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83 Seiten, Note: 3.89
Table of Contents
List of Acronyms And Abbreviations
List of Tables
List of Figures
1.1 Background of the Study
1.2. Statement of the Problem
1.3. Objectives of the Study
1.3.1 General objective
1.3.2 Specific objectives
1.4. Research Hypothesis
1.5. Significance of the Study
1.6. Scope of the Study
1.7 Limitation of the study
1.8. Organization of the study
REVIEW OF RELATED LITERATURES
2.1. Theoretical Overview of Microfinance
2.1.1. Definition of Microfinance
2.1.2. History of Microfinance
2.1.3. History of Microfinance in Ethiopia
2.1.4. Point of views in Performance Measures
2.1.5. Sustainability of Microfinance
2.1.6. Financial sustainability
2.1.7. Profitability Theory
2.1.8. Profitability of Retail Banking
2.1.9. The Concept of Profitability
2.1.10. Profit and Profitability
2.1.11. Market Power Theory
2.1.12. Efficient Structure Theory
2.1.13. Portfolio Theory
2.2. Determinants of Financial performance of MFIs: Empirical Review
2.2.1. MFIs-Specific Determinants (Internal)
2.2.2. Macroeconomic Variable (External Factor)
2.2.3. Industry–specific Determinants of MFIs (External Factor)
2.2.4. Ethiopian Scenario
2.3. Conceptual Framework
RESEARCH DESIGN AND METHODOLOGY
3.1. Research Design
3.2. Target Population
3.3. Sampling Technique and Sample size determination
3.4. Source of Data and Methods of Data Collection
3.5. Data Analysis and Technique
3.6 Checking validity and reliability
3.7 Ethical considerations
3.8. Variable definition
3.9. Model Specification
DATA ANALYSIS AND DISCUSSION
4.1. Descriptive Statistics of Variables
4.2. Correlation analysis
4.3. Tests for the Classical Linear Regression Model (CLRM) Assumptions
4.4. Findings of the Regression
4.5 Discussion of the Results
CONCLUSIONS AND RECOMMENDATIONS
Next to Almighty Allah the completion of this work cannot succeed without acknowledging the contributions made by some few special people who devoted their time, means and intellectual abilities to make this study fruit full. First I would like to sincerely thank my advisor Tolossa Negesse (Ass.Prof.) for his constructive comments, valuable suggestions and good guidance. I would also like to thank and acknowledge the contributions of Eastern Hararghe Zone credit bank (OCSSCO sub department) employees for their invaluable help, during data collection time, by providing me with all necessary financial data. Second I would like to thank Eskindir Amin (Lecturer in Haramaya University) his kind support and encouragement and I recognize my indebtedness to my employer that is Chinaksen Woreda Administration Office specially Abdunasir sh.Mohammed a positive thinker and owner of outstanding look. My sincere gratitude goes to my family, My Father Adem Mohammed and My Mother Fatuma Aman and my loved wife Fatiya Abba Salam for their good words of encouragement. I Love You Guys
Abbildung in dieser Leseprobe nicht enthalten
Table 3.1 Explanatory (Regressors) Description
Table 4.1.Descriptive statistics
Table 4.2.Correlation Matrix
Table4.3. Multicollinearity test
Figure: 1 conceptual frameworks
Figure 2 Normality Test for Residuals .
Figure 3: Regression Results for factors affecting financial performance of OCSSCO.
Microfinance promises to reduce poverty. To achieve this amazing objective Microfinance institutions have to become strong enough in financial performance because donor constancy is not a given. Thus the question is: In what extent the OCCSCO -specific, industry-specific (MFI) and macroeconomic factors that determine OCCSCO’s financial performance from the period 2013-2017,By using OLS estimation method to measure the effect of internal and external factors that affect financial performance in terms of return on asset. The researcher used SPSS 20.0 version to analyze the data that was obtained from secondary sources. The study was based on a five years secondary data obtained from AEMFI Financial performance analysis report and MOFEC economic forum report for10 selected OCCSCO in Eastern Hararghe branch. Beside this the study used primary data analysis to solicit managers, accountants and customer service officers perception towards factors affecting financial performance of Oromia credit and saving share company in Eastern Hararghe Branch. Regarding the explanatory variables, operational efficiency, GDP and size which affect OCCSCO financial performance significantly. The outcome of the study shows that Age of microfinance institutions has a positive but statistically insignificant effect on their financial performance. The other explanatory variables which is Portfolio at risk>30, Gearing ratio, capital to asset ratio and Market concentration affect negatively and not significant. The Oromia regional state MFIs policy makers and managers should give high concern to the credit risk management, expense management and large MFIs size management and also the government and policy makers should work combining both poverty reduction and financial self- sufficiency of OCCSCO.
Key words: financial performance, Micro finance institution, industry specific and macroeconomic factor
Throughout the world, poor people are not benefited from formal financial systems. According to Brau and Woller (2004) exclusion ranges from partial exclusion in developed countries to full or nearly full exclusion in lesser developed countries. In the past decade, financial authorities in most developing and transitional economies have given more emphasis on bringing formal financial services to the large numbers of the world’s poor who currently lack adequate access or excluded from formal financial service (CGAP, 2012). Most of the poor population and small enterprises in Sub-Saharan Africa countries have very limited chance to access deposit and credit facilities and other financial services provided by formal financial institutions (Basu et al, 2004). Lack of access to credit is a major obstacle to growth in the continent, where a large majority of households do not have enough collateral to secure a loan (Muriu, 2011).
According to Iswatia, & Anshoria (2013) performance is the function of the ability of an organization to gain and manage the resources in different ways to develop competitive advantage. Financial performance emphasizes on variables related directly to financial report. The Capital market plays a critical role in the economy by facilitating mobilization and allocation of capital resources to finance long term productive investments. In this way, it facilitates and promotes the process of economic growth in the country.
Microfinance institutions are found among the institutions which provide different financial services for the poor who are out of the conventional banking system particularly in developing countries. Microfinance Institutions (MFIs) provide financial services to poor clients who in most cases have no access to formal financial institutions. During the last three decades, microfinance has captured the interest of both academics and policy makers. This is, among other things, due to the success of the industry (Esubalew et al., 2013).
Performance is the result of the fulfillment of the tasks assigned. Company performance describes how individuals in the company try to achieve a goal. Company performance illustrates the magnitude of the results in a process that has been achieved compared with the company’s goal. Company’s performance is evaluated in three dimensions. The first dimension is company’s productivity, or processing inputs into outputs efficiently. The second is profitability dimension, or the level of which company’s earnings are bigger than its costs. The third dimension is market premium, or the level of which company’s market value is exceeding its book value financial performance plays an important role in the company performance that is expressed in monetary term. Before investing their funds, investors should first know about the performance of the company. The simplest way to determine the performance of the company is to look at the company’s financial statement (Wellage etal, 2012).
Profitability is a suitable mechanism for achieving long term viability and sustainability of the microfinance industry. At the micro level, profitability is a precondition to a competitive microfinance industry and the cheapest source of capital, without which no firm would draw external capital. MFIs profits are also an important source of equity, if profits are reinvested and this may promote financial stability. Moreover, market sources of funding are accessible only to MFIs that have established for to turn a profit. By minimizing the probability of financial crisis, remarkable profits are vital in reassuring MFIs stakeholders, including investors, borrowers, suppliers and regulators. At the macro level, a profitable microfinance industry is better placed to overcome negative shocks and contribute meaningfully to the stability of the overall financial system (Muriu, 2011).
According to the information obtained from AEMFI, (2015), currently there are about 35MFIs which are licensed and offering microfinance services. Since2015, 35MFIs registered with the National Bank of Ethiopia, have been serving 2.5 million borrowers with a portfolio of Birr 7.1 Billion mirroring their ever growing importance in the economy.
Oromia Credit and Saving Share Company is one of the microfinance institutions which were established in Oromia regional state in 2007. Oromia credit and saving share company founders were Oromia self help organization (OSHO), DINSHO, and Oromia regional state, and it gave the service in 29 districts from 180 districts in early beginning. But now a day the branches of this institute reached 305 in number and it has been given service in all 20 zones and two city administrations in Oromia regional state(AEMFI, 2013).
Microfinance can be seen as either from a business point of view or as a tool for development (Jorgeson, 2011). The objective of this study is to study microfinance institutions from a business view since its observed that an increasing number of institutions have become interested in becoming profitable. The industry is changing and profitability for the individual institution is vital for survival in the long run. Therefore, the objective of the study was to indentify factors that actually affect financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch.
Financial performance in this study was conceptualized in terms of profitability only.
The very rational behind for the emergency of MFIs was to help poor people who are financial constrained and vulnerable, with financial services to enable them to engage in productive activities or start small businesses as stated in Consultative Group to Assist the Poor (CGAP, 2009). MFIs provide financial services to low-income, economically active, borrowers who look for relatively small amounts to finance their businesses, manage emergencies, acquire assets, or smooth consumption. But it is common that Borrowers might lack credit histories, collateral, or both, and thus, do not have access to financing from mainstream commercial banks. For this reason, MFIs are seen as playing a role in the creation of economic opportunity, and in poverty alleviation (CGAP, 2009).
Profitability is an appropriate device for achieving long term viability and profitability of the microfinance industry. At the micro level, profitability is a precondition to a competitive microfinance industry and the cheapest source of capital, without which no firm would attract external capital. MFIs profits are also an important source of equity, if profits are reinvested As MFIs have the objective to give financial service to the poor, financial performance effectiveness is necessary to reach large number of poor and to provide adequate financial service in sustainable fashion. To achieve their prime objective which is alleviating poverty, MFIs should be able to perform effectively in their profitability. While a large body of research on financial institutions financial performance has been undertaken in the conventional banking industry in Ethiopia For instance Berhanu, (2012); Belayneh, (2011); Habtamu, (2012); Gemechu, (2013) rigorous empirical evidence on microfinance remains limited, largely due to lack of reliable data. Moreover, it is rare or uncommon such study has been conducted with regard to identification and assessment of factors that affect financial performance in Eastern Hararghe, Oromia regional state where the majority of MFIs are not well developed or small. The studies conducted in the areas of microfinance institutions in Oromia regional state are few in number and did not give such an emphasis on the factors affecting financial performance of Oromia credit and saving Share Company in East Hararghe branch.
Regarding MFI performance in Ethiopia different researches have been conducted. To mention some of them; assess the financial performance and challenges of MFI Ebsa et. al, (2012); Tilahun and Dereje (2012) conducted a research on the topic the financial performance and sustainability of microfinance institutions during the current financial crisis: The case of Amhara Credit and Saving Institution (ACSI) in Ethiopia. The objective of the research is to assess the financial performance and sustainability of Ethiopian MFIs during the current financial crisis with particular reference to Amhara Credit and Saving Institution (ACSI), the largest MFI in the country. The study employed a descriptive research design. For data analysis, descriptive statistics such as percentages and graph are used. However, this study has focused only selected issues such as the Legal frame work of micro-finance institutions, Licensing of micro-financing business, Operational and financial requirements, Structure of ownership of micro-finance institutions, The Financial performance of Microfinance Institutions and Challenges of the Micro Financing Industry, where financial performance of MFIs on this study focuses mainly on identifying factors that affect financial performance of Oromia credit and saving share company.
Alemeyhu (2008) studied the financial and operational performance of micro finance institutions by using simple descriptive analysis and employing graphs and percentage growth rates by classifying small, medium and large. The study did not say anything about factors affecting financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch. The study by Yonas, (2012) and Melkamu, (2012) tried to see the determinants of performance by using proxy of financial and operational sustainability of Ethiopian MFIs. They focused only on internal factors and have not considered external factors like macroeconomic and industry and also they have not addressed specifically the idea of financial performance of OCSSCO.
In addition Sima, (2013) studied determinants of profitability of Ethiopian micro finance by using microfinance specific and macroeconomic factors from secondary data only. Therefore, the above studies use limited variables which focus in MFI-specific and macroeconomic factors only and not say anything about industry specific factors in their study.
Ebsa. et.al (2012) conducted on the assessment of financial performance and challenges of MFIs and the financial performance assessment part covers few areas of indicators mainly of breadth of Outreach: number of clients and the amount of loan grant to borrowers. However, other financial performance indicators such as profitability, sustainability, efficiency, and Portfolio quality capital structure and asset allocation were not get attention. Since it is believed that MFIs must be profitable for their healthy operation and attainment of the long term goal which is alleviation of poverty, this study was find out the MFIs specific, macroeconomic and industry-specific factors affecting their financial performance by including primary data and fills the gap in the context of Eastern Hararghe OCSSCO branch.
The general objective of this study is to identify factors affecting financial performance of Oromia credit and saving Share Company.
The specific objectives include:
- To identify and assess the effect of Industry-specific (internal) factors on financial performance of OCSSCO in Eastern Hararghe branch.
- To identify and examine the effects of external or macroeconomic factors on financial performance of OCSSCO in Eastern Hararghe branch.
- To identify and assess how MFI- Industry specific factors (external) influence financial performance of OCSSCO in Eastern Hararghe branch.
In order to achieve the objectives of the study, a number of hypotheses were tested regarding factors affecting financial performance of Oromia Credit and Saving Share Company based on different empirical research and theoretical review made from banks. The reason is that there is rare theory developed in relation to MFIs financial performance. There are eight hypotheses which are included:
Hypothesis 1: capital Asset ratio is positively related with financial performance of OCSSCO in Eastern Hararghe Branch.
Hypothesis 2: Age is positively related with financial performance of OCCSCO in Eastern Hararghe Branch.
Hypothesis 3: Operational efficiency is negatively related with financial performance of OCSSCO in Eastern Hararghe Branch.
Hypothesis 4: Portfolio quality is negatively related with financial performance of OCSSCO in Eastern Hararghe Branch.
Hypothesis 5: size of OCSSCO is positively related with financial performance of OCSSCO in Eastern Hararghe branch.
Hypothesis 6: Gearing ratio is negatively related with the financial performance of OCCSCO in Eastern Hararghe Branch.
Hypothesis 7: Real GDP is positively related with the financial performance of OCCSCO in Eastern Hararghe Branch.
Hypothesis 8: Market concentration is positively related with financial performance Of OCSSCO in Eastern Hararghe Branch.
Although there have been numerous studies on Financial performance of MFIs in other countries where MFIs are relatively large and well developed compared to MFIs in Ethiopia; it is uncommon to find such studies in sufficient number in Eastern Hararghe zone. This study, as an attempt to identify factors affecting financial performance of Oromia credit and saving share company the case of Eastern Hararghe branch, provides evidence on what effect the firm-specific factors, industry-specific factors and the general macroeconomic factors have on the OCSSCO financial performance in Eastern Hararghe Branch by analyzing and understanding the impact of different factors on the financial performance of Oromia Credit and Saving Share Company in Eastern Hararghe Branch is a major stepping stone to enlighten what should be done if financial performance is to be achieved. The findings of the study will also be of benefits to donors, managers and others interested in the MFIs study for it will show the level of financial performance of the OCSSCO operating in the region have reached. This in turn helps them knowing factors affecting financial performance and thereby takes appropriate actions to increase financial performance of Oromia credit and saving share company and the study will also initiate other MFIs service providers to give due attention on the management of identified variables. It is hoped that the outcome of this study will also provide an insight of the MFIs industry to other researchers.
This study was confine only to know the key factors affecting financial performance of Oromia Credit and Saving Share Company in Eastern Hararghe branch by analyzing the financial statements starting from 2013 to 2017 fiscal year. Since the 2013th annual performance report that is published by AEMFI was included the recent data. Profitability was used as a measure of performance. With regard to the variables the research is limited to 8 variables only. In relation to support the secondary data analysis collecting the perception of Headquarters managers of OCSSCO was intended but accessing those key informants was difficult.
For this study purposes, the following are major limitations. These are:
This thesis was limited to financial performance of Oromia credit and saving Share Company in Eastern Hararghe Branch. Lack of awareness among respondents to fill out the questionnaire with due care and not returning the filled questionnaire on time affect the study. Insufficiency of the secondary data about MFIs may affect the study.
This thesis research has been organized in to the following chapters. Chapter one including introduction, statement of the problem, objectives, hypotheses to be tested in the study, significance, scope and limitation, and Chapter two consists of literature review both theories and empirical studies, and chapter three Research Methodology, chapter four data analysis and discussion and lastly chapter five: conclusions and recommendations.
Under this chapter the theoretical and empirical evidences focusing on the Factors affecting financial performance of Oromia credit and saving Share Company are presented. Accordingly, the first section, describes overall theoretical overview of micro finance concepts. The second section presents review of empirical studies on the internal and external factors affecting Oromia credit and saving share company financial performance.
The theoretical framework was, through a review of existing literature within the microfinance field, serve as a platform for the forthcoming empirical study.
Different authors and organizations have defined Microfinance institutions in different ways. However the concept or the meaning of the definitions is usually the same in which microfinance refers to the provision of financial services; primarily savings and credit to the poor and low income households that don’t have access to commercial banks service.
Consultative Group to Assist the poor (CGAP,2012) defined “microfinance” the provision of formal financial services to poor and low-income people, as well as others systematically not benefited from the financial system. As noted, “Microfinance” it is not only providing a range of credit products (for consumption, smoothing for business purposes, to fund social obligations, for emergencies, etc.) only, but also savings, money transfers, and insurance.
The other researcher defined about MFIs is that, it offers financial services to poor people. The aim of Access to financial services for poor people is help to alleviate risks, build their assets, improve their income, and furthermore contribute to development of the focal community (Cull et al, 2009). The popularly known institution which is Microfinance information exchange (MIX) defined the microfinance institutions as a variety of financial services that target low-income clients, particularly women. Since the clients of microfinance institutions have lower incomes or poor and often have limited access to other financial services, microfinance products tend to be for smaller monetary amounts than traditional financial services. These services not only provide micro credit service for those have lower incomes but also include loans, savings, insurance, and remittances. Micro-loans are given for a variety of purposes, frequently for micro-enterprise development. The diversity of products and services offered shows the reality that the financial needs of individuals, households and enterprises can change significantly over time, especially for those who live in poverty, which is not benefited from the formal bank. Because of these varied needs, and because of the industry's focus on the poor, microfinance institutions often use non-traditional methodologies, such as group lending or other forms of collateral not employed by the formal financial sector especially by bank.
According to Robinson, (2001) definition: Microfinance refers to small-scale financial services-primarily credit and savings-given to people who involved in farm or fish or herd; who work in small enterprises or microenterprises where goods are produced, recycled, repaired, or sold; who provide services; who work for wages or commissions; who gain income from renting out small amounts of land, vehicles, draft animals, or machinery and tools; and to other individuals and groups at the local levels of developing countries, both rural and urban (Robinson, 2001 p.9). Ethiopian Proclamation No. 626/2009 defines micro financing business as "the provision of financial services like accepting savings extend credit, drawing and accepting drafts payable, providing money transfer services and others specified in the Article 3(2) of the proclamation.
The ideas and aspirations towards microfinance are not new. Small, informal savings and credit groups have worked for centuries across the world, from Ghana to Mexico to India and beyond (Helms, 2006). In Europe, as early as the 15th century, the Catholic Church founded pawn shops as an alternative to usurious moneylenders. These pawn shops spread throughout the urban areas in Europe throughout the 15th century. Formal credit and savings institutions for the poor have also been around for generations, offering financial services for customers who were traditionally neglected by commercial banks. The Irish Loan Fund system, started in the early 1700s, is an early (and long-lived) example. By the 1840s, this system had about 300 funds throughout Ireland (Helms, 2006). On the other hand in the early 1800s a financial organization that was credit association to serve predominantly farmers in rural areas based on cooperative principles was founded by Friedrich Wilhelm Raiffeisen in Germany and expanded rapidly within Germany and later since it was successful also to the rest of Europe, North America and developing countries beyond.
Ledgerwood (1999) described the focus of these cooperative financial institutions as savings mobilization in rural areas that attempt to teach poor farmers how to save money and utilize it. In the early 1900s the concept of Raiffeisen began to appear with adaptations in parts of rural Latin America (Helms, 2006). Another milestone in the history of microfinance was the opening of the Indonesian People’s Credit Bank in 1895 that became the largest microfinance system in Indonesia (Helms, 2006).
In Bangladesh Professor Muhammad Yunus who was the Nobel Prize winner in 2006, disbursed first loans from his own pocket to a group of rural women in Jobra in 1976 and successfully developed the concept of microfinance with his Grameen Bank throughout the country and later the whole world (Ledgerwood, 1999).The Grameen bank, which is now serves more than 2.4 million clients (94 % of them women) and is a model for many countries. Other examples of early pioneers besides Grameen Bank are ACCION International in Latin America, Self-employed Women’s Association Bank in India and many more (Helms, 2006).
Beginning in the mid-1980s, the subsidized, targeted credit model supported by many donors was the object of steady criticism, because most programs accumulated large loan losses and required frequent recapitalization to continue operating. It became more and more evident that market-based solutions were required. This led to a new approach that considered microfinance as an integral part of the overall financial system. Emphasis shifted from the rapid disbursement of subsidized loans to target populations toward the building up of local, sustainable institutions to serve the poor. In the early 1990s the term “microcredit” was replaced by “microfinance” which included not only credits but also other financial services for poor people (Elia, M. 2006). The introduction of the term microfinance followed the success of many microcredit programmes around the world and in 1997, during the first Microcredit Summit, 2,900 delegates from 137 countries representing around 1,500 organizations gathered in Washington, D.C. During that occasion the birth of the global industry of microfinance was officially recognized. Since then the focus started to change and move from the predominant welfarist idea, where only the provision of credit was considered to be important, to the need of becoming financially sustainable through the provision of a complete range of financial products and to reach more people.
Initially, micro-credit started as a government and non-government organizations motivated plan. Following the 1984/85 severe drought and famine, many NGOs started to offer micro credit along with their relief activities although this was on a limited scale and not in a sustained manner (Alemeyhu, 2008) although the development of deposit-taking MFIs started only in 1996, the industry has shown outstanding growth. Since 1996, NBE has registered 30 MFIs to deliver financial services to the poor. As of 2008, these MFIs had an active loan portfolio of about ETB 4.5 billion delivered to 2.3 million active borrowers and 3 million total active clients. They also mobilized savings of about ETB 1.9 billion (USD 144 million). The average size of loans in 2006 was about USD 170, which indicates that MFIs target the active poor and also do a significant amount of their business (54 percent) with women. Despite their strong growth, MFIs provide less than seven percent of the total national loan portfolio, again with government-owned MFIs playing the major role (Wolday et al, 2010).
The various perspective on which the MFI performance is to be measured has created two contrasting but having the same goals school of thought about the MFI industry: the Welfarist approach and the Institutionist approach.
The Institutionist: According to the Institutionist school of thought financial deepening is the main aim of microfinance. That is, the setting up of a separate system of “sustainable” financial intermediation for the poor who are either neglected or are underserved by the formal financial system. The activists of this school of thought give emphasis to more on the achievement of financial self-sufficiency, breadth of outreach (numbers of clients), depth of outreach (levels of poverty reached) and positive client impact. The interest of the approach is that the institutions abstain from all kinds of subsidies as they insist on financial self-sufficiency (Nelson, 2011). The institutionists focus and believe that in order to effectively fight the problem of poverty, it is necessary to build a microfinance industry as a system in which able to reach a large number of people. In order to reach a large number of people a huge amount of financial resources should be contributed from MFIs them-self instead of donors provide is necessary. The institutionists start from the basic and obvious assumption that donors cannot subsidize enough MFIs to let them provide financial services to all of the potential microfinance clients. They also believe that the only way to overcome this constraint is to attract private sources of capital and this in turn requires MFIs to be sustainable and profitable (Elia, M. 2006). According to this point sustainable financial institutions that provide financial services to the poor are necessary if the main goal is a substantial poverty reduction.
The emphasis not on depth of outreach (level of poverty of clients) rather must be put on breadth of outreach (number of clients reached). If the system is not able to increase the number of clients reached, it would fail the target of poverty reduction. Furthermore, institutionists believe and focus that if the approach of building sustainable MFIs is used the poorest will also benefit from it, while the other way around of targeting the poorest with highly subsidized programs will have a low overall impact due to the limited and unstable donor funding. The institutionist’s position has clearly obtained success within the microfinance community (Elia, M. 2006).
The Welfarist School: self-employment of the poorer of the economically active poor, especially women is their main objective. Their interest depends in the “family” and they give more emphasis on the depth of outreach (the levels of poverty reached). They are more concerned with the use of financial services to minimize the effects of acute poverty among individual participants as well as communities. The focus of this school of thought is on the unexpected improvement in the well-being of participants. Though there are significant lines of differences between the two schools of thought, they have some similarities as well. In as much as the two approaches seek to solve the problem of financial needs of the poor, microfinance activities should aim at achieving the objectives of the two approaches (Nelson, 2011). The welfarist approach focuses on depth (number of clients reached) rather than breadth of outreach (poverty level of clients) and accept subsidies on an ongoing basis. Welfarists accept subsidies as they believe and focus that if sustainability is considered as a necessary requirement, the accomplishment of the social mission of microfinance is at risk. The center of attention is now the clients that are served rather than the institution or developing self sustained industry and also the welfarist accept the subsidies or required subsidies on ongoing basis and this school not just focuses on financial self-sufficiency as a necessary tool (Elia, M. 2006).
According to Letenah, (2009) Sustainability defined as the ability of a MFI to cover its operating and other costs from generated revenue and provide for profit. It is an indicator which shows how the MFI can run independent (free) of subsidies. This change in emphasis has created a different perspective on the analysis of performance of the MFIs. Guntz, (2010) point out that Sustainability in simple terms refers to the long-term continuation of the microfinance programme after the project activities have been terminated. It entails that appropriate systems and processes have been put in place that will enable the Microfinance services to be available on a continuous basis and the clients continue to benefit from these services in a routine manner or in the day to day activities. This also would mean that the programme would meet the needs of the members through resources raised on their own strength, either from among themselves or from external sources.
As the concept of microfinance came into focus, the question of whether donor support is necessary in the long term existence and the issue of sustainability of such institutions came up as well. It could be argued that the long term sustainability of MFIs is not important as long as money was given to micro entrepreneurs and a start up help was given. This would imply that sustainability of the micro enterprises is more important than the long term existence of the financial institution that stood behind the start up. As MFIs seek to reach as many poor people as possible in the long run to fulfill their goal to fight against the worldwide poverty, it became clear that this outreach is only possible on a sustainable and efficient basis. Some antagonist of this argument state that sustainability is not possible by reaching the poorest people on the planet (Guntz, 2010).
Financial sustainability indicates the ability of an MFI to survive in the long- run by means of its own income generating activity, i.e. without any contributions from donors (AEMFI, 2013). As per the MIX Market definition the term financial sustainability is defined as having an operational sustainability level of 110% or more, while Operational sustainability is defined as having an operational self-sufficiency level of 100% or more. Financial sustainability refers that the ability of a microfinance provider to cover all of its costs on an unsubsidized basis or without accepting donation. According to the United Nations sustainability is necessary to reach a larger number of people on an ongoing basis (Elia, M.2006). If MFIs remain dependent on limited donor funding they will be able to reach only a limited number of people. Financial sustainability is not an end in itself but is the only way to reach significant scale. To analyze the sustainability of an MFI the two known a set of ratios have been developed. These are widely accepted and they enable a comparison among MFIs all over the world. These two most important ratios are Operational Self Sufficiency (OSS) and Financial Self -Sufficiency (FSS).
Operational Self-Sufficiency (OSS) (%) = Operating income divided by Operating expenses. The above formula indicates or measures the degree to which operating income covers operating expenses. If the calculated figure is greater than 100%, the organization under evaluation is considered to be operationally self-sufficient. In microfinance, operationally sustainable institutions are able to cover their costs through operating revenues.
On the other hand financial self-sufficiency (FSS) % =Adjusted operating income divided by Adjusted operating expenses This also indicates the degree to which operating income covers adjusted operating expense. The adjustments try to show how the financial picture of the MFI would look on an unsubsidized basis or free from donation. Financial self-sufficiency requires adjustments for different reasons. Financial statements must be adjusted to conform to standard accounting practices, to take into account inflation and to remove the effect of subsidies and in-kind donations. FSS shows how an MFI would look if funds had been raised on a commercial basis and if services or equipment had been purchased at a market rate and were not received as a donation (Elia, M.2006). Operational self-sustainability is when the operating income is sufficient enough to cover operational costs like salaries, supplies, loan losses, and other administrative costs. And financial self-sustainability (which referred as high standard measure) is when MFIs can also cover the costs of funds and other forms of subsidies received when they are valued at market prices( Meyer, 2002).
Not all MFIs are become sustainable, able to return a profit, or even to break even and therefore still depend on help from donors and subsidies. The rapid growth in the industry is not due to a golden “one-way-road” to profitability since there is still big diversity or difference between the MFI‟s and their operations (Joergeson, 2011). This section explains the theory of banking practices that lead to profitability for MFIs.
There are large differences between banks, financial institutions or intermediaries especially the clients they serve. Retail banking is, however, the banking practice closest to microfinance institutions and is therefore interesting to look into when it comes to profitability. Conventional retail banks borrow from people who have surplus of money and lend to those people who have in deficit. The bank thereby makes money on the interest spread between the two, called the net interest income. In the retail bank around half to three-quarters of the income generated or come from this intermediation role. The rest of the revenue comes from a number of other services such as insurance, money transmission, advisory services, investment and taxation services, card and factoring services etc. These all service amount together represent the non-interest income for the retail banks. One of the key and great factors of success for conventional retail banks is getting enough customers. This is likewise considered as a key factor for MFI’s, but for different reasons, which depend on the purpose of the individual MFI’s, whether they are social or economical goals (Jorgensen, 2011).
It is obvious that the objective of conventional retail banks is to make a profit. A bank that own twice as big as a competitor will expect to make around twice as much profit. Profits are therefore in proportion to their size (total asset), though with some advantages from scale economies Since the microfinance industry is not as developed as the conventional banking industry, it is not expected that profit is in proportion to size (total asset), and also because the institutions motive and their products vary much more from each other than those of retail banks. Retail banking sector use investors to provide capital to get started and to keep running and in return the investors receive equity in the business, thus owning a part of the company. The company’s profit and the investors return on equity (ROE) are closely correlated. Retail bank shareholder would like the highest possible ROE, ten percent being below average, fifteen percent the standard, and 20 percent excellent. When we look MFIs only some MFIs have investors, yet this could be an interesting benchmark when looking at ROE for MFIs (Joergeson, 2011). Retail banks do however has to take on some risk, with the result of losing some money. If they lose too little they will have no customers because they will be excluding a major part of the population which they could lend to, but loose too much, and the bank will go bankrupt under this condition. MFIs operate or perform under a very different approach, where they take bigger risks, but MFIs find ways to compensate for this risk the MFIs charge larger interest rates to the borrower and with the innovative methods such as joint liability. This new approach opens up a much larger market segment than seem before seen in banking (Joergeson, 2011).
Profitability means ability to make profit from all the business activities of an organization, company, firm, or an enterprise. It shows how efficiently the management can make profit by using all the resources available in the market. The term Profitability however is not synonymous or the same meaning to the term ‘’Efficiency‟. Profitability is a measure of efficiency; and is regarded as a measure of efficiency and management guide to greater efficiency. Though, profitability is an important yardstick for measuring the efficiency, the degree of profitability cannot be taken as a final proof or indicator of efficiency. Sometimes satisfactory profits can mark inefficiency and conversely, a proper degree of efficiency can be accompanied by an absence of profit. The net profit figure simply indicates that a satisfactory balance between the values receive and value given. The change in operational efficiency is merely one of the factors on which profitability of an enterprise largely depends. Moreover, there are many other factors besides efficiency, which affect the profitability (Harward & Upton, 1961).
Sometimes, the people used the term “Profit” and “Profitability” interchangeably. But in real sense, there is a difference between the two. Profit is an absolute term, whereas, the profitability is a relative concept or meaning. However, they are closely related and mutually interdependent, having distinct roles in business. Profit refers to the total income earned by the firm during the specified period of time, while profitability refers to the operating efficiency of the firm. It is the ability of the firm to make profit on sales. It is the ability of firm to get sufficient return on the capital and employees used in the business operation (Harward & Upton, 1961). According to Weston and Brigham, (1972) rightly notes “to the financial management profit is the test of efficiency and a measure of control, to the owners a measure of the worth of their investment, to the creditors the margin of safety, to the government a measure of taxable capacity and a basis of legislative action and to the country profit is an index of economic progress, national income generated and the rise in the standard of living”, while profitability is an outcome of profit. In other words, no profit drives towards profitability (Weston and Brigham, 1972).
According to Al-Shami, (2008) there are different ways to measure profitability such as: return on asset (ROA), return on equity (ROE). Return on Asset indicates of how profitable a company is relative to its total assets. It gives us an idea as to how efficient management is in using its assets to generate earnings. On the other hand return on equity measures a company’s profitability which shows how much profit a company generates with the money shareholders have invested. This measure gives a sense of how well a company is in using its money to generate returns.
Applied in banking the Market Power hypothesis posits that the performance of bank is influenced by the market structure of the industry. There are two distinct approaches within the Market power theory; the Structure-Conduct-Performance (SCP) and the Relative Market Power hypothesis (RMP). According to the Structure-conduct-power approach, the level of concentration in the banking market gives rise to potential market power by banks, which may raise their profitability (Njerl, 2012). Banks in more concentrated markets are most likely to make abnormal profits by their ability to lower deposits rates and to charge higher loan rates as a results of collusive (explicit or tacit) or monopolistic reasons, than firms operating in less concentrated markets, irrespective of their efficiency. Unlike the Structure-conduct-power, the Relative market power hypothesis posits that bank profitability is influenced by market share. It supposes that only large banks with differentiated products can influence prices and increase profits. They are able to exercise market power and earn non-competitive profits. The above theoretical analysis shows that Market power theory supposes bank profitability is a function of external market factors (Njerl, 2012).
According to the efficient structure hypothesis, on the other hand posits that banks earn high profits because they are more efficient than others. There are also two distinct approaches within the Efficient Structure; the X-efficiency and Scale–efficiency hypothesis. According to the X-efficiency approach, more efficient firms are more profitable because of their lower costs. Such firms inclined to gain larger market shares, which may manifest in higher levels on market concentration, but without any causal relationship from concentration to profitability (Athanasoglou et al, 2006 cited in Njerl, 2012). The scale approach emphasizes economies of scale rather than differences management or production technology. Larger firms can gain lower unit cost and higher profits through economies of scale. This make possible to large firms to acquire market shares, which may manifest in higher concentration and then profitability. The ES like the Portfolio theory largely assume that bank performance is influenced by internal efficiencies and managerial decisions (Njerl, 2012).
The portfolio theory approach is the most important and plays a great role in bank performance studies. As per the Portfolio balance model of asset diversification, the best possible holding of each asset in a wealth holder’s portfolio is a function of policy decisions determined by a number of factors such as the vector of rates of return on all assets held in the portfolio, a vector of risks associated with the ownership of each financial assets and the size of the portfolio ((Njerl, 2012). The portfolio theory further explained as portfolio diversification and the desired portfolio composition of commercial banks are results of decisions taken by the bank management. Further, the ability to obtain maximum profits depends on the feasible set of assets and liabilities determined by the management and the unit costs incurred by the bank for producing each component of assets. Portfolio theory largely supposes that bank performance is influenced by internal efficiencies and managerial decisions (Njerl, 2012).
MFIs financial performance could be affected by a number of determining factors. In most literatures MFIs profitability usually expressed as a function of internal and external determinants. Muriu,( 2011) also point out that the determinants of MFIs profitability can be divided into two main categories namely the internal determinants which are management controllable and the external determinants, which are beyond the control of management. Empirical literatures in relations to determinants of MFIs financial performance are very limited. The previous studies done in the area highly depended upon theory of retail banking financial performance by assuming that MFIs also provide banking service to the poor. The following paragraphs present the empirical studies in connection with factors affecting of MFIs financial performance. Now let us see the first classification of MFIs financial performance determinant.
The internal determinants of MFIs financial performance are those management controllable factors which account for the inter-firm differences in profitability, given the external environment.
A. Portfolio Quality
Portfolio indicates to total funds available for the MFI to use as loans to its clients. Portfolio quality is a measure of how well or how best the institution is able to protect this portfolio against all forms of risks. The loan portfolio is by far an MFI‟s largest asset (Nelson, 2011) and, in addition, the quality of that asset and therefore, the risk it poses for the institution can be quite difficult to measure. Portfolio quality is a critical area of performance analysis, since the largest source of risk for any financial institution resides in its loan portfolio. For microfinance institutions, whose loans are typically not backed by bankable collateral, the quality of the portfolio is absolutely crucial (American Development Bank, 2003 cited in AEMFI, 2013) Portfolio quality is a vital area of analysis, since it is the largest source of risk for any financial institution. Therefore, as much as possible, MFI‟s must try to maintain the quality of their portfolios. For this study, portfolio quality is measured as portfolio at risk over 30 days (PAR >30 days).
According to Muriu, (2011) empirical study on determinants of profitability of African MFIs, under the study “what explains the low profitability of MFIs in Africa” tried to find the factors contributing to profitability of MFIs. He used Generalized Method of Moments (GMM) system using an unbalanced panel dataset comprising of 210 MFIs across 32 countries operating from 1997 to 2008. The proxies for profitability were both ROA and ROE. Credit risk measured by the sum of the level of loans past due 30 days or more (PAR>30) and still accruing interest is negatively and significantly related to MFI profitability. This study therefore finds evidence to support the conjecture that increased exposure to credit risk is normally associated with lower MFI profitability. The other study which is undertaken by Lafourcade et al, (2006) Overview of the Outreach and Financial Performance of Microfinance Institutions in Africa by taking 163 MFIs from 25 countries show that MFIs around the world continue to demonstrate low PAR > 30 days, with a global average of 5.2 percent but African MFIs maintain relatively high portfolio quality, with an average PAR > 30 days of 4.0 percent, performing better than their counterparts in South Asia (5.1 percent), LAC (5.6 percent), and East Asia (5.9 percent). When MFIs are faced with poor portfolio quality, they may write off the loans from their books or refinance the loans by extending the term, changing the payment schedule, or both. The result shows that loan at risk is negatively correlated with MFIs financial performance.
B. Capital asset Ratio
The capital to assets ratio is a simple measure of the solvency of MFIs. This ratio helps an MFI assess its ability to meet its obligations and absorb unexpected loss. The determination of an acceptable capital to asset ratio level is generally based on a MFIs assessment of its expected losses as well as its financial strength and ability to absorb such losses. Expected losses should generally be covered through provisioning by the MFI‟s accounting policies, which removes expected losses from both assets and equity. Thus, the ratio measures the amount of capital required to cover additional unexpected losses to ensure that the MFI is well capitalized for potential shocks.
As a proxy for the MFIs capital, this study used the ratio of equity to assets. MFI with higher capital to asset ratios are considered relatively safer compared to institutions with lower ratios. Given that MFI with low capital ratios are also riskier in comparison with better capitalized financial institutions. According to retail banking research which is done by Dietrich and Wanzried, (2009) what determines the Profitability of Commercial Banks? New Evidence from Switzerland. The study try to explain determinants of bank profitability by classifying in to Bank specific, macroeconomic and institutionalized factors and use unbalanced panel data from 1999 to 2006 from 453 banks and use linear regression method. The study conclude that the capital ratio, which is defined as equity over total assets, has a positive and significant effect on bank profitability in Switzerland as measured by the return on average assets ROA. Similar study in the banking sector by Vong and Chan, (2010) Determinants of Bank profitability in Macacao, which covers the data set 15-year period from 1993 to 2007, with a sample of five different banks which account for about 75% of the total asset and the same percentage of loans in the banking sector as at the end of 2007. In this study, the performance of a bank is measured by its return on assets (ROA).The ROA, defined as net income divided by total assets, and reflects how well a bank’s management is in using the bank’s real investment resources to generate profits. Panel regression techniques are used to analyze the internal determinants as well as the external determinants and generalized least squares (GLS) estimation technique. And the result shows that Capital asset ratio has significant impact on bank profitability meaning the positive coefficient estimate for the ratio of equity to total assets (EQTA) indicates an efficient management of banks‟ capital structure.
According to Muriu, (2011) study that is determinants of profitability of MFIs, Based on a panel data set of 210 microfinance institutions Muriu conclude that capital adequacy has robust and significant positive association with MFI profitability. This is depicted by the relatively high coefficient of the equity to assets ratio across the specifications this effect remains so even after the inclusion of the external factors. Intuitively, this is an indication that well capitalized MFIs are more flexible in dealing with problems arising from unexpected losses and are confronted with a reduced cost of funding or lower external funding.
C. Operational Efficiency
Operational Efficiency is performance measure that shows how well MFIs is streamlining its operations and takes in to account the cost of the input and/or the price of output. Efficiency in expense management should ensure a more effective use of MFIs loan able resources, which may enhance MFIs profitability. Higher ratios of operating expenses to gross loan portfolio show a less efficient management. Operational efficiency in managing the operating expenses is another dimension for management quality. The performance of management is often expressed qualitatively through subjective evaluation of management systems, organizational discipline, control systems, quality of staff, and others (Ongore and Gemechu, 2013) According to the study Nimal Sanderatne, 2003 cited by Dissanayake, (2012) a study on determinants of financial viability, defined that the operational efficiency and low administration costs have an important bearing. Besides, a study on financial performances, the study declared that, many MFIs are not considered sustainable. By stating the fact, the researcher confirmed that the operational efficiency is inevitable to attract funds.
Dissanayake (2012), Operating efficiency is proxies by operating expense ratio which is adjusted operating expense divided by adjusted average gross loan portfolio and concludes that Operating Expense Ratio, are statistically significant predictor variables in determining Return on Assets Ratio. In line with this idea Muriu, (2011) conclude that inefficiency in the management of operating expenses to significantly decrease MFI profitability.
D. Gearing Ratio / Debt to Equity Ratio
The debt to equity ratio is calculated by dividing total liability by total equity. Total debt includes everything the MFI owes to others, including deposits, borrowings, account payable and other liability accounts. The debt/equity ratio is the simplest and best-known measure of capital adequacy because it measures the overall leverage of the MFIs (AEMFI, 2012). The debt to equity ratio is a common measure used to assess a firm’s leverage, or in other words the extent to which it relies on debt as a source of financing (Lislevand, 2012). Microfinance institutions that employ higher debt in their capital structure are more profitable, and highly leveraged microfinance institutions are more profitable, (Muriu, 2011). Besides, a higher debt ratio can enhance the rate of return on equity capital during good economic times (Muriu, 2011). Moreover, it also appears that NGO type of microfinance institutions rely more on debt financing relative to other type of microfinance institutions, perhaps because many are not regulated to mobilize deposits. The significant correlation between performance and gearing ratio is an indication that perhaps more debt relative to equity is used to finance microfinance activities and that long term borrowings impact positively on profitability by accelerating MFIs growth than it would have been without debt financing (Muriu, 2011).
According to Nelson, (2011) study entitled that performance of assessment of micro finance institution in the Ashaiman municipality, its result show that the Rural Bank recorded debt/equity ratio of 50.89 in 2007 but increased to 54.05 in 2008. It increased further to 61.65 in 2009 and to 77.35 in 2010 showing an average of 60.99%;Depicting that most of its operations are financed by debt instruments and, should probably be regulated. The Savings and Loans recorded a rapid increase from 0.30 in 2007 to 0.8 in 2008. It again increased sharply to 2.97 in 2009 and to 4.89 in 2010 with an average of 2.24. The sharp increment may signify that Savings and Loans of approaching its borrowing limit which in turn will force it to curtail growth. The Credit Union’s debt/equity decreased throughout the study period from 0.89 to 0.61 to 0.45 to 0.77 respectively. Implying that, more equity is used to finance business than debt. It indicates what proportion of equity and debt the company is using to finance its assets. This is very much connected to where the MFI is located in its life cycle. Traditionally, the funding structure follows a certain pattern over the life cycle of an MFI. Start ups are characterized by a larger dependency on donations, usually in the form of equity grants, whereas the more mature MFI‟s tend to display higher debt leverage through borrowing and even evolve into a formal institution or a regulated niche bank. Some MFI’s even access capital markets by issuing bonds or by going public (IPO) (Jorgensen, 2011). Dissanayake, (2012) point out that debt/equity is a statistically insignificant predictor variable for the model at 5% level of significance. Besides the expected direction of the coefficient of the corresponding models are not as per the predicted direction of the researcher.
E. Size of Microfinance (Total Asset)
Another factor that can affect the financial performance of an MFI is its size. The size of an MFI is measured by the value of its assets (Hermes et al, 2008). According to Cull et al, (2007) the size of an MFI is significantly positively linked to its financial performance. This variable is included to capture the economies or diseconomies of scale. There is consensus in academic literature that economies of scale and synergies arise up to a certain level of size. Beyond that level, financial organizations become too complex to manage and diseconomies of scale arise. The effect of size could therefore be nonlinear (Amdemikael, 2012). Natural logarithm of total asset of MFIs is used as a proxy of size. The study observed that since the dependent variable in the model (ROA) can be deflated by total assets it would be appropriate to log total assets before including it in the model.
It is argued that failure to become profitable in microfinance is partly due to lack of scale economies Muriu, (2011) this implies that profitable MFIs in Africa have a greater 30 control of the domestic market, and therefore lending rates may remain high while deposit rates remain lower since larger MFIs may be perceived to be safer, therefore this high interest rate spread translates to and sustains higher profits margins. Cull et al, (2007) point out that size of MFIs and financial performance has significantly related but loan size is negatively related financial performance meaning Controlling for other relevant factors, institutions that make smaller loans are not necessarily less profitable. But the result find that larger loan sizes are associated with lower average costs for both individual-based lenders and solidarity group lenders. Since larger loan size is often taken to imply less outreach to the poor, the result could have negative implications.
F. Age of Micro finance institutions
There is a thought that as MFIs mature, and thus acquire experience in their sector; they increase their likelihood of attaining financial sustainability. This can be explained by the fact that MFIs gradually improve their control over all operations related to issuance of microcredit. In other case, MFIs that have considerable experience in the microfinance sector have diligently applied credit risk management and general efficient management techniques to attain financial sustainability (Ayayi, 2010). According to Cull et al, (2007) Sustainability could relate to the age of MFI. The age refers to the period that an MFI has been in operation since its initial inception. Studies indicate that the MFIs age relates to the financial performance. Jorgensen, (2011) states that Age, is grouping by new (1 to 4 years), young (5-8 years) or mature (more than 8 years). The number of years is calculated as the difference between the year they started their microfinance operations and the year of data submitted by the institutions. Therefore the result shows that Age (new) this dummy variable is significant with a positive sign. Implies that if MFI is new its ROA is 0.03642 higher than the ROA of mature MFIs, it is no longer maturity and experience that provides profitability as in many industries. This indicates that new MFIs entering the industry have different set of goals and operational set of skills leading to profitability.
The study undertaken by Dietich and wanzenried (2009) in the banking industry, that is determinants of profitability in commercial bank show that, larger banks are slightly less profitable than medium sized banks, with the coefficients being significant at the 10% level. This gives some indication that larger banks cannot benefit from higher product and loan diversification possibilities and even face scale inefficiencies.
A. Real GDP: The study used real GDP growth as a proxy of the macroeconomic environment. Arguably, this is the most informative single indicator of progress in economic development. Poor economic conditions can worsen the quality of the loan portfolio, thereby reducing profitability. In contrast, an improvement in economic conditions has positive effect on the profitability of MFIs, (Muriu, 2011). Thus, the variable is expected to exhibit positive relationship with MFIs profitability. According to the study undertaken by Imal et al., (2012) working paper entitled financial performance of microfinance institutions a macroeconomic and institutional perspective drawing up on the Microfinance information exchange data and cross-country data on macro economy, finance and institutions and use hausman-taylor to take account of endogeneity and they found GDP have positive impact on MFIs financial performance.
A. Market Concentration: there are different definitions and measurements for market concentration which is given by different banking area researchers Berhanu, (2012) it is the number, size and distribution of banks in a particular market or country. As indicated in other empirical studies market concentration is captured by Herfindahl-Hirschman (H-H) index which is the sum of the square of market share of the sample banks included in particular study. Market share of each bank is measured by the ratio of a bank’s total asset to total asset of all banks (Gajure and Pradhan, 2012).
Since highly concentrated market lacks proper competition as to setting the price of banking services, it makes the existing banks more profitable. On the other hand, when the concentration of the market reduced and the size and distribution of banks become more dispersed, the banking sector profitability is expected to reduce. According to Flamini, (2009) study determinants of profitability commercial bank in sub-sharan Africa and conclude that market concentration has no direct effect on bank profitability. Athanasoglou et al, (2005) the empirical results show that market concentration affects bank profitability negatively, but this effect is relatively insignificant. In other hand Molyneux and Thornton, (1992) in their study that is determinants of European bank profitability conclude Market Concentration shows a positive, statistically significant correlation with pre-tax return on assets which is consistent with the traditional structure conduct- performance paradigm.
The quality literatures on the Ethiopian MFIs industry financial performance are not as such available. However the study by Alemeyhu, (2008) on which have accessed to, is worth mentioning. He studied the performance of micro finance institution in Ethiopia by taking six MFIs using simple descriptive analysis using graphs and percentage growth rates. The result shows that Most MFIs are strong performers on return on asset. In connection with liquidity, most MFIs lack strong position to effect immediate obligations. Large MFIs are more efficient and productive than small and medium ones. But small MFIs seem to reach the poorest section of the society. Finally, the trend in performance of microfinance institutions during those years of operation was encouraging.
The study by Kidane, (2007) on one of the largest MFIs in Ethiopia Amhara Credit and Saving Institution (ACSI) shows that ACSI has served more than half a million clients. Over 1.6 million loans have been disbursed worth Birr 1.5 billion. By 2005, the institution was operationally and financially self sufficient at 119.9% and 115.3%respectively. ACSI is among a few MFIs that are able to achieve the highest efficiency at the lowest cost per borrower. The operating cost was as low as five cents in 2005.ACSI also has a high portfolio quality, as delinquency rates are around 1.9%.
Melkamu, (2012) Determinants of Operational and Financial Self-Sufficiency: he uses quantitative research approach using panel data regression as the main data analysis technique. The study was based on a six years secondary data obtained from the mix-market database for twelve selected MFI in Ethiopia. The study found that average loan balance per borrower, size of a MFI, cost per borrowers and yield on gross loan portfolio affects the operational sustainability of Ethiopian MFIs significantly. Whereas cost per borrower, number of active borrowers and yield on gross loan portfolio affect their financial sustainability. The Study also found that MFIs in Ethiopia are operationally self-sufficient while they are not financially self sufficient. Yonas, (2012) on his study regarding determinants of financial sustainability of Ethiopian MFIs, using 6 years data for 12 MFIs from AEMFI; he concluded three things. First, a high quality credit portfolio, coupled with the application of sufficiently high interest rates that allow a reasonable profit and sound management are instrumental to the financial sustainability of MFIs. Second, the percentage of women among the clientele has a weak statistically non-significant negative effect on financial sustainability of MFIs and finally, client outreach of microfinance programs and the age of MFIs have a positive but lesser impact on attainment of financial sustainability.
Sima, (2013) on his study examined internal and external factors affecting profitability of microfinance institutions in Ethiopia by including a total of thirteen microfinance institutions covering the period of 2003-2010. The researcher uses quantitative research mainly documentary analysis. The outcome of the study indicates that Age of microfinance institutions has a positive and statistically significant effect on their profitability. However, Operational efficiency and portfolio quality have a negative and statistically significant effect. However, capital adequacy, size and GDP are found to be statistically insignificant variables. The studies conducted in the areas of microfinance institutions in Ethiopia are few in number and did not give such an emphasis on the factors considered to be factors affecting financial performance of OCSSCO in Eastern Hararghe Branch. For example, Alemeyhu, (2008) studied the financial and operational performance of micro finance institutions by using simple descriptive analysis and employing graphs and percentage growth rates by classifying small, medium and large. The study did not say anything about factors affecting financial performance of OCSSCO in Eastern Hararghe Branch. The study by Yonas, (2012) and Melkamu, (2012) tried to see the determinants of performance by using proxy of financial and operational sustainability of Ethiopian MFIs. They focused only on internal factors and have not considered external factors like macroeconomic and industry and also they have not addressed specifically the idea of financial performance of OCSSCO. In addition Sima, (2013) studied determinants of profitability of Ethiopian micro finance by using Microfinance specific and macroeconomic factors from Secondary data. Therefore the above studies use limited variables which focus in MFI-specific and macroeconomic factors only and not say anything about industry specific determinants in their study. Since it is believed that MFIs must be profitable for their healthy operation and attainment of the long term goal which is alleviation of poverty, the study will find out the MFIs specific, macroeconomic and industry-specific factors affecting their financial performance by including primary data and fill the gap in the context of Oromia Credit and Saving Share Company.
Different empirical evidences suggested that financial performance of financial institutions specifically MFIs is affected by internal and external factors. This study used both internal and external factors affecting affecting of OCSSCO financial performance includes capital Asset ratio, operational Efficiency, portfolio quality, Gearing ratio, size, age, level of GDP. The study was identify how these variables are determined the financial performance of Oromia Credit and Saving Share Company in Eastern Hararghe Branch.
Figure: 1 conceptual frameworks
Abbildung in dieser Leseprobe nicht enthalten
Source: developed by self design, and partially adopted from Ongore, (2014)
This chapter sets to explain the research design and methodology, target population, sampling technique and sample size, methods of data collection, data analysis and techniques and also operational definition and model specifications were presented.
This study with the aims of identifying factors affecting financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch was used the explanatory research approach by using panel research design to realize stated objectives. According to Gujarati, (2004) using Panel or longitudinal research design has advantage for instance: The techniques of panel data estimation can take heterogeneity explicitly into account by allowing for individual-specific variables, By combining time series and cross-section observations, panel data give “more informative data, more variability, less Collinearity among variables, more degrees of freedom and more efficiency” By studying the repeated cross section of observations, panel data are better suited to study the dynamics of change, panel data can better detect and measure effects that simply cannot be observed in pure cross-section or pure time series data, by making data available for several thousand units, panel data can minimize the bias that might result if we aggregate individuals or firms into broad aggregates.
The study was employed explanatory approach as the literature on research methodology shows explanatory research approach tends to assume that there is a cause and effect relationship between known variables of interest. In line with this, quantitative research tests the theoretically established relationship between variables using sample data with the intention of statistically generalizing for the population under investigation. Therefore Ordinary least square (OLS) method particularly multiple regression models were used to identify the significant factors affecting financial performance of OCSSCO in Eastern Hararghe branch. To measure the financial performance of OCSSCO, ROA were applied as the dependent variables because the Microfinance Financial Reporting Standards recommends the use of ROA and ROE as measures of profitability rather than financial self-sufficiency (FSS) and operational self-sufficiency (OSS) (Muriu, 2011).
The population for this particular study was all Oromia Credit and Saving Share Company currently operating in Eastern Hararghe branch. According to AEMFI, (2013), there were 23 Credit and Saving Share Company which were providing a microfinance service to the society in Eastern Hararghe on the current period.
A sample of a subject is taken from the total population to make inference about the population because it is time consuming and expensive to collect data about every individual institutions in the population. However, where the selected sample can reliably represent the population, the sample can still be use to make inferences about the population (Collis and Hossey, 2003cited in Yonas, 2012). There were 23 OCSSCO sub branches in Eastern Hararghe Zone. This study has used a sample of 10(44% of the total population) Oromia credit and saving share company sub branches which are Haramaya Branch,Awwaday Brach,Diredawa Branch, Harar Branch,cinaksan Branch, Jarso Branch, Babile Branch ,Celenko Branch, Gursum Branch and Kersa Branch from the total of 23 sub branches in Eastern Hararghe Zone. The criteria for choosing among the OCSSCO’s sub branches were based on the availability and quality of data for the time period of 5 years (2013-2017).
There were 10 managers, 10 Accountants and 10 Customer service officers which totals 30 respondents whose work is more related with financial activities in the company currently operating in Eastern Hararghe branch. Since the numbers of the respondents whose work is related with finance are small, the researcher used all the respondents to fill the questionnaire. In this case, the researcher used a census. If population size is 100 or less, then include the whole population rather than taking a sample (Taylor, 2004).Therefore, based on the sample size and the time coverage, the sample consists of 50 observations.
In order to carry out any research activity; information should be gathered from proper sources. The sources of data for this research was almost secondary sources, but for the purpose of supporting the finding of the research, primary data used to some extent. Primary data were collected by soliciting the branch managers, Accountants and customer service officers of each OCSSCO included in the study through structured survey questionnaire by using census method. The secondary data which were used to analyze OCSSCO –specific variables were collected from AEMFI annual report and to analyze external-specific variables were collected from MoFEC with documentary survey.
The data collected from primary sources first assessed for their quality, reliability and accuracy using bench marks selected. After the researcher satisfied him selves on the quality of data collected the data will be tabulated, arranged and analyzed. The collected data regressed by panel least square method and interpret with the help of descriptive statistics including standard deviation, mean, minimum, maximum and inferential statistics which is multiple regression analysis (significant test).
The analysis of the data collected from financial statement followed number of basic statistical techniques. Descriptive statistics (mean and standard deviation) and inferential Statistics (Pearson correlation and multiple-regression function) were used to analyze data. Pearson correlation will be used to ascertain the interrelationship between the variables, whereas multiple-regression was used to assess the extent of the effect of the independent variables on the dependent variable. To conduct this, the researcher was used SPSS 20.0 version software package to analyze the data.
It is important to check the reliability and validity of the instrument that has been used. Triangulation technique has been used to improve the validity and reliability of research or evaluation findings. Patton (2001) and Matheson (1988), advocate the use of triangulation by that triangulation strength a study by combining methods. This can be attained by using several kinds of methods or data including both qualitative and quantitative approaches. By selecting complement methods, the researcher will able to offset the weakness of one method with strength of another.
To test the reliability of the questionnaires, Cronbach’s Alpha was employed. To proceed to the next step, the value of Cronbach’s Alpha (α) must be at least 0.7. George and Mallery (2003) provided more detailed categories of reliability values as i.e., (α>0.9 “Excellent”, α>0.8 “Good”, α>0.7 “Acceptable”, α>0.6 “Questionable”, α>0.5 “Poor”, while α<0.5 “Unacceptable”). To test the reliability of the instruments, 10 questionnaires were distributed to some clients of Oromia credit and saving Share Company which will not be part of the sample in the final study. After running the data using SPSS version 20.0, it was found that all the measures possess more than acceptable reliability standard ranging from 0.713 up to 0.807. Consequently, given the established benchmark of 0.70, all the constructs are reliable and therefore, there was no need to delete any item from any variable.
The other aspects of this are data quality control or assurance strategy.
Data quality control/quality assurance
The researcher was employed some measures to control the quality of the data. These included the following:-
This is where the data collection materials’ are tested and or piloted and refined. This was taken in to consideration the language spoken and understood by the respondents.
The researcher was carried out the research with the assistance of two research assistants/data collectors that were trained to assist the researcher with the collection of data especially using the structured questionnaires. They trained on how to administer the questionnaire guide and how to record any other useful information they would come across in the field.
According to leedy et al (2005), there are a number of key ethical issues that protect the rights of research respondts. These are protection from harm, informed consent, the right to privacy and honesty with professional colleagues. The principle of informed consent requires that respondents not to be forced to participate in a research. This means that prospective research respondents’ must be fully informed about the procedures and risks involved in research and must give their consent to participate. In this study all respondents will be informed about the nature of the study and participation will be based on voluntary basis. Ethical standards also require that researcher not put respondents in a situation where they might be at risk or harm as a result of their participation. Harm can be defined as both physical and psychological.
In this study the researcher was followed two standards in order to protect the privacy of the research respondents. First participants assured that their responses will be treated confidentiality and with anonymity of the respondents. Second, no person or firm will have access to their completed questionnaire. In addition to this, the researcher will report the findings complete and honest without any change in the respondents’ response to support personal interests.
In general, the following ethical principles have been adopted for this study from the works of (terell, 2012) by the researcher and are adhered throughout the course of this study.
- Respondents are not forced or influenced to participate without their consent.
- Respondents were be briefed about the purpose and procedures of the study.
- Respondents were informed about their rights of claiming the final copy of the results.
- The researcher considered the impact of his presence at research sites (i.e. office/work area) and will take due care so as to ensure that these sites are left undistributed at the end of the study.
- The researcher maintained anonymity during data analysis and data will be kept for a reasonable period of time.
- Finally, the details of the study were carefully explained within the actual report so as to allow readers the opportunity to judge the ethical quality of the study for themselves.
This section explains the variables used as dependent and independent (explanatory) variables in this study. The definitions/measurements used for these variables are described and summarized under the following table.
A. Dependent Variable
Return on Asset (ROA) measures how well the institution uses all its assets. It is also an overall measure of profitability which reflects both the profit margin and the efficiency of the institutions (AEMFI, 2013). Return on Asset (ROA) was applied as the dependent variables because the Microfinance Financial Reporting Standards recommends the use of ROA and ROE as measures of profitability rather than financial self-sufficiency (FSS) and operational self-sufficiency (OSS) (Muriu, 2011). ROA may be biased due to off balance-sheet items; It can however be argued that such activities may be negligible in MFIs. The ROA reflects the ability of MFI‟s management to generate profits from the MFI‟s assets. It shows the profits earned per birr of assets and indicates how effectively the MFIs assets are managed to generate revenues. In Banks and other commercial institutions, the most common measure of profitability is return on asset (ROA) for instance (Abate, 2012), (Sima, 2013). According to Yonas, (2012) which is done in the banking sector profitability, using return on equity has its own limitation than using return on asset. Among the limitation the study point out that, timing problem (it is believed that Managers should be forward looking but ROE is precisely the opposite: Because they focused on a single period. The risk period, ROE will not tell a company or a firm about what risks a company has taken to generate it. The Value period ROE measures the return on shareholders’‟ investment only by using Book Value of shareholders equity not the market value. Therefore based on the above rationality this study was used ROA as the proxy for financial performance.
Return on Asset = Net Profit After tax/Average Total Assets.
B. Independent Variable
To measure the predictor variables of financial performance of MFIs in Ethiopia, Eight measures were used as independent variables which were extracted from different studies. The variables namely, age, capital asset ratio, operational efficiency, portfolio quality, gearing ratio or debt to equity ratio, size, and GDP and market concentration.
Table 3.1 Explanatory (Regressors) Description
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This section covers the operational panel fixed regression model (multiple regression model) that was used in the study. The multiple regression model used for this study to identify the factors affecting the financial performance of Oromia credit and saving Share Company in Eastern Hararghe Branch is explained as follows. The model is adopted from different studies conducted on the same area.
ROAit = βoi + β1*CAPit + β2 *EFFit + β3 *PAR it +β4 *GRit +β5 *AGE it +β6 *SIZE it +β7 *GDPit +β8*CONSit+ μit
β1 to β8 are the coefficients of the variables and μit is the random error term.
Βoi; stands for the intercept term which varies across MFIs but constant over time
CAPit: stands for Capital asset ratio for MFI i at time t
EFFit: stands for operational efficiency for MFI i at time t
PAR it: stand for portfolio quality for MFI i at time t
GRit: gearing ratio or debt/equity ratio for MFI i at time t
AGE it: stands for age of micro finance for MFI i at time t
SIZE it: stands for size of micro finance for MFI i at time t
GDPit: stands for growth domestic product of the country
CONSit: stands for market concentration for MFI i at time t
This chapter deals with the results of study which include descriptive statistics of variables, correlation results for dependent and explanatory variables, model misspecification tests (tests for the Classical Linear Regression Model assumptions), and finally presentation of panel data regression analysis and discussion of results.
In this section the study present the results based on the descriptive statistics for both dependent variable, the Return On Asset ( ROA), and independent variables discussed in chapter three over 5 years. Table 4.1 provides a summary of the descriptive statistics of the dependent and independent variables. As discussed in the methodology part, the Return on Asset (ROA) indicates or measures how well the institution uses all its assets. It is also an overall measure of profitability which reflects both the profit margin and the efficiency of the institutions. The table below shows descriptive statistics for all variables. The financial performance of Oromia credit and saving share company, Eastern Hararghe Branch which is measured by Return on Asset for 50 observations indicates that averagely Positive value of 0.0820 during the study period of (2013-2017). In addition to this the Maximum value of ROA 0.141 and minimum value of -0.109. This shows that the OCSSCO included in the sample in the study period was gain on average 0.0820 cents in every one birr investment they made on total asset and the profitable OCSSCO earned 0.14 cent of profit after tax for a single birr investment they made on total asset. On the contrary, not profitable OCSSCO lost 0.109 cents for one birr investment made on total assets of the firm. This clearly illustrates the disparity of rates of return earned by OCSSCO.
Regarding the variable Par>30, the higher its value, the riskier the credit portfolio, which can have a negative influence on the financial performance of the OCSSCO. For this study case, the mean of the par is 3.04% and the maximum is 7.8% and minimum is 0 % respectively. According to AEMFI, (2013) any portfolio at risk (par > 30 days) exceeding 10 % should be a serious cause for concern; because unlike loans of commercial banks, most loans are not backed by bankable collateral. Therefore, the result of study shows during the study period, the loan portfolio portion of the portfolio in arrears or unpaid is 3.04 % averagely that is good and the maximum 7.8 % result implies that the credit portfolio of some OCSSCO in the sample is fairly risky.
In relation to the Capital to asset ratio variable the mean is 41 % and maximum value shows 88.6 %. This result indicates that above the minimum requirement which is set by CGAP, micro finance institutions should be subject to even higher adequacy capital to asset ratio to safeguard their portfolio and advises to maintain ratios approaching 20% AEMFI, (2013). The capital asset ratio mean value results suggest that about 40 % of the total assets of the Eastern Hararghe OCSSCO were financed by shareholders funds while the remaining 59% was financed by deposit liabilities.
In regard to gearing ratio or Debt to equity ratio implies that the average value of 2.46 and maximum value of 9.90 and 0.13 minimum value. Meaning as per the mean value of this variable (2.46) indicates, OCSSCOs are leveraged on average than financed through equity capital because the AEMFI’s suggested standard of debt to equity is 1.5. On the other side the minimum gearing ratio (debt to equity) is 0.13 indicating few OCSSCOs are financed more through equity capital than debt. However, the maximum value for this variable is 9.90 which indicate that debt financing is more considered instead of having proportional financing structure, therefore highly leveraged. The Standard deviation of gearing ratio is 2.4 this clearly illustrates the disparity of gearing ratio by OCSSCO in Eastern hararghe branch.
According to AEMFI, (2013) report Ethiopian micro finance institutions on average debt to equity ratio was able to maintained 1.5 of their equity. Therefore the result of the study shows the value higher than the minimum requirement. On the other hand, the average operating efficiency of Oromia Credit and Saving Share Company of eastern hararghe branch was 8.86% indicating that on average they are incurring 0.0886 cents in operating expense for each birr in the gross loan portfolio. Some highly efficient institutions incur operating expense of 0.01 cent for each birr in the gross loan portfolio. On the other hand, inefficient institutions in the industry incur an operating expense of 0.42 cents for each birr on their gross loan portfolio. The standard deviation showed 9.10% implying the large variation in terms of operational efficiency (operating expense management). Here, the result indicated that the most efficient Oromia credit and saving share company have a low operating expense ratio.
The MFIs size plays an important role to maintain the position of a MFI in the market. The mean value of the variable is 8.43 in its natural logarithm value, whereas the maximum and minimum values are 9.52 and 6.57 respectively. These values are in their log form and when they are transformed into their real values they become 347,031,021, 3,279,192,202 and 2,479,546 for the mean, maximum and minimum values respectively. The size of OCSSCO under this study has mean value of 8.43 and the maximum and minimum value of 9.52 and 6.57 respectively. But the standard deviation value is 0.75 which is the fourth highest value among independent variables and indicating higher disparity of size (total asset) in OCSSCO in Eastern Hararghe Zone.
Finally, the descriptive statistics of the Herfindahl – Hirschman index shows that there is high concentration of OCSSCO in the MFI industry in Eastern Hararghe Branch that is average market concentration has 0.26 and maximum 0.29 and also minimum score of 0.23. According to H-H index when H-H index value is below 0.01 indicates that highly competitive market, when the value is below 0.1 shows that unconcentrated market, when the value is between 0.1 to 0.18 indicates that moderate market concentration and when H-H index above 0.18 indicates that high market concentration (Gajure and Pradhan,2012). Therefore the results indicate the existence of high market concentration in the market. This is practically visible in Oromia credit and saving Share Company in Eastern Hararghe Branch.
Table 4.1.Descriptive statistics
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Source: Survey output, (2019)
Multiple correlations are a measure of the degree of association between dependent and all the independent (explanatory variables) jointly (Gujarati, 2004). The analysis was meant to first, indicate whether variables were correlated or not. If variables are not correlated then using several simple regressions or one multiple regression models could give the same results (Dougherty 2006 as cited Yonas, 2012). The main aim of conducting correlation is whether Multicollinearity is strong enough to invalidate the simultaneous inclusion of the explanatory variables in regressions. According to Gujarati, (2004) Multicollinearity could only be a problem if the pair-wise correlation coefficient among repressors is above 0.80 and according to Hailer et al, 2006 cited in Berhanu, (2012) Multicollinearity could only be a problem if the pair wise correlation coefficient among repressors is above 0.90 which is not more or less in the case of this study variables.
By taking a correlation result which is presented below from 2013 up to 2017 the study period the independent variables to dependent variable which is the Return to asset ratio (ROA), except GR and AGE, which are positively correlated to return to asset ratio of OCSSCO Eastern hararghe branch, implies the change in these explanatory variables positively contributes towards the change in return to asset ratio of Oromia credit and saving Share Company, other variables have negatively correlated with ROA, implies that when PAR, SIZE, CONS, EFE, GDP and SIZE increases ROA move in opposite direction. The size of Oromia credit and saving Share Company of Eastern hararghe branch (log of total asset) which are included in this study shows improvement. Increase in the size of the Oromia credit and saving Share Company shows a higher negative correlation with portfolio at risk>30 (-0.063), market concentration (-0.582), GDP (-0.377), operational efficiency (-0.85) and capital to asset ratio (-0.598). Except size and age the other variables have negatively correlated with ROA, imply that when PAR, GR, CONS, GDP, EFE and CAP increases ROA move in opposite direction and the size has positively correlated with GR ratio (0.024), and indicate that the majority of the asset of the Oromia credit and saving Share Company composed from deposit liability. In addition, market concentration have had inversely correlated with variables, portfolio at risk >30 days (-0.066), gearing ratio or debt to equity (-0.052) and age (-0.142). This is because the concentration of Oromia Credit and Saving Share Company is reduced through time and contrary portfolio at risk >30 days, gearing ratio or debt to equity ratio and age of the Oromia credit and saving Share Company increases. Market concentration (CONS) is negatively correlated with ROA (-0.177) indicating that when market concentration of OCSSCO of Eastern Hararghe branch increase financial performance decreases because of inefficiency. By the same token, as operating efficiency increases, ROA moves in opposite direction which is indicated by -0.226 and as GDP increases ROA moves with the same direction. On the other hand size, portfolio quality, Real GDP and age indicated that a positive correlation with ROA (0.332), (0.205),(0.200) and (0.17) respectively indicating that the increase in size (total asset) of Oromia credit and saving Share Company and the increase in number of years of their operation will tend financial performance to increase.
Table 4.2.Correlation Matrix
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Source, Survey Output, (2019)
*. Correlation is significant at 0.05 level
**. Correlation is significant at 0.01 level
A. Normality Assumption
If the residuals are normally distributed, the histogram should be bell-shaped be significant meaning disturbance to be normally distributed around the mean. This means that the p -value given at the bottom of the normality test screen should be bigger than 0.05 to not reject the null of normality at the 5% level (Brooks, 2008).
Ho: Normally distributed errors
Ha: Non-Normal Distribution error
Therefore, the normality tests for this study as shown in figure below, which indicates that the errors are normally distributed. Based on the statistical result, the study failed to reject the null hypothesis of normality at the 5% significance level.
Figure 2 Normality Test for Residuals
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B. Homoscedasticity Assumption (variance of the errors is constant)
According to Brooks, (2008) it has been assumed thus far that the variance of the errors is constant, σ 2 - this is known as the assumption of homoscedasticity. If the errors do not have a constant variance, they are said to be heteroscedastic. To test for the presence of hetroscedasticity, the popular white test was employed. It is hypothesized that as follows
Ho: There is no heteroskedaticity problem (homoskedasticity)
Ha: There is heteroskedaticity
According to Brook, (2008) indicated that if the P-values of these test statistics are considerably in excess of 0.05, then the test give conclusion that there is no evidence for the presence of hetroscedasticity. It is clear evident that the errors are homoskedasticity. Therefore, based on this statistics we fail to reject the null hypothesis that is indicated as there is no Hetroscedasticity for the models (Appendix IV).
C. Test for Assumption of Autocorrelation
It is assumed that the errors term are uncorrelated with one another. If the errors are not uncorrelated with one another, it would be stated that they are auto correlated. This is an assumption that the errors are linearly independent of one another (uncorrelated with one another). The simplest test is due to Durbin and Watson (Brook, 2008). To test this assumption, the DW stat value in the main regression table should be considered. The Durbin-Watson test statistic value in the regression result was 1.665. To identify factors affecting financial performance of Oromia credit and saving share company, 50 (5*10) observations were used in the model. Therefore, to test for autocorrelation, the DW test critical values were used. Then relevant critical lower and upper values for the test are dL= 1.421 and dU=1.670 respectively. The Durbin-Watson test statistic of 1.665 is clearly between the upper limit (dU) which is 1.670 and the the lower values of 1.421 and thus, the null hypothesis of no autocorrelation is within the non- rejection region of the number line and thus there is no evidence for the presence of autocorrelation.
D. Multicollinearity Test
An implicit assumption that is made when using the panel LS estimation method is that the explanatory variables (independent variable) are not correlated with one another. If there is no relationship between the explanatory variables (independent variable), they would be said to be orthogonal to one another. If the explanatory variables were orthogonal to one another, adding or removing a variable from a regression equation would not cause the values of the coefficients on the other variables to change (Brook, 2008). According to Gujarati, (2004) Multicollinearity could only be a problem if the pair-wise correlation coefficient among Regressors is above 0.90 Hailer et al, 2006 cited in Berhanu, (2012) which is not more or less the case in the study variables.
Table4.3. Multicollinearity test
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Source: survey output, (2019).
This part presents the empirical findings from the econometric results on the factors affecting the financial performance of Oromia credit and saving Share Company, Eastern Hararghe branch. The section covers the operational panel data regression model used and the results.
Operational model: The specific panel fixed regression model used to study factors affecting financial performance was: ROAit = βoi+ β1*CAP + β2 *EFF + β3 *PAR +β4 *GR +β5 *AGE +β6 *SIZE +β7 *GDP +β8*CONS+ μit.
Deciding on whether the random effect (RE) model or fixed effect model (FE) was an appropriate model for this study depended on whether the individual effect were fixed or random. Despite increasing availability of panel data, panel data regressions may not be appropriate in every situation so one has to use some practical judgment in each case (Gujarati, 2004). Based on the outcome of the two in the regression or in the model the current study applied fixed effect model; since the adjusted R square figure, significance level and Durbin-Watson stat value increases with the use of cross-sectional fixed effect model.
Figure 3: Regression Results for factors affecting financial performance of Oromia credit and saving Share Company, Eastern Hararghe Branch.
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SPSS result, (2019) *Significant@5% **Significant@1%
Based on the regression result, the R2 value is 0.67 (67.0 %) which implies that 67.0% of fitness can be observed in the sample regression line. This can be further explained as, 67.0% of the total variation in the financial performance that is ROA is explained by the independent variables (Capital to Asset ratio, Size, Age, GDP, Gearing ratio, Operational efficiency, Portfolio at Risk>30 days and Market concentration) jointly. The remaining 33 % of change is explained by other factors which are not included in the model. The Prob (F statistic) value is 0.00 which indicates strong statistical significance, which enhanced the reliability and validity of the model. Each variable are described in detail under the following sections.
A. Capital to Asset ratio
The coefficient of the capital to asset ratio (CAP) is negative (-0.0212) and statistically insignificant even at 10%. This confirms that for the study period 2013 up to 2017 capital strength of Oromia credit and saving Share Company do not have a positive relationship with their financial performance or holding constant all other variables, increasing CAP by one unit causes to decrease the ROA nearly 0.02 birr. Therefore hypothesis No.1 which is financial performance is positively related with capital asset ratio of Oromia Credit and Saving Share Company in Eastern Hararghe branch is rejected because the data did not support the hypothesis. Even though the theory says the argument that well capitalized MFIs is more flexible in dealing with problems arising from unexpected losses and against credit risks and results in a better chance for financial performance but Contrary to this majority of Oromia Credit And Saving Share Company branch managers, accountants and customer service officers have a perception (mean 4.00 see appendix 3) that capital to asset ratio can have a significant impact on the financial performance of their branches. This might be due to managers, accountants and customer service officers are measuring the performance of their institution based on the total profitability, which means ignoring the details of financial transaction data. The result of this study is similar to the findings of Sima, (2013) but inconsistent with the finding of Jorgensen, (2011) and Muriu, (2011) perhaps this can be attributed to external factors which are responsible for such variations result of the study not supports the argument.
B. Age of OCSSCO
The Age of microfinance institutions refers to the period that MFI has been in operation since its initial inception. Previously, in hypothesis no.2 indicated that Age has a positive relationship with financial performance of Oromia Credit and Saving Share Company in Eastern Hararghe branch. According to this finding, the variable confirms or supports the hypothesis and its coefficient is 0.0066 but statistically insignificant even at 10% significance level or in the other interpretation holding constant all other variables, increasing Age by one year causes to increase the ROA nearly by 0.007birr.
The positive relationship between age and financial performance of Oromia Credit And Saving Share Company in Eastern Hararghe Branch implies that as MFIs mature, and thus gets experience in their industry; they increase their likelihood of attaining financial performance. This can be explained by the fact that MFIs gradually improve their control over all operations related to issuance of microcredit and their critical activities. In other words, OCSSCO’s that have considerable experience in the microfinance industry have diligently or carefully applied credit risk management and general efficient management techniques to attain financial performance. On the other hand branch managers, accountants and customer service officers do not perceive years of operation have a relationship with financial performance of Oromia credit and saving Share Company. This can be branch managers, accountants and customer service officers believed that if the structure of the organization is in line with its provision of service it is possible to attain its financial performance within short period of time. The result is similar to Joergenson, (2012), Sima, (2013) and Yonas, (2012).Therefore this study concludes that age is Oromia credit and saving Share Company’s internal factor that affects its financial performance positively. This is also practical in Oromia Credit and Saving Share Company where matured OCSSCO branch earn high financial performance compared to new one.
C. Operational Efficiency
Operational Efficiency is performance measure that shows how well MFIs is streamlining or reforms its operations and takes in to account the cost of the input and/or the price of output. Efficiency of the MFIs management measured in terms of adjusted operating expense to adjusted average gross loan portfolio. By taking the above formula as the tool to calculate, the current study which covers the time period from 2013 to 2017 indicates that coefficient of -0.319 and it was statistically significant at 5% significance level (P-value 0.001) this result shows that holding constant all other variables, increasing operational expense in one unit on gross loan portfolio cause to decrease ROA nearly by 0.32 birr. It is an indication that OCSSCO of East Hararghe branch should give great attention in cost minimization technique. The result indicated that there was a negative relationship between efficiency and financial performance of Oromia Credit And Saving Share Company during the study period. The result confirms the common rule of thumb that the higher our expense the lower our financial performance. Based on the finding the study fail to reject null hypothesis no.3 namely there is a negative relationship between Operational efficiency and financial performance in Oromia Credit And Saving Share Company because the result supports the expectation. Generally operational efficiency was a key determinant of financial performance of Oromia Credit And Saving Share Company’s for the study period 2013-2017. The perception of managers, accountants and customer service officers towards operational efficiency result supports the regression finding which is minimizing expense to loan portfolio have a significant role to achieve the financial performance of their institution. The result was consistent with findings many research like, Dissanayake, (2012), Muriu, (2011) and Sima, (2013) but inconsistent with Jorgensen, (2011) perhaps this can be attributed to external factors which are responsible for such variations.
D. Portfolio quality
Portfolio quality is a measure of how well or how best the institution is able to protect total funds available for the MFI to use as loans to its clients against all forms of risks. The coefficient of the portfolio-at-risk at > 30 days is negative, as expected but statistically insignificant. This confirms the hypothesis, namely that a significant reduction in the portfolio-at-risk at > 30 days in the portfolio should have a positive impact on the Oromia credit and saving share company financial performance in Eastern Hararghe Branch. In other words, a high portfolio-at-risk would limit the revenue derived from microcredit operations and therefore decrease the amount of lendable funds. As a result this would lead to the addressing of credit outreach problem and ultimately the inability to sustainably supply quality services to the clientele, and have a negative impact on Oromia credit and saving share company financial performance results. The negative value of the coefficient of -0.111 of the portfolio-at-risk clearly illustrates this problem.
The portfolio at risk (PAR) measure indicates how efficient MFI is in making collections. The higher the PAR implies low repayment rates, an indication of inefficient MFI. The higher the PAR, the more inefficient the MFI will be and, therefore, the less financial performance. In general it shows that the portfolio-at-risk (Par>30) is the most determining indicator of the financial performance of Oromia credit and saving share company in Eastern Hararghe branch. Regarding the quality of portfolio, managers, accountants and customer service officer have a positive perception in keeping its quality. Meaning a high portfolio-at-risk would limit the revenue derived from microcredit operations and therefore decrease the amount of lendable funds so managers, accountants and customer service officers are familiar with this risk thereby improving the quality of their portfolio. The result is similar to Muriu, (2011), Yonas, (2012), Sima, (2013) but inconsistent with Dissanayake, (2012) finding.
E. Size of OCSSCO (Total Asset)
Natural logarithm of total asset of MFIs is used as a proxy of size of MFIs. As with relative market power theory and scale efficiency theory, size of a firm expands its market power and profits increases. The finding of the study had opposite to the theory that is negative coefficient -0.052 and statistically significant at 10 % (p-value 0.079) the negative sign implies that size of OCSSCO does not determine its financial performance during the study period, indicates that large OCSSCO branch in Eastern Hararghe branch have not significantly enjoyed economies of scale. In fact, the negative coefficients bring to attention the possibility that diseconomies exist, which adversely affect their financial performance. This might occur due to the existence of bureaucratic bottleneck system and managerial inefficiencies to manage their assets and the result is consistent with AEMFI, (2013) report, that is in MFIs economies of scale have much less impact on efficiency than is usually believed because of high variable cost, the report also point out that if the loan portfolio of an MFI exceeds 1 to 2 million USD, growth does not seem to bring significant efficiency gains, and small MFIs can often be more efficient than their much larger peers. In other ways, the result confirms that the smaller size Oromia Credit and Saving share company might be advantageous by their size to generate more return from their assets. The result was in contrary with hypothesis no.5 namely size of Oromia credit and saving Share Company has positive relation with financial performance in Eastern Hararghe OCSSCO Branch. Therefore the study rejected the hypothesis because the data did not support the result. Concerning the size of total asset branch managers, accountants and customer service officers oppositely believed that an increase in total asset would have positive impact in financial performance of their Oromia credit and saving share company branches. This can be managers, accountants and customer service officers are highly focusing on increasing in asset by giving less attention to an increase operating expense as asset of their branches is increased. This ends up with no profit. The result was not consistent with Cull et al. (2007) and Muriu, (2011) but similar to the banking industry result, Dietich and wanzenried, (2009) and MFIs result, Sima, (2013).
F. Gearing ratio/Debt to Equity ratio
The debt to equity ratio is a common measure used to assess a firm’s leverage, or in other words the extent to which it relies on debt as a source of financing. The ratio showed up a negative coefficient (-3.99) and it is statistically insignificant variable (P-value 0.986). This implies that for the study period (2013-2017) there was insignificant correlation between financial performance and gearing ratio that is perhaps more debt relative to equity is used to finance microfinance activities and that long term borrowings impact positively on financial performance by accelerating Oromia credit and saving share company growth than it would have been without debt financing. Therefore, based on the regression result from the study, the study fail to reject the hypothesis no.6 namely gearing ratio has negative relationship with financial performance of Oromia credit and saving Share Company which was formulated to show the absence of a significant relationship between debt to equity ratio and financial performance of Oromia credit and saving Share Company. Similarly branch managers, accountants and customer service officers have also perceived that gearing ratio would not have a positive impact on the financial performance of their OCSSCO branches. The result is inconsistent with Dissanayake, (2012) and Muriu, (2011) but consistent with Melkamu, (2012).
Economic growth (GDP) is among the most commonly used macroeconomic indicators, as it is a measure of total economic activity within an economy and the study used real GDP growth as a proxy of the macroeconomic environment. The Result shows that a negative coefficient of -0.005 but it was statistically significant at 10% significance level (P-value 0.09) indicating that growth in economic condition measured in terms of real GDP growth did not affect financial performance of Oromia credit and saving share company for the study period. On the same way branch managers, Accountants and customer service officers also believed GDP has non- significant role for financial performance of OCSSCO. Therefore, the current study found that real GDP growth is not positively affect financial performance of Oromia credit and saving Share Company, Eastern Hararghe branch. Therefore the study rejects the hypothesis no.7 namely real GDP has positive relationship with financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch because the data did not support the result. The result was consistent with Muriu, (2011) and Sima (2013).
H. Market concentration
According to Herfindahl-Hirschman (H-H) index, market concentration is measured with the sum of the square of market share of the sample banks included in the particular study and the researcher adopt from different literatures in the banking industry and look MFIs market concentration in the same fashion. Even though the descriptive result shows that there is market concentration in Oromia credit and saving Share Company but the regression result indicates a negative and statistically insignificant even at 10% impact on OCSSCO, Eastern Hararghe branch financial performance, the reason behind is most likely inefficiency and the motive that OCSSCO is established in Oromia. The banking theories on market concentration argue that if the size and firm distribution of a specific sector is concentrated, the profitability of firms becomes high because they could get monopoly power to set the price of their products/service and determine their desired level of profit. This empirical results show that market concentration affects MFIs financial performance negatively (-0.866), but the effect was statistically insignificant (p-value 0.105). On the contrary the branches managers, accountants and customer service officers believe that market concentration have positive impact on the financial performance of their branches. The reason is most likely they could get monopoly power to set the price of their products/service and determine their desired level of profit. Hence, this study finds no evidence to support the hypothesis no.8 namely market concentration has positive relationship with financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch. The study is consistent with banking sector result Flamini, (2009), Athanasoglou, (2005) Berhanu, (2012) but inconsistent with Mohneux and Thornton, (1992), Belayneh, (2011) and Habtamu, (2012).
This chapter presents conclusions and recommendations based on the analysis made in previous chapter.
Microfinance has been accepted not only as a financial mean to target specific people who excluded from the formal financial system to gain access to sources of financing, but it comprehends also a social aspect contributing to poverty reduction, women empowerment, economic development and employment creation. In order to survive negative shocks and maintain a good financial stability, the financial managers and policy maker should identify the key factors affecting financial performance of Oromia credit and saving Share Company in Eastern Hararghe Branch. The current study use both primary and secondary data for an empirical framework to investigate the effect of MFI-specific, industry-specific and macroeconomic factors affecting financial performance of Oromia credit and saving Share Company in Eastern Hararghe Branch from 2013 to 2017. To attain this objective the researcher began by reviewing the literature, also applied commercial banking theories in order to test theories and then identified factors affecting financial performance that could apply to the empirical data. After collecting these data, the researcher formed a basic sample of 10 Oromia credit and saving Share Company operating throughout the zone. Subsequently, the researcher processed and analyzed the data gathered to test the model and clarify factors affecting financial performance of Oromia credit and Saving Share Company in Eastern Hararghe Branch.
Based on the descriptive and empirical evidence obtained from the econometric results in Chapter 4, the researcher generally conclude that financial performance of Oromia credit and saving Share Company in Eastern Hararghe Branch is highly affected by the internal factors than external one.
Descriptive analysis results show that Oromia credit and saving Share Company averagely generating positive ROA. This is an indication that Oromia credit and saving Share Company in Eastern Hararghe is more focused on profit orientation than poverty reduction. The capital to Asset mean value results suggest that about 41.8% of the total assets of Oromia credit and saving Share Company were financed by shareholders funds while the remaining 58.20 % was financed by other source which is above the standard set by CGAP, 20%. The mean value of operating expense to loan portfolio indicates that about 40.8 percent of operating expense which is above rest of Africa, 24.27% (AEMFI, 2013). The mean value of Gearing Ratio shows that Oromia credit and saving Share Company in Eastern hararghe branch was much leveraged (2.47), which is more than the minimum statutory 1.5 set by AEMFI. The mean value of Market concentration (0.26) shows that the industry is highly controlled by few Oromia credit and saving Share Company branches in Eastern hararghe branch. Operational Efficiency of Oromia credit and saving share company management measured in terms of adjusted operating expense to adjusted average gross loan portfolio, the current study which covers the time period from 2013 to 2017 indicates that coefficient of -0.319 and it was statistically significant at 1% significance level (P-value 0.001) as expected. The result shows that the higher the cost, the lower the financial performance of Oromia credit and saving Share Company. The result indicates the real evidence for Oromia credit and saving Share Company which was less efficient in managing their expenses. Operational efficiency in microfinance is an important and key factor of financial performance and therefore Oromia credit and saving Share Company have much to gain if they improve on their managerial practices. Efficient cost management is a prerequisite to financial performance since Oromia credit and saving Share Company may not have reached the maturity level required to link quality effects emanating from increased spending to higher Micro Finance Institution financial performance.
The coefficient of the portfolio-at-risk at 30 days is negative, as expected but statistically insignificant. In other words, a high portfolio-at-risk would limit the revenue derived from microcredit operations and therefore decrease the amount of lendable funds. As a result this would lead to the addressing of credit outreach problem and ultimately the inability to sustainably supply quality services to the clientele, and have a negative impact on Oromia credit and saving share company’s financial performance results. The positive relationship between age and financial performance of Oromia credit and saving Share Company implies that as the institution mature, and thus gets experience in their industry: they increase their likelihood of attaining financial performance. This can be explained by the fact that Oromia Credit and Saving Share Company of Eastern Hararghe Branch gradually improve their control over all operations related to issuance of microcredit and their critical activities. When we look the other variables that is GR, CAP, PAR, AGE of Oromia credit and saving Share Company of Eastern Hararghe branches and Market Concentration their influence in the financial performance (ROA) is not significant. when we look the primary data result with the secondary data, although the secondary data regression result shows size, operational efficiency and GDP have significant influence in financial performance but by looking the mean value the primary data result shows that portfolio quality, market concentration, operational efficiency and capital to asset ratio have significant influence on financial performance in Eastern Hararghe Branch. Since their mean value is near to 4(see appendix 3). The gearing ratio, age of OCSSCO ,size and GDP growth were not had influence on financial performance of Oromia credit and saving share company in Eastern Hararghe branch since their mean value is below 2 (see appendix 3). Thus, it can be concluded that financial performance in Oromia credit and saving Share Company is largely driven internal or MFIs-specific factors than external factors.
Generally these findings have responded to the primary aims of the study and made a contribution to the existing literature. Overall, these empirical results provide evidence that Oromia Credit and Saving Share Company financial performance is shaped by MFI-specific factors (that is MFIs level management) than External Variables (that are not the direct result of MFIs manager decisions).
Based on the findings of the research, the researcher has recommended certain points what he thought to be very critical if considered and implemented by the Oromia Credit and Saving Share Company accordingly and properly. Therefore, the following recommendations have been given.
Size, Growth Domestic Product and Operational Efficiency are significant determinants of financial performance of Oromia Credit and Saving Share Company in Eastern Hararghe Branch Since inefficiency is the bottleneck of MFIs in Ethiopia, the management should give great attention to a good expense management policy or reduce operating costs and credit risk management by employing different technologies which can minimize cost example mobile banking.
The Oromia Credit and Saving Share Company in Eastern Hararghe Branch managers and policy makers should give high concern in the motives of MFIs that is MFIs should be perform their activity with comprising the two motives together. Meaning the government and policy makers should give due attention for both poverty reduction and financial self-sufficiency of Oromia Credit and Saving Share Company.
Oromia Credit and Saving Share Company have to emulate profit-making banking practices by implementing a sound financial management and good managerial governance to assure their financial sustainability in the long run financial performance.
Since Oromia Credit and Saving Share Company in Eastern Hararghe is in infant stage the government should avail different facilities or infrastructures to reduce inefficiencies.
Recommendations for Future Research
This study focused mainly on the internal factors affecting financial performance of Oromia credit and saving Share Company specifically in Eastern Hararghe Branch. By taking this study as a standing point, it could be possible to come up with a better insight and several extensions to this study. Considering the available time and resource the outcome of this study can be more robust, if future researchers conduct a study on this area.
First, by further increasing the study population and the sample size to the whole Micro finance institutions found in Eastern Hararghe zone. Secondly, by taking evidence from other industries, using longer years of data and increasing the number of independent variables will generate more useful information and will enhance further the scope of the future studies.
In addition to that it is recommended further that future researchers may also consider assessing of factors affecting financial performance of Oromia credit and saving Share Company with non-monetary variables such as corporate governance, personnel quality, level of management etc.
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OROMIA STAE UNIVERSITY
POST GRADUATE STUDIES
SCHOOL OF ACCOUNTING AND TAX ADMINSTRATION
DEPARTMENT OF PUBLIC FIANCIAL MANAGEMENT
This questionnaire is prepared for Accountants and customer service officers of OCSSCO ( Oromia Credit and Saving Share Company).
The objective of the questionnaires is to collect information about the factors that affecting financial performance of Oromia Credit and Saving Share Company in eastern Hararghe branch.
- No need of writing your name
- The information you provide will be valuable for the success of the research paper. Please be honest and objective while filling the questionnaire.
- The information you give is used only for academic purpose and will be kept confidential.
Thank you in advance for your cooperation!!!
Part one: Demographic Information
Abbildung in dieser Leseprobe nicht enthalten
Part two: Factors affecting of financial performance of Oromia credit and saving share company, Eastern Hararghe Branch
1. The major factors that affecting financial performance of Oromia credit and saving Share Company in Eastern Hararghe branch are listed below. After you read each of the factors, evaluate them in relation to your experience in OCSSCO and then put a tick mark √ under the choices below.
5=strongly agree 4=agree 3=undecided 2=disagree 1=strongly disagree
Abbildung in dieser Leseprobe nicht enthalten
Appendix II the raw data used for analysis (source AEMFI and MOFEC).
Abbildung in dieser Leseprobe nicht enthalten
Appendix III Branch managers’, Accountants and customer service officers perception analysis on factors affecting financial performance of Oromia credit and saving share company in Eastern Hararghe Branch. In this part primary data collected from 30 respondents of Oromia credit and saving Share Company through structured survey questionnaire (see appendix 1) was analyzed and discussed. All 30 employees were solicited to rank the major factors that affect financial performance of OCCSCO in Eastern Hararghe branch.
demography of the respondents
1. Educational background of the respondents
Abbildung in dieser Leseprobe nicht enthalten
NB: 1 stands for Diploma
2 stand for first degree
2.work experience of the respondents
Abbildung in dieser Leseprobe nicht enthalten
NB: 1 Strongly Disagree 2.Disagree 3.Undecided 4.Agree 5.Dtrongly Agree
Appendix-IV: Tests for the Heteroskedasticity Test: White Heteroskedasticity Test: White
Abbildung in dieser Leseprobe nicht enthalten
Appendix-V: Regression Results For Factors Affecting Financial Performance Of Ocssco, Eastern Hararghe Branch.
Dependent Variable: ROA
Method: Panel Least Squares
Date: 16/6/19 Time: 04:37
Sample: 2013 2017
Periods included: 5
Cross-sections included: 10
Total panel (balanced) observations: 50
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