Effect of Chief Executive Officer’s Characteristics on Capital Structure of Publicly Listed Firms in Kenya

Based on a panel of publicly listed firms in Kenya over the period of 2008 to 2014, we examined if Chief Executive Officer’s Characteristics affects capital structure. CEO tenure, CEO gender and CEO age and CEO education were used as independent variables while the capital structure was used as the dependent variable of the study. The study used upper echelon theory, trade-off theory and agency theory. Majorly, descriptive statistics, Pearson correlation analysis and panel regressions were performed. Panel regression analysis was used to determine the effect of CEO characteristics on capital structure. CEO tenure had a negative and significant effect on capital structure, CEO age had a positive and significant effect on the capital structure, CEO gender and CEO education indicated a negative and significant effect on capital structure respectively. The study indicates that there is an association between CEO characteristics and capital structure of listed firms in Kenya. It is therefore instrumental for firms to appoint their CEOs based on the duration they have served the company, CEOs to sit in their position for a longer period of time and those who have the requisite knowledge and experience hence they can be tasked with making important decisions pertaining firms' financing. Keywords: capital structure, CEO characteristics, Upper Echelon Theory, Trade-Off Theory, panel data and Agency Theory DOI: 10.7176/RJFA/11-18-07 Publication date: September 30 th 2020


Introduction
The capital structure framework has been studied for a long time with no satisfactory theoretical model or significant empirical tests (Harris and Raviv 1991Bae, et al., 2011. Enormous academic effort has gone into identifying the relevant factors associated with the debt-equity choice but still remains a puzzle in the sense that financial theories have unable to ccurately describe firms' behavior (Malmendier, 2018). To date, a theoretical explanation is still lacking and empirical results are not yet sufficiently consistent to resolve the capital structure issues on how firms choose between the different methods of financing. Indeed, several theories have been proposed to offer different explanations of capital structure since the publication of the seminal paper of Modigliani and Miller (1958). Modigliani-Miller (MM) propagated that the choice between debt and equity financing has no material effect on the firm value and consequently management should not be concerned about the proportion of debt and equity that constitute the capital structure of the firm. Various capital structure theories have been developed during the last 62 years in order to determine the determinants and financing mix used by corporations to finance investments, however there is no universal determinants and the theory of the debt-equity choice (Saona et al., 2018). Outstanding empirical and theoretical work in the field of capital structure has been done using several explanatory variables to explain capital structure. For example, Modigliani and Miller (1963) added the effect of corporate taxes to the capital structure framework Modigliani and Miller (1958) and found that firm value is maximized when the firm is financed entirely with debt which is of course impracticable because some ownership equity must exist in a firm. Since then, theories of capital structure have been developed to determine whether it plays a key role in the financing activity. For instance, debt and taxes (Miller, 1977), bankruptcy costs (Stiglitz, 1972;Titman, 1984), agency costs (Jensen and Meckling, 1976;Myers, 1977), information asymmetries Myers, 1984), firm level determinants, , industry-level determinants ( Lööf, 2004; showed contradicting point of view in describing the impact of particular factor on capital structure. There is a large body of work arguing that a firm's capital structure is influenced by managerial disposition (Bancel and Mittoo, 2004;Majumdar & Chhibber, 1999;Barton & Gordon, 1988). Artikis et al., 2007 & and implications for firm outcomes. It proposes that organizational outcomes are related to the particular demographic characteristics of top level decision-makers. The core assumption underlying Hambrick and Mason's (1984) theory is the belief that demographic characteristics serve as surrogates for cognitive orientations, beliefs, values, perceptions and knowledge.
According to Hambrick (2007), CEOs act on the basis of their personal interpretations of given situations, and these interpretation are a function of their experience. Studies grounded in upper echelons theory contend that demographic characteristics such as age (Wiersema & Bantel, 1992;Díaz-Fernández et al., 2019;Richardet et al., 2019), tenure (Chen et al.,2019), experience Zhang, 2019), educational level (Shahab et al., 2020), functional background (Chen et al., 2019), gender .) and ethnicity (Carter et al., 2010) are important proxies for cognitive bias, and that these characteristics have an impact upon the ability to make decisions that enhance firm performance.
Although upper echelons theory is based on top management Hiebl (2014), it is important to note that boards of directors are involved in making decisions which have an effect upon firm performance Naciti (2019). Research indicates that the role of the board includes advising and monitoring, hiring and firing management and reviewing, approving, and facilitating strategic decisions Tarus & Aime, 2014;Johnson, et al., 2013). In the light of the theory it can be argued that to remain relevant in an increasingly competitive world, having the optimal mix of skills, expertise and experience is paramount to ensure that the board as a collective is equipped to guide the business and strategy any firm. Companies that fail to dip into the ever-deepening talent pool of diverse, well-educated and ambitious individuals run the risk of limiting value creation, compromising sustainability and undermining their long-term competitiveness (Squires, & Elnahla, 2020). Thus, on the basis of these arguments, we examined optimal mix of skills which include CEO tenure, CEO gender, CEO age and CEO education in relation to capital structure

CEO tenure
Tenure of the board of directors means the average period the board members have been in their board positions ( Tejerina-Gaite, & Fernández-Temprano, 2020). Board tenure reflects the likelihood that board members' control over the monitoring of executives will increase as the average tenure period increases (Graham, 2020). Most of the existing research has argued that lengthy CEO tenure is negatively related to leverage Kaur & Singh, 2019).). further it is that argued that longer tenure exacerbates entrenchment, which is an important aspect in decision-making (Zwiebel,1996). For example, Berger et al., (1997) argue that entrenched managers are likely to pursue lower leverage in the capital structure to avoid monitoring pressures relating to high levels of debt. Vafeas (2003) developed an expertise hypothesis suggesting that longer tenure leads to greater firm and industry knowledge, thereby improving the monitoring ability of the board members. The expertise hypothesis is used to argue that longer tenure is associated with improved director performance, because directors develop more expertise over time and become more willing to criticize the management (Bebchuk et al., 2002). Thus, longtenure boards are expected to have more information and experience at their disposal and, thus, to be able to provide more active monitoring and advice to management.
In general, upper echelons theory studies suggest longer-tenured CEOs initiate fewer strategic actions. In fact, some upper echelons theory scholars use CEO tenure to proxy constructs like persistence, commitment to the status quo, and rigidity (Finkelstein & Hambrick, 1990;Graf-Vlachyet al., 2020). According to Matta & Beamish, (2008) CEOs are more concerned about their legacies and are less willing to pursue new initiatives and launch risky investments that threaten those legacies and during their tenure, CEOs accumulate power, knowledge, and skills to resist pressure from other stakeholders (Meyer, 1975 andBoyer, 2005).). Longer-tenured CEOs, for example, have had more opportunities to handpick subordinates (Miller, 1991;Hambrick & Fukutomi, 1991).) and nominate board members (Westphal, 1999 andFan et al., 2019). Through these selections, CEOs can minimize dissent and surround themselves with people who have worldviews similar to their own (Acharya & Pollock, 2013;Zajac & Westphal, 1996a). Thus, as tenure increases, CEO autonomy may increase, and the pressure CEOs receive from other constituencies may decrease and willingness to initiate or fund new strategic actions declines as their tenure as CEO increases (Miller, 1991).
Conversely, CEOs tend to confront power struggles early in their tenure. During this time, for example, they are at higher risk of dismissal (Shen & Cannella, 2002). Thus, CEOs are motivated to prove their competence and demonstrate their power, often by investing in major strategic actions, early in their tenure (Zona 2016). For example, strategic actions to change the firm's scope or strategy are a way for CEOs to exert their authority and begin to implement their visions for the firm. In addition, new CEOs may seek to co-opt or appease knowledgeable top management team or board members who provide mentoring and support early in their tenure (Shen, 2003). In turn, they may authorize strategic actions that are favored by these powerful individuals. Last, because shorttenured CEOs have less experience in the CEO position, it might be necessary for them to experiment with the different strategic actions available (Hambrick & Fukutomi, 1991;Ferreira, et al., 2016). Thus, we posit that: H1: CEO tenure is positively related to capital structure of listed firms in Kenya.

CEO Gender
A considerable body of work has been conducted on the effects of director gender, much of which takes the stance that gender diversity affects board cognition, dynamics, and decision making and in turn, firm-level outcomes (Torchia, 2016). It's argued that gender diversity affects board dynamics but not the firm's bottom line (Terjesen, et al., (2009). Adams & Ferreira (2009) reported that gender diverse boards are better in monitoring executive directors and show that women have a better attendance rate in board meetings than men. According to Alves et al., (2015) increased presence of female directors in the board could improve the effectiveness of the board, reduce information asymmetry between the management and outside investors, and consequently lead firms to have better access to external capital.
The claim that gender diversity has a positive role in firm performance may be supported from different theoretical perspectives. The first of these is agency theory, which is concerned with the independence of directors and the ability to monitor management (Bathala & Rao, 1995). Research shows that gender diversity provides a board with the wherewithal to monitor management (Carter et al., 2003;Konrad et al., 2010;Terjesen et al., 2009). Studies suggest that having more women directors is an effective way of executing monitoring functions (Hillman et al., 2002;Carter et al., 2003). Women are likely to possess managerial skills such as legal, human resources, communication and public relations skills, as compared with men, who are more likely to possess the line functions of marketing and operations (Zelechowski and Bilimoria, 2004). It is argued that if women directors are known to be effective monitors, then investors will place higher valuation premiums on those firms with greater gender diversity in the boardroom Campbell et al., (2008).
Arfken et al., (2008), Nielsen & Huse (2010) and Burgess & Tharenou (2002) all explain the competitive benefits that can be enjoyed by firms employing women on boards of directors. They point to women having an intimate knowledge of consumer markets and customers and to women being innovative but also socially and community minded. A combination of changing social attitudes and stronger equality legislation appears to have had some effect in improving the participation of women on company boards as reported in US-based studies (Kang et al. 2007;Lückerath-Rovers 2013;Adams and Ferreira 2008). However, evidence from other developed countries is less encouraging. In the case of Australia, Kang et al. (2007) report that 33% of companies have no female directors and 51% only have one woman on the board. In 2002, only 37% of companies in Tennessee had at least one female director on the board (Arfken et al., 2004).
There is a strong evidence to suggest that women participation is purely seen as a legitimating device in regard to internal and external stakeholders (Mahadeo, 2012;Adams and Ferreira 2008). As a result, the positive features of women participation in boards do not consistently emerge from empirical studies-at least not in a statistically significant way and in relation to financial outcomes. Nonetheless, Catalyst (2004) reports on 353 Fortune 500 companies in the United States over the period of 1996-2000. They found that companies with the highest representation of women on their top management teams had a 35% better return on equity and 34% better total return to shareholders than those companies with the lowest female representation.  also find that women tend to serve on better performing boards but overall there is little systematic evidence of direct links between gender diversity and performance. Alternatively, Adams and Ferreira's (2008) study uncovers both indirect and direct links and finds a positive link between gender and governance but also a positive relationship between return on assets and gender. Thus, we posit that: H2: CEO Gender is positively related to capital structure of listed firms in Kenya.

CEO Age
In a research review, Hambrick and Mason (1984) hypothesized that age affects behavior relating to risk-seeking, novelty and information-seeking. Other empirical studies have showed that age is an important variable which influences behavior, beliefs, values and attitudes, as well as strategic orientation (Yang & Wang, 2014;Herrmann and Datta, 2005). Kang et al., (2007) argued that there is inherent nature of company management and career progression does play a significant role in having a board which mainly consists of mature, experienced and by default older directors. Retired executives are generally seen as ideal non-executive board members (Krames, 2003) and appear more likely to be invited to sit on boards relative to other less experienced and younger age groups. According to Chen (2014), there is a significant relationship between capital structure and age plus experience of top employees. Firms with older and qualified board membership have low leverage or debt ratio. According to Yasser et al., (2015), there is a significant relationship between capital structure and CEO age. The finding concurs with Khurana (2004) that firms with older CEOs generally have low gearing levels. He argued that older CEOs exert pressure on managers to follow lower gearing levels and enhance firm performance. It is argued that age difference affects the capital structure decisions of managers and younger managers, more frequently select to operate in a more competitive environment than older do (Shan et al., 2020). However, the difference still exists not due to different risk aversion, but because young managers are more overconfident and there are age differences in preferences for performance in a competitive environment (Choi, 2018) The arguments for promoting age homogeneity or heterogeneity at board level remain unconvincing from a Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.18, 2020 53 functional perspective. Whilst an age-diverse board may enable some division of labour and encourage board development and learning, it relies on the assumption that directors will play their selected roles and does not address the likely short-term issues of communication and trust arising from generational gaps (Finkelstein & Hambrick, 1996). On the other hand, a homogeneous board is likely to avoid these latter issues but composition may encourage complacency, cronyism, lack of interest in new ideas/strategies and decisions based on compromises. Thus, we posit that: H3: CEO Age is positively related to capital structure of listed firms in Kenya.

CEO Education
Drawing upon upper echelons theory, Hambrick and Mason (1984) postulated that educational level is a measure of an individual's knowledge, skill base and cognitive skills. Similarly, social scientists have suggested that different educational levels are associated with varied social status, networking and professional development paths (Mirowsky & Ross, 2003). Evidence from earlier studies interrogating the role of education has established a link between education and innovation levels (Wang & Yin, 2018) The educational background of the CEOs is believed to be positively related to debt, implying that bettereducated owners do have greater possibilities of borrowing (Abor, 2008). The studies on the effect of the education levels have focused mainly on the graduate level of education or MBA degrees. For instance, Kaplan et al., (2012) noted that education levels are considered as key determinants of corporate decisions. This would be particularly important if the owner had no book-keeping knowledge. According to  the level of education appears to have an important positive impact on micro and small enterprises' debt-raising capacities. There is no consistent, long-term relationship between CEO education and capital structure decision. Furthermore, there is no strong evidence of a relationship between CEO education and capital structure decision, while it is weak-and, perhaps, statistically insignificant. Ting et al., (2015) who studied Malaysian firms and found that CEO education level positively correlated with leverage. Cronqvist, et al., (2012) observed that CEOs with MBAs are more comfortable with debt and thus they aggressively use more debt. Within Eastern Europe, Rakhmayil and Yuce (2009) observed firms ran by CEOs with MBA degrees, graduates from highly reputable business schools and with have professional certification tend to use higher leverage when compared to their counterparts.
Regarding the educational levels of the CEOs, Cronqvist, et al., (2012) indicated that CEOs with MBAs are more comfortable with debt, while CEOs from older age cohorts are not. In another study, Custódio and Metzger (2014) observed that educational levels have a significant role in the use of debt in corporate financing. The study indicated that CEOs with financial management backgrounds tend to use more debt notwithstanding the credit conditions.
The empirical studies on the education level of the CEO have shown a significant positive association with the corporate leverage decision such that executives with MBAs or graduate -level are more likely to issue debt instruments (Custódio & Metzger, 2014). The empirical studies have been done on developed capital markets where the capital markets are vibrant as opposed to the country which has bank-based systems. These studies have elaborately considered developed with more emphasis on the developed capital markets. The differences in the context confer other researchers with an opportunity for studies in the burgeoning capital market in Sub -Saharan Africa. Indeed, many directors engage in occupations and activities that have little in common with their original professional or academic studies or they may have studied different subject areas (Chao et al., 2017). However, Boards with diverse educational levels are better equipped to enhance the quality of decision making by bringing in different perspectives. Thus, we posit that: H4: CEO education is positively related to capital structure of listed firms in Kenya.

Methods and data
The data used in this study were derived from publicly listed firms in Kenya during the period 2008-2014. The total number of firms listed on the NSE, as at the end of 2014, was 64: these firms fall under different sectors of the economy, such as agricultural, commercial and services industry, telecommunications and technology, automobile and accessories, investment, manufacturing and allied and construction. Firms which issued initial public offers (IPOs) after 2008 and those that were delisted or suspended between 2008 and 2014 were excluded to offer consistency, precision, completeness and robustness of the result. Therefore, the the total number of firms used in the study was 37, yielding a total of 264 firm year observations. The study was conducted using secondary sources which were achieved by analyzing the content of financial reports of 37 companies quoted in NSE Kenya. This was suitable for this study because all the audited information about the NSE firms was readily available for the public as required by the company law of Kenya.

Measurement of Variables
Capital structure was measured as ratio of debt to equity .) While CEO tenure was Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.18, 2020 measured by counting the years that a chief executive has been in office (Ali & Zhang, 2015). CEO age was measured using a number of years ages (Dagsson, 2011). CEO education was measured by the level of education (King et al., 2016) and finally gender was measured using a dummy variable, where male were coded as 1 and female 0 (King et al., 2016).
The study incorporated control variables into the analysis, firm size and firm performance is known to affect capital structure. Firm size was measured as a natural log of total assets . This was controlled because previous studies have found firm size to be positively related to leverage (Friend and Lang, 1988;, whereas others have found it to be negatively related . Large firms may use more leverage in their capital structure because of the availability of tangible assets to secure debts (Nicodano & Regis, 2019) The study also controlled for firm performance, because of strong indications of its effect on capital structure (Le and Phan, 2017). For example, pecking order theory postulates that firms generating profits finance their assets from retained profits first before resorting to debts. Thus, a negative relationship was found between profitability and leverage . Consistent with previous studies, we calculated firm performance as earnings before depreciation, interest and tax divided by total assets .

Model specification
The regression model which assumes linearity, normality, constant and independence is as follow  Table 4.1 presents a summary of descriptive statistics of the dependent and independent variables used in the study. The statistics of capital structure of the firms had a mean of 8.79 with the standard deviations of 16.96. CEO tenure showed a mean of 6.76 and standard deviations of 3.27 suggesting that majority CEOs in NSE firms hold an average of 5 years or most contracts of employment ends at the fifty year. The longest CEO tenure in NSE is indicated to be 14 year. Result further indicates that the average age for the CEOs for publicly listed firms in Kenya is 48 years and it is dominated by males. The study found that majority of CEOs in NSE holds Master's degree suggesting that for one to be a CEO, it requires high academic achievements.  Table 4.2 presents Pearson correlation results for the variables used to assess its association. The findings shows that CEO tenure was negatively and significantly correlated to capital structure (r = -0.29, ρ<0.01) suggesting that as the tenure of the CEO increases it reduces capital structure of a firm. Additionally, CEO age was indicated to be positively related with capital structure (r = 0.192, ρ<0.01) suggesting that CEOs' age at an average of 48 year is likely to initiates changes to capital structure in a positive away. CEO education is negatively and significantly correlated to capital structure (r = -0.177, ρ<0.01) suggesting advanced education of a doctoral-level degree in business, engineering, science, and other fields) is likely to equip directors with skills in research that facilitate assessment of research projects in the local firm. It may provide them with knowledge related to innovation Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.18, 2020 management. However, boards can be configured to improve efficiencies, thereby reducing R&D spending. CEO gender is negatively and significantly correlated to capital structure (r = -0.08, ρ<0.01) however this relationship is very negligible suggesting that CEOs gender have lower leverage. The association of the control variables showed that, firm performance, board size and firm size has negligible association with capital structure.  Breusch and Pagan, (1979) if the test statistic has a pvalue below an appropriate threshold (p<0.05) then the null hypothesis of homoskedasticity is rejected and heteroskedasticity assumed.

Model Selection-The Hausman test
According to Baltagi, (2008) there are a variety options to estimates a panel data regression model. These approaches are ordinary least squares (OLS), fixed effects, and random effects. Each estimator has some specific assumptions of the error term. While OLS does not take into account firm individual effects and period specific effects, fixed effects and random effects control for these elements.
The study used The Hausman test for the random effects versus the fixed effect model in order to determine the proper model. According to Clark and Linzer, (2015) fixed effects and random effects are two options that are widely used in panel data regression analysis. However, which one should be applied depends on the standard Hausman test (Baltagi, 2008).
According to Greene (2003) the Hausman test is a useful device for determining the preferred specification of the common effects model. Random effects and fixed effects estimations are based on different assumptions that whether the unobserved factors are correlated with independent variables in the model. While the fixed effects estimator allows the unobserved effects to be arbitrarily correlated with the included explanatory variables, the random effects approach assumes the unobserved individual effects are uncorrelated with the observed explanatory variables (Hsiao, 2014).
In this case, fixed effects model is appropriate. Shown in table 4.4 the Hausman test calculates the value of P = 0.2398 hence, fixed effect estimate is proper for data analysis. Furthermore, Hausman test compares an estimator (b) that is known to be consistent with an estimator (B) that is efficient under the assumption being tested. The null hypothesis is that the estimator (b) is indeed an efficient (and consistent) estimator of the true parameters. If this is the case, there should be no systematic difference between the two estimators. If there an exists a systematic difference in the estimates, you have reason to doubt the assumptions on which the efficient estimator is based (Hausman, 1978).
Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.18, 2020 (5) Table 4.6 illustrates the coefficient estimates of CEO tenure to be significant at (β = -1.36,ρ<0.05), hence we concluded that CEO tenure has a negative and significant effect on capital structure, this suggest that entrenched CEOs employ lower debt in order to reduce the performance pressures associated with high debt capital. CEO gender had negative and insignificant effect on capital structure (β = -7.20, ρ>0.05). This suggests that the presence of gender diversity does not offer better insight on the adjustment process toward the target debt-to-equity ratio. Table 4.6 further illustrated the coefficient estimates of CEO age to be significant at (β=.533, ρ<0.05) this suggest that older executives are more likely to initiate changes positively. For example old executives is deemed to have a diverse experience and well conversant with the industry-level determinants of financial leverage of the company than young executives therefore prompting better leverage. Finally table 4.6 indicated that CEO education had negative effect and it's significant on capital structure (β=5.55, ρ=<0.05), this suggests that boards can be configured to improve efficiencies, thereby reducing R&D spending. Further since most CEOs of listed firms in Kenya possess advanced degrees there is likelihood that these firms engage large research and development (R&D). If a large R&D intensity relative to one's industry peers indicates that the firm is trying to be an innovator, then there is good reason to predict that it will also want to maintain low leverage

Empirical results
The empirical analysis of the study as indicated in table 4.5 shows that the control variables of the study that is firm performance and firm size had no influence on the effect of CEO's characteristics and capital structure

Discussion and conclusions
The study established that CEO tenure has a negative and significant effect on the capital structure. According to  long tenure of CEOs increases their credibility and independence, making them Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.18, 2020 overconfident hence complacent subordinates becomes reluctant to challenge anything which could influence their capital structure decision making skills. In a similar nature, long tenure magnifies a CEOs ego to the extent that/he may think that he can do no wrong, even if her/his action could jeopardize debt equity. This negatively impact on firms' capital structure. Myers, (2001) showed a negative relationship between executive firm tenure and capital structure. However, prior authors Graham, & Leary (2011) propose a positive relationship between tenure and capital structure on the basis that tenure improves the experience of the CEO, which consequently decreases his reliance on subordinates and so makes delegation of decisions including leverage less frequent. Nonetheless, in terms of board tenure, a board with a long tenure tends to run a good supervision in order to achieve the company's goals (Farag & Mallin, 2019). Simply because the longer the tenure of directors on the board, the better knowledge of company and their executives they will get. The study findings are in line with the prior literature with regard to the negative influence of CEO tenure on capital structure.
With respect to CEO gender, the finding of the study showed that CEO gender had negative and insignificant effect on capital structure. The findings concur with Jianakoplos and Bernasek (1998) and (Ali, et al., 2011) who found that single women are more risk-averse than single men in capital structure decisions. Additionally, Niessen and Ruenzi (2007) are of the opinion that female fund managers are more risk-averse than male fund managers in their investment decisions which could influence the liquidity and debt equity ratio of a company. Furthermore, Bennedsen et al., (2006) argued that the control of female CEOs grow slower than firms under the control of male CEOs. Besides, Zeng & Wang (2015) argued that gender, affects investment-cash flow sensitivity and corporate investments made by male CEOs are more sensitive to cash flow, particularly in the equity dependent companies, compared to investments made by female CEOs.
Concerning the CEO age, the finding of the study showed that that CEO age has a positive and significant effect on capital structure. This implies that the CEOs ability to bear risk could be shaped by his or her age thus influencing his capital structure decision making skills. Consistently, prior literature indicates that the structure of responsibility and power of decision making in publicly traded companies is hierarchical according to the age of top executives. As such, the CEO who is an older person is at the top and is influential in capital structure decision making Graham, et al., (2010) According to Niederle and Vesterlund (2007) age difference affects the capital structure decisions of managers. Similarly, to Graham, et al., (2010) there is a significant relationship between capital structure and age plus experience of top employees. Consistently, Abor (2007) also show a positive relationship between age of the qualified board and financial leverage (capital structure). In addition, Naseem, (2019) showed that there is a significant relationship between capital structure and CEO age.
Finally the study found that CEO education has a positive and significant effect on capital structure. The results is Contrary that of Naseem, (2019) who noted that the educational background of the CEOs is believed to be positively related to debt, implying that better educated owners do have greater possibilities of borrowing. As well, the level of education appears to have an important positive impact on micro and small enterprises' debtraising capacities .

Conclusion
This study examined the effect of CEOs characteristics on capital structure of publicly listed firms in Kenya. On CEO tenure, the study has established that CEO tenure has a negative effect on the capital structure. As CEOs acquire firm specific knowledge early in their tenure, the result is better firm performance. Eventually as tenure continues to advance, boards lose their oversight and firms engage in more value-destroying activity. The study furthermore concludes that, majority of the CEOs are male. The CEO position for the firms listed in NSE is therefore male dominated. Gender diversity is likely to bring on board a wide array of individuals that are knowledgeable and conversant with the management of the firms. However, the study has indicated that CEO gender has no significant effect on the capital structure. There is thus need for further studies on the same so as to validate this concept. We further found that CEO age has a positive and significant effect on the capital structure. The average age for the CEOs is 48 years. This is an indication that the CEOs are older individuals. The CEOs are therefore more likely to pursue lower leverage or debt ratio so as to enhance the firm performance. Finally the existence of educated CEOs could lead to better management decisions and help firms in attracting better resources, the study has indicated that CEO education has a negative effect on the capital structure. It can therefore be inferred that the more educated the CEO gets, the more cautious he/she becomes of the risk of bankruptcy lied in debt. As a result, firms will have less capacity to borrow in times where financing is necessary.

Further Research Recommendations
The study focused on the effect of CEO characteristics on capital structure of publicly listed firms in Kenya. The results are confirmable to the literature in international setting. However, further insight into the idea is needed to support the findings. This study therefore recommends that another study be done to augment finding in this study; it therefore recommends a study be done on more number of firms rather than including only firms in the NSE for the sake of generalizing the results of the study. Moreover, including moderator factors can also be made in the