EFFECT OF DEBT FINANCING ON FINANCIAL PERFORMANCE OF PRIVATE SMALL AND MEDIUM HEALTH CENTRES IN NAIROBI COUNTY KENYA
A PROPOSAL SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF MASTERS OF SCIENCE DEGREE IN COMMERCE IN THE SCHOOL OF BUSINESS AND PUBLIC MANAGEMENT AT KCA UNIVERSITY
1.1 Background of the study
When a company needs capital to finance new and existing activities there are two major decisions to take into consideration. There is the debt-versus-equity decision (capital structure) and there is also the decision on debt structure. Capital structure refers to the way a firm finances its assets through some combination of equity and debt. Debt structure can comprise of short term debt, medium-term debt and long-term debt. Short-term debt is a type of debt, which has maturity tenure of one year or less, and is recorded as a current liability in a firm’s balance sheet, medium-term debt has a maturity of between one and two years while long-term debt is an obligation that has a maturity period of more than two year such as bonds (Scherr;Hulburt, 2011).
Debt financing has been found to relate positively with financial performance (Fama ; French, 2013). This is due to lack of benefits from taxation as the agency problems that come with debt financing cancel out the tax benefit. However debt financing was found to be negatively correlated with financial performance of Taiwan listed firms (Cheng, 2009). Where there are high cash flows, the relationship was found to be negative.
SMEs have displayed a strong correlation between financial performance and debt financing. Inadequate capital sources has been a major challenge to the growth of SMEs especially those in the health sector. This has reduced the competitiveness of the SMEs in their sectors of operation. Uptake of credit by the SMEs would make the firms sustainable financially and so experience improved financial performance (UNCTAD, 2012).
Uptake of external debt financing enables SMEs to have improved cash flows, generation of income and enable the firms to build their production capacity (Alexandra, 2014). According to FSD (2009) external funds are used in order to increase the number of members as individuals are pulled to a firm with accessibility of funding for loans. KUSCCO (2009) noted that firms opted for debt financing in order to meet the loan disbursements, savings and withdrawals demands of savings, withdrawals, and cover operating expenses. Most of the SMEs in Kenya have closed business because of their poor financial management policies, including debt financing (Debrah ; Toroitich, 2015). The aim of this study, therefore, is to determine the effect of debt financing on financial performance of SMEs in Kenya and specifically health centres in Nairobi County.
1.1.1 Debt Financing
The main source of external financing for firms is debt (Baltaic ; Ayaydin, 2014). Debt financing is a financing option that is structured to improve the owners’ rate of return on investments by producing a rate of return that is higher than the overall cost of the borrowed funds (Saadet al., 2015). Leverage financing entails the purchase of interest bearing instruments that are protected by the asset-based security and they have term structures (Githaigo&Kabiru, 2015). Debt financing comprises of the main sources of external funding for most business firms. It provides a mechanism of filling financing deficits for firms that have insufficient financial resources (Onchong’a, Muturi ; Atambo, 2016).
The effect of debt financing on a firm is both positive and negative (O’Brien & David, 2010). Debt financing deducts the interest on tax and reduces problems that come with free cash flows (Fama & French, 2012). Debt financing however increases the chances of the firm becoming bankrupt, and increases stakeholders’ conflict due to the repayment of the debt. This, according to Kraus ; Litzenberger (2013), calls for sober financing decisions to balance the benefits and costs of debt financing. According to Jensen and Meckling (2016), the agency costs have to be considered when making financing decisions especially when debt is the better financing option for a firm.
The core of debt is that the borrower will have to repay the borrowed funds which are accompanied with service charges such as loan origination fees and interest charges (Harelimana, 2017). Debt financing offers a means of satisfying financing deficits of businesses that have insufficient internal resources to finance their operational activities and investments (Onchong’a, Muturi & Atambo, 2016).
In the capital structure of a company, debt capital entails the long-term bond that the company uses during the financing of its investment decisions since the company has a period of repaying the loan amount, whereas the payment interest is only limited with the present time. The healthiness of a firm’s balance sheet is a key determinant of the cost of debt capital in the structure of capital of a firm (Lambe, 2014). Leverage financing can lower the firm’s costs of financing due to the availability of liabilities tax shields task and thus improving the value of the firm (Xu, Ou & Chen, 2016).
Leverage financing choice carry the form of trade credit from bank loans and other financial institutions, suppliers, loans from individuals and the governments (Obuya,2017). Though debt financing is less costly because of the tax exemption, it subjects firms to some constraints as well as default risk of repaying the principle and interest amount (Liaqatet al., 2017). The measure of debt in this study was done using debt ratios that compare the firm’s total debt to its total asset. A low percentage will mean that the firm is less reliant on debt i.e., funds obtained from others or that is owed to others. The lesser the percentage of debt ratio, the lower the firm is using debt finance and the stronger its equity state is (Makanga, 2015).Debt ratio (DR) indicates the fraction of money that financed the total assets by use of an outside source of funds. A higher ratio shows that most of the firm’s assets are offered by creditors relative to the owners (Harelimana, 2017).
The measure of debt in this study is the debt ratio. The debt ratio compares a company’s total debt to its total asset. A low percentage means that the company is less dependent on debt i.e., money borrowed from and/or owed to others. The lower the percentage, the less debt a company is using and the stronger is its equity position. In theory, debt ratio can be measured in different ways i.e. total debt ratio, current debt ratio, and non-current debt ratio. In our study, we defined debt maturity ratios i.e. current debt to total assets, non-current debt to total assets, and total debt to total assets.
1.1.2 Financial Performance
Financial performance has been defined by Metcalf and Titard (2016) as the achievement of financial objectives by an individual or a firm over a period of time. It measures the achievement in monetary terms. Financial performance defines how healthy a firm is financially.
Financial performance is a method of ascertaining impacts of company’s policies and the operations in a monetary language (Harelimana,2017). This shows the situation of an organization at a moment in time as presented in the balance sheet or it may show a series of actions over a stipulated time period as it is revealed by the statement of comprehensive income (Makanga, 2015). Financial performance is an indicator of the firm’s general financial condition in a stipulated time period and can also be employed to contrast related companies in the same business or to contrast sectors or businesses in aggregate (Harelimana, 2017).
According to Metcalf and Titard (2016), financial performance is based on financial elements that relate to a firm. Financial performance is described in financial statements prepared by a firm. The statements show the financial position for a certain period most probably a year. Financial performance also shows the financial activities that a firm has been undertaking over that period of time as it may be seen fir by the management and financial consultants.
Financialperformancegivesapropergaugeontheuseoffirms’resourcesformaximizationofwealthandprofits.Thefiscalfinancialfunctionsareconductedoccasionallyfromtheaccountsoffice,balancesheetsortheprofitandlossstatementsofthefirmssoastoevaluatethedegreeofsuccessinthebusiness(Obuya,2017).Financialperformanceisabiased gaugeofhoweffectivelyafirmcanmake goodexploitationofitsassetsfromitskeybusinessobjectiveconductandthesuccessiverevenuegeneration(Ikapel&Kajirwa,2017).
Financialperformancecanbemeasuredinmanydifferentways,butallthesewaysshouldbeaggregated.ThetraditionalaccountingKeyPerformanceIndicators(KPIs)thatincludeOperatingProfitmargin,Salesgrowth, Returnon Assets,EconomicValueAddedorEarningsbeforeInterestandTaxareoftenusedinthecalculationoffinancialperformance (Abshir &Nigib, 2016).To appraise a firm’s performance, business entities normallyapply financial ratios since they provide a simplified description of the entities current financial state in contrast to previous accounting period and they provides clues on how a firm’s management can improve performance (Tauseef, Lohano& Khan, 2013).
Ratios are used as a benchmark for evaluating financial performance of a firm and help to summarize large quantities of financial data and to make qualitative judgments about the firm’s performance. Measures of financial performance of a firm are return on equity and return on assets (Tharmila;Arulvel, 2013). However, the performance measure, ROA is widely regarded as the most useful measure to test firm’s performance (Long & Ravenscraft, 2014, Abdel Shahid, 2013), as a result, ROA will be applied to measure the firm’s performance of small and medium health centres in Nairobi.
1.1.1 Private small and medium health centres in Kenya
SMEs are very significant to the economic success for most countries and their citizens and in recent times have been observed to employ an increasing proportion of the workforce of most countries. There is a fast growth in the number of privately owned small and medium-sized companies worldwide; however, this category of business is plagued by several issues that deter this growth.
In Kenya, private health centres are small and medium-sized units which cater for a population of about 80,000 people and owned by private practitioners. Private health SMEs are individually owned and offer health services available in the government hospitals/health centres. The health centres offer maternal and basic health services like children prevention and cure. There are more than 5,000 private small and medium health centres in Kenya. Minor surgeries are also done in these health centres.
The network of health centres provides many of the ambulatory health services. Health centres generally offer preventive and curative services, mostly adapted to local needs. Private health care centres do not handle complicated cases but work hand in hand with referral hospitals to assist with such cases. The centres only offer basic health services like laboratory services and treatment of small health issues.
According to the licensing department of Nairobi City County there were one hundred and thirteen licensed private health centres in Nairobi County by December 2017 (Nairobi City County, 2017). Private health centres in Nairobi provide primary care and focus mainly on preventative care such as vaccinations. They tend to fall short when it comes to curative treatment.
Majority of the small and medium health centres in Kenya face financing problems.The availability of financing has been highlighted as a major factor in the development, growth and successfulness of SMEs in the health sector (Ou; Haynes, 2013; Cook, 2011). Debt financing has been identified as the main source of financing for small and medium health centres (He ; baker, 2012). A key challenge for most health centres is the problems of financing, according to Da Silva et al. (2010), all small firms live under tight liquidity constraints, therefore making finance a major problem for them.
1.2 Statement of the problem
Small and medium firms in the health sector face challenges in accessing debt as they cannot afford collateral and deal with sensitive services that make customer loyalty low. Despite the proliferation of many private health centres which fall under the category of small and medium enterprises, there have been minimal studies on theirfinancing. According to Coldren and Liu (2013), debt financing is crucial for financial deepening in SMEs. In Kenya, there has been repeated cases of private health centres that have closed due to financial challenges (Muchugia, 2013). Moreso, there are some which have been taken over by corresponding financiers due to the default in payment of debts to finance their operations (Oguna, 2014). There is no clarity on debt and financial performance of small and medium private health centres.
The effect of debt financing on financial performance has been researched globally. Baltac and Ayaydn (2014) established a negative correlation between debt and firm profit. Gungoraydinoglu and Öztekin (2011); and Kouki and Said (2012) established a positive correlation. These findings are inconclusive. Locally, Onsomu (2009) found no relationship between debt finance and firm value in his study on debt financing and firm value for listed firms in Kenya. A significant effect of debt finance on ROA but not ROE was found by Oguna (2014) in his study on capital structure and financial performance. Muchugia (2013) investigated the influence of debt financing on commercial banks’ profitability and found a positive correlation.
No studies have determined the effect of debt financing on the financial performance of private small and medium health centres. Most of the studies have concentrated on different sectoral enterprises hence leaving gaps on the health centre. Moreover, majority of the studies done have been conducted either in developed countries or in developing countries but the empirical analysis in Kenya is relatively scarce. The question is how does debt finance affect the financial performance of small and medium private health centres in Nairobi County?
1.3 Objective of the Study
1.3.1 General Objective
To determine the effects of debt financing on financial performance of small and medium private health centres in Nairobi County
1.3.2 Specific Objectives
To establish how long term debt affect the financial performance of small and medium private health centres in Nairobi
To assess how short term debt influence financial performance of small and medium private health centres in Nairobi
To establish the influence of medium term debt on financial performance of small and medium private health centres in Nairobi
1.4 Research Questions
How does long term debt affect financial performance of private health centres in Nairobi County, Kenya?
How does short term debt affect financial performance of private health centres in Nairobi County, Kenya?
To what extent does medium term debt affect financial performance of private health centres in Nairobi County, Kenya?
1.5 Significance of the Study
1.5.1 Policy Makers
Policy makers especially the government may benefit from this study in that it forms a basis for policy formulation on health debt financing to SMEs. Relevant policies may lead to improved financial performance through effective debt management and financing among health centres in Kenya.
1.5.2 Management of Health Centers
The findings may be beneficial to management of private health centres. The findings of this study would provide information on how debt financing may affect the financial performance of their firms. This would, enable them come up with strategies that would ensure improved financial performance of their health centres through debt financing.
SMEs may also benefit from the study. This is because they exist in the same economic sector which means that their financial performance may be affected by debt financing in their firms. This study would provide information on how debt financing may affect the financial performance of their firms.
1.5.4 Researchers and other Scholars
Other researchers and scholars may benefit from the study. This study may form a basis for further research. The findings of this report may provide literature for assignments by students.
1.7 Scope of the Study
The study seeks to determine the effect of debt financing on the financial performance of SMEs private health centres in Nairobi, Kenya. The study will be based on long term debt, short term debt and total debt and their effect on the financial performance. The target population will be53private health centres. The study will be carried out in Nairobi County. The study will run for the period between February 2018andOctober 2018.
The literature on debt financing and financial performance will be reviewed. The chapter will also give a critique to the literature and establish the empirical gaps that exist in the review. The variables will be conceptualized and operationalized in this chapter.
2.2 Theoretical review
2.2.1 Trade-off Theory
Trade-off Theory was developed by Myers in 1984. As indicated by Myers(1984)the vital inferences ofthistheoryarethatdebtshowsgoalmodificationssuchthatanydeviationsaregradually expelled. FrankandGoyal (2007)notedthat thereareinfactprosandconsofutilizingleverage.
ModiglianiandMiller (1963)suggest thattheimportanceofleveragefinancingdiminishes withan individual’s tax obligation on their earnings.TheTrade-offhypothesisexpressesthatthereareprosandconsofusingleverage,theprosbeingthetaxbreaksassociatedwithleverageandtheconsbeingthecostoffinancing,forexample,theexpensesofmoneyrelatedtroubleincorporatingliquidationcostsrelatedwiththeobligationandnon-liquidationcosts(e.g.disadvantageouspayoutdemandsbysellers,debtholder/investorclashes,andsoon).
Makanga(2015)notedthatforafirmtoachieveoptimizationinitsvalue,itshouldpayattentiononthistrade-offwhendeterminingthefinancingmixbetweendebtandequityasdebtincreasesthere’sadecreaseinthemarginalbenefitofadditionalincreasesindebt,whilethemarginalcostincreases.AccordingtoKrausandLitzenberger(1973),ascitedtobyFrankandGoyal(2007),amoreclassicalexplanationoftheTrade-offhypothesisisthatidealuseofdebtmirrorsasanexchangeoffbetweentaxgainofadebtandthedeadweightinsolvencyexpenses.AsperMyers(1984),forafirmtotakeintoconsiderationthetradeoffhypothesisitsetsanobjectivedebt-to-valueproportionandafterwardscontinuouslymovestowardsaccomplishingtheobjective.Theobjective isattainedbystrikingequilibriumbetweenthetax gainfromdebt andthedeadweightinsolvencyexpenses(Frank &Goyal,2007)
Asthetermtrade-offwouldmean,decisionmakersneedtoevaluatebetweentheprosand cons ofdebt and makechoicethat best suits thefirm. Debt would thereforehavebothgoodandbadeffectsonthefinancialperformanceoffirms.Trade-offtheorythereforepreludesthatafirmwouldconsiderdebtifthetaxbenefitishigherthanthecostsassociatedwithdebtfinancing.Thismaynotnecessarilybethecase.Researchesontrade-off theoryhowever,conclude mixed results.Titman andWessels(2008),RajanandZingales(2015),andFamaandFrench(2012)affirmthatorganizationswithhigherproductivityhaveatendencytoacquirelessleveragewhichisconflictingwiththetradeoffproposalthatbetterperformingfirmsoughttogetmoreleveragetolowertaxobligations.Graham(2010)whileassessingprosandconsofdebtobservedthattheconsiderablylargeorganizationswithminimalfinancialstrainexpectationsemployleveragemoderately.This theory will guide this study in understanding the tradeoff between gains from debt financing and the costs associated to the adoption of debt as a form of financing. This would in turn determine the financial performance of the private health centres in Nairobi.
2.2.2 Signalling and Liquidity Risk Theory
Signaling theory was developed by Spence in 1973. This theory postulates that signals on cash flows are sent by a firm using certain form of financing. The theory further states that the information received may deviate from the sent information which may affect the financial performance of a firm (Spence, 1973). A firm may send signals on information that they want to release to the outside world. This would guide the decisions of the business owners, investors, employees and customers who would base their decisions and perceptions on the firm (Spence, 1973).
Flannery (2016) notes that asymmetrical of data from the management to the investors can be avoided through debt maturity. Where the investors have no relevant information to analyse information in order to determine the firm that performs well, the high quality would issue short term debt other than long term or medium term debt. This is because they want to be underpriced to attract investors in the short run. On the other hand, low quality firms would over price their bonds by issuing long term debt. Flannery (2016) also states that firms issuing short term debt are highly monitored which makes high quality firms to issue more of short term debt compared to low quality firms.
Mitchell (2011) states that high quality firms would issue short term debt but low quality firms would issue long term and medium term debt due to transactional costs that come with short term debt. High quality firms which have a strong financial standing can issue short term debt as they can be able to cover the financial costs that come with rolling short term debt over (Jun & Jen, 2003). The assertion is supported by the empirical study of Guedes and Opler (2016).
According to Goswami and Rebello (2015) where the symmetry of the information received creates uncertainty in cash flows in the long run a firm issues long term and medium term debt. Short-term debt is issued where the information symmetry lies between long and short term debt. Contrary to the findings above, Lishenga (2013) finds little evidence that firms use the maturity structure of their debt to signal information to the market.The theory is relevant to the study in that it will help explain how private health centres in Nairobi would choose debt financing for improved financial performance. This may be based on the signals and the liquidity level of their firms which would in turn affect the financial performance of the private health centres.
2.2.3 Pecking Order Theory
In 1984 Myers and Majluf came up with this theory. Equity financing is preferred to debt according to this theory. The theory postulates that debt financing is used where internal financing is depleted or not enough to finance the operations of the firm. Information symmetry determines the optimal ratio of debt to equity. However, the firm maximizes financial; performance through debt.
The theory suggests that firms have a particular preference order for capital used to finance their business (Myers & Majluf, 1984). Owing to this information asymmetries between the firm and potential investors, the firm will prefer retained earnings to debt, short term debt over long-term debt and debt over equity.
Myers and Majluf (1984) argued that if firms issue no new security but only use its retained earnings to support the investment opportunities, the information asymmetry can be resolved. This implies that financing options becomes more expensive as information asymmetry between insiders and outsiders increases. Firms that have large information asymmetry should issue debts other than equity. The information symmetry in small and medium private health centres is important in the financing options available for them. This theory is relevant in that it will guide the study to creating an understanding on the kind of debt financing that would enhance the financial performance of the health centres.
2.3 Empirical review
2.3.1 Long term debt
Kaumbuthu (2011) carried out a study to determine the relationship between capital structure and return on equity for industrial and allied sectors in the Nairobi Securities Exchange during the period 2004 to 2008. Capital structure was proxied by debt equity ratio while performance focused on return on equity. The study applied regression analysis and found a negative relationship between debt equity ratio and ROE.
Ebaid (2016) did a study that investigated the impact of capital structure choice of firms in Egypt as one of the emerging or transition economies based on a sample of non-financial listed firms from 1997 to 2005. The methodology used was multiple regression analysis. The sample was 64 firms drawn from ten non-financial industries. The findings of the study revealed that there is a negatively significant influence of medium term debt on financial performance measured by return on assets but no significant relationship founded between long term debt and financial performance.
Mwangi et al. (2014) investigated capital structure and financial performance of listed firms in Kenya. The study was based on 42 non-financial firms in Kenya for the period between 2006 and 2012. Panel data from financial reports was used in the study based on an exploratory research design. Feasible Generalised Least Square (FGLS) regression was done. The study found that long term debt displayed a negative and statistical correlation with ROA and ROE.
Koskei (2017) examined the relation between financial performance and ratio of long-term debt in Kenyan sugar firms. A survey was done on 6 private sugar firms. The study was based on a descriptive research design. Data was corrected from annual reports of the firms and analysed using correlation and regression analysis. It was found that long term debt ratio has a positive correlation with financial performance of the sugar firms as measured by ROA.
2.3.2 Short term debt
Onchong’a, Muturi and Atambo (2016) examined the effects of leverage financing in financial performance of selected firms in the country. The study targeted a population of 60 firms with debt in their capital structure in Nairobi Security Exchange, and utilized secondary data from audited financial reports of these firms between periods of 2009-2012. Using regression analysis coefficient on the debt effects on return on as set the study revealed that a unit increase of short term debt reduces return on asset. However, the study found a unit increase in short term debt however will reduce the profit margin ratio.
Ahmad, Abdullar and Roslan (2012) analyzed the relationship between capital structure and firm performance of Malysian firms. Short term debt was found to have a significant relationship with ROA. It was also established that ROE had significant relationship with short-term debt, long-term debt and medium debt. An analysis on corporate cash flows was done by Teruel and Solane (2008) on SMEs in Spain. It was revealed that the SMEs with high debt in the short term had higer cash levels compared to those that held more of long term debt.
An insignificant negative correlation between short term debt and ROA was found by Makanga (2015) in his study on debt and ROA as a measure of financial performance of listed firms in Kenya. Quantitative data was used and analyzed through regression and correlation analysis using SPSS.
2.3.3 Medium Term Debt
Gabrijelcic, Herman and Lenarcic (2016) studied the impacts of financial debts and the foreign funding on a firms’ performance prior to and in times of the current crisis. The study used a large panel of firms in Slovenia. The study found a considerable negative effect of medium term debt on the firms’ performance.
Saad et al. (2015) studied the association between the source of funds via medium term leverage, and the performance of SMEs in Malaysia. The study sampled 177 Malaysian SMEs involving manufacturing and agriculture sectors. Using the ordinary least squares method, the study revealed that medium term debt financing has considerably positive connection with the performance of businesses which was insignificant.
Using a sample of 64non-financial listed firms from 1997 to 2005, Ebaid (2016) did an investigation on financial performance and debt financing of listed Egyptian firms. The methodology used was multiple regression analysis. The sample was 64 firms drawn from ten non-financial industries. A significant negative correlation was found between ROA and medium term debt. However, medium term debt displays an insignificant relation with ROE.
Firms in Jordan were studied by Soumadi and Hayajneh (2012) in order to establish how corporate performance correlates with the capital structure over a period of 5 years from 2007-2011. OLS regression was used to analyze the data. Medium term debt was found to have a statistically significant negative relationship with financial performance of the sampled firms.
2.4 Conceptual framework
The independent variables are long term debt, medium term debt and short term debt. The dependent variable is financial performance of small and medium private health centres in Nairobi. The variables are conceptualized in figure 2.1.
Independent Variables Dependent Variable
Figure 2.1: Conceptual Framework
2.5Operationalization of variables
Table 2.1: Operationalization of variables
Long term debt Long term debt to total assets ratio
Medium term debt Medium term debt to total assets ratio
Short term debt Short term debt to total assets ratio
Financial performance Return on Assets=net profit/total assets
The methodological approach adopted is given in this chapter. The research design, target population, sampling procedure, data collection and data analysis and presentation will be given in the chapter.
3.2 Research Design
A research design descriptive in nature will be used. It enables the researcher establish relationship between the variables of the study (Mugenda ; Mugenda, 2003). The design is deemed relevant in that the study is based on the debt financing and its relationship to the financial performance of small and medium private health centres in Nairobi County.
3.3 Target Population
Small and medium private health centres in Nairobi County operational between 1999 and 2017 will be targeted. According to the Nairobi County Council (2017), there are 53 small and medium private health centres in Nairobi County that have been operational between 1999 and 2017.
3.4 Sample and Sampling Procedure
The sampling describes the sampling unit, sampling frame, sampling procedures and the sample size for the study (Hill, 2009). Small and medium private health centres will serve as the unit of analysis. All the 53 private health centres that have been operational from 1999-2017 will be involved in the study. This sample is sufficient as Kothari (2004) recommends a sample of more than 30 units.
3.5 Data Collection Instruments
The study will be based on secondary data. The data will be collected through desk research where the data will be collected from the websites and publications of the SMEs. The data will be collected from the financial reports of small and medium private health centres in Nairobi County. The study will be based on annual data.
3.6 Data Analysis and Presentation
STATAsoftware version 13 will be used to analyze the data collected in the study.The data will be analyzed using descriptive statistics such as mean, standard deviation, percentages and frequencies. Inferential statistics through multiple regressions will also be used in data analysis. The regression equation will be;
Y = ?0 + ?1X1 + ?2X2 + ?3X3 +?
Y = Financial performance of health centres
X1 = Long term debt
X2 = Medium term debt
X3 = Short term debt
?1-?3 =Coefficients of determination
? =error term
3.7 Diagnostic test
The following diagnostic tests will be done.
3.7.1 Normality test
Normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable. It is assumed that data should be normally distributed in a linear regression. The error term shows the factors that should be considered in the study but have been assumed by the researcher in developing the model. In OLS there has to be a normal distribution of the error. Shapiro-Wilk test will be used in establishing the normality of data.
3.7.2 Hausman test
The Hausman Test will be done to detect endogenous regressors (predictor variables) in the regression model.Endogenous variables have values that are determined by other variables in the system. Having endogenous regressors in a model will cause ordinary least squares estimators to fail, as one of the assumptions of OLS is that there is no correlation between a predictor variable and the error term.In panel data analysis (the analysis of data over time), the Hausman test can help you to choose between fixed effects model and a random effects model. The null hypothesis is that the preferred model is random effects; the alternate hypothesis is that the model is fixed effects.
Autocorrelation is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them. Autocorrelation occurs mostly in time series data. The reason behind this is the fact that such data assumes a certain trend as the time changes. This means that successive observations are mostly likely to show inter-correlation. Autocorrelation does not affect the unbiasedness, linearity and asymptotic nature of the estimators. The only problem is a violation of the Best property of OLS, which will make conclusion hypothesis testing wrong. Breusch Godfrey test will be used to check on autocorrelation.
Multicollinearity is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from the others with a substantial degree of accuracy. Multicollinearity is usually a common problem where the researcher uses time series data. The variables increase or decrease over time. Multicollinearity makes the coefficient of regression to be indeterminate. Multicollinearity also makes the standard errors to be infinite. To check for the presence of multicollinearity, variance inflation factors (VIF) test will be used. VIF values below 10 will translate to no worries regarding multicollinearity problems while VIF values above 10 will detect problems regarding multicollinearity and which needs to be resolved.
Heteroscedasticity refers to the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. Heteroscedasticity does not cause bias or nonlinearity of regressing coefficients. Heteroscedasticity is very common in OLS. Breusch-Pagan test will be done for heteroscedasticity.
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Appendix I: Research budget
Item Amount (Kshs.)
Typing, Internet and printing 10,000
Data collection 30,000
Data Analysis 20,000
Appendix II: Work plan
1 2 3 4
Final defense and presentation of final report