THE EFFECT OF CAPITAL STRUCTURE ON FINANCIAL PERFORMANCE OF
MANUFACTURING FIRMS LISTED ON NAIROBI SECURITIES EXCHANGE
BYTERER NAOMID33/2549/2012CHEPKOECH VIVIAN D33/2550/2012IAN ACHANDOD33/2554/2012GEOFFREY NALIANYAD33/2619/2012WILSON WAWERUD33/2827/2012A MANAGEMENT RESEARCH PAPER SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF BACHELOR OF COMMERCE, SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI.
We affirm that this research development is our unique work and has not been given in for examination in any other institute of higher learning.
IAN ACHANDO______________________________________GEOFREY NALIANYA______________________________________WILSON WAWERU______________________________________This research project has been presented for degree consideration with my approval as the University Supervisor
Signature: ________________________ Date: _________________________
ACKNOWLEDGEMENTWe stretch our thanks to the Almighty God for His loveliness, grace and guidance in completing this research project. We further acknowledge our associates for their backing during the course of the research.
We additionally acknowledge all our professors, facilitators and lecturers of the School of Business for the innumerable roles they each separately played towards the efficacious accomplishment of this research project.
Our exceptional thanks goes to the project supervisor, Dr. Mirie Mwangi, for whole heartedly extending his useful, extensive and intellectual annotations and guidelines towards the success of this research paper.
DEDICATIONThis academic study is dedicated to our networks especially our friends and families for the invocations and encouragement during the course of the research.
TABLE OF CONTENTS
TOC o “1-3” h z u DECLARATION PAGEREF _Toc455970089 h iiACKNOWLEDGEMENT PAGEREF _Toc455970093 h iiiDEDICATION PAGEREF _Toc455970094 h ivTABLE OF CONTENTSv
LIST OF TABLES PAGEREF _Toc455970096 h viiiLIST OF FIGURES PAGEREF _Toc455970097 h ixLIST OF ABBREVIATIONS PAGEREF _Toc455970098 h xABSTRACT PAGEREF _Toc455970106 h xiCHAPTER ONE: INTRODUCTION PAGEREF _Toc455970107 h 11.1 Background of the Study PAGEREF _Toc455970109 h 11.1.1 Capital Structure11.1.2 Financial Performance2
1.1.2 Capital Structure and Financial Performance31.1.4 Manufacturing Firms Listed at the NSE PAGEREF _Toc455970113 h 41.2 Research Problem PAGEREF _Toc455970114 h 51.3 Research Objective PAGEREF _Toc455970115 h 61.4 Value of the Study PAGEREF _Toc455970116 h 6CHAPTER TWO: LITERATURE REVIEW……………… PAGEREF _Toc455970117 h 72.1 Introduction PAGEREF _Toc455970119 h 72.2 Theoretical Review PAGEREF _Toc455970120 h 72.2.1 Capital Structure Irrelevance Theory PAGEREF _Toc455970121 h 72.2.2 Trade-off Theory Capital Structure PAGEREF _Toc455970122 h 82.2.3 The Pecking Order Theory PAGEREF _Toc455970123 h 92.2.4 Agency Theory PAGEREF _Toc455970124 h 102.3 Determinants of Capital Structure11
2.3.1 Liquidity PAGEREF _Toc455970125 h 112.3.2 Firm’s growth. PAGEREF _Toc455970126 h 112.3.3 Firm’s Size PAGEREF _Toc455970127 h 122.3.4 Leverage PAGEREF _Toc455970129 h 132.4 Empirical Studies PAGEREF _Toc455970130 h 132.5 Summary of the Literature Review PAGEREF _Toc455970131 h 19
CHAPTER THREE: RESEARCH METHODOLOGY PAGEREF _Toc455970132 h 21
3.1 Introduction PAGEREF _Toc455970134 h 21
3.2 Research Design PAGEREF _Toc455970135 h 21
3.3 Target Population PAGEREF _Toc455970136 h 21
3.4 Data Collection PAGEREF _Toc455970137 h 22
3.5 Data Analysis PAGEREF _Toc455970138 h 22
CHAPTER FOUR: DATA ANALYSIS, FINDINGS AND INTERPRETATION PAGEREF _Toc455970139 h 24
4.1 Introduction PAGEREF _Toc455970141 h 24
4.2 Descriptive Statistics. PAGEREF _Toc455970142 h 24
4.2.1 Short Term Debt Raio. PAGEREF _Toc455970143 h 25
4.2.2 Return on Assets. PAGEREF _Toc455970144 h 26
4.2.3 Long Term Debt Ratio PAGEREF _Toc455970145 h 26
4.2.4 Debt to Equity Ratio PAGEREF _Toc455970146 h 27
4.3 Inferential Statistics PAGEREF _Toc455970147 h 28
4.3.1 Correlation Analysis28
4.3.2 Regression Analysis30
4.4 Analysis of Variance31
4.5 Discussion of Research Findings32
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS34
5.2 Summary of Findings34
5.4 Recommendations for Policy and Practice.35
5.5 Limitations of Study. PAGEREF _Toc455970158 h 36
5.6 Suggestions for Further Research.36
APPENDICES PAGEREF _Toc455970161 h 43
Appendix 1: List of Manufacturing Firms Listed at the NSE PAGEREF _Toc455970162 h 43
Appendix 11: Data Summary of Averages 2011-2015 PAGEREF _Toc455970163 h 44
Appendix 111: Mean of Variables used for each year, 2011-2015 PAGEREF _Toc455970164 h 45
Appendix 111: The Yearly Mean Data for each Company PAGEREF _Toc455970164 h 46
LIST OF TABLESTable 4.1 Descriptive Statistics
Table 4.2Correlation Analysis
Table 4.3Model Summary
Table 4.4Analysis of Variance
Table 4.5Coefficients and t-statistics
LIST OF FIGURESFigure 4.1 Short Term Debt Ratio
Figure 4.2Return on Assets
Figure 4.3Long Term Debt Ratio
Figure 4.4Debt to Equity Ratio
LIST OF ABBREVIATIONSEPSEarnings per shareGDPGross Domestic Product
MMModigliani & MillerNPMNet profit marginNSENairobi Securities ExchangeROAReturn on assetsROEReturn on equitySPSSStatistical Package for Social Sciences
ABSTRACTWhen firms are seeking an ideal composition of the capital structure, the two major options are debt or equity. In the past most of the studies carried out have showed that using a lot of debt in the capital structure generally leads to a firm having better performance financially. Contrary to that the Modigliani and Miller theory asserted that the market value of a firm is not affected by the debt levels. The weight and constant debate on the above topic has led to a lot of researchers to investigate the effects of the composition of the capital structure on the performance of various firms financially. The principal objective of this study was to find out the effect of the composition of the capital structure on the performance of manufacturing firms listed at the Nairobi Securities Exchange. The empirical parameters used were the debt to equity ratio, short term debt ratio and long term debt ratio which was used to quantify the capital structure while the return on assets was used to quantify the yearly financial performance. The period under study was 2011, 2012, 2013, 2014 and 2015. The study population was 10 manufacturing firms listed at the Nairobi Securities Exchange. Most of the secondary data we applied was acquired from the specific company’s published financial statements and also a handbook from the Nairobi Securities Exchange. After we acquired all the relevant data we applied the multiple regression analysis method and also analysis using the Statistical Package for Social Sciences Software, (SPSS). In the end, the results from our study showed there is a positive correlation between capital structure and a firm’s yearly performance financially. The outcome of the study showed a negative correlation between long term debts ratio and return on assets hence an increase in the long term debts ratio, reduces ROA.
CHAPTER ONEINTRODUCTION1.1 Background of the StudyFinance is in the best interest of an organization and hence there is a need to come up with right capital structure so that the organization is able to thrive in the market and make profits which is its major goal. There is the need to take into consideration how firms structure their mode of financing, therefore, getting to understand how firms, finance their operations. This can be equity financing or leverage. Every company is required to come up with the right capital structure but this is difficult to know the exact proportion to be used in terms of equity and leverage. Modigliani and Miller (MM) theory of 1958 shows that the kind of a capital structure a company assumes does not in any way affect the performance of the company.
Capital structure effect on financial performance has been a major concern in finance over the years since MM theory in 1958. The bankruptcy will be high in an organization if it employs huge leverage levels since the company will not be able to pay off its debts hence reducing the performance of the company (Stiglitz, 1969). Umer (2014) pointed out that most empirical studies reflected a negative effect of capital structure on profitability of the company. Titman and Wessels (1988) research dictated that debt in a firm had negative correlations on the financial performance of a company. There is no specific theory yet that can be relied upon by managers to determine an optimal level of capital structure. Therefore, there is the need to do more research so as to come up with a proper capital structure.
1.1.1 Capital StructureAccording to Damodaran (2001), referred capital structure to the different combination of the liabilities in the firm used for different organization’s activities. The capital structure consists of leverage and equity. Debt financing constitutes of the borrowed funds such as notes payable while equity, on the other hand, constitutes the shareholders ownership in the firm such as common stock. Given the fact that financing is an issue in every organization since it determines it the success or not, make the stakeholders especially those who supply, to gain control over firms they put financial resources. The associated levels of control, benefits and risks are different for the shareholders and for the debt holders. Creditors have little control in the company, they are given constant returns and they have priority if the company goes into liquidation hence need to have collateral to protect themselves. Shareholders, on the other hand, carry the residual claims but their earnings fluctuate depending on the profitability of the company and they have control in the company.
Modigliani and Miller (1958) demonstrated that in markets that have no any kind of frictions that make them fluctuate and also with the expectations which are uniform in nature, then the capital structure of a firm will not matter that is, irrelevant. This discovery made the capital structure a major issue in financial economics. However, theories have been developed seeking to determine whether there existed an optimal capital structure by analysing whether Modigliani and Miller’s assumptions were correct or it can be relaxed a bit to make it more relevant, and if so, find out the determinants of this optimal capital structure. High leverage levels of a firm are caused by various factors such as the large size of the firm , the presence of non-current assets, high chances of financial distress, an increase in profitability, the product differentiation and the different investments available to the firm. Desai (2009) came up with two effects of capital structure, firstly, that firms which experience the same kind risk are most likely to have higher leverage hence given the high cost of capital. Secondly, firms with high levels of debt will be valued less as compared to the firms which do not have high levels of debts.
The management always set the company strategic focus which is to ensure that there shareholders’ maximization of wealth. So to achieve this, the management comes up with a capital structure that ensures the company shares sells at a high price which is the interest of the shareholder. Managers have a wide range of opportunities to exercise their managerial duties with discretion as to matters of capital structure decisions. According to Dimitris and Psillaki (2007), the capital structure used by a firm might not always be for not be the maximization of shareholders’ wealth or company value for this matter but it could be for the management personal gains. This is done most in cases where the company important decisions are made by managers alone and no involvement of other stakeholders.
1.1.2 Financial PerformanceThe way in which a firm performs in terms of how much revenue is generated as compared to the expenditures that were used and how it utilize the available resources is financial performance. It shows the financial health of a company during a certain year of study. In a shareholder’s perspective, it is used to determine the extent to which the shareholders wealth has improved during the end of the period as compared to the start of the period. The financial ratios from the financial statements; mainly the statement of financial position and the statement of comprehensive income or stock market data can be used in coming up with the status of the shareholder (Berger ; Patti, 2006). Financial performance evaluation ratios include Profitability, Liquidity, Gearing, Return on Assets (ROA), investor ratios, Return on Equity (ROE) and debt ratio, the list is long, are the ratios to be considered. With these ratios, one can tell if a firm is achieving its objectives of shareholders’ wealth maximization. They can also be used to compare the company performance to that of different companies in the industry as well as depicting trends of performance over time. It is conclusive, therefore, that the measurement of a firm’s performance has to show the extent the shareholder has become better on his wealth due to the investments undertaken by the firm over a given time frame.
1.1.3 Capital Structure and Financial PerformanceThe effects that capital structure has on the performance a firm is a topic that requires proper research different scholars have not yet found a proper. Research by Modigliani and Miller (MM), 1958, claimed that in seamless market setting capital structure will have no effect on the firm’s value. Consequently, in the 1963 publication, MM via introduction of levies into their model where the method of financing becomes relevant. A corporation can fully maximize its value via the utilization of leverage that provides an interest tax shield. A firm has more value if it uses debt financing because debt reduces the corporate tax. A company that uses extra debt tend to save further in the form of corporate tax shield.
Therefore, there is direct effect between financial performance and leverage of a company. Myers (1984), under the pecking-order theory, concluded that there is a direct correlation amid leverage and financial performance of a going concern. He reiterated that firms have more preference to internal sources of finance. This theory states that firms give first priority to internal financing and only desires to raise finances from equity in situations where there is no alternative. He contends that the reason behind why equity is not being used mostly by companies is that managers take advantage of the insider information and sell shares when there is overvaluation in the market for their own benefit.
Therefore, investors tend to think that when there is a new issue of shares as negative and that it has lower value in the market. Jensen and Meckling (1976) together with Jensen and Ruback (1983) established a direct correlation between the leverage and the performance of a company. They content that managers do not at all constantly work for the ultimate goal of maximizing the shareholders return. They take advantage of ease access to the company cash for their use and forget about the key objective, which is doing businesses that boost the shareholders to the next level in their wealth investment in a company. Jensen (1986) put across that there will result in agency problem which forces the company to incur agency cost such as monitoring cost. The reduction conflict between management and the shareholders, there is an argument by Pinegar and Wilbricht in 1989 that the capital structure is useful in the sense that it can be increased especially debt levels and at the same time reducing the agency cost.
Hence, the management will be made to make an investment in the projects that have positive yields for the shareholders’ advantage because they will face the unfavourable consequences such as liquidation, loss of decision-making role, the threat of being fired among others. Thus, the higher debt levels, the higher the performance of the corporation for the reason that agency costs are minimized. The excessive use of leverage in a company brings about conflict of interest among the debentures and the shareholders and this thus leads to an indirect relationship between the debts of the firm and its profitability (Fama ; French, 1998).
1.1.4 Manufacturing Firms Listed at the Nairobi Securities Exchange
A manufacturing firm is any business enterprise that uses raw materials or components to produce a finished product that can be used by consumers or other manufacturing firms in the production of other products (Kungu,2014). Kenya has relatively small number manufacturing firms and only ten are listed at the Nairobi Securities exchange (www.nse.co.ke). The listed firms deal mainly in agricultural and fast moving commodities.
Manufacturing firms listed on the NSE, both from the public sector and private sector have had challenges on how to determine the right capital structure which will result in the improvement of the performance of a company. The sector being a non-financial institution, needs a clear way in determining their capital structure. This can be achieved through research studies which have been done over the years by different scholars but no specific conclusion yet as many researchers have had different conclusions (www.nse.co.ke).
Nairobi Securities Exchange provides a platform that enables different companies to trade their share and is able to attract many potential investors as their share are made public. There is trading of derivatives, debt, and equity. The manufacturing firms listed ten at March 2016 out which nine of them are active traders (NSE 2016).
1.2 Research Problem
Capital structure is a basic requirement for all firms, so for these firms to run smoothly without the financial constraints then they have to develop an optimal capital structure. Different research has been done since the Modigliani and Miller (1958) indicated that capital structure that a company assumes does not determine how it will perform. Equity holders will not invest even in high yield projects if they expect the company to go into a financial distress since they are the ones who will bear the cost as the debt holders are paid their dues since they have priority claims over a firm’s assets hence the more the leverage, the more profitable projects are rejected (Myers, 1977). According to agency theory, financial performance is improved when the debt level is high as managers will be more cautious in the kind of investments they do as they are answerable to the debt holders who have priority over the firm’s assets in case of liquidation.
Many studies have been carried out to determine whether there are effects of capital structure on how a firm performs financially. Kiprop (2014 work revealed that there was a direct relationship between financial performance and capital structure of a company. Abor (2005) established a direct correlation between debt in the company and profitability (return on equity) having used regression analysis in studying the listed firms in Ghana. Adera et al. (2015) study showed the direct correlation between debts in a company and its performance having used no experimental research design.
There are other empirical studies which have shown an indirect impact on financial performance and capital structure. Gichovi (2014) looked into how the performance of a company will be affected given the capital structure of companies listed on NSE from 2008-2012 and found out a negative relationship, high debt ratio fewer returns on equity. Boodhoo (2009) used four financial measures, return on equity, return on assets, Tobin’s Q and resulted in an indirect relationship but with a direct effect on growth and performance. Lawal Babatunde Akeem et al. (2014) work in Nigeria found out that there is a negative relationship having used descriptive design and regression analysis.
From the above arguments, an optimal capital structure which boosts financial performance of a company has never been found. Moreover, many academic researchers have dwelt so much on the studies of all firms listed on the NSE in Kenya and few on different sectors especially manufacturing firms in Kenya. The studies have also been done mostly in the developed nations and Western Africa, so there is a need to study the impact of capital structure on how a company will perform financially for those firms which are in the manufacturing sector and are listed on the NSE. Manufacturing industry also needs to know the kind of capital structure to use so as to ensure better performance thus boosting the GDP of the country and employing many young people in the nation given the fact that the country is a developing nation.
1.3 Research ObjectiveTo determine the effect of capital structure on the financial performance of manufacturing firms listed on NSE.
1.4 Value of the StudyThe reason for this study is to be able to come with useful substances that will enable people in the manufacturing sector and even other sectors to know the right mixture of the finances to assume as this area has not been extensively researched. Capital structure is of high importance because it shows how the company will relate with its shareholders and also debt holders.
The findings will go a long way in helping manufacturing sector in Kenya generally but will be more specific on listed manufacturing firms. The Capital Markets Authorities in Kenya can also use the findings of this research to channel funds to helping manufacturing firms better utilize resources and also through creating enabling and favourable regulation
CHAPTER TWOLITERATURE REVIEW2.1 IntroductionThis chapter discusses the literature about capital structure theories and its determinants. It has four sections; the first section is dealing with the theoretical framework capital structure. The theories underlying capital structure is dealt with, such as pecking order theory. The second section deals the conceptual framework of capital structure determinants. The third second deals with the empirical studies that is the previous research that have been done by different researchers on capital structure and their conclusions. The final section summarises the literature review and gives the research gap from the previous studies.
2.2 Theoretical ReviewThe following modern financial theories of capital structure have been reviewed in the subsequent section:
2.2.1 Capital Structure Irrelevance TheoryIn the year 1958 Modigliani and Miller both came up with the first proposition of the irrelevance of the capital structure. They theorized that in markets that are perfect, the capital structure of firms is not important. In the proposition they said that the value of a firm is not dependent on its capital structure thus it is irrelevant. Rather, the value of a firm is determined by its ability to raise earnings year by year and also by the risk levels of the financial instruments it holds. The fundamental proposition I was based on the belief that the parties in the market had perfect information, no personal or even corporate taxes, no costs incurred in transactions, no costs for bankruptcy costs, and also that individuals and companies could both borrow at nearly the same interest rates.
Modigliani and Miller also theorized that if all factors like the earnings power and going concern were held constant the value of a company with debt and one without debt could be equal. After a period of around five years Modigliani and Miller relaxed the assumptions and theorized that when the capital markets are not perfect corporate taxes exist, a firm that uses debt as the source of finance maximizes its value due to interest tax shield. Therefore, in the year 1963 they said that the value of a firm will increase as it uses more and more debt to finance its operations due the firm paying less and less corporate taxes. Therefore, the theory acknowledges that if capital structure is at the highest level of debt the weighted average cost of capital will be reduced and the financial performance of the firm will improve. The capital structure irrelevance theory proposes that a firm’s level of debt is directly proportional to its performance but the approach has not taken into consideration other factors that affect leverage and the different sizes of the company.2.2.2 Trade-off Theory Capital StructureThe trade-off theory asserts that firms have ideal compositions of capital structures which is achieved by balancing the benefits and costs of using debt or equity together or even separately. One of the major advantages of using debt is debt tax shields and also the managers of a firm are under pressure to always perform better in order to service debts. On the other hand, one of the drawbacks of using debt includes paying interest and additional costs that may come up if the firm is in financial distress and is not able to service its debts. In that case using debt forces a firm to trade-off the demerits of threats of being in financial distress and advantages of tax shields. Brigham and Ehrhardt in the year 2004 asserted that the value of a firm with debt can be equated with the value of a firm without debt but adding the adverse effects of financial distress and benefits brought about by debt tax shields. A firm that has very low levels of debt in its capital structure has a low and insignificant possibility of bankruptcy.
The widespread use of debt leads to the escalation of bankruptcy occurring and thus most lenders asked for more in risk premiums. He thus asserted that firms ensure they don’t use too much debt which leads to interest rate payments for the debts being more than the tax shield advantages (Baxter, 1967). Consequently, firms would use debt up to the level which the chances of financial distress rise to those of tax shield advantages. Bas et al. (2009) theorized that the trade-off theory is mostly relevant to big firms only that have huge earnings. On the other hand, most small firms do not enjoy merits of tax shields since they mostly have lower earnings (Pettit & Singer, 2005).
2.2.3 The Pecking Order TheoryMyers and Majluf (1984) asserted that an ideal capital structure for most firms is not used but the firms start by first financing their activities using internal finances as compared to using external sources. This theory therefore states that firms that have potential investments that have positive NPV will fund the investments using internal funds first, secondly debt and lastly with equity if no other options exist. This is based on the assumption that using internal debt incurs the least costs. Thus, the pecking order theory asserts that businesses adhere to the above hierarchy of financing sources.
The pecking order theory also considers the costs of asymmetric information in that the necessity for external funding. In Myers and Majluf model (1984), external investors reasonably discount the firm’s stock pricing when a firm issues new shares instead of debt that has no risk. They perceive the issuance of equity as an overvaluation of the firm and the managers are taking advantage of this. The management of most firms shun equity in order not to pay this discount paid for the overvaluation when issuing new capital. The Myers and Majluf model leads to the assertion that most managers will respect the pecking order theory. When investment opportunities are nonexistence firms retain their earnings in order not to have to raise external funds in near of far future.2.2.4 Agency TheoryBerle and Means (1932) came up with the agency theory which asserts that disagreements arise from possible diverse interests between shareholders and managers. The main obligation of managers is to maximize shareholders returns by investing on higher risky investments that is likely to increase profitability of the firm. Jensen and Meckling (1976) said that the management of a firm sometimes do not work toward maximizing shareholders returns rather they work to fulfill their personal interest. The major source of disagreement between the management of a firm and its owners is the presence and quantity of free cash flows.
Some incompetent managers use the present free cash flows for their own personal benefits using funds they could use to invest in projects with positive NPV that would increase the shareholders wealth (Jensen and Ruback, 1983). Therefore managers are forced to choose between investing in projects with positive NPV or in non-profitable investments and not being in a position to pay interest payments as they fall due. When a firm does not pay its debt the debt holders may in turn force the liquidation of the firm and the managers may have to face unfavorable consequences of demotion and loss of job. Therefore in the end high levels of debt lower the cost of agency since the management of the firm will be more efficient and effective and therefore the firm will have better performance in the consequent years.
2.3 Determinants of Financial Performance
The factors that determine the capital structure of a company is normally made only after very careful planning and consideration. According to Titman (1988) there are many factors, both quantitative and qualitative, and also subjective judgment, that together influence the capital structure of that particular company. The management of a company should come up with a target capital structure and every single financing decision undertaken after that should have the target capital structure in mind.
Most manufacturing firms require funds to continuously finance purchase of raw materials and other inputs. When funds are needed the finance manager should consider the advantages and disadvantages of every single financing source. The capital structure decision is undertaken continuously and it takes place every single time the firm needs financing. It is not possible to rank the determinants of capital structure since all the following factors determine of capital structure and the intensity of their influence change with time.
2.3.1 LiquidityLiquidity is the amount of cash that the company has at hand and those assets which can be converted to cash with ease. The liquidity helps the company in meeting its current obligations which are due to the debt holders (Brealey et al., 2001). When we are investigating the liquidity of a manufacturing firm we use the coverage ratio. The ratio measures constant finances that are required to cover the net cash flows. The smaller the coverage ratio, the smaller the amount of debt that a firm can use hence directly correlated.
The pecking order theory claims that companies with high liquidity like to use internal cash which is the retained earnings for their investment projects. In contrast, trade-off theory depicts a direct correlation and thus a firm with high liquidity borrows more due to the perceived ability to pay and access to benefits of tax shield. In the past most studies that have been done have found it to be a negative relationship (Mazur, 2007). One of the major uses of liquidity is to determine the capacity a firm to have or readily develop easily capital to operate.
2.3.2 Firm’s GrowthGrowth and stability of sales greatly influence the capital structure of manufacturing firms. A manufacturing firm that is expected to have stable sales can raise a higher level of debt. As stated by Titman (1988) that for companies to expand or rather grow they need to secure more debt and have higher dividend payout ratio. Stability in earnings ensures that a firm is not faced with prolonged problems in meeting its fixed obligations of paying interests and principal for loans. The rate of growth of earnings of a manufacturing firm also affects is capital structure decisions.
Most firms especially manufacturing firms when growing require large capital outlays and so financing through debt is the easiest and most available method. Under pecking order theory a firm will first use internal cash but in most cases for a growing firm it is not enough. Drobetic and Fix (2005) suggested that after considering internal funds a company will then turn to debt financing and thus a positive relationship between growth and leverage.
2.3.3 Firm’s Size
A firm’s size largely influences the availability of funds from various sources. It is always quite difficult for small firms to raise long-term loans and if they are able to they come with very stringent terms and high rates of interest. Smalls firms are therefore faced by quite inflexible capital structures due to the highly restrictive loan agreements. On the side large firms can obtain good loan conditions easily. Donaldson (1961) claimed that large firms have a larger degree of flexibility in constructing a capital structure and will prefer debts as repayment is cheaper for them.
Large firms in the seven most developed countries are usually more diversified and thus have high chances of paying debt on time (Rajan & Zingales, 1995). The study by Rajan and Zingales supports the trade of theory which predicts that big companies prefer borrowing because they face little financial distress, agency and monitoring costs. Wald (1999) showed a direct correlation between debt and the size of the company in Japan and USA but an indirect relationship for those large companies in Germany while in France it was a positive relationship.
Leverage measures enable us to define the financial structure of the organization. Financial leverage is the degree to which operating assets are financed with debt versus equity (Penman, 2001). Debt obligations generally require compulsory payment of debt when it falls due. Common equity does not have a mandatory call on cash either for period returns to capital providers or for retirement of equity holders’ capital investment in the firm. Thus, debt holders receive a fixed payment while equity holders receive the residual after all other claimants have been satisfied. Accordingly, if a firm is able to earn profits in excess of the cost of borrowed capital, the spread of those profits in excess of the cost of the borrowed capital become additional profits for the equity holders. If a firm is unable to earn profits in excess of the cost of its borrowed capital, the equity holders take a loss to the extent of that spread while the debt holders continue to earn a return. Hoskisson et al. (2003) said that greater the ratio of capital provided by debt to the capital provided by equity, the higher the potential gains and losses for equity holders. This relationship is often referred to as the risk-reward trade-off. The greater a firm’s leverage, the greater the bankruptcy risk in poor times, and conversely, the greater the profits in good times, for equity capital providers.
Brush et al. (2009), found that the strategic choices available to managers may be limited in highly leveraged firms because of the inability to raise additional debt capital or by being forced to use more costly equity capital. As a consequence, leverage may be used as a control variable in strategic management studies
2.4 Empirical StudiesCapital structure theories have resulted in a lot of empirical studies being done by different researchers. For example, trade-off theory which requires a balance between costs and benefits so as to avoid bankruptcy costs. However, these theories have given rise to different conclusions regarding the effect of capital structure on financial performance. Voulgaris et al. (2010) studied the statement of comprehensive income of large sized enterprises of the manufacturing firms in Greece to determine the correlation between capital structure and financial performance. The study utilised regression analysis on a sample of 143 firms and it was demonstrate that there is a substantial relationship between capital structures, profitability and asset growth. Akinyomi & Olagunja (2013), using three manufacturing companies in Nigeria used random selection to get a sample from the beverage and food categories for a duration of 5 years (2007-2011) using static trade-off theory and the pecking order theory point of view. He used correlation analysis and discovered that each of short term debt to total debt, debt to capital, debt to common equity and the age of the firms’ is substantially and positively related to ROE and ROA but long term debt to capital is substantially and relatively related to ROA and ROE. His proposition also tested whether there is a substantial relationship between capital structure factors and financial performance using ROA and ROE.Khalaf (2013) utilised a sample of 45 manufacturing firms listed on the Amman Exchange. The samples utilised for this research covered a period of 5 years from 2005 to 2009. Multiple regression analysis was employed to performance indicators which are ROA and NPM in addition to long-term debt to total assets, short term debt to total assets and Total debt to equity as capital structure factors. The results indicated that there is a negative and trivial relationship between short term debt to total assets and long term debt to total assets, and Return on assets and profit margin; while total debt to equity is positively related with return on assets and negatively related with net profit margin. Short term debt to total assets is substantial using return on assets while long term debt to total assets is substantial using net profit margin. The research concludes that capital structure is an insignificant determinant of financial performance of firms. The policy recommendation is that managers of manufacturing firms should apply caution in selecting the level of leverage to utilise in their capital structure as it influences their firm financial performance negatively.Kamere (1987) conducted a study on various variables that affect capital structure decisions of public firms in Kenya. This research found out that profitability was the key variable that affected the selection of the various capital structures in the companies listed at the NSE. He noted that the firms which had high profit margins did not borrow as much as those firms with low profit margins. The highly profitable companies did not borrow much because they would reinvest some of their profits back into the business. On the other hand, those firms with relatively small profit would not be able to reinvest any significant amount in the business. This problem therefore forced such companies to seek additional funding for their projects from without the organization. This research went along with the pecking order theory that argues that in the existence of asymmetric information, a company would favour internal financing over the other external sources of finance, but would accept debt if internal finances were exhausted.Rajan and Zingales (1995) did a research and found a negative relationship between a company’s growth and its level of debt, which contrasted the pecking order theory. They argued that bondholders often impose much higher costs when lending to growing companies because of the speculation that such firms may choose to invest in risky projects in the future. Established companies have a lot of flexibility regarding their future investments and that is why their agency costs are expected to be higher. Therefore, established companies that are facing high costs of debt have more preference for debt financing than equity.Magara (2012) researched on the determinants of capital structure at NSE not taking into consideration the effect of macro- economic factors such as interest rates and inflation. The aim of the study was to establish the determinants of capital structure. In his research, he established that within the period of 2007 and 2011, there was a positive substantial relationship between the company size, tangibility and rate of growth and the level of debt of the company to the capital structure.In 2010, Mwangi examined the relation between capital structure and financial performance on companies listed at the NSE. In his research methodology, structured questionnaires were used. The research identified that there was a strong positive relation between financial leverage and ROE, liquidity, and ROI. His findings are also backed by a number of previous studies. To these researches, the benefits of debt financing are far less than their negative aspects, therefore firms prefer to fund investments by internal sources Rajan and Zingales (1995), Jensen and Meckling (1976), and Fama and French (2002). Musiega et al. (2013) conducted a study to find out the relation between a firm’s capital structure and financial performance. He studied 30 non-financial firms listed on NSE over a 5-year period of 2007-2011. In the study the analysis was employed using both descriptive statistics and inferential statistics by applying linear regression analysis. The study used five performance measures: return on equity, return on assets, and dividend pay-out ratio, market price to book ratio of stock as dependent variables and three capital structure measures: long term debt to asset ratio, short term debt to asset ratio and total debt to asset ratio as independent variables. Size of the firm taken as natural logarithm of sales was considered as a moderating variable. His research found a significant positive correlation between total assets of a firm and capital structure proxies, showing that long term debts were used by large companies that had large assets which could be used as collateral for securing loans. He further noted that, firms on NSE appeared to use far less debt in their capital structure making many companies pay less interest thereby not increasing the risks the firm may be exposed to, as debt tends to reduce performance.Kaumbuthu (2011) considered companies listed at the NSE where he was investigating the influence of capital structure on the returns from equity for the five years after 2004 in the allied and industrial section of the NSE. The parameter used to find out the composition of capital structure was the debt to equity ratio whereas the performance of a firm was calculated using the returns from the firm’s equity. In the study Kaumbuthu, (2011) used the regression analysis method and he found out that there was an inverse relationship between the debt equity ratio and ROE. The outcome of the study cannot be broadly used on all other sectors of an economy.
Ibrahim (2009) investigated the effect of capital structure on a variety of firms in the Egyptian economy. Ibrahim applied the multiple regression analysis model on the firms to find out the relationship between debt and the performance, and also three other calculated ratios that is ROE, ROA and gross profit margin. The period of the study was for the eight years after 1997 and the outcome was that the capital structure composition has minimal impact on the financial performance of the firms.
Muhammed and Wali (2008) investigated the factors that influence the composition of the capital structures for companies in the chemical industry of Pakistan. He selected a fraction of the chemical firms listed at the Karachi Stock Exchange and applied multiple regression and he came to the conclusion that earnings, profit variation, firm’s growth, size of the firm, size of debt shield and also tangible assets had a lot of influence in leverage except tangibility of assets. The policy implications could be used by the researchers, investors and managers in future decision making. Kazmierska et al. (2015) critically analysed the determinants of capital structure on Polish enterprises listed at Warsaw Stock Exchange. Having used five independent variables, they found out that there was a big inverse relationship between the size of the firm, rate of growth, earnings, tangibility of assets and the debt level. He found a direct relationship between the leverage of the firm and its growth. The study asserted that the pecking order theory showed that changes in the level of debt of the analysed firms than any other capital structure theories.
Abor (2005) studied the relationship between the earnings and the composition of capital structure in the Ghana Stock Exchange during the five years under study. He applied the regression analysis model and found out that there was a direct relationship between debt held for the short-term to total assets and ROE but an inverse relationship between the ratio for debt held in the long-term to total assets and ROE. Thus, he found out that the relationship between total debt to total assets and ROE was significantly direct. Allahham (2015) investigated the relationship between the performance of banks in Saudi Arabia and the composition of their capital structure. In the end, he found out that there was an inverse relationship between the capital structure of the banks and capital invested and yearly performance financially. Thus, there is no consensus on the ideal capital structure that firms should use. Saheli et al. (2009) studied the relationship between the capital structure and yearly financial performance in Iran. They used three factors which were book value, market value and also adjusted valuations. The study covered five years from 2002 onwards for companies listed at the Tehran Stock Exchange. The investigation found out that the composition of capital structure had an effect on the performance financially of the listed firms. Khaham et al. (2014) investigated the existing impact of capital structure on firms’ financial performance of Pakistan food sector firms. They used ROA, ROE, net profit margin, EPS and capital employed as dependent variable whereas debt to equity, long term debt to total assets and short term debt to total assets debt ratio as independent variables. Quantitative data was used with a total of 49 firms on the food sector. It covered the period from 2007 to 2012. Linear regression analysis was employed as a method of research design with descriptive statistics. The results indicated that there exist an inverse relationship between capital structure, ROA, NPM,ROE and return on capital employed on firm’s financial performance while insignificant negative relationship with earnings per share.
Vatavu (2013) analyzed the influence of composition of capital structure on performance of manufacturing firms found in the stock exchange in Bucharest, Romania. The research covered a period of eight years from 2003 to 2010. The study employed a cross sectional regression analysis and used short-term debt, long-term debt, total equity and total debt as indicators of capital structure whereas ROA and ROE were the performance proxies. The results indicated that use of equity leads to better performance as compared to use of debt in Romania companies.
Kibet (2013) surveyed the correlation between capital structure and share prices on energy firms listed at NSE. They used equity, gearing and debt ratio on share price and also employed panel data over the period 2006-2011. Multiple regression analysis was used. The findings showed that debt and gearing ratio had a direct relationship with share prices whereas equity ratio had an inverse relationship with share prices.
2.5 Summary of the Literature ReviewThis literature review had an aim of coming up with evidence to show the existence or non- existence of correlation between capital structure composition and financial performance of manufacturing firms listed at NSE. Past researches have shown an inverse and also direct relationship between the composition of capital structure and financial performance of various companies. Theoretical and empirical reviews and also the determinants of capital structures in firms are also discussed. The major theories under review were capital structure irrelevance theory, trade-off, pecking order and agency theories. Since 1958 when Modigliani and Miller asserted that the financial performance and capital structure were not directly related several studies have come up for and against. In Kenya, Mwangi, (2010) asserted that there was a significant relationship between the financial performance of firm’s and the composition of the capital structure. Kaumbuthu used the multiple regression model and found an inverse relationship between the debt to equity ratio and ROE. Kamere 1987 suggested that profitability was a major consideration for the capital structures of firms at the NSE. Kibet, 2013 findings showed that share prices were negatively related to equity while debt and gearing ratios were positively related to share prices. The above study therefore comes to fill the knowledge gap that exists for manufacturing firms listed at the NSE when you consider the composition of the capital structure and the yearly financial performance.
CHAPTER THREERESEARCH METHODOLOGY3.1 IntroductionThis particular chapter of the research outlines the procedures and methodologies that were employed in data collection and analysis. This includes the research design used, our target population and the specific data collection and analysis instruments.3.2 Research DesignWe made use of both the descriptive design and the longitudinal research design, using secondary quantitative data. Descriptive design is a scientific method used to describe a certain phenomenon. Longitudinal design follows the same population over time and makes repeated observations. Descriptive design was used to depict the actual effect of capital structure on manufacturing firms’ financial performance specifically those listed at the NSE whereas quantitative data was collected and analyzed so as to determine the statistical relationship between capital structure and financial performance. The data was obtained from the NSE handbooks and audited published financial statements of manufacturing firms.3.3 Target PopulationPopulation is the study of all the elements in the universe (manufacturing firms) when making inferences about the variables of the study. We focused on ten manufacturing firms listed at the NSE as at 31st December 2015. A period of 5 years was considered sufficient enough to acquire data that aided in analysis of statistical association between capital structure and financial performance.3.4 Data CollectionThe data in this study is primarily secondary data. We collected the data from annual reports of the firms under study, the NSE handbooks and published financial statements from the financial year 2011–2015. The data encompassed statements of financial position, comprehensive income and cash flows. We collected data comprising of net profits/loss, total debts, short term debts, long term debts, total equity and total assets.
3.5 Data Analysis
The Data was then tested for its validity, reliability and accuracy. The data was then analyzed using Statistical Package for Service Solution (SPSS) in consideration to ratio analysis, multiple regression analysis and correlation analysis. The following ratios were computed; debt to equity ratio, short term debt ratio and long term debt ratio. We then applied correlations and regression analysis to establish the comparison of how the independent variable affects the dependent variable under study. In our study, financial performance formed the dependent variable whereas we had capital structure components as the independent variables. The relationship that exist between the variables was depicted by regression analysis whereas correlation analysis was instrumental in determining the relative strength of the existing relationship, if any, between capital structure and the firms’ financial performance.
The model that was regressed in this study is presented in a relational form as follows:
Firm’s financial performance (ROA) = f (capital structure)
Hence the firm’s financial performance= f (debt/equity ratio, short term debt ratio, long term debt ratio)
Return on Assets (ROA) = a+b1X1+b2X2+b3X3 +e; Where a =Constant
Return on Assets= (Net income/ Total assets)
X1= Debt/Equity Ratio (Total debt/ stockholders equity)
X2= Short Term Debt Ratio (Short term debts/total assets)
X3= Long Term Debt Ratio (long term debts/Total assets)
e= Error term and a, b1, b2 and b3 are parameters to be estimated. The appropriate expectation is that a?0, b1?0, b2?0 and b3?0CHAPTER FOURDATA ANALYSIS, FINDINGS AND INTERPRETATION4.1 Introduction
This chapter discusses the findings of the study on the capital structure effect on financial performance of manufacturing firms listed at the NSE between the years 2011 to 2015. The variables used in the study included: return on assets which acted as a financial performance measure, debt/equity ratio, and short term debt ratio and long term debt ratio. This chapter examines the variables and model estimates used in the study.4.2 Descriptive StatisticsDescriptive statistics in our case help us to analyse the data from the eight manufacturing firms listed at the NSE. Therefore, we will be able to summarize and describe the data in a meaningful way showing patterns that may come up. They provide simple summaries about the measures together with simple graphic analysis. The data obtained was for the following firm; British American Tobacco, East Africa Breweries, Mumias Sugar Company, Unga Group, Eveready East Africa, Kenya Orchads, Carbacid Investments and B.O.C Kenya.
Table 4.1 Descriptive Statistics
Mean Std. Deviation N
ROA 21.823271 36.2312554 40
Debt to Equity Ratio -9.530368 187.3168981 40
Short Term Debt Ratio .308661 .1567121 40
Long Term Debt Ratio .249563 .3039818 40
Sources: Research Findings 2016
The value for the return on assets for the eight manufacturing firms was 21.82 for a period of five years and the standard deviation was 36.23. The debt to equity ratio from the year 2011 to 2015 was -9.53 and the cause of this large negative figure was Kenya Orchards which had an average debt to equity ratio of -107.20 for the five-year period. This eventually led to a high standard deviation figure of 187.32. The short term debt ratio was 0.31 with a standard deviation of 0.16. On the other hand, the long term debt ratio for the five years was 0.25 with a standard deviation of 0.30.
4.2.1. Short Term Debt Ratio
Short term debt ratio is a good pointer of the financial performance of the firm. This is because it shows the liquidity of the firm and how the firm is able to meet the maturing obligations. The analysis shows that there was high ratio was highest in 2015 at 0.35 and lowest in 2013 at 0.27. The data is in the appendix 111.
Figure 4.1 Short Term Debt Ratio
Source: Research findings 20164.2.2 Return on AssetsReturn on assets is a profitability ratio that measures the level of profitability firms attain relative to their total assets they possess. It enables one to know how good the firm’s management is at making profits using the available resources. The year 2011 and 2012 had high values of ROA at 10.39 and 11.11 respectively. In 2013 the ROA sunk to 7.55 but in 2014 was worse at 2.10. The year 2014 had the least ROA for the five-year period under research. The final year of research that is 2015 had the highest ROA for the five years at 13.07. The data is in the appendix 111.
Figure 4.2 Return on Assets
Source: Research Findings 2016
4.2.3 Long Term Debt RatioLong term debt ratio is a financial ratio that measures a firm’s long term debts relative to its total assets. The analysis we carried out shows that the ratio was the highest in 2014 when compared to other years. It then rose from 0.19 in 2011 to 0.29 in 2014. In 2015 the ratio reduced to 0.14 which was the lowest in the period of study. The data is at appendix 111.
Figure 4.3 Long Term Debt Ratio
Source: Research Findings 2016
4.2.4 Debt/Equity RatioThis is a financial ratio that measures a firms’ financial leverage. It is computed by dividing a firms’ total debt by total shareholders’ equity. This ratio shows the amount of debt a firms uses to finance its total assets relative to its shareholders’ equity. The data is in appendix 111.
Figure 4.4 Debt/Equity Ratio
Source: Research Findings 2016
In 2011, the average of the debt to equity ratio was -127.118. The average was mainly influenced by the debt to equity ratio of Kenya orchards which was -1023. The ratio decreased sharply in 2012 to around 65.09. The ratio fell in 2013 to 4.82. In 2014, it fell marginally to acceptable levels of 1.24. It increased marginally to 1.54 in 2015.
4.3 Inferential StatisticsInferential statistics was used to make inferences from the data and hence drawing conclusions that extend beyond the immediate data.
4.3.1 Correlation Analysis Partial correlation analysis using Karl Pearson correlation coefficient was performed. A negative coefficient signposted an inverse connection amongst the variables correlated which implies that a decrease in one variable leads to an increase in the other variable and vice versa. On the other hand, a positive coefficient implies a positive relationship in the variables; meaning an upward movement in one variable leads to an upward movement in another variable and vice versa. The outcomes of correlation analysis were umpired based on the strength of association existing between the variables correlated.
The measures used combined dependent and independent variables. The correlation coefficient (r) ranging from 0.50 to 1.0 is considered to be strong, a value ranging from 0.30 to 0.49 is regarded medium and a value ranging from 0 to 0.29 is regarded weak. Coefficient of correlation should not go above 0.8 to ensure non-existence of multicollinearity. In our findings, the highest coefficient of correlation is 0.036, and therefore no cases of multicollinearity.
Table 4.2 Correlation Analysis
ROA Debt to Equity Ratio Short Term Debt Ratio Long Term Debt Ratio
Pearson Correlation ROA 1.000 .033 .036 -.290
Debt to Equity Ratio .033 1.000 .033 -.102
Short Term Debt Ratio .036 .033 1.000 -.120
Long Term Debt Ratio -.290 -.102 -.120 1.000
Sig. (1-tailed) ROA . .419 .413 .035
Debt to Equity Ratio .419 . .421 .266
Short Term Debt Ratio .413 .421 . .231
Long Term Debt Ratio .035 .266 .231 .
Source; Research Findings 2016
The results indicate that debt to equity ratio has a weak positive relationship with ROA (r = 0.033). The relationship was statistically not significant based on the sig. (1 tailed) = 0.419 which is greater than the acceptable significance level of 0.05.
On the other hand, long term debt ratio showed a negative relationship with ROA. This is inferred from the correlation coefficient of -0.29. The relationship was statistically significant since the Sig. value of 0.035 was less than acceptable significance level of 0.05.
The short term debt ratio indicated a positive relationship with ROA inferred by the correlation coefficient of 0.036. The relationship was not statistically significant since the Sig. of 0.413 was greater than 0.05.
4.3.2 Regression AnalysisMultiple regression analysis was adopted to establish the capital structure effects on manufacturing firms’ financial performance. The dependent variable was the financial performance measured by ROA against independent variable which was capital structure determined using these ratios; debt to equity ratio, short term debt ratio and long term debt ratio.
Table 4.3 Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change df1
1 .290a .084 .008 36.0850971 .084 1.106 3
a. Predictors: (Constant), Debt to Equity, Short Term Debt, Long Term Debt
b. Dependent Variable: ROA
Source: Research Findings given by SPSS
Table 4.3 presents regression model summary result. The value of R and R2 are 0.29 and 0.084 respectively. The R value of 0.29 shows the correlation between financial performance measured by ROA and the independent variables (predictor variables). The adjusted R2 value of 0.084 shows the explanatory power of independent variables.
4.4 Analysis of VarianceTable 4.4 ANOVA
Model Sum of Squares Df Mean Square F Sig.
1 Regression 4318.618 3 1439.539 1.106 .360b
Residual 46876.832 36 1302.134 Total 51195.451 39 a. Dependent Variable: ROA
b. Predictors: (Constant), Debt to Equity, Short Term Debt, Long Term Debt
Source: Research Findings given by SPSS
The results of the analysis of variance that explains if the regression model measured by F-ratio is significant. These results indicate that the model had an F-ratio of 1.106 which was significant at p value of 0.36. This result showed a substantial evidence to deduce that at least one of the independent variables is linearly correlated to return on assets (ROA). Therefore, it is denoted that there is substantial effect of debt to equity on manufacturing firms’ financial performance as measured by ROA.
Table 4.5 Coefficients and t-statistic
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta 1 (Constant) 30.378 14.139 2.149 .038
Debt to Equity Ratio .001 .031 .004 .023 .982
Short Term Debt Ratio .245 37.147 .001 .007 .995
Long Term Debt Ratio -34.554 19.240 -.290 -1.796 .081
Dependent Variable: ROA
Source: Research Findings 2016
The results show the computed t-values: Debt to equity was 0.023, Short term debt ratio was 0.007 and Long term debt ratio was -1.796 were less than the 5% significant threshold. This thus shows a substantial relationship between financial performance and capital structure measured by debt to equity ratio, short term debt ratio and long term debt ratio.
4.5 Discussion of Research FindingsThe main objective of this study was to establish the capital structure effect on the financial performance of the manufacturing firms listed at the NSE. The capital structure was determined by debt to equity ratio, short term debt ratio and long term debt ratio while financial performance was determined by ROA.
The results show that leverage (debt/equity ratio) is positively related to ROA which is the measure of financial performance. The coefficient of determination is 0.29 indicates that the relationship is weak. These results provide reasonable evidence to the consistent view that, the higher the leverage, the better the financial performance. The beta of debt/equity ratio is 0.004 with a t-statistic of 0.023. The positive coefficients mean a 1% increase in debt leads to a 0.023% increase in financial performance and the t-statistic value shows that the effect is statistically significant at 0.05, (5%) test level. This finding concurs with Myers (1984) that higher profitability will correspond to a higher leverage holding other factors held constant.
There is a negative correlation between long term debts ratio and firms’ financial performance as indicated by the correlation coefficient of -0.29. The effect was majorly brought by the unpredictable trend in the level of growth in different sizes of the capital structure of the listed manufacturing firms at the NSE. The results did have some significance since the 1 tailed test significance was 0.035 which was less than the threshold of 0.05.
The results indicate that short term debt ratio is positively correlated to return on asset (ROA), the financial performance measure. The beta of 0.001 and t-statistic of 0.007 confirms that the relationship is significant. This means an increase in long term debt ratio by 1% leads to a decrease in financial performance by 0.007%. This impact is significant at least, at 5% test level.
In conclusion the results showed that the capital structure factors had a substantial effect on the manufacturing firms’ financial performance between the periods of 2011 to 2015 at least, at 5% test level. This means that capital structure has an effect on financial performance of manufacturing firms listed at NSE significantly.
CHAPTER FIVESUMMARY, CONCLUSION AND RECOMMENDATIONS5.1 IntroductionThe summary of the study has been discussed in the chapter, then the conclusions that arose from the findings are laid down, recommendations are given based on the conclusions, there is also the discussion of the limitations that were faced during the study and suggestions for further research drawn on financial performance impacts that are caused by the capital structure.5.2 Summary of Findings
This research work was carried out solely in the determination of the financial performance’s influence set off by the capital structure presumed by an organization or an entity and most specifically in the manufacturing sector and are listed at the NSE. Averagely, ROA over the five-year period was 21.82 with a standard deviation of 36.23. Debt to equity ratio over the five-year period was -9.53 with 187.32 as its standard deviation. Furthermore, short term debt ratio was 0.31 and long term debt ratio was 0.25, which was at its average and a standard deviation of 0.16 and 0.30 respectively. The correlation analysis indicated that debt/equity ratio had a positive correlation with ROA (r=0.033). Long term debt ratio indicated a negative relationship with ROA (r =-0.29). The significance level was less than the threshold of 0.05 with the p-value of 0.035. Short term debt ratio showed a positive correlation with return on asset. This is inferred from the correlation coefficient of 0.036. However, the correlation was not statistically significant because its p value was 0.413 which is greater than the significant p-value of 0.05.
5.3 ConclusionThe study findings indicated that, long term debt ratio was the only variable that had a significant relationship with the return on asset. It showed a negative relationship with ROA indicating that an increase in long term ratio decreases firms’ financial performance and vice versa. This is because of the effects of financial distress. Short term debt and debt to equity ratios had an insignificant correlation as seen from the p value and the t-statistic. Their relationships were not significant at 95% confidence level. Therefore, based on the significant variable, this study adds to the body of knowledge that performance of manufacturing sector in its financial terms is influenced by its kind of capital structure.
5.4 Recommendations for Policy and PracticeIt was considered that long term debt ratio was the most important variable in determination of the performance of a company. Firms should fund their capital budgets with the proportion of more debt short term debt and mixture of debt to equity as opposed to dwelling majorly on long term debts. It is important however that financial directors and managing directors in making financing decisions to know the kind of capital structure mixture they are using so that the company can benefit and get it at low cost. Additionally, analysts ought to give financial advice to organizations and potential investors on capital structure that is optimal and that would meet the requirements so as to reduce high leverage which may lead to other costs such as bankruptcy costs. When borrowing, firms should understand that it brings the company close to financial distress then lessens retributions to the corporation’s shareholders because debentures have first priority. Moreover, cost -benefit analysis on leverage should be carried out to check and make sure that the benefits of any project undertaken outweigh the cost of doing the same project and the finances that need to be repaid to the external funds plus the interests attracted. Failure to consider this may force the company to exhaust its residual income to meet their debt obligations since returns on investment will not be sufficient enough to meet such obligations. Therefore, a firm must select a source of funding that is not likely to expose them to debt risks which are difficult to handle.
5.5 Limitations of StudyA number of limitations relating to this research were encountered and which need to be addressed to ensure that a researcher puts them into consideration when planning for a research project. Some of these limitations include: This study used only three measures of capital structure which does not seem to have much effect on the financial performance. Hence, there is need to carry out the study with other different factors both qualitative and quantitative in order to be able to establish the crucial factors. The study used a span of five years (2011-2015) and over that period of five years there has been tremendous change within our economy. In 2011 and 2012, Kenya was still experiencing high inflation rate compared to 2013 and 2014. Hence, the analysis done in these two segments may lead to contradicting sequence flow of information as the factors that influenced the decision were different. Secondary data was used hence in case of any errors, they might have been transferred to the analysis of the study. Nevertheless, the data used was from sources which are reliable. There was a challenge of accessing financial records because of unpublished financial statements by some manufacturing companies. For example, A. Baumann Ltd had no information at all within our period of study.
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APPENDICESAppendix 1: List of Manufacturing Firms Listed at the NSEBritish American Tobacco Limited
East Africa Breweries Limited
Mumias Sugar Company
Unga Group Limited
Eveready East Africa Limited
Kenya Orchards Limited
Carbacid Invest Limited
B.O.C Kenya Limited
A. Baumann Company Limited
Flame Tree Group Holdings Limited
Source: NSE 2016 (www.nse.co.ke/)
Appendix 11: Data Summary of Averages 2011-2015Name of the Company ROA Short Term Debt Ratio Long Term Debt Ratio Debt to Equity Ratio
Mumias -2.76356 0.352608969
BOC 9.630557 0.239887632
Kenya Orchards -11.3826 0.219768094
EABL 14.83027 0.328840841
Eveready 3.695282 0.551657213
BAT 23.19044 0.382497337
Unga Group 6.08397 0.303550384
Carbacid 18.22917 0.068739395
Source: Research Findings 2016
Appendix 111: Mean of Variables used for each year, 2011-2015Year Debt to Equity Ratio Short Term Debt Ratio Long Term Debt Ratio ROA
Source: Research Findings 2016
Appendix IV: The Yearly Mean Data for Each Company
Years 2011 2012 2013 2014 2015
Mumias ROA 17.41418 7.345514 -5.33354 -11.6313 -21.6126996
Debt to Equity 0.60103 0.742601 1.038633 1.2142 2.439550347
Short Term Debt Ratio 0.126158 0.208782 0.308217 0.451348 0.668539624
Long Term Debt Ratio 0.244455 0.217363 0.201258 0.097022 0.040724699
BOC ROA 8.289506 12.98499 -10.2229 27.47061 Debt to Equity 0.367507 0.359654 0.268313 0.316584 Short Term Debt Ratio 0.252526 0.262288 0.204278 0.240459 Long Term Debt Ratio 0.016216 0 0.00489 0 Kenya Orchads ROA 1.012713 0.355338 3.421292 -50.3196 Debt to Equity -1023.26 569.1991 28.45001 -3.19847 Short Term Debt Ratio 0.201463 0.181954 0.167767 0.327888 Long Term Debt Ratio 0.800084 0.818046 0.832233 1.126975 EABL ROA 18.5849 19.64803 10.97098 10.87003 14.07739207
Debt to Equity 0.850833 5.524431 6.596197 5.907702 4.013020341
Short Term Debt Ratio 0.313194 0.278566 0.243195 0.436813 0.372435788
Long Term Debt Ratio 0.146508 0.568164 0.62516 0.418421 0.428083672
Eveready ROA -12.1932 6.0904 4.787868 -19.0944 38.88579811
Debt to Equity 2.639548 2.292604 1.378786 3.257275 0.874984496
Short Term Debt Ratio 0.641536 0.599106 0.471459 0.615331 0.430853397
Long Term Debt Ratio 0.083705 0.097183 0.108158 0.149777 0.03580886
BAT Debt to Equity 1.144573 1.138208 1.243265 1.246093 1.110132159
ROA 22.52927 21.55235 21.92394 23.30996 26.63668968
Short Term Debt Ratio 0.440186 0.351914 0.379666 0.387367 0.353353675
Long Term Debt Ratio 0.09352 0.180405 0.174556 0.167415 0.172742359
Unga Group ROA 7.725538 5.440692 4.170945 5.911535 7.171139331
Debt to Equity 0.524425 0.612906 0.889492 0.712431 0.627700069
Short Term Debt Ratio 0.283557 0.307501 0.390567 0.27065 0.265477546
Long Term Debt Ratio 0.060458 0.0725 0.08019 0.145385 0.122159813
Carbacid ROA 19.74212 19.34042 21.57237 17.22388 13.267067
Debt/Equity 0.185789 0.217844 0.02203 0.316319 0.198504578
Short Term Debt Ratio 0.031143 0.090857 0.040993 0.080937 0.099767221
Long Term Debt Ratio 0.130416 0.104272 -0.01855 0.178819 0.082383796
Source: Research Findings 2016