 Maximum  0.880000  16.00000  2.782000  177.7520  1.374000 

 Minimum  0.250000  6.000000 -0.208600  0.012000 -0.208600 

 Std. Dev.  0.146967  2.535770  0.472392  28.01534  0.256758 

 Skewness  0.057854  0.384007  3.839422  6.080913  2.678825 

 Kurtosis  2.878814  2.296248  21.03965  37.99427  14.20627 

      

 Jarque-Bera  0.046791  1.808520  640.6561  2287.515  257.1415 

 Probability  0.976876  0.404841  0.000000  0.000000  0.000000 

      

 Sum  23.43000  413.0000  11.03786  201.3110  5.863930 

 Sum Sq. Dev.  0.842378  250.7750  8.703003  30609.50  2.571053 

      

 Observations  40  40  40  40  40 

Source: Extracts from E-view print out and Author’s Computation, 2017. 

 

5.2 Correlation Analysis  

Correlation analysis is concerned with describing the strength of the relationship between two variables. In this 

study, the correlation co-efficient analysis is undertaken to find out the relationship between capital structures, 

board size and board composition on corporate performance. To show the amount of relationship that exists 



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between the variables.
 

Table 2: ROA as a firm performance measure to capital structure (measured as DER). 

  ROA DER 

ROA Pearson Correlation 1 -.147 

Sig. (2-tailed)  .364 

N 40 40 

DER Pearson Correlation -.147 1 

Sig. (2-tailed) .364  

N 40 40 

Source: Author’s Computation 

Table 2 shows the relationship between debt to equity DER (measure for capital structure) and return on asset 

(ROA) a measure of performance. There is a negative relationship between the ROA and DER at (-0.147) at a 

significance level of 0.01 with a low coefficient of determination at (0.364).  

Table 3: ROE as a firm performance measure to capital structure (measured as DER). 

  ROE DER 

ROE Pearson Correlation 1 -.053 

Sig. (2-tailed)  .744 

N 40 40 

DER Pearson Correlation -.053 1 

Sig. (2-tailed) .744  

N 40 40 

Source: Author’s Computation 

Table 3 above shows the relationship between debt to equity DER (measure for capital structure) and return on 

equity (ROE) a measure of performance. There is a negative relationship between the ROE and DER at (-0.053) 

at a significance level of 0.01 with a high coefficient of determination at (0.744).   

Table 4: ROA as a firm performance measure to Board composition (BCOMP). 

Correlations 

 ROA BCOMP 

Pearson Correlation 1 .026 

Sig. (2-tailed)  .871 

N 40 40 

Pearson Correlation .026 1 

Sig. (2-tailed) .871  

N 40 40 

Source: Author's Computation 

 

Table 4 shows the relationship between Board composition (BCOMP) and return on asset (ROA) a measure of 

performance. There is a positive relationship between the ROA and BCOMP at (0.026) at a significance level of 

0.05 with a high coefficient of determination at (0.871).   

 



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Table 5: ROA as a firm performance measure to capital structure (measured as DER). 

  ROE BCOMP 

ROE Pearson Correlation 1 .252 

Sig. (2-tailed)  .116 

N 40 40 

BCOMP Pearson Correlation .252 1 

Sig. (2-tailed) .116  

N 40 40 

Source: Author's Computation 

 

Table 5 shows the relationship between Board composition (BCOMP) and return on equity (ROE) a measure of 

performance. There is a positive relationship between the ROE and BCOMP at (0.252) at a significance level of 

0.01 with a low coefficient of determination at (0.116).   

Table 6: ROA as a firm performance measure to Board size (BSIZE). 

  ROA BSIZE 

ROA Pearson Correlation 1 .206 

Sig. (2-tailed)  .203 

N 40 40 

BSIZE Pearson Correlation .206 1 

Sig. (2-tailed) .203  

N 40 40 

Source: Author’s Computation 

Table 6 shows the relationship between Board size (BSIZE) and return on equity (ROA) a measure of 

performance. There is a positive relationship between the ROA and BSIZE at (0.206) at a significance level of 

0.05 with a low coefficient of determination at (0.203).  

Table 7: ROE as a firm performance measure to Board size (BSIZE). 

  ROE BSIZE 

ROE Pearson Correlation 1 .386* 

Sig. (2-tailed)  .014 

N 40 40 

BSIZE Pearson Correlation .386* 1 

Sig. (2-tailed) .014  

N 40 40 

Source:   Author’s Computation 

 

*. Correlation is significant at the 0.05 level (2-tailed). 

Table 7, shows the relationship between Board sizes and return on equity (ROE) a measure of performance. 

There is a positive relationship between the ROE and BSIZE at 0.386 with a low coefficient of determination at 

0.014. 

However, descriptive and correlation analysis only indicates the associate link between variables. Hence, the need 

 

 



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for further analysis. 

5.3 Cointegration Test 

Table 8: this shows the long run relationship between variables. 

Normalized cointegrating coefficients (standard error in parentheses) 

   BSIZE     ROA     ROE        BCOMP   DER 

 1.000000  0.000000  0.000000 0.0 -0.007836                 

 

5.4 Granger Causality
 

 

Table 9 

 Null Hypothesis: Obs F-Statistic Prob.  

        
 ROA does not Granger Cause BSIZE  38  2.22348 0.1242 

 BSIZE does not Granger Cause ROA  0.53336 0.5916 

        
 ROE does not Granger Cause BSIZE  38  1.29497 0.2875 

 BSIZE does not Granger Cause ROE  2.08834 0.1400 

        
 DOE does not Granger Cause BSIZE  38  0.68782 0.5097 

 BSIZE does not Granger Cause DER  1.03945 0.3649 

        
 ROE does not Granger Cause ROA  38  0.76387 0.4739 

 ROA does not Granger Cause ROE  0.93945 0.4010 

        
 DOE does not Granger Cause ROA  38  0.00574 0.9943 

 ROA does not Granger Cause DER  0.48306 0.6212 

        
 DOE does not Granger Cause ROE  38  1.25892 0.2972 

 ROE does not Granger Cause DER  1.77768 0.1848 

        
Source: Author’s Computation 

 

Table 9 shows that none of the variables has a cause-effect relationship even though they are correlated.
 

 

5.5 Regression Result (Veto Autoregression Analysis) 

Table 10; ROA as dependent variable on all independent variables (DER, BSIZE, AND BCOMP) with a two 

year lag of the dependent variable plus each the independent variables.
 

   

 Standard errors in ( ) & t-statistics in [ ]  

          
 ROA BCOMP BSIZE DER 

          
ROA(-1)  0.076280 -0.025353  1.595734  2.775061 



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  (0.19250)  (0.06018)  (0.99609)  (11.1405) 

 [ 0.39625] [-0.42127] [ 1.60200] [ 0.24910] 

     

ROA(-2)  0.122775 -0.004151 -0.488644 -2.580817 

  (0.19465)  (0.06085)  (1.00720)  (11.2648) 

 [ 0.63074] [-0.06822] [-0.48515] [-0.22911] 

     

BCOMP(-1) -0.704506 -0.065026  2.454896 -44.46992 

  (0.61063)  (0.19090)  (3.15961)  (35.3378) 

 [-1.15374] [-0.34063] [ 0.77696] [-1.25842] 

     

BCOMP(-2) -0.596228 -0.171614 -2.704170  56.64832 

  (0.68509)  (0.21418)  (3.54492)  (39.6473) 

 [-0.87029] [-0.80126] [-0.76283] [ 1.42881] 

     

BSIZE(-1) - 0.029638  0.002080  0.004183 -4.034596 

  (0.04195)  (0.01312)  (0.21709)  (2.42799) 

  [0.70642] [ 0.15860] [ 0.01927] [-1.66170] 

     

BSIZE(-2)  0.003344  0.004126 -0.092841 -0.552188 

  (0.03976)  (0.01243)  (0.20573)  (2.30095) 

 [ 0.08410] [ 0.33193] [-0.45127] [-0.23998] 

     

DER(-1) -0.001417 -0.000806  0.001519  0.044145 

  (0.00366)  (0.00114)  (0.01892)  (0.21160) 

 [-0.38747] [-0.70498] [ 0.08029] [ 0.20863] 

     

DER(-2) -0.001417  0.001020  0.013428  0.059459 

  (0.00329)  (0.00103)  (0.01704)  (0.19053) 

 [-0.43039] [ 0.99068] [ 0.78827] [ 0.31207] 

     

C  1.290009  0.664585  11.05782  44.08397 

  (0.85402)  (0.26700)  (4.41904)  (49.4236) 

 [ 1.51051] [ 2.48913] [ 2.50231] [ 0.89196] 

          
 R-squared  0.108986  0.123705  0.194486  0.185419 

 Adj. R-squared -0.136811 -0.118031 -0.027724 -0.039293 

 Sum sq. resids  7.433493  0.726541  199.0255  24895.55 

 S.E. equation  0.506288  0.158282  2.619723  29.29961 

 F-statistic  0.443400  0.511736  0.875234  0.825140 



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 Log likelihood -22.91945  21.26423 -85.38075 -177.1320 

 Akaike AIC  1.679971 -0.645486  4.967408  9.796420 

 Schwarz SC  2.067820 -0.257637  5.355257  10.18427 

 Mean dependent  0.297349  0.581579  10.39474  5.281711 

 S.D. dependent  0.474847  0.149694  2.584146  28.74040 

          
 Determinant resid covariance (dof adj.)  23.98164   

 Determinant resid covariance  8.134606   

 Log-likelihood
 -255.5051   

 Akaike information criterion  15.34237   

 Schwarz criterion  16.89377   

     
 

From table 10, all the variables were lagged by two years to put into consideration the time effect. Since there is 

no cause-effect relationship between any of the variables even though they are correlated, DER shows a 

negative relationship for the two years, contrary to the correlation test, the board duality shows a negative 

relationship and board size a mixed result, the first year showing a negative while the second year was positive, 

the R2 shows the percentage variation in performance (ROA). By implication, the value 0.10 means that only 

about 10 percent of the total variation in ROA is as a result of changes both DER, BSIZE and BCOMP. 

Individually, BCOMP report for 12% variation in performance, BSIZE has 19% and DER has 18%. But since 

they do not a cause-effect relationship, our model will only consist of the group together. This means that there 

are other factors which affect performance using ROA as a measure which was not included in this study. 
 

 

According to the above regression analysis, VAR Model is formulated as follows: 

=============================== 

ROA = C(1,1)*ROA(-1) + C(1,2)*ROA(-2) + C(1,3)*BCOMP(-1) + C(1,4)*BCOMP(-2) + C(1,5)*BSIZE(-1) + 

C(1,6)*BSIZE(-2) + C(1,7)*DER(-1) + C(1,8)*DER(-2) + C(1,9) 

 

VAR Model - Substituted Coefficients: representing the regression equation. 

=============================== 

ROA = 0.0762804703126*ROA(-1) + 0.122774866448*ROA(-2) - 0.704506276015*BCOMP(-1) - 

0.59622826345*BCOMP(-2) - 0.0296376599455*BSIZE(-1) + 0.00334392278428*BSIZE(-2) - 

0.00141673170334*DER(-1) - 0.00141696323721*DER(-2) + 1.29000863403 

 

6. Discussion of Findings 

Ho1: There is no positive relationship between a firm’s capital structure and firm performance in Nigeria.At a 

5% level of significance, ROA and ROE which are measures for performance shows a negative relationship with 

the debt to equity ratio (a measure of capital structure), ROA at (- 0.147) and ROE at (-0.053), we therefore 

acceptH01 since the research result shows a negative relationship between the capital structure and firm’s 

financial performance. This can be found in the result on table 2 and 3. 

H02: There is no significant relationship between board size and firm performance of firms in Nigeria.  

From table 4 and 5, the correlation analysis shows that there is a positive relationship between board size 

(BSIZE) and the measures of performance which are ROA and ROE with a coefficient of 0.116 and 0.87 



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respectively at a1% level of significance. The regression result reports a negative relationship in the first year 

lag (-0.030) and a positive relationship at the second year lag at  (0.03) with a coefficient of  (0.706) and 

(0.084) for ROA and ROE are also positive results for the lags with a coefficient of (1.132) and (1.49) 

respectively Therefore, we reject the null hypothesis at both 1% and 5% level of significance, there is a 

significant relationship between the board size and performance as recorded by the correlation analysis. 

H03: There is no significant relationship between the board duality and firm performance of firms in Nigeria.  

There exist a relationship between BCOMP and both ROA and ROE from the correlation analysis but the 

regression result, showed the relationship to be inverse since both the ROA and ROE reported a negative 

relationship at a significance of (-1.1537) and (-0.8703) for ROA and (-0.413) and (-0.968) for ROE. Therefore 

we accept the null hypothesis that there is no significant relationship between BCOMP and performance. This 

shows that the number of independent directors has a negative impact on firm value (ROA) and (ROE) but it is 

not significant. This result does not support the argument that board with a higher number of independent 

directors will add more value for firms and this supports previous studies. Board composition is very important 

since the regression result shows that it can have a negative impact on performance. 
 

6.1 Summary of the Findings 

Based on our discussion of findings, the following summary was evident from the research analysis; 

 A capital structure consists of the combination of both equity and debt as seen in the financial statement 

of the firms used for the study. Capital structure is also related to ROA and ROE that are measures of 

performance using the debt to equity ratio as a proxy and also has a negative impact on corporate 

performance.
 

 Board size has a significant relationship to ROE and ROA but it has an inconclusive impact on 

corporate performance since it shows both a positive and negative relationship in the first and 

second-year lag respectively. The variance in the board size exists because of the different industries 

and policies governing them like the banks and insurance companies and the size of the firm.
 

 Board composition is related to ROE and ROA and it has a negative impact on corporate performance 

that is not significant.  

7. Conclusion and Recommendation 

With the existence of a negative correlation between capital structure and performance, this result can be 

interpreted that high leverage companies would have less profitability meaning that the debt level is at the 

optimal level. Other factors that may cause the negative impact includes
 

 The high cost of external debt given the high-interest rate of borrowing in the country.
 

 Inefficiency and instability suffered by the market in recent times. In short, it can be called the market 

condition of the country. 

 Business risk which is the basic risk a firm or industry is exposed to as they carry out their activities. 

Findings from the regression analysis on board size reflect a negative impact consistent with previous works 

Hakin (2012) and Frick and Bermia (2009) and a positive impact which shows that reducing the size of boards 

of directors does not contribute to higher firm performance contradicting those of prior research rendering our 

interpretation inconclusive. 
 

We, therefore, suggest that there is a need for firms to have policies that ensure the consideration of potential 

board members' skills before appointment to the board and also, there is the need for continuous training and 

development for board members to ensure efficient discharge of their responsibilities.
 

The regression result on board duality suggests that there is no significant relationship between board duality 



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and any performance measure used such as Return on Equity (ROE) and Return on Assets (ROA). This means 

that non-executive directors do not add to the performance of firms in Nigeria. Even though the non- executive 

directors play a significant role in providing independent advice during corporate decision-making process, 

while such advice may enhance overall corporate policies, such advice may not be significant enough as to 

create any economic value added to the overall corporate performance. This can be due to the fact that as 

outsiders, the non-executive directors may be constrained in term of information hence they rely on the insiders 

for the information required for the decision making and there may be information asymmetry. Therefore, the 

introduction of regulations stipulating the number of non-executive or independent directors on the boards of 

companies, while it is appealing from the agency theory point of view, may not directly enhance performance 

since the role they play as important as it is, may be of indirect enhancement on performance. 
 

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