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THE RELATIONSHIP BETWEEEN FINANCIAL LEVERAGE AND PROFITABILITY OF FIRMS LISTED AT THE NAIROBI SECURITIES EXCHANGE LYDIAH KABARE KUNGA A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN FINANCE, SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI OCTOBER 2015 DECLARATION This research project is my original work and has not been presented to any other University or Institution for an award of a degree. Signature ……………………………………… Date……………….………… Lydia Kabare Kunga D63/70982/2014 This research project has been submitted for examination with my approval as the University of Nairobi supervisor Signature ……………………………………… Dr. Kennedy Okiro Lecturer Department of Finance and Accounting School of Business, University of Nairobi ii Date……………….………… ACKNOWLEDGEMENT Thanks to Almighty God for His grace and lighting my path daily. I am fully indebted to my supervisor, Dr. Kennedy Okiro who made a monumental task much lighter. Thank you for your advice, insightful criticisms and guidance. My immeasurable appreciation to my family and friends for helping me survive the stress from this year and encouraging me not to give up. Thank you. My deepest gratitude goes to my colleague, Christopher Githuku who took on extra duties while I worked on the project and Sally Cheptoo, my most trusted cheerleader. iii DEDICATION This project is dedicated to my family. Thank you for your solid support and encouragement during this entire period. A special dedication goes to the memory of my sister Loise, her strong faith in what she stood for and believed. iv TABLE OF CONTENTS DECLARATION ..................................................................................................... ii ACKNOWLEDGEMENT ...................................................................................... iii DEDICATION ........................................................................................................ iv LIST OF TABLES ................................................................................................ viii LIST OF ABBREVIATIONS AND ACRONYMS................................................ ix ABSTRACT ............................................................................................................. x CHAPTER ONE: INTRODUCTION ..................................................................... 1 1.1 Background of the Study...................................................................................... 1 1.1.1 Financial Leverage ................................................................................ 2 1.1.2 Firm Profitability ................................................................................... 3 1.1.3 The Relationship Between Financial Leverage and Profitability ............ 4 1.1.3 Nairobi Securities Exchange .................................................................. 4 1.2 Research Problem ................................................................................................ 5 1.3 Research Objective .............................................................................................. 7 1.4 Value of the Study ............................................................................................... 8 CHAPTER TWO: LITERATURE REVIEW ........................................................ 9 2.1 Introduction ......................................................................................................... 9 2.2 Theoretical Framework ........................................................................................ 9 2.2.1 Modigliani-Miller Theorem ................................................................... 9 2.2.2 Pecking Order Theory ......................................................................... 10 2.2.3 Trade-Off Theory ................................................................................ 12 2.3 Determinants of Firm Profitability ..................................................................... 12 2.3.1 Profitability ......................................................................................... 13 2.3.2 Firm Size ............................................................................................. 13 v 2.3.3 Liquidity ............................................................................................. 14 2.4 Empirical Review .............................................................................................. 14 2.5 Summary of the Literature Review..................................................................... 18 CHAPTER THREE: RESEARCH METHODOLOGY ...................................... 20 3.1 Introduction ....................................................................................................... 20 3.2 Research Design ................................................................................................ 20 3.3 Population ......................................................................................................... 20 3.4 Data Collection .................................................................................................. 20 3.5 Data Analysis .................................................................................................... 21 3.5.1 Analytical Model................................................................................. 21 3.5.2 Tests of Significance ........................................................................... 22 CHAPTER FOUR: DATA ANALYSIS, RESULTS AND DISCUSSION........... 23 4.1 Introduction ....................................................................................................... 23 4.2 Response Rate ................................................................................................... 23 4.3 Descriptive Statistics.......................................................................................... 23 4.4 Pearson Product Moment Correlation Coefficient .............................................. 25 4.5 Regression Analysis and Hypothesis Testing ..................................................... 26 4.5.1 Model Summary .................................................................................. 26 4.5.2 Analysis of Variance ........................................................................... 27 4.5.3 Model Coefficients .............................................................................. 27 4.6 Discussion of Findings ....................................................................................... 29 CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS ................................................................................................................................ 30 5.1 Introduction ....................................................................................................... 30 5.2 Summary of Findings ......................................................................................... 30 vi 5.3 Conclusion......................................................................................................... 32 5.3 Recommendations.............................................................................................. 32 5.4 Limitations ........................................................................................................ 33 5.5 Suggestions for Further Research ....................................................................... 33 REFERENCES ...................................................................................................... 34 APPENDIX I: LIST OF FIRMS LISTED AT NSE (2014) .................................. 38 APPENDIX II: SECONDARY DATA OF QUOTED FIRMS EXTRACTED FROM AUDITED REPORTS .............................................................................. 41 vii LIST OF TABLES Table 4.1 Descriptive Statistics ................................................................................ 24 Table 4.2 Pearson’s Correlation Analysis ................................................................. 25 Table 4.3 Model Summary ...................................................................................... 26 Table 4.4 Analysis of Variance ................................................................................ 27 Table 4.5 Model Coefficients ................................................................................... 27 viii LIST OF ABBREVIATIONS AND ACRONYMS CMA Capital Markets Authority NSE Nairobi Securities Exchange ROA Return on Assets ROE Return on Equity SPSS Statistical Packages for Social Sciences ix ABSTRACT This study sought to establish the relationship between financial leverage and profitability of firms listed at the Nairobi Securities Exchange. To achieve this objective a descriptive research design was used. The study considered firms that have been listed on the NSE for the past five years and utilized secondary data obtained from the period 2010-2015. Data was collected from 47 listed firms which represented a response rate of 73 percent. This was considered sufficient for making generalization on the whole population. The study covered a period of five years from 2010-to-2014. Data was analyzed using descriptive statistics, correlation analysis and regression analysis. The results indicated that liquidity and financial leverage depicted a negative relationship with profitability. Size of the firm was found to have a positive relationship with profitability of listed firms at the Nairobi Securities Exchange. The limitation of this study is that it used only four variables only, namely; financial leverage, firm size, profitability and liquidity. Profitability is affected by many factors other than the ones discussed in this study and therefore it is important to consider other factors that have bearing on profitability and establish whether the findings will hold or not after which conclusive results can be drawn. The study recommends that listed firms should look for alternative ways of financing their projects other than using financial leverage. From the results obtained it is evident that financial leverage does not contribute to profitability of the firm. This is because when a firm borrows more from its creditors then the firm has to pay more amount of cost of debt to the creditor which is the interest rate. This leads to less net income for the firm and hence lower profitability. x CHAPTER ONE INTRODUCTION 1.1 Background of the Study Businesses deploy a number of strategies to improve profitability, including streamlining processes, outsourcing and integrating new technologies. Financial leverage offers an alternative way to increase profits by financing a portion of the business through loans or by issuing stock. Akhtar (2012) indicates that financial leverage does not guarantee an improvement in profitability. All businesses must cope with a degree of uncertainty regarding future sales, but businesses offering new or untested products and services run much higher risks of failure. As a consequence, securing financial leverage for such businesses may come at the cost of unfavorable interest rates and higher dividend payments for stockholders, which makes it more difficult to improve profitability. Businesses offering products or services with a demonstrable track record with consumers can often secure financial leverage at more favorable rates. Cheng and Tzeng (2010) a firm that successfully uses leverage demonstrates by its success that it can handle the risks associated with carrying debt. This can become an important factor when additional financing is needed. Not only will loans more likely be available, but they will be available at more attractive interest rates. Like individuals, companies with solid financials, but little credit history, sometimes have trouble convincing lenders that they are deserving of a good rate. Leverage under financial strategy planning helps to increase the rate of return by generating a greater return on borrowed money than the cost of using that money. If firms return on assets is greater than the before tax interest rate paid on debt then we can say that leverage is positive. Companies that dislike to borrow funds for the 1 financing of their assets have to rely completely on equity financing therefore they are free from any fixed amount of charges to pay which means there is no financial leverage associated with that company. It is obligatory that every individual organization has to give especial focus towards the most important questions of amount of financial leverage, associated cost of capital and their impact on the firm’s profitability (Amalendu, 2012). 1.1.1 Financial Leverage Abor (2005) defines financial leverage as the amount of debt that an entity uses to buy more assets. Leverage is employed to avoid using too much equity to fund operations. An excessive amount of financial leverage increases the risk of failure, since it becomes more difficult to repay debt. The financial leverage formula is measured as the ratio of total debt to total assets. As the proportion of debt to assets increases, so too does the amount of financial leverage. Financial leverage is favorable when the uses to which debt can be put generate returns greater than the interest expense associated with the debt. Many companies use financial leverage rather than acquiring more equity capital, which could reduce the earnings per share of existing shareholders. Financial leverage is a risky approach in a cyclical business, or one in which there are low barriers to entry, since sales and profits are more likely to fluctuate considerably from year to year, increasing the risk of bankruptcy over time (Amalendu, 2012). Agrawal and Nagarajan (1990) argue that financial leverage may be an acceptable alternative when a company is located in an industry with steady revenue levels, large cash reserves, and high barriers to entry, since operating conditions are sufficiently steady to support a large amount of leverage with little downside. There is usually a 2 natural limitation on the amount of financial leverage, since lenders are less likely to forward additional funds to a borrower who has already borrowed a large amount of debt. 1.1.2 Firm Profitability Penman (2007) defines profitability as the ability to make profit from all the business activities of an organization, company, firm, or an enterprise. It measures management efficiency in the use of organizational resources in adding value to the business. Profitability may be regarded as a relative term measurable in terms of profit and its relation with other elements that can directly influence the profit. Profitability is ‘the ability of a given investment to earn a return from its use (Srivastava & Srivastava, 2006). Profit maximization is said to be the main objective of all firms. In a competitive marketplace, a business owner must learn to achieve a satisfactory level of profitability. Increasing profitability involves determining which areas of a financial strategy are working and which ones need improvement. Maheshwari (2001) explains that profitability is the final measure of economic success achieved by a company in relation to the capital invested. This economic success is determined by the magnitude of the net profit. To achieve an appropriate return over the amount of risk accepted by the shareholders is the main objective of companies operating in capitalist economies. After all, profit is the propulsive element of any investments in different projects. The assessment of profitability is usually done through the Return on Assets (ROA) which equals to Net Income divided by Total Assets and ROE (Return on Equity) that is equal to Net Income divided by Equity, which is the ultimate measure of economic success. 3 1.1.3 The Relationship Between Financial Leverage and Profitability Wald (2000) observes that highly profitable firms have lower levels of leverage than less profitable firms because they first use their earnings before seeking outside capital. In addition, stock prices reflect how the firm performs. Firms tend to issue equity rather than use debt when their stock price increases, so that their leverage levels stay lower than firms using debt. Similar findings were reported in Gu (1993), Sheel (1994), Sunder and Myers (1999) and Wald (2000). According to Wald (1999), profitability, which is the most significant determinant of firms’ financial leverage, negatively affects the debt to asset ratios. Sheel (1994) also supported the negative relationship between debt-to-asset ratio and non-debt tax shield and between a firm’s leverage behavior and its past profitability. According to previous studies, financial leverage affects cost of capital, ultimately influencing firms’ profitability and stock prices. Several researchers have studied the firms’ debt use and suggested the firms’ debt-equity decision is generally based on a trade-off between interest tax shields and the costs of financial stress (Upneja & Dalbor, 2001). According to the trade-off theory of capital structure, the optimal debt level balances the benefits of debt against the costs of debt. The tax benefits of debt dominate up to certain debt ratio, resulting in higher return on equity, but the benefit would be less than the cost after the level of debt ratio. The more a company uses debt, the less income tax the company pays, but the greater it’s financial risks. 1.1.3 Nairobi Securities Exchange The Nairobi Securities Exchange (NSE) is a market that deals with exchange of securities issued by public quoted companies and the government. The Nairobi Securities Exchange is licensed and regulated by the Capital Markets Authority 4 (CMA). It has the mandate of providing a trading platform for listed securities and overseeing its Member Firms. NSE (2014) there is 64 firms licensed under the NSE; this is provided in Appendix I of this study. The stock exchange market helps in the transfer of savings to investment in productive ventures rather than keeping the savings idle. This helps to cultivate a culture of saving to local and foreign investors who are interested in investing. Kale (2014) noted that listed firms that use financial leverage to finance their assets are likely to pay low taxes due to allowable interest deductions. Tax rules permit interest payments as expense deductions against revenues to arrive at taxable income. The lower the taxable income, the less tax a company pays. For instance dividends paid to equity holders are not tax-deductible and must come from after-tax income. Tax savings help further reduce a company’s debt financing cost, which is an advantage that equity financing lacks that might significantly lead to improved profitability. Firms use financial leverage as a result of utilizing their finance assets. As a result, the firms bear less risk, compared to firms that finance their assets using equity. Upon liquidation of the firm, debt holders have more claiming rights to company assets; this gives them security for their investments. Listed firms that finance their projects using financial leverage might easily retain profits and financial performance within the firm as compared to those using equity. Firms prefer financial leverage to finance stable business operations in which they can more easily make ongoing interest payments and retain the rest of the profits to themselves (Adongo, 2012). 1.2 Research Problem 5 Dittmar (2004) indicates that if firm use less amount of debt then it has to pay less amount of fixed cost associated with that borrowed money. Such fixed cost associated with the borrowed money is the cost of debt which is generally called interest amount. Padron and Santana (2005) assert that if firm borrows more money from its creditors then the firm has to pay more amount of cost of debt to the creditor which is called interest rate this leads to less net income for the firm and hence lower profitability. This is consistent with the findings by Eunju and SooCheong (2005) who concluded that there was an inverse relationship between financial leverage and profitability of firms. In Kenya, listed firms consider four basic elements of debt financing, these are: business risk, the need for financial flexibility, the degree of ownerships’ risk aversion, and tax considerations. Nduati (2010) argues that listed firms adopt more debt so that they can enjoy less income tax. However; the firm is more exposed to financial risks. Kale (2014) in his study argued that debt is worthwhile if the firm reach excessive profits which improve the return to shareholders. He further explains that most local firms utilize debt for their future plans because fixed cost of debt is usually pre decided and this enables the firm to plan since the cost is apparent. Mahira (2011) investigated the effect of firm profitability and its financial leverage on capital structure in automobile sector companies in Pakistan. The study found that the profitability of the firm and its financial leverage have no significant impact on the capital structure of the studied firms. Akhtar (2012) studied the impact of leverage on corporate financial performance applied on oil and energy companies sector. The results showed that financial leverage leads to improved performance. Subaii (2012) study examines the relationship between financial leverage and return on assets at the level of each sector of the three economic sectors of the Kuwaiti economy. The study 6 concluded that there is a positive relationship between financial leverage and return on investment for all economy sectors. Adongo (2012) studied the effect of financial leverage on profitability and risk of firms listed at the Nairobi Securities Exchange. All the 58 firms listed at the NSE as at 2011 were not covered in this study. The results were based on a sample while 15 firms were excluded from the same sample. The study did not factor in firm size which is an important consideration for a firm that finances its projects using financial leverage. The results found that there was an insignificant relationship between returns adjusted by risk and financial leverage on firms listed at the Nairobi Securities Exchange. Nduati (2010) investigated on the relationship between leverage and financial performance of listed firms. It was found that there was a positive correlation between leverage and financial performance. Kale (2014) examined the impact of financial leverage on firm performance: the case of non-financial firms in Kenya. The findings revealed that there is a significant negative relationship between leverage and return on assets in non-financial firms in Kenya. The above studies show that little has been done in relation to financial leverage and profitability of listed firms in the Nairobi Securities Exchange. Further, the studies did not factor in liquidity which is important in establishing whether firms that utilize financial leverage are able to meet their financial obligations. This study therefore attempts to answer the question: What is the effect of financial leverage on the profitability of firms listed at the Nairobi Securities Exchange? 1.3 Research Objective To determine the relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. 7 1.4 Value of the Study This study is helpful to listed firms as it shows the impact of cost of financing and financial leverage and in particular how it contributes to profitability. The findings will be used to guide listed firms on financial decisions in the areas of management and the use of funds to maximize the market value of the business which is a key financial goal of most firms. Firms in other sectors can learn the benefits of utilizing financial leverage and how it impacts on profitability. The findings of this study might be used as a reference point to firms seeking to finance their projects using financial leverage. This study adds to the existing body of knowledge on the significance use of financial leverage to the firm and how this contributes to profitability of the firm. Future researchers and academicians interested in this area of study or other related topics will use the findings of this study as a reference point. In addition, this study can be used as a basis for further research. 8 CHAPTER TWO LITERATURE REVIEW 2.1 Introduction This section provides the theoretical framework of the study, the determinants of the profitability, the empirical review and the summary of the literature review. 2.2 Theoretical Framework This section covers the theories that support the relationship between financial leverage and profitability of the firm. These theories include: Modigliani-Miller theorem, Pecking Order Theory and Trade-off Theory. 2.2.1 Modigliani-Miller Theorem Modigliani-Miller (1958) maintains that a firm’s market value is calculated by the risk associated with the underlying assets of the firm and also on the earning capacity of the firm. The theorem further states that the market value of the firm is not affected by the choice of financing the investments or on the decisions of distributing the dividends. The three ways that a firm can select to finance the investments are borrowing outside capital, issuing the shares and reinvesting the profits. According to the theory, under some market assumptions whether or not the firm investments are financed with equity or debt makes no difference. The Modigliani-Miller theorem is very often referred to as the capital structure irrelevance principle. This suggests that the valuation of a firm is irrelevant to the capital structure of a company. Whether a firm is highly leveraged or has lower debt component in the financing mix, it has no bearing on the value of a firm (Modigliani & Miller, 1963). 9 Modigliani and Miller Approach further states that the market value of a firm is affected by its future growth prospect apart from the risk involved in the investment. The theory stated that value of the firm is not dependent on the choice of capital structure or financing decision of the firm. If a company has high growth prospects, its market value is higher and hence its stock prices would be high. If investors do not see attractive growth prospects in a firm, the market value of that firm would not be that great (Miller, 1977). Going by the assumptions of this theory on no taxes, the capital structure does not influence the valuation of a firm. In other words, leveraging the company does not increase the market value of the company. It also suggests that debt holders in the company and equity share holders have the same priority, that is, earnings are split equally amongst them. The proponents of this theory argue that financial leverage is in direct proportion to the cost of equity. With increase in debt component, the equity shareholders perceive a higher risk to the company. Hence, in return, the shareholders expect a higher return, thereby increasing the cost of equity. The theory assumes that debt holders have an upper-hand as far as claim on earnings is concerned. Thus, the cost of debt reduces. 2.2.2 Pecking Order Theory Pecking order theory was first suggested by Donaldson (1961), it was later modified by Myers and Majluf in 1984. The theory states that firms prioritize their sources of financing (from internal financing to equity) according to the cost of financing, preferring to raise equity as a financing means of last resort. Hence, internal funds are used first, and when that is depleted, debt is issued, and when it is not sensible to issue 10 any more debt, equity is issued. The pecking order theory states that there are three sources of funding available to firms namely: retained earnings, debt, and equity (Myers, 1994). Retained earnings have no adverse selection problem. Equity is subject to serious adverse selection problems while debt has only a minor adverse selection problem. From the point of view of an outside investor, equity is strictly riskier than debt. Both have an adverse selection risk premium, but that premium is larger on equity. Therefore, an outside investor will demand a higher rate of return on equity than on debt. From the perspective of those inside the firm, retained earnings are a better source of funds than debt and debt is a better deal than equity financing. The firm will fund all projects using retained earnings if possible (Harris & Raviv, 2003). The pecking order theory makes predictions about the maturity and priority structure of debt. Securities with the lowest information costs should be issued first, before the firm issues securities with higher information costs. This suggests that short-term debt should be exhausted before the firm issues long-term debt (Baskin, 2002). The pecking order theory assumes that there is no target capital structure. Due to adverse selection, firms prefer internal to external finance. When outside funds are necessary, firms prefer debt to equity because of lower information costs associated with debt issues. This theory maintains that businesses adhere to a hierarchy of financing sources and prefer internal financing when available, and debt is preferred over equity if external financing is required (equity would mean issuing shares which means bringing external ownership into the company). Thus, the form of debt a firm chooses can act as a signal of its need for external finance (Myers, 2001). 11 2.2.3 Trade-Off Theory The trade-off theory of capital structure refers to the idea that a company chooses how much debt finance and how much equity finance to use by balancing the costs and benefits. Myers (1984) posits that trade-off theory of capital structure basically entails offsetting the costs of debt against the benefits of debt. The Trade-off theory of capital structure discusses the various corporate finance choices that a corporation experiences. The theory describes that the companies or firms are generally financed by both equity and debt. Trade-off theory of capital structure primarily deals with the two concepts, cost of financial distress and agency costs (Welch, 2004). An important purpose of the trade-off theory of capital structure is to explain the fact that corporations usually are financed partly with debt and partly with equity (Kraus & Litzenberger, 1973). Frank and Goyal (2011) explain that there is an advantage to financing with debt, the tax benefits of debt, and there is a cost of financing with debt, the costs of financial distress including bankruptcy costs of debt and non-bankruptcy costs for example, suppliers demanding disadvantageous payment terms, bondholder and stockholder infighting. The marginal benefit of further increases in debt declines as debt increases, while the marginal cost increases, so that a firm that is optimizing its overall value will focus on this trade-off when choosing how much debt and equity to use for financing (Fama & French, 2002). 2.3 Determinants of Firm Profitability There are a number of factors that affect profitability of the firm, this study has discussed the following factors: 12 2.3.1 Profitability According to the pecking order theory in the presence of asymmetric information, a firm will prefer internal finance, but would issue debt if internal finance is exhausted. The last alternative would be issue new equity. Myers (1984) prescribed a negative relationship between profitability and debt. Daskalakis and Psillaki (2008) argue that profitability may be regarded as a relative term measurable in terms of profit and its relation with other elements that can directly influence the profit. Profitability is ‘the ability of a given investment to earn a return from its use. Profit maximization is said to be the main objective of all firms Profitable firms are likely to have more retained earnings. Successful companies do not depend as much on external finance. Empirical evidence from previous studies like Al-Sakran, (2001); Kayo and Kimura (2010) appears to be consistent with the pecking order theory. Most studies found a negative relationship between profitability and debt financing (Daskalakis & Psillaki, 2008; Vasiliou et al., 2009). 2.3.2 Firm Size Profit interacts with size: Large firms are less susceptible to bankruptcy because they tend to be more diversified than smaller companies. Therefore, lower expected bankruptcy costs enable large firms to take on more debts. The larger firms can reduce the level of information asymmetries in the market and obtain financial resources more easily. Large firms are more likely to access debt as compared to small firms since they are more stable. (Padron et al., 2005). If two companies have same profitability, larger company will get more external finance. Size plays an important role in capital structure (Abor & Biekpe, 2009). Small firms are often managed by very few managers whose main objective is to minimize the 13 intrusion in their business and that is why internal funds will lie in the first place of their preference of finance. If internal funds are not enough, small firms will prefer debt to new equity mainly because debt means lower level of intrusion and lower risk of losing control. Hussain and Matlay (2007) assert that small firms strive for external sources of finance only if the internal sources are exhausted. Small firms try to meet their finance needs with a pecking order of personal and retained earnings, debt and issuance of new equity. 2.3.3 Liquidity According to Padron, Apolinario and Santana (2005), companies with more liquid assets are likely to perform better as they are able to realize cash at any point of time to meet its obligation and are less exposed to liquidity risks. By not having sufficient cash or liquid assets, listed companies may be forced to sell investment securities at a substantial loss in order to settle claims promptly. However, there are contrasting views with regard to performance and liquidity in relation to the agency theory. Kayo and Kimura (2010) argue that high liquidity could increase agency costs for owners by providing managers with incentives to misuse excess cash-flows by investing in projects with negative net present values and engaging in excessive perquisite consumption. Liquidity measures the ability of managers to meet their immediate commitments to shareholders and other creditors without having to increase profit from investment activities and/or liquidate financial assets. 2.4 Empirical Review This section discusses the empirical studies in relation to the two main variables of this study which are financial leverage and profitability of listed firms. It consists of both local and global studies as follows: 14 Abdussalam (2006) examined the relationship of firm structure and profitability. The study considered major characteristics such as firm size, firm age, and debt ratio and ownership structure of 48 Jordanian industrial companies listed in Amman Stock Exchange for a period of one decade (1995 to 2004). The study employed two model specifications in order to test the hypotheses, using the profitability measurement of Rate of Return on Equity (ROE) and Rate of Return on Investment (ROI). The empirical findings suggest that firm structure emerges as an important factor affecting profitability. The results indicate that there was a positive relationship between firm size and profitability. Yuan and Kazuyuki (2011) carried out a study on the impact of the debt ratio on firm investment. Using a sample of Chinese listed companies showed that total debt ratio had a negative impact on fixed investment. A firm with a high debt ratio will channel most of its income to debt repayments thereby forgoing investment using internal funds. As more debt is employed in the capital structure of a firm, the business risk also increases. Yuan and Kazuyuki argued that creditors will be reluctant to lend more funds to a highly indebted firm which can result in underinvestment. Firm operations will be affected if insufficient investment is undertaken. Pouraghajan and Bagheri (2012) investigated on the impact of capital structure on the financial performance of companies listed in the Tehran Stock Exchange. The study tested a sample of 40 firms among the companies listed in the Tehran Stock Exchange. Results suggest that there is a significant negative relationship between debt ratio and financial performance of companies, and a significant positive relationship between asset turnover, firm size, asset tangibility ratio, and growth opportunities with financial performance measures. 15 Soumadi and Hayajneh (2012) studied the relationship between capital structure and corporate performance on Jordanian shareholdings firms. The study used multiple regression models by least squares (OLS) to establish the link between capital structure and corporate performance of firms over a period of 5 years. The results showed that capital structure was associated negatively and statistically with the performance of the firms in the sample. Another finding from the study was that there was no significant difference in the impact of financial leverage between high financial leverage firms and low financial leverage firms in their performance. The study also concluded that the relationship between capital structure and firm performance was negative for both high growth firms and low growth firms. Ahmad, Abdullar and Roslan (2012) carried a study in Malaysia which sought to investigate the impact of capital structure on firm performance by analyzing the relationship between return on assets (ROA), return on equity (ROE) and shortterm debt and total debt. The study established that short-term debt and long-term debt had significant relationship with ROA. It was also established that ROE had significant relationship with short-term debt, long-term debt and total debt. Nduati (2010) examined the relationship between leverage and financial performance of companies quoted at the Nairobi Securities Exchange. A descriptive research design was adopted in the collection of data. Data was collected using interviews and secondary sources such as annual financial reports of the targeted companies. Data was analyzed using the Statistical Packages for Social Sciences (SPSS) and findings presented in the form of pie charts, graphs and tables. The findings concluded that leverage did not contribute to financial performance of firms quoted at the Nairobi stock Exchange. 16 Adongo (2012) studied the effect of financial leverage on profitability and risk of firms listed at the Nairobi securities exchange. A casual research design was adopted for the study. Population consisted of fifty eight companies out of which thirty companies were sampled. The sample excluded fifteen companies listed under banks and insurance because these companies are regulated and are to meet certain liquidity and leverage ratios. Six companies were suspended. The study covered a five year period January 2007 to December 2011. Three companies were newly listed and therefore not continuously listed over the period of study. Four companies had information missing for some years required for the computation of the variables. Secondary data was used and data was collected from thirty sampled firms. Source data included NSE database, Capital Markets Authority (CMA) and Annual Audited Financial Statements of sampled companies. Data was analyzed using Statistical Packages for Social Sciences (SPSS) version 17. Cross-sectional time series fixed model was used with the regression and correlation analysis to determine the nature and the strength of the relationship between the independent and dependent variables. The findings revealed an insignificant relationship between returns adjusted by risk and financial leverage. This contradicted with the hypothesis of the study which had predicted a positive relationship between financial leverage, profitability and risk of listed firms. Suhaila (2014) investigated the effect of liquidity and leverage on financial performance of commercial state corporations in the tourism industry in Kenya. The study adopted descriptive research design where data was retrieved from the Balance Sheets, Income Statements and Notes of ten (10) Commercial State Corporations in the tourism industry in Kenya during the study period 2008-2012. A regression model was used to assess the impact of liquidity and leverage on financial 17 performance measured with profitability. A positive relationship was found to exist between tourism industry liquidity and profitability of Commercial State Corporations in the tourism sector in Kenya. A study by Tale (2014) investigated on the relationship between capital structure and financial performance of non-financial firms listed at the Nairobi securities exchange in Kenya. The study used a descriptive survey. The population of the study consisted of all the 40 nonfinancial firms listed and duly registered with capital market authority of Kenya. Secondary data used was obtained mainly from the annual audited and published books of accounts, financial statements and the NSE. Data analysis was done by use of regression analysis model. However, the results showed that there was a negative relationship between financial performance and the size and growth of the firm. Wainaina (2014) studied the relationship between leverage and financial performance of top 100 small and medium enterprises in Kenya. The study used descriptive cross sectional research design. The target population for the study was the top 100 SMEs (2013) in Kenya. The study used a sample of 30 SMEs randomly selected from the population of the study. The study collected secondary data for a period of five years (2008-2012). The study made use of SPSS version 20, to aid in the analysis. The study concluded that leverage had a significant influence on the financial performance, and that there was a positive relationship between leverage (debt equity ratio) and financial performance of small and medium enterprises in Kenya. 2.5 Summary of the Literature Review From the above literature, studies have been carried out in relation to financial leverage, capital structure, profitability and financial performance both in the local 18 and global setting. However, the empirical findings have found mixed results, for example: Tale (2014) and Abdussalam (2006). The hypothesis for this study projects a negative relationship between financial leverage and profitability of listed firms. This is supported by the theories anchoring this study which are: Modigliani-Miller theorem, Pecking Order Theory and Trade-off Theory. Most studies in the local setting for example Adongo (2012) that have investigated the relationship between financial leverage; profitability and financial performance in the context of listed firms are inconclusive since they have relied on a sample to make generalization on the findings. Secondly, most studies have tested the relationship between leverage with financial performance and profitability which measures debt to equity ratio unlike financial leverage which measures total debt. Thirdly, most studies have ignored firm size as a key determinant of profitability which the current study has factored in. This creates a need to investigate the relationship between financial leverage and profitability of listed firms at the Nairobi Securities Exchange. 19 CHAPTER THREE RESEARCH METHODOLOGY 3.1 Introduction This chapter provides the research methodology that was used to achieve the objective of the study. This chapter constitutes the research design, population, data collection, analytical model, data analysis and the tests of significance. 3.2 Research Design A descriptive research design was used. A descriptive research design is used to establish the relationship between variables. According to Cooper and Schindler (2006) a descriptive study is one that explains a phenomenon, to estimate a proportion of a population with the same characteristics and to establish relationships that exist between different variables. The study investigated the relationship between financial leverage and profitability of listed firms at Nairobi securities exchange. 3.3 Population Singh and Nath (2010) maintain that a population is the entire group of individuals, events or objects having similar and observable characteristics. The population of this study comprised of all the 64 firms listed at the Nairobi Securities Exchange. Currently, there are 64 listed firms that are licensed to work and operate in Kenya (NSE, 2014). The study considered firms that have been listed for the last five years as the secondary data to be collected covered the period between years 2010-2014. 3.4 Data Collection The study used secondary sources of data since the nature of data to be collected is quantitative. The study covered a period of five years as from 2010-2014. This period 20 was considered sufficient for establishing the relationship that exists between the variables. Secondary data was obtained from Nairobi Securities Exchange Handbook. Secondary data was extracted from the financial statements of all the listed firms based on the availability and accessibility of data in the period of study. Secondary data selection and measurements was done based on the all variables under investigation, namely; financial leverage, profitability, firm size and liquidity. 3.5 Data Analysis Data was cleaned, sorted and then coded before being captured into the Statistical Package for Social Sciences. Data was analyzed using descriptive statistics, correlation analysis and regression analysis. The measurements that were analyzed included: the financial leverage which is the independent variable. It was measured using long-term liabilities divided by total assets. Profitability which is the dependent variable was measured using Return on Assets (ROA). Control variables included the firm size and liquidity which were measured using logarithm of total assets and current assets divided by current liabilities. 3.5.1 Analytical Model The study adopted a regression model to establish the relationship between financial leverage and profitability of listed firms at Nairobi Securities Exchange. The study projected a negative relationship between financial leverage and profitability of listed firms at Nairobi Securities Exchange. The study sought to extend the model as advanced by the previous works of Adongo (2012); the regression model was as follows: Y =β0 + β1X1 + β 2X2 + β 3X3 +e b1 to bn are the regression coefficients 21 Y = profitability was measured using financial performance. This was measured using return on assets (ROA) which is net income divided by total assets. X1 is financial leverage (independent variable) which was measured using long-term liabilities divided by total assets. X2 is the size of the firm (control variable) which was measured using natural logarithm of total assets. X3 is Liquidity (control variable) which was measured using current assets divided by current liabilities. β0 = gradient or slope of the regression measuring the unit of change in y associated with a unit change in X ε is error term within a confidence interval of 5% 3.5.2 Tests of Significance Model for coefficients was used to test the hypothesis of this study. The level of significance was determined using probability values. If the p-value(s) is more than 5% then the null hypothesis is true since this means that there is no statistically significant relationship between financial leverage and profitability of listed firms at the Nairobi securities exchange. Similarly, if the p-value is less than 5% then the alternative hypothesis was considered true since this means that there is a positive relationship between variables. The coefficient of determination was used to determine if the model is a satisfactory predictor or not using the R2. Correlation was conducted to find out whether there is multi-colinearity between the variables. All the tests were performed at 95% degree of confidence. 22 CHAPTER FOUR DATA ANALYSIS, RESULTS AND DISCUSSION 4.1 Introduction This section covers the analysis of data and findings of the study as set out in the research objective and research methodology. The study findings are presented below on the relationship between financial leverage and profitability of listed firms at the Nairobi Securities Exchange. This study used secondary data that was extracted from financial statements of listed firms. 4.2 Response Rate Data was collected from 47 listed firms. This represents a response rate of 73% which was considered sufficient for making generalization on the whole population. The researcher managed to collect data from 47 listed firms although very few measurements were missing on only specific variables. The study covered five years (2010-2014). The findings have been presented in Appendix II. 4.3 Descriptive Statistics Descriptive statistics have been used to show the summary of the relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. The findings show the mean, standard deviation, maximum and minimum values of the variables under investigation as tabulated in table 4.1 below 23 Table 4.1 Descriptive Statistics Descriptive Statistics N Minimum Maximum Mean Std. Deviation Financial Leverage 235 .00 1.07 .4663 .20280 ROA 235 -.21 4.34 .1408 .38954 Liquidity 230 .00 18.76 1.7270 1.81492 Log ASSETS 235 .00 19.06 15.6151 1.99841 Valid N (listwise) 235 Source: Research Findings From the findings in table 4.1 above, most listed firms utilized financial leverage in the period of study. It was further observed that financial leverage increased rapidly over the years from .00 to 1.07. The mean value for financial leverage is 0.4663 while the standard deviation is .20280. This is an indication that most listed firms were stable and thus were able to access financial leverage. The findings further revealed that profitability was estimated at 1.4% which is a moderate performance. This is an indication that financial leverage did not necessarily contribute to profitability of listed firms. These findings are consistent with Padron and Santana (2005) who assert that if a firm borrows more money from its creditors, then the firm has to pay more amount of cost of debt to the creditor as interest. This leads to less net income for the firm and hence lower profitability. This is consistent with the findings by Eunju and SooCheong (2005) who concluded that there was an inverse relationship between financial leverage and profitability of firms. The level of liquidity of listed firms was found to be 1.73. This means that most listed firms were able to meet their short-term financial obligations as and when they fell due. This ratio (current ratio) is consistent with the standard conventional rule of current ratios which is 2:1. This is the stipulated range upon which firms that seek to maintain an optimal level of liquidity should meet. 24 The findings further revealed that most firms were financially stable in terms of assets to access financial leverage. The percentage mean of logarithm of assets is 15.6% which is a strong indicator that most listed firms had a strong asset base. 4.4 Pearson Product Moment Correlation Coefficient The Pearson’s correlation is a measure of the strength and direction of association that exits between two variables on at least an interval scale. Below are the results of the findings presented in table 4.2. Table 4.2 Pearson’s Correlation Analysis ROA Financial Liquidity Log of assets Leverage ROA 1 Financial Leverage -.107 1 Liquidity .212 -.305 1 Log of Assets -.547 .218 -.209 1 Source: Research Findings The strength of the association between the variables was specified by Pearson correlation scale where: values between 0.0 to 0.3 indicate that there is no correlation, between 0.31 to 0.5 shows a weak correlation, between 0.51 to 0.7 a moderate correlation and between 0.71 to 1.0 indicates that there is a strong correlation between the variables (Pearson and University of London, 1985). The findings in table 4.2 above reveal that there was no correlation between financial leverage and profitability of listed firms. The correlation which is represented by R is -.107. The results also revealed that there was no correlation between liquidity and profitability of listed firms. This is represented by a correlation of .212. Further, the findings also indicated that there was a moderate correlation between logarithm of 25 assets and profitability of listed firms. The correlation score is -.547. This can be attributed to the ability of listed firms to be able to access debt due to their level of financial stability in terms of assets. 4.5 Regression Analysis and Hypothesis Testing This study sought to establish the relationship that exists between financial leverage and profitability of listed firms at Nairobi Securities Exchange. Regression analysis was used to establish the hypothesis for the study which was predicted to be negative. The results were as shown in table 4.3 below: 4.5.1 Model Summary The model summary depicts the summary of the model. It consists of the multiple correlation, the coefficient of determination and the adjusted R square. Below are the results of the findings: Table 4.3 Model Summary Model Summary Model R R Square Adjusted R Std. Error of the Estimate Square 1 a .524 .274 .263 .17417 a. Predictors: (Constant), Log Assets, Financial leverage, Liquidity From the above results in table 4.3 , R which represents multiple correlation show a moderately strong correlation between the variables as follows R=.524. R2 which is the coefficient of determination show the extent to which the variance in the dependent variable which is profitability can be explained by the independent variables. This is represented by 27.4% which shows the regression model is a moderate predictor. 26 4.5.2 Analysis of Variance Analysis of variance was carried out to test the ‘goodness of fit’ for the data. A regression model was used for this purpose and the results are tabulated in table 4.4 below. Table 4.4 Analysis of Variance ANOVAa Model 1 Sum of Squares df Mean Square F Regression 4.116 3 1.372 Residual 7.086 226 .031 11.201 229 Total Sig. 43.756 .000b a. Dependent Variable: ROA b. Predictors: (Constant), Log Assets, Financial Leverage, Liquidity From the above results in table 4.4, the findings show that the probability value is below 5%, p=0.000 which is an indication that the regression model is statistically significant in predicting the relationship between financial leverage and profitability of listed firms in Nairobi Securities Exchange. 4.5.3 Model Coefficients The study tested the model coefficients to determine the direction of the variables in the regression model. The results are provided in table 4.5 below. Table 4.5 Model Coefficients a Coefficients Unstandardized Coefficients Model B 1 Std. Error (Constant) -.172 .104 Liquidity -.024 .007 Financial Leverage -.021 .043 Log Assets a. Dependent Variable: ROA 27 Standardized Coefficients t Sig. Beta -1.657 .099 -.215 -3.466 .001 .032 -.040 -.656 .512 .006 .428 6.829 .000 From the above findings, the regression model is as follows; ROA= -.172-.024X1+.-021X2 + ε Logarithm of assets was excluded from the regression model because it was found to have a positive relationship with the profitability of listed firms. These findings contradicted with the hypothesis of this study which had predicted an inverse relationship between financial leverage and profitability of listed firms. From the regression model obtained above, holding all the other factors constant, a unit increase in liquidity and financial leverage, results to a corresponding decrease in ROA by 0.024 and -0.021. The regression model obtained shows an inverse relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. The above analysis was conducted at 5% significance level. The criteria for comparing whether the predictor variables were significant in the model was done by comparing the corresponding probability value obtained; α=0.05. If the probability value was less than α, then the predictor variable was significant. From the model coefficients logarithm of assets and liquidity were found to be statistically significant in the model. This is because its p-value was less than 5%. The results were as follows p=0.000 and p=0.001. On the other hand, financial leverage was found to be statistically insignificant with a probability (p)-value of 0.512 which was above 5%. These findings are consistent to the hypothesis of the study which predicted the existence of a statistically insignificant relationship between financial leverage and profitability of listed firms at Nairobi Securities Exchange. 28 4.6 Discussion of Findings The descriptive results found that most listed firms utilized financial leverage because most listed firms had a stable asset base. However, the findings concluded that financial leverage did not contribute to profitability of listed firms; the financial performance of listed firms was 14% which is a moderate score. The results of the Pearson’s correlation concluded that there was no correlation between financial leverage and profitability of listed firms. The correlation score was found to be R is -.107. Similarly, it was discovered that there was no correlation between liquidity and profitability of listed firms. The correlation score was found to be -.212. There was a moderate correlation between logarithm of assets and profitability of listed firms. The correlation score is -.547. The regression results found that there was an inverse relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. Results suggest that there is a significant negative relationship between debt ratio and financial performance of companies. The findings depict that the logarithm of assets and liquidity were found to be statistically significant in the model. This is because its p-value was less than 5%. The results were as follows p=0.000 and p=0.001. On the other hand, financial leverage was found to be statistically insignificant because its pvalue was above 5%. The result was as follows p=0.512. 29 CHAPTER FIVE SUMMARY, CONCLUSION AND RECOMMENDATIONS 5.1 Introduction This chapter summarizes the study and provides the results and discussions drawn from the analysis presented in chapter four. It captures the summary of findings, conclusions, limitations as well as recommendations for further research. 5.2 Summary of Findings The study investigated three dimensions of a firm’s profitability, namely, financial leverage, firm size and liquidity. The descriptive results indicated that most listed firms utilized financial leverage as most listed firms had a stable asset base. However, the findings concluded that financial leverage did not contribute to profitability of listed firms. The financial performance of listed firms was 14%, which is a moderate score. This was an indication that financial leverage did not contribute to profitability of listed firms. These findings are however consistent with Padron and Santana (2005) who assert that if a firm borrows more money from its creditors then the firm has to pay more amount of cost of debt to the creditor in terms of interest and this leads to less net income for the firm and hence lower profitability. The findings of the Pearson’s correlation concluded that there was no correlation between financial leverage and profitability of listed firms. The correlation score was found to be R is -.107. Similarly, it was discovered that there was no correlation between liquidity and profitability of listed firms. The correlation score was found to be -.212. These findings are consistent to a study by Yuan and Kazuyuki (2011) who found that there was an inverse relationship between total debt and profitability of Chinese listed companies. It was also found that there was a moderate correlation 30 between logarithm of assets and profitability of listed firms. The correlation score is .547. The regression results found that there was an inverse relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. These findings are consistent with a study by Pouraghajan and Bagheri (2012) who investigated the impact of capital structure on the financial performance of companies listed in the Tehran Stock Exchange. Results suggest that there is a significant negative relationship between debt ratio and financial performance of companies. The findings depict that the logarithm of assets and liquidity were found to be statistically significant in the model. This is because its p-value was less than 5%. The results were as follows p=0.000 and p=0.001. These findings are consistent with Pouraghajan and Bagheri (2012) who found that there was a statistically significant relationship between asset turnover and liquidity of companies listed in the Tehran Stock Exchange. On the other hand, financial leverage was found to be statistically insignificant because its p-value at 0.512 was above 5%. These findings are consistent with a study conducted by Nduati (2010) that examined the relationship between leverage and financial performance of companies quoted at the Nairobi Securities Exchange. The findings concluded that leverage did not contribute to financial performance of firms quoted at the NSE. These findings are also consistent with Adongo (2012) who studied the effect of financial leverage on profitability and risk of firms listed at the Nairobi Securities Exchange. The findings concluded that there was an insignificant relationship between returns adjusted by risk and financial leverage. 31 5.3 Conclusion The findings revealed that profitability was not correlated with financial leverage of listed firms in Kenya. The study therefore concludes that firms should consider alternative methods of financing their projects other than relying on financial leverage. Financial leverage might lead to poor performance of firms due to excessive costs of financing debt that might override the returns obtained from investing in projects. The results of the model coefficients estimates of the independent variables found an inverse relationship with profitability of listed firms. The results indicated that liquidity and financial leverage depicted a negative relationship with profitability apart from the logarithm of assets that showed a positive relationship with profitability of listed firms in the Nairobi Securities Exchange. These findings are consistent with the hypothesis of this study which predicted a negative relationship between financial leverage and profitability of listed firms. It can therefore be concluded that financing firms using debt is costly and might expose the firm to financial difficulties. From the regression model, the coefficient of determination was 27.4% showing the extent to which the variance of profitability was explained by the independent variables. This is an indication that the model used was a moderate predictor in explaining the relationship between financial leverage and profitability of listed firms in the Nairobi Securities Exchange. 5.3 Recommendations The study recommends that listed firms should look for alternative ways of financing their projects other than using financial leverage. This is because from the results 32 obtained it is evident that financial leverage does not contribute to profitability of the firm. There is a proportionate increase in the cost of debt represented by the interest rate payable to a firm’s borrowing. This leads to less net income for the firm and hence lower profitability. 5.4 Limitations One of the limitations of this study is that it utilized secondary data sources and might not necessarily reflect the exact needs of the study. This might negatively affect the accuracy and reliability of the results and impact negatively on the findings drawn in this study. Another limitation of this study is that it was limited to four variables only; financial leverage, firm size, profitability and liquidity. It is imperative to note that profitability is affected by many factors other than the ones confounders discussed in this study that have a bearing on profitability. Other factors considered, it would be important to establish whether the findings will hold or not after which conclusive results can be drawn. 5.5 Suggestions for Further Research Although the study targeted to study 64 firms, only 58 firms were active in the NSE for the period under study. Due to time and cost constraints, only 47 firms were investigated in the study. The study recommends that future researchers interested in this field of research might consider investigating all the firms and increase the period of study to ten years. This will increase the scope of study and the findings obtained will be more conclusive. The results obtained can be compared with the findings obtained in this study then conclusions can then be drawn based on more concrete facts. 33 REFERENCES Abdussalam, M. A. (2006). An empirical study of firm structure and profitability relationship: The Case of Jordan, Journal of Economic and Administrative Sciences, 22, 11, 41 – 59 Abor, J. & Biekpe, N. (2009). How do we explain the capital structure of SMEs in sub-Saharan Africa, Evidence from Ghana, Journal of Economic Studies, 36(1), 83-97 Abor, J. (2005). The effect of capital structure on profitability: empirical analysis of listed firms in Ghana, Journal of Risk Finance, 6(5), 438-445. Adongo, J. (2012). The effect of financial leverage on profitability and risk of firms listed at the Nairobi securities exchange, Unpublished MBA Project, University of Nairobi Adongo, J. (2012). The effect of financial leverage on profitability and risk of firms listed at the Nairobi securities exchange, Unpublished MBA Project, School of Business, University of Nairobi Agrawal, A. & Nagarajan, N. J. (1990). Corporate capital structure, agency costs and ownership control: the case of all equity firms, Journal of Finance, 45, 13251331. Ahmad, Z., Abdullah, M.H. & Roslan, S. (2012). Capital Structure Effect on Firms Performance: focusing on consumers and industrials sectors on Malaysian firms. International Review of Business Research Papers, 8 (5), 137 – 155 Akhtar, et al., (2012). Relationship between financial leverage and financial performance: evidence from fuel & energy sector of Pakistan, European Journal of Business and Management, 4, 11, 2222-2839. Akhtar, S., & Oliver, B. (2009). Determinants of capital structure for japanese multinational and domestic corporations, International Review of Finance, 9, 1-26. Al-Najjar, B. (2011). The inter-relationship between capital structure and dividend policy: empirical evidence from Jordanian data, International Review of Applied Economics, 25 (2), 209-224. Al-Najjar, B., & Taylor, P. (2008). The relationship between capital structure and ownership structure: new evidence from Jordanian panel data, Managerial Finance, 34 (12), 919-933. Al-Sakran S.A. (2001). Leverage determinants in the absence of corporate tax system: the case of non-financial publicly traded corporations in Saudi Arabia, Managerial Finance, 27, 58-86. 34 Amalendu, B. (2012). Leverage impact on firms investment decision: a case study of Indian pharmaceutical companies, International Journal of Contemporary Business Studies, 3, 1, 35-45. Baskin, J. (2002). An empirical investigation of the pecking order hypothesis, Financial Management, 18, 26-34. Cheng, C. & Tzeng, C. (2010). The Effect of leverage on firm value and how the firm financial quality influences on this effect, National Chung Cheng University, Taiwan.7. Cooper, D. R., & Schindler, P. S. (2008). Business research methods. Boston: McGraw-Hill Irwin. Daskalakis, N, & Psillaki, M. (2008). Firm factors explain capital structure, Evidence from SMEs in France and Greece, Applied Financial Economics, 18, 87-97 Dittmar, A. (2004). Capital structure in corporate spin‐offs, Journal of Business, 77 1, 9‐43. Eunju, Y. & SooCheong, J. (2005). The effect of financial leverage on profitability and risk of restaurant firms, The Journal of Hospitality Financial Managements, 13,200-210 Fama, E. & French, K. (2002). Testing tradeoff and pecking order predictions about dividends and debt, Review of Financial Studies, 15, 1-37, Frank, M. Z., & Goyal, V. K. (2011). Trade-off and pecking order theories of debt, handbook of empirical corporate finance: Empirical Corporate Finance. Elsevier, 135–202 Gu, Z. (1993). Debt use and profitability: A reality check for the restaurant industry, Journal of finance and accounting, 7, 135-147. Harris, M. & Raviv, A. (2003). Capital structure and the informational role of debt, Journal of Finance, 45 (2), 321-349. Hussain J. & Matlay H. (2007). Financing preferences of ethnic minority owner and managers in the UK, Journal of Small Business and Enterprise Development, 14(3), 487-500. Kale, A. (2014). The impact of financial leverage on firm performance: the case of non-financial firms in Kenya, Unpublished MBA Project, University of Nairobi Kayo, E.K. & Kimura, H. (2010). Hierarchical determinants of capital structure, Journal of Banking & Finance, 35, 358-371. 35 Kraus, A. & Litzenberger, R.H. (1973). A state-preference model of optimal financial leverage, Journal of Finance, 7, 911-922. Mahira, R. (2011). Effect of profitability & financial leverage on capital structure: a case of Pakistan’s automobile industry, Economics and Finance Review, 1(4)50 – 58, Miller, M. H. (1977). Debt and taxes, Journal of Finance 32 (2), 261–275. Modigliani, F. & Miller M.H. (1958). The cost of capital, corporation finance and the theory of investment, American Economic, 48 (3), 261-297. Modigliani, F. & Miller M.H. (1963). Corporate income taxes and the cost of capital: a correction, American Economic Review, 53,433-443. Myers S.C. (2001). Testing static tradeoff against pecking-order model of capital structure, Journal of Financial Economic, 51 (2), 219-245. Myers, S. C. & Majluf, N.S. (1984). Corporate financing and investment decisions when firms have information that investors do not have, Journal of Financial Economics, 13 (2), 187–221. Myers, S.C. (1982). Determinants of capital borrowing, Journal of Finance Economics, 5, 5147-5175. Myers, S.C. (1984). The capital structure puzzle, The Journal of Finance, 39, 3, Papers and Proceedings, Forty-Second Annual Meeting, American Finance Association, 575-592 Myers, S.C. (1994). The capital structure puzzle, Journal of Finance, 39,575-592. Nduati, M. (2010). The relationship between leverage and financial performance of companies quoted at the Nairobi stock exchange, Unpublished MBA Project, University of Nairobi Padron, Y.G., Apolinario, M.C., & Santana, O. (2005). Determinant factors of leverage: An empirical analysis of Spanish corporations, Journal of Risk Management, 6, 60-68. Pearson, K., & University of London. (1985). On further methods of determining correlation. London: Cambridge University Press. Pouraghajan, A., & Bagheri, M. (2012). The Relationship between capital structure and firm performance evaluation measures: Evidence from the Tehran Stock Exchange, International Journal of Business and Commerce, 1(9): 166-181. Singh, Y. K., & Nath, R. (2010). Research methodology. New Delhi: Publishing Corporation 36 Soumadi, M. & Hayajneh, S. (2012). Capital structure and corporate performance: Empirical study on the public Jordanian shareholdings firms listed in the Amman stock market, European Scientific Journal, 8(26), 173-189. Subaii, B. (2012). The relationship between financial leverage and return on investment in Kuwaiti public shareholding companies, Master Thesis, Middle East University, Amman Jordan Suhaila, A. M. (2014). The effect of liquidity and leverage on financial performance of commercial state corporation sin the tourism industry in Kenya, Unpublished MBA Project, School of Business, University of Nairobi Tale, W. (2014). Relationship between capital structure and performance of nonfinancial firms listed at the Nairobi securities exchange, Unpublished MBA Project, University of Nairobi Upneja, A & Dalbor, M. C. (2001). An examination of capital structure in the service industry, Journal of finance and Accounting, 13(2), 54-59. Vasiliou, D., Eriotis, N. & Daskalakis, N. (2009). Testing the pecking order theory: the importance of methodology, Qualitative Research in Financial, 1(2), 8596. Wainaina, J. N. (2014). The relationship between leverage and financial performance of top 100 small and medium enterprises in Kenya, Unpublished MBA Project, School of Business, University of Nairobi Wald, J. K. (1999). How firm characteristics affect capital structure: an international comparison, Journal of Financial research, 22(2), 161-188 Wald, J. K. (2000). How firm characteristics affect capital structure: an international comparison, Journal of Financial research, 24(2), 217-218 Welch, I. (2004). Capital structure and stock returns, Journal of Political Economy 112 (1): 106–132. Yuan, K. & Kazuyuki, H. (2011). Impact of the Debt Ratio on Firm Investment: A case study of listed companies in China, RIETI Discussion Paper Series, 08-E011. 37 APPENDIX I: LIST OF FIRMS LISTED AT NSE (2014) AGRICULTURAL Eaagads Ltd Kakuzi Ltd Kapchorua Tea Co. Ltd The Limuru Tea Co. Ltd Rea Vipingo Plantations Ltd Sasini Ltd Williamson Tea Kenya Ltd AUTOMOBILES & ACCESSORIES Car & General (K) Ltd Marshalls (E.A.) Ltd Sameer Africa Ltd BANKING Barclays Bank of Kenya Ltd CFC Stanbic of Kenya Holdings Ltd Diamond Trust Bank Kenya Ltd Equity Bank Ltd Housing Finance Co.Kenya Ltd I&M Holdings Ltd Kenya Commercial Bank Ltd National Bank of Kenya Ltd NIC Bank Ltd Standard Chartered Bank Kenya Ltd The Co-operative Bank of Kenya Ltd COMMERCIAL AND SERVICES Express Kenya Ltd Hutchings Biemer Ltd Kenya Airways Ltd Longhorn Kenya Ltd 38 Nation Media Group Ltd Scangroup Ltd Standard Group Ltd TPS Eastern Africa Ltd Uchumi Supermarket Ltd CONSTRUCTION & ALLIED ARM Cement Ltd Bamburi Cement Ltd Crown Paints Kenya Ltd E.A.Cables Ltd E.A.Portland Cement Co. Ltd ENERGY & PETROLEUM KenGen Co. Ltd KenolKobil Ltd Kenya Power & Lighting Co Ltd Kenya Power & Lighting Ltd 4% Pref 20.00 Kenya Power & Lighting Ltd 7% Pref 20.00 Total Kenya Ltd Umeme Ltd INSURANCE British-American Investments Co.(Kenya) Ltd CIC Insurance Group Ltd Jubilee Holdings Ltd Kenya Re Insurance Corporation Ltd Liberty Kenya Holdings Ltd Pan Africa Insurance Holdings Ltd INVESTMENT Centum Investment Co Ltd Olympia Capital Holdings Ltd 39 Trans-Century Ltd INVESTMENT SERVICES Nairobi Securities Exchange Ltd Ord 4.00 MANUFACTURING & ALLIED A.Baumann & Co Ltd B.O.C Kenya Ltd British American Tobacco Kenya Ltd Carbacid Investments Ltd East African Breweries Ltd Eveready East Africa Ltd Kenya Orchards Ltd Mumias Sugar Co. Ltd Unga Group Ltd TELECOMMUNICATION & TECHNOLOGY Safaricom Ltd GROWTH ENTERPRISE MARKET SEGMENT (GEMS) Flame Tree Group Holdings Ltd Ord 0.825 Home Afrika Ltd 40 APPENDIX II: SECONDARY DATA OF LISTED FIRMS EXTRACTED FROM AUDITED REPORTS KAKUZI - 1 Financial Leverage effect(TL/TA) 2010 2011 2012 2013 2014 0.34 0.31 0.28 0.22 0.22 Liquidity 1.02 0.89 1.19 0.851 0.82 0.12766003 0.0412346 0.33035058 0.15361 0.361367 14.87 14.98 15.16 15.09 15.13 EAAGADS - 02 Financial Leverage effect(TL/TA) 0.25 0.3 0.25 0.16 0.2 Liquidity 2.73 1.81 1.21 1.15 1.12 0.13931136 0.1376066 0.05629291 0.013908 0.038333 12.47 12.53 12.78 13.26 13.12 KAPCHORUA TEA - 03 Financial Leverage effect(TL/TA) 0.41 0.45 0.38 0.42 0.38 Liquidity 1.68 1.64 2.1 1.65 2.12 1.01068056 4.340312 0.16021744 0.318189 0.038333 13.97 14.22 14.27 14.49 14.55 LIMURU TEA-04 Financial Leverage effect(TL/TA) 0.34 0.25 0.22 0.24 0.16 Liquidity 2.34 2.34 6.7 5.94 18.76 0.07376946 0.1052401 0.14861985 0.038031 0.171714 11.35 11.97 12.16 12.68 13.26 REA VIPINGO - 05 Financial Leverage effect(TL/TA) 0.31 0.42 0.36 0.28 0.25 Liquidity 2.24 1.34 2.1 3.41 4.71 0.06411035 0.2417681 0.0511335 0.039721 0.011016 ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) 14.16 14.35 14.64 14.68 14.84 SASINI - 06 Financial Leverage effect(TL/TA) Firm size effect(LNTA) 0.29 0.28 0.29 0.28 0.3 Liquidity 2.56 2.37 2.13 1.89 1.77 0.03506332 0.1418446 0.22574588 0.117973 0.106374 15.89 16.02 16.06 16 16.02 0.33 0.35 0.29 0.32 0.27 ROA(NI/TA) Firm size effect(LNTA) WILLIAMSON - 07 Financial Leverage effect(TL/TA) Liquidity ROA(NI/TA) Firm size effect(LNTA) 2.74 2.03 3.38 2.41 3.63 0.06520726 0.0085179 0.04709468 0.202253 0.054975 15.18 15.49 15.61 15.8 15.9 41 CAR&GENERAL - 08 Financial Leverage effect(TL/TA) 0.59 0.6 0.65 0.62 0.64 1.3 1.31 1.12 1.16 1.11 0.07583452 0.0897654 0.045673 0.08605 0.038333 Firm size effect(LNTA) 14.98 15.17 15.53 15.56 15.75 CMC HOLDINGS - 09 Financial Leverage effect(TL/TA) 0.6 0.63 0.65 0.56 0.53 0.93 1.03 1.53 1.05 0.95 0.10877572 0.0918055 0.05885937 0.081555 0.036607 Firm size effect(LNTA) 16.4 16.5 16.5 16.38 16.32 MARSHALLS E.A. - 10 Financial Leverage effect(TL/TA) 0.67 0.88 0.63 0.31 0.45 Liquidity 1.83 2.78 2.91 1.94 0.82 0.10877572 0.0918055 0.05885937 0.081555 0.036607 14.18 13.93 13.89 13.25 13.15 0.24 0.28 0.32 0.27 Liquidity ROA(NI/TA) Liquidity ROA(NI/TA) ROA(NI/TA) Firm size effect(LNTA) SAMEER GROUP - 11 Financial Leverage effect(TL/TA) Liquidity 1.4 0.92 0.94 0.84 0.0980098 0.10425597 0.066812 0.095582 14.92 14.86 14.95 15.04 15.12 EXPRESS KENYA LTD - 12 Financial Leverage effect(TL/TA) 0.68 0.71 0.46 0.6 0.59 Liquidity 0.83 0.93 0.86 1.27 1.25 0.07717125 0.093799 0.54786 -0.10948 -0.20948 14.08 14.11 13.55 13.11 13.08 KQ - 13 Financial Leverage effect(TL/TA) 0.77 0.73 0.71 0.7 0.75 Liquidity 1.49 2.01 1.42 1.24 1.33 0.07526565 0.0424968 0.05473956 0.052365 0.038333 18.13 18.11 18.18 18.16 18.63 LONGHORN - 14 Financial Leverage effect(TL/TA) 0.34 0.43 0.43 0.6 0.44 Liquidity 1.91 1.54 1.98 0.89 0.93 ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) 0.07965084 0.0535708 0.28445326 0.021438 0.038333 Firm size effect(LNTA) 12.97 13.17 13.47 13.4 13.44 NATION MEDIA - 15 Financial Leverage effect(TL/TA) 0.28 0.32 0.31 0.31 0.28 Liquidity 1.01 1.05 0.92 0.91 0.81 0.19058894 0.2679858 0.17894718 0.036336 0.061016 15.7 15.89 15.99 16.18 16.25 ROA(NI/TA) Firm size effect(LNTA) 42 SCAN GROUP - 16 Financial Leverage effect(TL/TA) 0.4 0.55 0.49 0.43 0.36 0.92 2.02 1.84 0.84 1.03 0.05381389 0.0281204 0.02403531 0.045591 0.069792 15.18 15.9 15.95 15.94 16.36 STANDARD GROUP - 17 Financial Leverage effect(TL/TA) 0.58 0.54 0.53 0.47 0.51 Liquidity 1.05 1.22 1.19 2.01 1.17 0.08092432 0.0617275 0.22112635 0.235104 0.047772 14.92 15.01 15.07 15.07 15.24 TPS SERENA GROUP - 18 Financial Leverage effect(TL/TA) 0.42 0.37 0.39 0.39 0.32 Liquidity 1.28 1.23 2.01 1.24 0.98 0.08092432 0.0617275 0.22112635 0.235104 0.047772 15.76 16.29 16.39 16.42 16.6 1.07 0.51 0.43 0.46 0.48 Liquidity ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) UCHUMI - 19 Financial Leverage effect(TL/TE) Liquidity 1.34 0.92 0.85 0.92 0.74 0.07526565 0.0424968 0.05473956 0.052365 0.038333 14.71 14.96 15.2 15.41 15.53 ATHI RIVER MINING - 20 Financial Leverage effect(TL/TA) 0.66 0.7 0.7 0.74 0.72 Liquidity 1.38 1.51 1.49 1.49 1.08 ROA(NI/TA) 0.151 -0.02 0 -0.07 0.15 Firm size effect(LNTA) 16.31 16.62 16.84 17.11 17.21 BAMBURI - 21 Financial Leverage effect(TL/TA) 0.35 0.35 0.28 0.28 0.27 Liquidity 1.19 1.13 2.01 0.92 0.83 0 0.222218008 0.113434639 0.085387 0.095216 Firm size effect(LNTA) 17.28 17.32 17.33 17.58 17.58 CROWN PAINTS - 22 Financial Leverage effect(TL/TA) 0.55 0.54 0.52 0.48 0.54 Liquidity 0.75 0.78 0.94 0.92 0.61 0.046440801 0.046349584 0.058230927 0.059135 0.072602 14.44 14.49 14.61 14.63 14.9 EAST AFRICAN CABLES - 23 Financial Leverage effect(TL/TA) 0.53 0.5 0.54 0.53 0.55 Liquidity 1.25 1.79 1.83 1.63 1.85 0.083545301 0.040688777 0.063033844 0.083548 0.091756 15.08 15.32 15.42 15.65 15.73 ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) 43 EAST AFRICAN PORTLAND - 24 Financial Leverage effect(TL/TA) 0.49 0.53 0.58 0.67 0.56 Liquidity 1.37 2.01 1.43 2.01 1.35 0.15238116 0.032655358 0.017843436 0 0.065922 Firm size effect(LNTA) 16.3 16.3 16.41 16.45 16.6 KENGEN - 25 Financial Leverage effect(TL/TA) 0.41 0.53 0.57 0.57 0.61 Liquidity 1.56 1.49 1.05 1.48 1.51 0.018335553 0.021827426 0.01292055 0.017301 0.027827 18.54 18.83 18.9 18.91 19.06 KENOL/KOBIL - 26 Financial Leverage effect(TL/TA) 0.67 0.63 0.75 0.8 0.76 Liquidity 1.81 1.62 0.98 1.03 2.01 0.09680441 0.0264158 -0.0291893 0.060904 0.016998 Firm size effect(LNTA) 17.2 17.23 17.64 17.3 17.15 KPLC - 27 Financial Leverage effect(TL/TA) 0.62 0.64 0.67 0.68 0.73 ROA(NI/TA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Liquidity 1.37 1.41 1.42 1.44 0.51 0.018335553 0.021827426 0.01292055 0.017301 0.027827 18.09 18.2 18.6 18.71 18.99 TOTAL KENYA - 28 Financial Leverage effect(TL/TA) 0.72 0.68 0.74 0.57 0.62 Liquidity 1.12 1.17 1.1 1.29 1 ROA(NI/TA) 0.02 0.03 0 -0.01 0.03 17.27 17.23 17.38 17.31 17.5 CENTUM - 29 Financial Leverage effect(TL/TA) 0.04 0.05 0.22 0.13 0.28 Liquidity 1.25 0.09 0.23 0.33 0.2 0.11968666 0.1654789 0.1406176 0.046215 0.222479 Firm size effect(LNTA) 15.7 15.93 16.33 16.26 16.76 OLYMPIA - 30 Financial Leverage effect(TL/TA) 0.29 0.39 0.4 0.43 0.43 Liquidity 1.14 1.48 1.16 2.27 2.79 ROA(NI/TA) Firm size effect(LNTA) Firm size effect(LNTA) ROA(NI/TA) ROA(NI/TA) 1.09034822 1.7388818 2.79678248 0.117786 0.038333 Firm size effect(LNTA) 13.58 13.79 13.89 14.44 14.46 TRANSCENTURY- 31 Financial Leverage effect(TL/TA) 0.6 0.53 0.7 0.66 0.66 Liquidity 1.8 1.59 1.22 1.28 1.49 0.14606199 0.2729494 0.23476437 0.099206 0.103232 15.98 16.23 16.93 16.9 16.99 ROA(NI/TA) Firm size effect(LNTA) 44 NSE-32 Financial Leverage effect(TL/TA) 0.13 0.15 0.1 0.44 0.36 Liquidity 1.92 0.854 2.05 1.99 1.46 0.20033039 0.1667232 0.16333995 0.03455 0.124608 12.62 12.91 13.07 13.69 13.95 BOC KENYA-33 Financial Leverage effect(TL/TA) 0.24 0.26 0.27 0.27 0.21 Liquidity 2.64 2.48 1.94 2.08 2.23 0.077402395 0.039279437 0.082895063 0.099206 0.076957 14.44 14.46 14.41 14.51 14.78 BAT-34 Financial Leverage effect(TL/TA) 0.56 0.54 0.53 0.53 0.55 Liquidity 0.98 1.17 1.31 1.18 1.26 0.140093067 0.158901794 0.225282343 0.24616 0.219222 16.17 16.22 16.44 16.54 16.65 0.15 0.14 0.16 0.18 0.13 ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) CARBACID-35 Financial Leverage effect(TL/TA) Liquidity 10.63 5.79 8.84 4.26 10.09 0.186269054 0.20327927 0.173676785 0.193404 0.215724 14.13 14.23 14.37 14.52 14.61 EABL-36 Financial Leverage effect(TL/TA) 0.35 0.38 0.46 0.84 0.86 Liquidity 1.69 1.49 1.05 0.81 0.7 0.02682845 0.0143603 0.15530312 0.409461 0.026276 17.39 17.46 17.72 17.82 17.89 0.6 0.66 0.73 0.7 0.58 1.02 1.01 1 1 0.96 0.5 0.5 0.5 0.6 0.7 ROA(NI/TA) Firm size effect(LNTA) ROA(NI/TA) Firm size effect(LNTA) EVEREADY-37 Financial Leverage effect(TL/TA) Liquidity ROA(NI/TA) Firm size effect(LNTA) KENYA ORCHARDS-38 Financial Leverage effect(TL/TA) Liquidity ROA(NI/TA) -0.02 -0.01 0 0 0.04 Firm size effect(LNTA) 18.18 18.13 18.07 18.05 18.07 0.38 0.43 0.51 2 1.25 0.84 0.02166631 0.083548 0.048276 16.95 17.13 17.12 MUMIAS-39 Financial Leverage effect(TL/TA) Liquidity ROA(NI/TA) Firm size effect(LNTA) 45 UNGA LTD-40 Financial Leverage effect(TL/TA) 0.43 0.34 0.34 0.38 0.47 Liquidity 1.84 2.36 2.52 2.54 1.84 0.14964667 0.0823855 0.22545921 0.348471 -0.08312 15.53 15.44 15.56 15.67 15.91 0.44 0.4 0.41 0.41 0.38 0.911 0.69 0.69 0.91 0.6 0.10685473 0.0934247 0.08246009 0.026287 0.190102 18.33 18.46 18.55 18.62 18.67 0.82 0.51 0.82 0.83 0.84 1.117 1 1 1 1 0.036943139 0.06147377 0.048572404 0.047293 0.036873 24 26 26 26 26 Total Debt 0.86 0.87 0.88 0.85 0.84 Liquidity 1.16 1.15 1.14 1.17 1.19 0.026816531 0.029674936 0.031881268 0.038507 0.039393 18.52 18.85 18.94 19.12 19.26 Total Debt 0.88 0.88 0.89 0.86 0.86 Liquidity 1.14 1.14 1.14 1.16 1.166 0.020312743 0.029690966 0.027807955 0.030031 0.031412 18.01 18.24 18.49 18.72 18.93 Total Debt 0.77 0.82 0.83 0.82 0.81 Liquidity 2.29 1.23 1.21 1.21 1.22 0.041998953 0.049863089 0.0526005 0.049678 0.047808 25.33 25.69 26 26.21 26 0.85 0.85 0.87 0.87 1.17 1.14 1.14 ROA(NI/TA) Firm size effect(LNTA) SAFARICOM-41 Financial Leverage effect(TL/TA) Liquidity ROA(NI/TA) Firm size effect(LNTA) Barclays Bank-42 Total Debt Liquidity ROA Size Cooperative Bank-43 ROA Size Diamond Trust Bank-44 ROA Size Equity-45 ROA Size HFCK-46 Total Debt 0.78 Liquidity 1.29 ROA 1,17 0.012839048 0.012962834 0.019524949 0.018149 0.021 23 24 24 24 24 KENYA REINSURANCE CORPORATION-47 Total Debt 0.61 0.61 0.61 0.38 0.64 Liquidity 1.64 1.63 1.65 2.61 1.57 0.088589862 0.089403013 0.100258682 0.117786 0.106313 23 23 23 23 24 Size ROA Size 46 Source: (NSE, 2015) 47