The Impact of Board Structure on Firm Performance: Evidence from the Nonfinancial Companies Listed on Ghana Stock Exchange

The fundamental aim of this study is to examine the relationship that exit between board structure and firm performance of non-financial Ghanaian listed companies. In order to achieve the objectives of the study, unique data were collected from a sample of 28 non-financial companies covering five financial year periods 20122017 was used and thereafter analysis done within panel data framework/multiple linear regression framework. The variables such as CEO duality, CEO tenure, board size, board composition and its independence were considered as predictors of the firm performance that was measured employing accounting based performance measures such as the return on assets (ROA), return on equity (ROE) and EPS. I found board size to have a positively significant relationship with firm performance.

literature pertaining to the topic; the Impact of board structure on Firm Performance as well as some theories and views of others who have previously studied into the subject will be examined. Most studies have examined the impact of the board characteristics (CEO duality, CEO tenure, audit committee, board size and composition of the Board) on firm performance. Hence this study will investigate the relationship between corporate governance mechanisms namely, board size, board composition, CEO duality and CEO tenure with the firm's performance.

Independent Variables and Definitions 2.1.1 Board Size and Corporate Performance:
Theoretically, the relationship between board size and firm performance in general remains inconclusive (Weerakkodi, 2015). The finance literature has generally found evidence consistent with the agency theory perspective that a smaller board is related to better firm performance (Gertner & Kaplan, 1996); (Yermack, 1996); (Eisenberg, Sundgren, & Wells, 1998); (Sanda, Mikailu, & Garba, 2005), (Denis & Sarin, 1999). Due to management costs and free rider problems inherent in large boards, shareholder groups generally favor smaller boards and have pressured companies to reduce board size (Gertner & Kaplan, 1996). For many years, empirical studies have tried to find the optimal size of a board of directors of a company. (Lipton & Lorsch, 1992) argue that, the optimal size of the board of directors should be between seven and nine to ensure accountability, coordination, reduce free ridding problem and faster decision making which enhances performance. A level below ten is optimal; a smaller board works better and could be less manipulated by the delegated director. The relevant literature examined the relationship between board size and firm performance, the findings turned up to be inconclusive. In examining this relationship, (Shakir, 2008) found a negative relationship between board size and firm performance which supported the conclusion of (Conyon & Peck, 1998) that for a firm to be effective in its monitoring, it should have a relatively small board of directors. In relation to that, (Haniffa & Hudaib, 2006) argued that a large boards are seen as ineffective in monitoring performance and could also cost more for companies in terms of compensation and increased incentives for them to avoid. The same conclusion was drawn by (Al-Matari et al., 2012) based on his study carried out on the Canadian public companies. His conclusion implies that the board size was also shown to have a negative relationship with performance measured by return on sales, sales efficiency and ROA. However, prior studies pertaining to the size of the board also supported the positive relationship between the size of the board of directors and corporate performance and these studies seem consistent with resource dependency theory, which supports a positive relationship between board size and firm performance (Riaz, Khan, & Shaheen, 2017); (De Andres & Vallelado, 2008). However, both theories support the notion that board size has a significant economic impact on firm value. Large boards are viewed to lead to a better business performance owing to the wide variety of skills present for better decision making and monitor the performance of the CEO. Moreover, (Rechner & Dalton, 1991) have also reported that large boards are associated with stronger performance. These results supported the conclusion made by (Pfeffer, 1972) and (Zahra & Pearce, 1989)regarding the relationship between the board size and firm performance. Therefore, based on the theoretical perspective and discussions above, the first hypothesis is formulated: H1: There is a significant positive relationship between board size and firm performance.

Board Composition and Firm Performance
Board composition has been highly debated in the fields of economics, organizational science literatures, and finance on the empirical and the theoretical frameworks .One of the key characteristics of a firm's board is the blend of executive and non-executive directors which is very important for its performance. Non-executive directors are the ones(professional referees) who are not involved in the day to day management of the firm, but are involved in the decision making and the planning policies. The proportion of directors would obviously to a large extend determine the quality of decision making since objectivity would play an important role, moreover, whether the board can objectively monitor and control the management. Previous studies by (Kaplan & Reishus, 1990), (Byrd & Hickman, 1992),Therefore, a board is seen to be more independent if it has more non-executive directors (John & Senbet, 1998) (Brickley, Coles, & Jarrell, 1997), (Abor & Adjasi, 2007), (Khan & Awan, 2012) argued that there is a positive relationship between independent directors and firm performance. Also (Rashid, De Zoysa, Lodh, & Rudkin, 2010) documented that firms with independent directors have less agency problems and have more alignments to shareholders. It has also been debated that, the effective ways of monitoring boards is by making executives function effectively to take care of the shareholder's interests rather than their own (Al-Matari et al., 2012). According to agency theory, a larger proportion of independent directors generally provide better firm performance. It has been concluded by (Al-Matari et al., 2012) that the proportion of independent directors has an effect on firm performance. Previous studies examining the relationship between board composition and firm performance have been inconsistent. Whilst some studies found that firms with board of directors dominated by outsiders are able to perform better (Adams & Mehran, 2005), (John & Senbet, 1998;Kyereboah-Coleman & Biekpe, 2006)and supported by (Wang & Coffey, 1992)who also found out that, there is a positive association between the proportion of outside board members and performance. Others studies such as (Bhagat & Black, 1999); (Kajola, 2008); (Hermalin & Weisbach, 1991); (Zahra & Pearce, 1989); (Daily & Dalton, 1992); (Pearce & Zahra, 1992); (Baysinger & Butler, 1985)) Arguably supported the premises of the agency theory. (Hermalin & Weisbach, 1991) and (Bhagat & Black, 2001), (Mura, 2007)found there is no relation between the degree of board independence and four measures of firm performance. Based on the theoretical perspective and discussion above, the following hypothesis was to be tested: H2: There is a significant positive relationship between board composition and firm performance.

CEO Duality and Firm Performance
One aspect of corporate governance, which has given rise to concern, is the personality phenomenon which involves role duality. One important function of the board of directors is to monitor the top management`s actions, but a problem may arise when the Chief Executive Officer and chairperson positions are held by the same person. CEO duality is an important governance mechanism due to its sensitive nature of the relationship between agents and principals (Tian & Lau, 2001); (Krause & Bruton, 2014). Agency theory suggests that CEO's should run the firm in the best interest of shareholders( (Brickley et al., 1997); (Mishra & Mohanty, 2014). Agency Theory shows that great conflicts may arise from the action of duality. (Blackburn, 1994;Dahya, Lonie, & Power, 1996), Argue that combining the two roles may undermine the board's monitoring power, but Stewardship Theory supports the idea. Stewardship is one of the most important theories of Corporate Governance which states that managers don't work for their self-interest but they are working for the corporation favor, as they are steward for corporation assets. Managers are working for making high reputation for them and so it benefits the corporation.
CEO non-duality leads to better performance than CEO duality (Brickley et al., 1997); (Ramdani & van Witteloostuijn, 2009). (Ramdani & Witteloostuijn, 2010) argued that CEO duality plays an important role in affecting the value of a firm. A single person being the Chairman and the CEO leads to the enhancement of the firm's value and the cost is minimized. This is supported by (Rechner & Dalton, 1991)who argued that a combined leadership helps in monitoring the activities of top management and thus decreases the agency costs. However, (Baliga, Moyer, & Rao, 1996) indicate that CEO duality can lead to the board's worse performance as the board is unable to fire under or nonperforming CEO which can generate agency costs in cases where the CEO works for his own interest as opposed to the shareholders. (Yan Lam & Kam Lee, 2008), (Yusoff & Alhaji, 2012)argue that, when the CEO and board chair positions are separate, it increases the firm's value. (Brickley et al., 1997) argue that CEO duality in a firm favours the under or nonperforming CEO as it is difficult for the board to remove him. Based on the previous arguments and other supporting ones, it is reasonable to test the following hypothesized relationship: H3: There is a significant relationship between CEO duality and firm performance.

CEO Tenure and Firm Performance:
This is how long a CEO served in that position before he or she is removal or resignation from office. All other things being equal, the longer a CEO stays in office the better the corporate performance. This is because the CEO as the head of the executive needs job security to be able to take decisions that would enhance firm performance. In this regard, longer tenure is expected to have a positive influence on performance, although some studies have revealed that long serving CEOs resort to building an empire rather than focusing of productivity. However, some studies conducted to investigate the relationship between CEOs tenure and firm performances found mixed results. Example, (Kyereboah -Coleman, 2007) found that there is negative relationship between CEO tenure and Ghana firms' performance. Performance-related turnovers are clearly observed in cases where the CEO left before retirement. Simply put, the shorter the CEO's tenure in office, the poorer is his performance and vice versa. Contrary, in an earlier study carried out by (Hill & Phan, 1991), it was found that there is no significant relationship between CEO tenure and firm performance. Thus it is meaningful to test the relationship postulated in the following hypothesis: H4: There is a significant positive relationship between CEO tenure and firm performance.
The study also considered the effect of two control variables namely, firm size and leverage, when investigating the corporate board characteristics and firm performance relationship. The two variables are as follows and briefly described.

Firm Size
Using firm size as the control variable in this study is motivated by the fact that it has been found to be associated with companies with different characteristics. (Cheng, Evans, & Nagarajan, 2008) argued firm size and growth are important determinants of the size and structure of the boards. They found that firm size is directly related to the size and inversely proportional to the proxy for growth opportunities, that insider representation is inversely proportional to firm size and directly related to the proxy for opportunities growth and thus, a firm size has an effect on the firm performance.

Leverage
Leverage has been widely used as a control variable by a number of empirical studies (such as (Kyereboah-Coleman & Biekpe, 2006); (Alsaeed, 2006)that have examined the relationship between corporate governance and financial performance of the company. In their attempt to justify taking the leverage as a control variable, these studies have revealed that the debt has an effect on the financial performance of the company. As suggested by (Alsaeed, 2006), the firm leverage was measured by dividing total of liabilities by the total of assets. In the light of the above discussion, Table 1 summarizes the operational definitions of the variables used in this study following the common literature.

Measuring Firm Performance
This study also considered these performance indicators normally include profitability, efficiency, Size, leverage and liquidity. According to (Bourne, Franco, & Wilkes, 2003) a good performance measure must have broad base measure, Structured understanding of strategy, provide feedback and take actions on results. This study emphatically focused on those predominant measures that are important for the success of the various companies.
In that regard, the study would measure the financial performance of firms using accounting based measures. Examples used commonly in the governance literature namely ROA and ROE (Yusoff & Alhaji, 2012); (Abduh, Omar, & Duasa, 2011); and (Yusoff & Alhaji, 2012)and EPS.

Methodology
Research design: In order to achieve the objectives of this study, the correlation study research design was used to investigate the relationship (namely board size, board composition and independence(non-executive directors), CEO duality, CEO tenure, firm size and leverage as independent variables and firm performance using Return on Asset, Return on Equity, Earnings per share as dependent variables.  (14) represents 33% on the Ghana Stock Exchange totaling 42 companies. These companies have been excluded in this study owing to the differences in the regulatory requirements of the financial reports of the non-financial companies (Alsaeed, 2006). This study also employed secondary data to answer the research questions. The data was secondary collected from the annual reports of the selected companies that were on the Ghana Stock Exchange website. These annual reports includes; financial statements namely, Income statements, Cash flow statements, statement of changes in owner's equity, Statement of financial position, statement of corporate Governance as well as from the director's profile. The study used panel data framework which follows (Abor & Biekpe, 2007). It involves the pooling of observations on cross-sections of units over several time periods and it provided results that are not noticeable pure time-series in pure cross section or pure time series studies. Also firms that lack the independent variables` data are excluded and those lacking data for calculating the proxies for firm performance are also excluded. Hence, the final panel's data are of 28 observations, by this way the real contents only are retained and this is useful to maintain data away from any distortion.

The Proxy of Firm Performance
From the prior empirical studies the most commonly used proxies to measure the firm performance are ROA, ROE, and EPS (Denis & Sarin, 1999;Eisenberg et al., 1998), (Lipton & Lorsch, 1992) and (Hillman & Dalziel, 2003), (Ameer, Ramli, & Zakaria, 2010). All of thesis researches and many others used the same proxies for measuring performance. ROA is the accounting proxy for measuring performance.  Table 2 Measurements and expected relations are consistent with prior research.

0 Data Analysis And Model Specification 4.1. Data Analysis and Management Model Specification
The relationship that is subject to investigation is firm performance as a function of board characteristics. To ensure the robustness of the model and to reduce specification bias, the model includes control variables. Therefore, the model is restated as performance is a function of board structure and control variables. FIRMPFR=βit+ β (board structure) + K (Control factors) + ɛit.

Descriptive Statistics
The main objective of this analysis is to measure the level of firm performance of the nonfinancial companies. The descriptive analysis study shows the average of firm performance and the averages of the other components of dependent and independent variables.  Table 4 shows the descriptive statistics of the panel data for the period tested (2012 -2017). On the average, most of the companies achieved return on asset of -0.6% with the maximum of -91.64% and minimum of 29.76% respectively. The mean value of the return on equity was 5%, maximum of 62% and minimum of -71%. In terms of EPS, the mean value was -17% meaning and minimum value -6% and a maximum value of 2%. The descriptive statistics for board size shows that the average number of board members is 8 members of the sample. It also shows the minimum number in the sample is 5 members and the maximum is 11 members. Moreover, the average percentage of the independent directors in the board of the checklist is 4.14%. However, the minimum percentage of independent directors in the board is 2% and the maximum is 8% of the board is independent directors. The average number of years that CEOs stays in office is 2.5 years this is up to a maximum of 5 years and minimum of less than 1 year. Besides, relating to the standard skewness statistics which shows the normality of data. The data to be normally distributed the standard skewness should be within the range ±1.96 (Haniffa & Hudaib, 2006). From table 4, it's observed that board size, board composition, CEO duality and CEO tenure are normally distributed and within the range of standard skewness.

Correlation Analysis
This analysis is done as an initial step in the statistical modeling to determine the relationship between the dependent and independent variables. Prior to carrying out the multiple regression analysis, a correlation matrix was developed to analyze the relationship that exit between the independent variables as this will help in developing a prediction multiple models which will reveal no relationship in cases where the value of the correlation is 0. On the other hand, a correlation of ±1.0 means there is a perfect positive or negative relationship (Hair, 2010). The values are interpreted between 0 (no relationship) and 1 (perfect relationship). Also, the relationship is considered small when r = ±0.1 to ±0.29, while the relationship is considered medium when r = ±0.30 to ±0.49, and when r is ±0.50 and above, the relationship can be considered strong. Table 5 below reveals the correlation between board size, board composition, CEO duality, CEO tenure, firm size and leverage with firm performance (ROA), (ROE) and EPS 14 -0.08 1.00 ****P<0.01 ****P<0.05 Table 5 shows the correlation between firm performance, governance variables and the control variables. These findings reveal that Board size is negatively correlated (r = -0.04, p<0.05) with ROA but significant at the 0.05 level of significance. Moreover, there is also a Board compositions positive correlation (r= 0.58, p<0.01) with ROA at level of significance. However, CEO tenure is positively correlated (r=0.34, P<0.01) but not significant at 0.01. The firm size is also positively correlated (r=0.12, P>0.05) with ROA, whiles leverage is negatively correlated (r= -0.17, P>0.05) and CEO duality has no relationship and it's insignificant. To sum up, it is evidenced from above that, three variables namely, Board composition, CEO tenure and firm size have a positive correlation with ROA. In contrast, two variables, board size, and leverage have a negative correlation with ROA whiles CEO duality has no correlation with ROA.

3 Hypothesis Testing, Results and Discussions
In order to test the hypothesis of the study, the multiple linear regression analysis was adopted using the firm's financial performance (ROA), ROE and EPS as dependents and Board characteristic comprising board size, board composition, CEO duality and Tenure as independent variables and the firm size and leverage as control variables. The result of the regression was posted in Table 6. Based on the regression the model meaning that, at least one of the variables is a significant determinant of the firm performance (F value= 15.403, p<0.001). Besides, the variables included in the model were to explain % of the variance in the ROA, ROE and EPS as shown by the adjusted by R2indicator. These results also indicate that 57% of the variance in the ROA, ROE and EPS might be explained by other factors which were not included in the model.  Table 6, board size was found to have a positively significant effect on firm performance at the 0.05 level of significance (β= 0.6927, z= 4.86, p<0.000) which is consistent with the hypothesis predicted. Therefore, the hypothesis (H1) is accepted. This result suggests that larger boards are better than smaller boards, therefore the larger the board the better the performance of the company. This position is established on the assumption that larger boards are created with members with different skills and professional expertise from different backgrounds. This facilitates a better decision making and places the board in the better position to monitor the activities of management. This is support of (Rechner & Dalton, 1991) who reported that large boards are associated with stronger performance. These results supported the conclusion made by (Pfeffer, 1972) and (Zahra & Pearce, 1989) regarding the relationship between the board size and firm performance. A negative effect supports the findings of Shirk (2008) and Jessen 1993. This is also consistent with the agency theory perspective that a smaller board is related to better firm performance (Gertner and Kaplan, 1996;Yermack, 1996;Eisenberg et al., 1998;Sanda et al, 2005, Denis andSarin, 1999). However, due to management costs and free rider problems inherent in large boards, shareholder groups generally favor smaller boards and have pressured companies to reduce board size (Gertner & Kaplan, 1996). Similarly, the board composition was also found to have a positively impact on firm performance (β= 2.0039, Z= 7.31, p<0.000) at the 0.000 level of significance. This means that, the hypothesis formulated (H2) is accepted. Therefore, this is supported by (John & Senbet, 1998) (Brickley, Coles, & Jarrell, 1997), (Abor & Adjasi, 2007), (Khan & Awan, 2012) argued that a board is seen to be more independent if it has more non-executive directors. They all found is a positive relationship between independent directors and firm performance. Also (Rashid, De Zoysa, Lodh, & Rudkin, 2010) documented that firms with independent directors have less agency problems and have more alignments to shareholders. Again, there was no relation between CEO duality and firm performance. CEO duality has no relationship with firm performance. Therefore, I reject the H3.This means that, the only way to maintain the CEO position is performance. Following the same reasoning, CEO tenure was also found to have a positive impact on firm performance at the 0.000 level of significance (β=1.5581, Z=12.40, p<0.000).The statistical results provide a support for the hypothesisH4 regarding the relationship between CEO tenure and firm performance. I therefore accept the hypothesis H4. This result indicates that the longer period the CEO spends in his position the better the firm performance. This is because if the job security of the CEO is guaranteed then he/she would be prepared to take capital investment decisions that would have long-term effect on performance. It is also important that the board adopt a comprehensive approach in evaluating the performance of the CEO so that they do not concentrate only on the short term earnings of the firm but must look into the future the benefits the firm is likely to derive from decisions taken.
While the firm size was not a significant predictor of the firm performance (β= 0.9267, z= 25.4, p>0.1), the leverage was found to have no significant predictor of the firm performance at the 0.1 level of significance (β=