Publication thesis

Chapter -1 Introduction

Gender discrimination, marginalization, unequal treatment and unequal access to resources between women and men hinder women's progress. Due to these inequalities women are still vulnerable to poverty and they are marginalized from different economic, social and political activities (Batliwal, 1994). Gender equality is a means to promote growth, reduce poverty and particularly to empower women (World Bank, 2001). In subsistence agriculture and low income developing countries, microfinance provision to rural areas is taken as a mechanism to handle poverty and to empower women economically (Gebrat, 2013).

The term empowerment stands for a broad range of concepts and has different meaning in different contexts (Baden, 1997;Malhotra et al., 2002). Different authors define the word empowerment according to the need of their work in different ways. Empowerment is the enhancement of assets and capabilities of diverse individuals and groups to engage, influence and hold accountable to the institutions which affect them (Bennett, 2002). Women's empowerment is a means to promote growth, reduce poverty and promote better governance (World Bank, 2001).

Empowerment is not a top-down strategy rather it is a bottom-up process. In most cases, the meaning of empowerment has three dimensions that are economic empowerment, social empowerment and political empowerment but sometimes it includes cultural empowerment. Since the focus of this study is on economic aspect, let us define what economic empowerment means (Mayoux. 2005).

Particularly, economic empowerment is defined as women's access to savings and credit which gives them a greater economic role in decision making through their decision about savings and credit (Mayoux. 2005). Economic empowerment looks for guarantee of skills, capabilities, resources and access to secure and sustainable incomes and livelihoods as well as access to assets and resources (Luttrell, 2009).

Economic empowerment of women with microfinance programmes, focusing and claiming to empower women, have become popular among donors and NGOs in recent years. The shift in development policies from the emphasis on women's active role in production as a means to more well-organized development, to the approach of women's empowerment through women organizing for greater selfsufficiency, has also meant a change in policies for the improvement of women's economic role (Baden, 1997).

The birth of microfinance was in Bangladesh in 1970's. Muhammad Yunus shocked by the appalling poverty and human suffering in Bangladesh and began to think about microcredit to improve the situation (Bateman, 2010).

Microfinance is a financial service which is provided to those who are excluded from the formal financial sector. Microfinance can be categorized as formal, semi-formal, and informal (Elisabeth, 2013). Microfinance is becoming an instrument for the empowerment of the rural poor households particularly women in a way that is self-sustaining (Gebrat, 2013).

According to Bateman (2010), the importance of microfinance to the poor is for the following reasons. Microfinance serves as social solidarity in poor communities, gives everyone the opportunity to escape from poverty if they want, it saves the poor from traditional money lenders, and it is important in helping women empowerment and helps the poor in terms of consumption smoothing.

Today, in many developing countries microfinance plays crucial role in alleviating poverty. It is a real development instrument for the improvement of the economic life of the poor, particularly women. Ethiopia is one of the poorest countries in the world and to address this challenge, the government is implementing different developmental programs like licensing the formal credit sector to reach the rural poor at the grass root level. Providing financial services to the poor particularly for women is central to economic empowerment.

The informal financial system is one of the most important sources of finance for poor households in rural parts of Ethiopia due to limited access to financial institutions. Under the informal financial scheme the main sources of loans are friends, relatives and moneylenders (Al-Bagdadi and Bruntrup, 2002). The rapid growing microfinance industry in Ethiopia is a recent phenomenon (Ebisa et al., 2002).

The establishment of formal credit sector in Ethiopia dates back to 1995. Particularly, the licensing and supervision of microfinance institution proclamation of the government encouraged the spread of microfinance institutions in rural areas (Getaneh, 2005). The microfinance industry in Ethiopia has shown a significant qualitative and quantitative growth since its establishment. The formal base has been laid by the issuance of proclamation No. 40/96 which established the licensing and supervision of MFI as share companies in accordance with the commercial code of Ethiopia (Al-Bagdadi and Bruntrup, 2002).

Microfinance contributes to poverty reduction through increasing income, accumulations of capitals, and diversification of income sources for investment (Tesfay, 2003). In Ethiopia studies show that, microfinance programs benefited the poor in terms of increased income, employment creation, changing the saving habits of households and their expenditure pattern drastically increased on different goods and services (Haymanot, 22007;Balamurugan, 2012;Gebrat, 2013). As client of microfinance institutions, women's income was increased proportionally as men income increased (Gebru and Paul, 2011).

Omo MFI is one of the MFI established in Ethiopia in the South Nations Nationalities and Peoples Region (SNNPR) following the proclamation No. 40/1996 in 1997, which is intended to fill the shortage of formal financial institutions by meeting the needs of the poor households and small scale borrowers in income generating schemes. OMFI is operating in all zones and woredas of the region. According to Balamurugan (2012), OMFI serves more than 872,000 loan and saving clients.

Agriculture in the study area is characterized by rain-fed and subsistence nature which serve as main source livelihood. Though, OMFI is the only financial institution in the study area, women clients of OMFI in Gimbo woreda are too few in number compared with the total population of the woreda because of its limited outreach in all kebeles. Therefore, this study is intended to identify and analyze the impact of microfinance on women's economic empowerment in Gimbo Woreda of South Nations Nationalities and Peoples Region.

Statement of the Problem

In the world as well as in Ethiopia women constitute more than fifty percent of the total population. But these parts of the population have been discriminated and marginalized from different activities specifically from economic aspects in the past with no appropriate earnings. This action makes women poor and dependent on their husbands or parents in the family. About 1.3 billion people who live below absolute poverty line and, seventy percent (70%) of them are women (UNDP, 1995 as cited in Balamurugan, 2012).

Empowering women are vital, both to recognize the right of women and to attain developmental objectives like economic growth, poverty reduction, health, education, welfare and the like (Golla et al., 2011). Women empowerment takes three dimensions. These are economic, social, and political empowerment but it encompasses beyond this dimension like cultural empowerment (Luttrell, 2009).

Women's work in most parts of the world, mainly in developing countries, but not resulted in the same level of economic empowerment as that of men (CIDA, n.d). Following the collapse of derge regime, the EPRDF government adopted different policies to address the poor in general and to empower women in particular through affirmative action. Organizations like NGOs and CSOs on the other hand tried to play their role in solving these problems of discrimination and marginalization of women. Microfinance is one tool to empower women, though it is not given emphasis in the past. However, currently governments and various organizations have began to recognize microfinance as an important intervention in empowering the poor particularly women.

In developing countries, traditional beliefs and other obstructions such as discrimination and unequal treatment, heavy domestic workload, high rate of illiteracy among women, have restricted their roles in the household decision making and limited women's involvement in the economy and their access to resources. Unless women are empowered economically, they would be unable to play significant role in economic development. Providing credit which is easily accessible to them is one means of empowering women to run their business (Ablorh, 2011).

The impact of microfinance on women empowerment is still debatable. Though microfinance plays a great role, there is no agreement that microfinance programs have positive effects on economic status of women (Aghion and Morduch, 2005). Some empirical findings show that microfinance has positive impact on women's economic empowerment while others argue that microfinance has negative impact on women's empowerment.

Optimist advocators of microfinance argue that microfinance has positive impact in empowering women through an increase in household consumption expenditure, ability to make small and large purchase, control over assets, involvement in family decision making, mobility and freedom from family domination are listed as channels through which women could be empowered (Hashemi et al., 1996;Schuler et al., 1996;Pitt and Khandker, 1997;Kato and Kratzer, 2013;Awojobi 2014). Similarly, studies in Ethiopia depict that microfinance has significant impact on women's empowerment (Tesfay, 2003;Haymanot, 2007;Balamurugan, 2012;Ahmed, 2013).

On the contrary, other studies on microfinance show that microfinance has insignificant effect on women empowerment. They argue that women have little or no control over their loan and the loan is controlled by male relatives, a number of borrowers were to lose their property for repaying the loan. Thus opponents of microfinance argue that microfinance has negative impact on women empowerment (Vengroff and Creevey, 1994;Goetz and Gupta, 1996;ILO, 1998;Kulkami, 2011).

According to Tesfay (2003), in Ethiopia microfinance services have limited impact on entrepreneurial development, microenterprise sustaining and profitability. A study conducted by Yimer (2011) on rural microfinance and women empowerment indicates that one third of the respondents included in the study did not perceive meaning full changes in their life and the impact of microfinance is not same and alike to all matured women clients.

Thus, there is no uniformity among scholars and researchers on the impact of microfinance on women economic empowerment. Therefore, this study is conducted to fill the existing literature gaps where there are inconclusive findings by including additional variables on previous studies. On the other hand, the researcher couldn't find any research undertaken on the research question at hand in the study area. So, the finding of this study will help to visualize the impact of microfinance on women economic empowerment in the study area.

Objective of the Study

General Objective

The general objective of this study is to analyze the economic impact of Omo microfinance institution in empowering women.

Specific objectives

The specific objectives of this study are:

❖ To assess the impact of microfinance on women's access to resources and their control over assets. ❖ To investigate the contribution of microfinance on women's participation in household decision making. ❖ To examine the effects of microfinance on women's income. ❖ To examine the impact of microfinance on the saving habits of women.

Significance of the Study

Women as an essential part of the society and have immense potential, their participation and decision making on socio-economic issues in the past was very low due to different reasons. Economically empowering women is crucial. In the study area as well as in the western parts of the region, the researcher couldn't find any research undertaken regarding the impact of microfinance in empowering women. So this study may serve as a reference for further researchers who want to investigate in this regard. Furthermore, this study serves for concerned bodies as an input for further policy issues in the area. Finally, this paper comes with findings in the study area that depict the impact of microfinance on women economic empowerment.

Scope and Limitation of the Study

Regarding geographical scope, the study was conducted in SNNPR, Gimbo Woreda sub-branch OMFI. Whereas the subject matter of the scope is limited to the impact of Omo microfinance on women's economic empowerment aspect.

The study focuses only on the impact of Omo microfinance on rural women's economic empowerment aspect. Therefore, the study does not assess the impact on urban women's clients and does not include other dimensions of women empowerment like social, political and cultural empowerment. On the other hand, few responsive rates of respondents due to different reasons limited this study.

Organization

This study was organized as follows. The first chapter describes about background of the study followed by a review of concepts and literature of microfinance and women's empowerment. The third chapter describes the data and methodology part. The last two chapters that are, fourth and fifth chapters are devoted to the analysis of the data and conclusion and recommendations respectively. According to Asian Development Bank (ADB), microfinance is the provision of a broad range of finance such as deposits, loan payment services, money transfers, and insurance to poor and low-income households and their microenterprises (Binh, 2000;ADB, 2000). Microfinance is the provision of financial services to low-income clients, including self-employed. They give broad base function and termed as developmental tool (Ledgerwood, 1999). Microfinance is being recognized as one of the development strategy for the poor (Otero, 1999).

"Microfinance refers to the provision of formal services to poor and low-income peoples, as well as for others systematically excluded from the financial system. It embraces not only a range of credit products but also savings, money transfers and insurance (WB, 2012).

Microfinance is not simply banking, rather it is a multi-dimensional development instrument in which different activities usually engage such as small loans, informal appraisal of borrowers and investments, collateral substitutes, such as group guarantees or compulsory savings, access to repeat and larger loans based on repayment performance, streamlined loan disbursement and monitoring, and secure saving products (Ledgerwood, 1999). Cornford differentiates the meaning between microfinance and microcredit as microfinance is the provision of a broad range financial service to lowincome microenterprises and households. The financial service range includes savings and loans while other products include insurance, leasing, and money transfers. On the other hand, microcredit emphasizes the provision of credit services to low-income clients, usually in the form of small loans for microenterprise and income generating activities (Cornford, 2002).

Microfinance covers many varieties of institutional arrangements and approaches. They range from small self-helping groups with a handful of members to huge organizations that have nationwide coverage and millions of clients (McGuire and Conroy, 2010). MFIs can be non-governmental organizations (NGOs), savings and loan cooperatives, credit unions, government banks, commercial banks, or non-bank financial institutions and clients of microfinance are characteristically selfemployed, low-income entrepreneurs in both urban and rural areas. Traders, street vendors, small farmers, service providers, and artisans and small producers, are those normal clients of MFIs. These clients are poor but they are not poorest of the poor (Cornford, 2002; McGuire and Conroy, 2010).

Conceptualizing Women's Empowerment

Empowering women's are vital, both to recognize the right of women and to attain developmental objectives like economic growth, poverty reduction, health, education and welfare and the like (Golla et al., 2011). The term empowerment has many definitions in different socio-cultural perspectives, and does not interpret easily into all languages (Narayan, 2002).

'A woman is economically empowered when she has both the ability to succeed and advance economically and the power to make and act on economic decisions'. (Golla et al,p: 4).

There is no consensus how empowerment is viewed as outcome or process, how power operates, strategies for inclusion, its implication, approaches and definition. In most literature empowerment takes three dimensions that are economic, social and political empowerment but it encompass beyond this dimension like cultural empowerment. But for the sake of this study, it focuses on economic empowerment aspect only. According to Luttrell (2009) economic empowerment is defined asan economic empowerment that looks for guarantee of different skills, capabilities, resources, and access to assets and resources. Regarding types of power relation, it can be classified as power over (ability to influence), power to (organize and change existing hierarchies), power with (increased power from collective action), and power from within (increased individual consciousness). Empowerment is associated with the gender and development approach and challenging the way in which the inclusion of women in the development process can increase their work burden (Luttrell, 2009).

On the other hand, meaning of empowerment refers to generally to the expansion of freedom of choice and action. This means one can decide on what she wants to do freely and act on it. The need of empowerment is to achieve quality of life and human dignity, good governance, pro-poor growth, project efficiency and enhanced service delivery. Empowerment, particularly, empowerment of poor people (women), remains in almost all developing countries is an ideal rather than a realism in which poor people's experiences are pervaded by a common sense of powerlessness and voice lessens (Narayan, 2002).

Various dimension indicators of empowerment includes economic, education, governance, health and media empowerment. Among others economic empowerment indicators includes market participation (labor force participation or composition in the market) measured by accuracy of productivity and equity (ownership of land and other assets) (Chung et al., 2013). According to UNDP (2011), gender empowerment is measured through political representation indicated by female and male shares of parliamentary seats, representation in senior positions in the economy depicted by female and male shares in office and managerial position and power over economic resources indicated by professional and technical position. Poverty is one of the main indicators of women's disempowerment. As their poverty reduces women empowerment increases in various decisions making. Malhotra et al., (2002) differentiates ordinary/common dimensions of empowerment and its operationalization into three areas. At household level economic empowerment is measured through women's control over resources and their role to family support and at community level asset and land ownership, access to credit, access to markets and representation in local trade associations are indicators/measurements of women's economic empowerment. In the broader sense women economic empowerment is measured through their representation in high paying works, women CEO's and representation of their economic interest in macroeconomic policies and strategies of local and federal budgets (Malhotra et al., 2002).

Microfinance and Women Economic Empowerment

In the past women having huge talent and potential have been discriminated and marginalized from different activities, particularly from economic aspects which is responsible for social exclusion. Empowering women has many roles and seeks to meet strategic gender needs through participation on resources and development issues that concern the life of women. Most women particularly, those who are poor, are more vulnerable because of uneven distribution of resources and are unable to meet the basic requirements that worsen the unmet gender needs. Thus, lack of entitlement arising from inadequate assets and capabilities, makes women so poor and unable for the fulfillment of basic livelihood needs. The consequence is social and economic exclusion of a certain class and category of people and their consequent is disempowerment. That is why the idea of empowerment has influenced development practitioners, development agencies (both governments and NGOs), theoreticians and governments and donor agencies in the last decade (Padma and Getachew, 2004).

Microfinance and women empowerment interface at both intrinsic and extrinsic levels in which, the extrinsic level of empowerment refers to gaining greater access to and control over financial and physical assets, while the intrinsic level involves changes within, such as the rise in self-reliance, confidence, motivation and positive hope for the future (Yimer, 2011). Microfinance enables to mobilize and organize the poor and women at grassroots level and offer hitherto denied access for critical assets to them (Amin et al., 1998).

To achieve gender justice in the microfinance sector there is still a long way to go. In spite of increased access to small loans and savings, women's access to more advanced products is still unequal in many countries particularly in the LDCs. Evidences on membership of clients depict very little about the quality of the services accessed by women compared with men. Generally, women's loan is lower than their spouse or men, which constrains them to run good business that requires large loan. Most of their loan does not buy assets like land, house, machinery and equipment. The fact is that, women are the majority of savers, but men receive the majority of loans (Mayoux, 2010).

Availability of credit may also reduce willingness of customers and relatives to give interest-free loans and/or access to more charitable forms of credit from traders. Moreover, a recent study has found that women's access decreases compared to that of men as NGOs change to formal institutions, become more profitable and mature (Mayoux, 2010).

The logic of microfinance's potential for empowerment is similar to the economic model of empowerment; microfinance makes women economically independent by putting capital and financial resources in their hands. Economic independence results in higher bargaining power for women in their households and communities, and subsequently results in higher prestige and self-esteem. Here the functions are synchronous with its potential to empower (Kulkami, 2011).

In some cases, microfinance may even disempower women. The extent, to which women are able to benefit from simple financial services which do not take gender clearly into consideration, depends largely on context and individuals condition. Primarily, there is the subject of financial indicators of access: women's program membership, numbers and size of loans and repayment data cannot be used as indicators of real access or proxy indicators of their empowerment. Registration for loans in women's names does not necessarily indicate even participation in decisions about loan application, as men may simply negotiate loans with male program experts as an easier means of getting access to credit.

Secondly, the contribution of financial services to increasing incomes varies widely. Experiences from South Asia and Latin America show that, most women use their loans for their husband's activities, either as a rational investment choice where their own economic activities are limited or because their husbands claim the money as their right due to gender inequality. Finally, women's better contribution to household income does not ensure that women necessarily benefit or that there is any challenge to gender inequalities within the household though women seek to increase their power within joint decision-making process rather than seek independent control over income, neither of these outcomes can be assumed to occur (Mayoux, 2010).

Overview of Microfinance Sector in Ethiopia

Most of the population in Ethiopia resides in rural area under widespread poverty. A program like microcredit makes the government to reach these marginalized populations at the grassroots level. The history of microfinance in Ethiopia goes to the mid of 1990's. As a recent phenomenon, microfinance service in Ethiopia was introduced for the first time in 1994 as an experiment when the relief society of Tigray (REST) attempted to rehabilitate drought and war affected people through rural credit scheme in Tigray region (Yohannes, 2006).

Regarding ownership, financial foreign investment in Ethiopia is prohibited by law. Particularly, proclamation No. 84/1994 precludes a foreign national from undertaking banking business in Ethiopia, and no person is permitted to own more than twenty percent (20%) of a banking company's shares. On the basis of this proclamation, MFIs in Ethiopia should be established as share companies, the capital thereof owned fully by Ethiopian nationals and/or organizations wholly owned and registered under the laws with a head office in Ethiopia (Getaneh, 2005). The microfinance sector in Ethiopia is characterized by its rapid escalation, wide geographic coverage and increasing numbers of clients, large shares of government, focus on rural households, promoting credit and saving products (Ebisa et al., et al., 2012).

Recently microfinance institutions in Ethiopia are increasing rapidly to provide credit for the poor with various technical assistances. The number of microfinance in Ethiopia reached 33 with total capital and asset 3.8 billion and 13.3 billion birr respectively. Of the existing microfinance institution seventy five percent of the total capital in the industry is occupied by Amhara credit and saving institution (ACSI), Dedebit credit and saving institution (DCSI), Oromiya and Omo credit and saving institutions. In Ethiopia, out of the existing microfinance institutions fifty percent of the MFI are operating in Addis Ababa (Gashaw, 2014).

Overview of Omo Microfinance Institution (OMFI)

OMO microfinance institution (OMFI) was established in the South Nations Nationalities and Peoples Region (SNNPR), which is intended to fill the shortage of formal institutions by meeting the needs of the poor households and small scale borrowers in income generation schemes. The prime mission of OMFI is improving the economic status of low income, productive poor people particularly poor women in the region through increased access to credit and saving services. OMFI exerts its maximum effort to bring about accelerated and sustainable economic development in the region by the provision of efficient, effective and sustainable financial services to economically active poor people through effective partnership with GO and NGOs.

OMFI is established in 1997 and at the same time registered as a share company as per the requirement of proclamation number 40/1996 which states the provision of licensing and supervision of the business of microfinance institutions. It has been established with five shareholders, these are, SNNP regional government, southern Ethiopia peoples development association (SEDA), Wondo Trading Company and two natural persons 1

Empirical Literature

Various studies within the country or across countries may find different results on the impact of microfinance in empowering women. Some studies argue that microfinance has significant role in empowering women while other argues that microfinance has no role in empowering women. Even if microfinance plays a great role, there is no agreement that microfinance programs have positive effects on economic status of women (Aghion and Morduch, 2005).

Microfinance credit provision by Grameen Bank and Bangladesh Rural Advancement Committee (BRAC) argues that microfinance has significant effect in empowering women through increased mobility, economic security, involvement in major decision making, ability to make large purchase, freedom from family domination, political and legal awareness, participation in public protests and political campaigning (Hashemi, et al., 1996). Impact participation by gender three group based credit programs, Grameen Bank, Bangladesh Rural Advancement Committee (BRAC) and Bangladesh Rural Development Board's (BRDB) on women and men in general find that significant effect on the wellbeing of the poor household but the effect is greater if women are the program participant (women annual household expenditure increased more than men) (Pitt and Khandker, 1997).

A study by Roxin et al (2010), on impact of microfinance in Sierra Leone revealed that MF had improved clients' business expansion, increased their income and expenditure. Their study depict that microcredit has considerable impact on economic empowerment but it has only initial impact on social empowerment. At the same time their finding reveals no impact on women political empowerment.

Different scholars argue that, microfinance has no role in empowering women since women have little or no control over their loan and the loan is controlled by male relatives, a number of borrowers were to lose their property for repaying the loan (Vengroff and Creevey, 1994; Goetz and Gupta, 1996).

. OMFI operates for the achievement of government policies and strategies. Currently it is operating in 11 branches and 69 sub-branches which constitute exactly more than half of the region's geographical outreach (Dilayehu, 2014).

The main services provided by MOFI to its clients are credit, savings, pension fund administration, and micro lease. The target groups of clients includes from the agricultural sector, micro and small scale enterprises or business, petty traders, handcraft, and services sectors.

The study in Tigray region on the impact of microfinance on poor women shows that directly or indirectly, microfinance services provided by Dedebit credit and saving institution (DECSI) are contributing to the sustenance and improvement of the life of the poor women and their households. This study was conducted using multi-stage sampling with descriptive method of analysis. The evidence from this study depict that microfinance has positive impact in increasing income, diversifying sources and reducing variability of income. It also show that increased consumption, 1 Natural persons are those individual persons who are the shareholders of OMFI improved living condition in terms of house repairs and expansions, medical services and capital accumulation in the form of increased saving. This study critically depicts that women empowerment in terms of improved attitude and respect of their husband, increased self-confidence and self-image (Tesfay, 2003).

A research conducted at ACSI indicates that microfinance participant women are much better than non-participants in terms of household asset holding, yearly average off farm income, and involvement in decision making process in the household. The study was conducted using simple random sampling method with log it econometric method of analysis. Similarly, the estimation result of the logit model indicates out of 23 explanatory variables used 15 of them are significant (Gebrat, 2013). The study by Haymanot (2007), using descriptive statistics and binomial logit regression method of analysis reveals that microfinance has a positive impact on women economic empowerment in terms of increased participation of women in the household decision making, and improved living standard condition of its clients. Matured clients of ACSI have improved their household incomes, asset possession level, and saving habit; thereby positively affecting their ability to fully participate in household decision making.

A study by Yimer (2011), at ACSI using explanatory research method, show that in majority cases matured women clients have gone substantial change in many dimensions, to mention some indicators, like change in terms of skills essential for making and managing businesses, level of confidence and self-esteem and worth, personal cash assets, level of financial independence, income and diversifying income sources. But one third of the respondents included in the study did not perceive meaning full changes in their life. Therefore, the impact of microfinance is not same and alike to all matured women clients.

A study in Harari microfinance institution (HMFI) using descriptive statistics and logistic regression depict that, HMFI participants have been better in their income, improved their saving habits and control over resources than non-participants. The study used 123 sample respondents of which 15 of them are non-participants used as a control group. At the same time, the study used PSM method of analysis to identify the impact of HMFI on its clients. But the validity of the control group is questionable to apply PSM method of impact evaluation because of low number of non-participants which may result biased estimates of ATT. Moreover the study doesn't carry out sensitivity analysis to see the effect of unobservable covariates between participants and non-participants (Ahemed, 2013).

The study in SNNPR of OMFI by Balamurugan at Wondogent indicates that microfinance has significant effect on women empowerment. The descriptive statistics and regression analysis of the study was conducted using before and after method of analysis. OMFI contributes to social and economic empowerment of women in the study area. Women's hope and self-confidence improved through active participation in OMFI. Wondogent OMFI gives to women significant changes in terms of employment creation and income generation, saving habits and decision making. Therefore the study concludes that Wondogent OMFI affects women in terms of social and economic empowerment (Balamurugan, 2012).

Most of the studies conducted on women's empowerment particularly economic empowerment were carried out using either descriptive statistics or logistic regression. Few studies tried to use PSM method of impact evaluation particularly in Ethiopia is rare and even those conducted on similar topic fails to carry out full PSM procedures. Therefore, in the existing literature there is no uniformity among scholars and researchers on the impact of microfinance on women economic empowerment and their findings are yet inconclusive.

III. RESEARCH METHODOLOGY

Brief Description of the Study Area

Kaffa Zone is one of the 14 administrative zones found in the SNNPR state located in the south western part of Ethiopia at a distance of 449 Km from Addis Ababa and 729 Km from the capital of SNNPR state, Hawassa. It is bordered to the north and east by Oromia region, to west and south west by Benchi Maji Zone, to North West by Shaka Zone and to east by Konta special woreda. The Zone is located between 6 0 24 1 and 8 0 13 1 north latitude and 35 0 48 1 and 36 0 78 1 east longitudes. The Zone constitutes ten rural woredas (Gimbo, Gewata, Gesha, Sayilem, Bita, Chena, Decha, Telo, Cheta, and Addiyo) and one town administration, Bonga, which is the capital of Kaffa Zone.

Gimbo woreda is located between 7 0 23 1 and 7 0 49 1 north latitude and 36 0 00 1 and 36 0 47 1 east longitudes. It is bordered to the north by Oromia region, to west Cenna and Gewata woreda, to south by Decha woreda and to east by Addiyo woreda. The woreda contains 33 rural kebeles and three urban kebeles 2 Agriculture is the major economic activity practiced in the area followed by trade. More than 85% of the population of the woreda is engaged in mixed agricultural farming (crop and livestock) and the remaining population remains in commercial/ trading activity, government sector employment, and wage laborer. OMFI is the only institution in the woreda that provides financial services to the poor households particularly to women (KZFaED statistical abstract bulletin, 2014).

Data Type and Source

Primary data was collected by means of a structured questionnaire responded by OMFI matured clients (being clients 3 to 5 years), incoming clients (clients for 1 to 2 years), and non-clients (loan applicants but yet not given) in Gimbo woreda. At the same time, semi-structured interviews were held with clients to get additional information of respondents' opinions, perceptions and attitudes to verify information given by clients. An interview of different officials and experts was conducted at different levels.

This study was also used secondary data obtained from various sources like reports, manuals, abstracts etc. Mainly quantitative data was used.

Study Population

The study population consists of all poor women in the study area. These include all women clients of OMFIs and women non-clients (loan applicants as control groups).

Sampling Design and Technique

The survey was used cross-sectional data. Under this study, multi-stage and purposive sampling methods were used. At the first stage Gimbo woreda is selected among ten woredas and one town administration in Kaffa Zone because it is one of the two sub-branches of OMFI opened their office early (Bonga and Gimbo, beginners) and compared with Bonga town, Gimbo woreda encompasses large clients. Gimbo woreda has a total of thirty five Kebeles. For the purpose of facilitating its service delivery, Gimbo woreda sub-branch OMFI has five clusters or ketenes (Gimbo, Wush Wush, Kuti, Kayikelo and Gojeb).

In the second stage, three clusters were selected purposively according to the distance from the woreda town, one from the remote, one from the middle and one from the nearest. In the third stage, two kebeles were selected from each cluster randomly. Finally, from these six kebeles, respondents were selected using simple random sampling method from the list file of the clients in the institution.

Similarly, non-clients (control groups) are those applicants to take loan from Gimbo OMFI sub-branch office in the near future after they fulfill the institution selection criteria. To assess the impact of microfinance, it is necessary to compare the outcomes of clients with control groups that have similar characteristics. The control groups are future clients that are very similar to clients in their overall characteristics. The justification for the use of purposive sampling is intended to include women clients only.

Sample Size Determination

To determine the sample size, the researcher tried to consider information from prior studies in the same topic, the available budget at hand for the study and time frame to accomplish this study within the calendar were considered. Prior studies like Haymanot (2007), Balamurgan (2012) and Ahmed (2013) used their sample size 171, 120, and 123 respectively. In addition by taking into account my budget, time and its feasibility, for this study data was collected from 200 women. Of the total samples 115 of them are non-clients which are used as a control group for the study. Regarding the distribution, 15 clients were selected from each 5 kebeles and 20 clients from 1 kebele since it has large number of client compared with the rest 5 kebeles. Non-clients were selected by 1.35 ratio scale to 1 client (1.35:1).

Method of Analysis

The empirical analysis of this research was employed both descriptive statistics and regression analysis. The descriptive statistics was used measure of dispersions (mean, SD, variance), percentages, tables and maps. The regression analysis was employed logit to estimate propensity score matching using STATA software.

Propensity Score Matching (PSM)

Propensity score matching method of impact analysis is a method of comparing microfinance clients and non-clients in the programme areas, where both groups experiences similar communication facilities, socio-economic characteristics, topography, development infrastructure programs and others, to examine whether there is economic variation between program participants and nonparticipants. The assumption behind this study is that at most microfinance benefits the poorest of the poor at the grass root level.

The justification for choice of PSM method over other impact analysis method like DID method was that, PSM method uses only cross-sectional data collected at point of time while DID method needs baseline data. Another justification for the use of PSM method was that, self selection bias can be best controlled or minimized by using PSM and PSM reduces dimensionality. In non-experimental data, PSM compares treatment effects across participant and matched non-participant units. PSM assumes selection bias is based on only observed characteristics (not account for unobserved factors). Because of the above reasons, PSM method is chosen for this study.

There are a range of assumptions to hold PSM method of analysis. To hold PSM, first participants and non-participants have similar distribution of observed characteristics and have similar distribution of unobserved characteristics (if not it causes problems of selection bias), the same set of questionnaire is distributed for both groups with the same economic environment and assumption of unit homogeneity (there is no unobserved heterogeneity).Finally the assumption of conditional independence (there is no reverse causality) must be hold.

The PSM is defined as the conditional probability of receiving treatment (participant) given pretreatment characteristics (Rosenbaum and Rubin, 1983).

Where D= (1, 0) is the binary variable indicating whether a woman has empowered (=1) or not (=0) and X is a multidimensional vector of pre-treatment characteristics (observable characteristics) and p(X) is the propensity score.

Let W i1 and W i0 represents the outcome when women are participant in microfinance and the outcome when not participate respectively. So, the difference between the treated and control group is given as,

Where, W i1 is the outcome if treated and W i0 is the outcome of untreated. Let equation (2) is expressed as B i o to express the causal effect, the treatment variable takes 1 if the individual I receives treatment and 0 otherwise. Then, ATT of an individual I can be expressed as:

The E (Wi0/B=1) from equation (3)is unobservable outcome known as counterfactual. In other words E(Wi0/B=1) is the average outcome of treated individuals had they not received the treatment).

Selection bias is shown by the difference between left hand side of equation (4) and ATT. Since the main parameter interest is ATT, it can be defined as:

In estimating propensity scores, all variables that affect participation in microfinance are included. Therefore, the average treatment effect on those treated conditional on propensity score p(x) is given as:

ATT is the difference between expected outcome values with and without treatment for those who actually participate in treatment. In equation (6), the PSM estimator is the mean difference in outcomes over the common support region, appropriately weighted by propensity score distribution of participants (Caliendo and Kopeinig, 2005).

ATT is average treatment effect on treated (i.e the effect of treatment) if the woman participate in microfinance (B=1) and otherwise (B=0).

According to Becker and Ichino (2002), the assumption of common support region falls between 0 and 1 (i.e. 0p(x) 1). This implies that the test of balancing propensity is performed only on the observations whose propensity score belongs to the common support region of the propensity of treated and control groups. Those individuals that lay outside the common support region would be excluded in treatment estimation and this improves the quality of matching to estimate ATT.

In order to estimate the missing counterfactual outcome for each treated observation different matching estimators are used: Nearest Neighbor matching, Kernel matching, caliper matching and Radius Matching. The selection of matching algorithm is tested using lower value in pseudo R 2 , balancing test (number of insignificant explanatory variables after matching) and better number of matched observation.

By comparing the result of all matching estimators, kernel with bandwidth 0.5 is selected for this study with different criteria. In this regard, kernel matching algorithm matches several nonparticipants with a participant.

Estimation of the Propensity Scores

The probability of women clients to be empowered (women's involvement in major decision making), P i is given as;

The logistic representation of women's involvement in major decision making is;

The probability of women's does not involve in major decision making is given as; 1-Pi= ) =Z i = β 0 +β 1 β 1 +β 2 X 2 +β 3 X 3 +…. +β n X n--.

By taking the error term into consideration, the log odds ratio model becomes Zi = β 0 +β 1 X 1 +β 2 X 2 +β 3 X 3 +...+β n X n +u i (12) Where ✓ P i is the probability of participating in a programme ✓ Z i is a function of explanatory variables (Xi) ✓ X i is the explanatory variables ✓ L i is log of the odds ratio which is linear in X i 's and B's ✓ U i is the disturbance/error term Here Z, takes two possible values i.e. z=1 women are economically empowered means participates in major decision and z=0 if not.

Description of Variables

For the purpose of this study different variables were selected based on economic theory and previous empirical findings from the existing literatures on similar studies. In impact evaluation study, variables choice must be those variables which affect both participants and non-participants (i.e. both treated and non-treated groups share characteristics of X covariates). Heckman et al., (1998), argues that, only variables that affects both program participation and outcomes should be included in the estimation propensity scores. Thus, in this study variable which affect clients OMFI and non-clients are selected depending on observable characteristics of respondents in the study area.

Outcome variables (impact indicators): In this study three outcome variables namely average yearly household income (ayhi), personal cash saving (pcs), and asset ownership and possession are used as an indicator of the impact of OMFI on women economic empowerment. Average yearly household income is a continuous variable which determines women's status in signifying their empowerment. It has positive expected sign. Existence of personal cash savings is also expected positively related with women empowerment. Household assets ownership (ownast) like farm land, house, jewelry and livestock's etc are assumed that positively related with women empowerment.

The dependent variable is women's involvement in major decision making in the family which includes decisions on sales/purchase/rent/repair of house, farm land, livestock's like ox and cows, grains and the like. As a result, women's involvement in major decision making, as a proxy variable is used to indicate the economic empowerment of women. This variable was used in Hashem et al., (1996) as independent variable to explain women's empowerment. Initial wealth: dummy if a woman has initial wealth (=1) and = 0 if a woman has not initial wealth. The expected sign is positive, if there is initial wealth otherwise negative. Chapter -4

VI. RESULT AND DISCUSSION

This section presents both the descriptive and econometric result and findings of the study. The study examined the impact of OMFI on women's economic empowerment based on primary data collected from women clients and non-clients in the study area. The questionnaire was designed in line with the pre-determined objectives of the study and distributed to the sampled respondents. The information given in the questionnaire was checked with semi-structured interview from randomly selected sampled respondents.

General Characteristics of the Respondents

From the total sampled respondents, the data was collected from 196 respondents. Of the total respondents 84 of them are clients of OMFI while remain 112 of them are non-clients. Non-clients are those respondents that came to the organization for loan after they fulfill the requirements but not yet given loan. Regarding the response rate of the questionnaire, 98.8%of client respondent returned the questionnaires while 97.3% of the control groups were returned the questionnaire. Of the total respondents 2% of women were not willing to give information because some of them were on work and some others were not available at the time.

The religion statistics of the respondents show that 73.98%,16.84%, and 9.18% of them are followers of Orthodox, Protestant and Muslim religions respectively. The total sample result of age distribution depict that 27.55% respondents were between the age 20 to 30 while 48.47% of the respondents are between the age 31 to 40 and 14.29% of respondents are between the age of 41 to 50. From the total samples 3.57% of respondents are above the age of 50 years and 6.12% of the respondents don't know their age. The minimum and maximum age of the respondents is 20 and 60 respectively and their mean age is 37. The age distributions of the respondents indicate that most of the respondents are in the working or productive age group.

Source: own computation, 2016

To examine separately, the minimum and maximum age of client respondents' is 20 and 57 where as non-client respondents' age is 20 and 60.

Regarding marital status, the sample result show that 70.41% of the respondents were married whereas out of the total respondents 15.31%, 8.67% and 5.61% of them are widows, single and divorced respectively. The descriptive statistics depict 53.57% of the respondents are headed by their husbands while 41.84 % of the respondents are head of themselves. Out of the total respondents only 4.59 %of respondents responded that they are headed by their family. The mean household head difference between client and non-clients is -0.1686684 with p-value 0.0401 which is significant at 5% level of significance. The result indicates that much of the clients are heads of their family (see Table3 in the appendix). 8,3.57 % them are learned from grade 8 to 12 and 0.51 % of them are above grade 12. The mean education level difference between client and non-non-clients is -0.782237 and the p-value 0.000 (highly significant at 1% of significance level) which leads to reject the null hypothesis that is there is no difference between the groups in women's education level (i.e. clients are better educated than non-clients) (see table 1 in the appendix).

Regarding their (women) spouse education level the sample result depict that 14.29% of their husband are illiterate, 29.08 % of them can read and write, 28.57 % of them are learned from grade 1 to 4, 21.94% of them are learned from 4 to 8 and 6.12% of them are learned from 8 to 12. The mean spouse education level difference between client and non-clients' husband is -0.264881 and the p-value 0.1047 (which is insignificant) that leads to accept the null hypothesis that there is no difference between the groups in spouses' education level (see Table 2 in the appendix). The respondents' family size ranges from 1-10. The minimum and maximum family sizes of clients are 1 and 10 while for non-clients it is 1 and 9. On average, both client and non-client respondents have 5 family sizes. The mean household family size difference between client and non-clients is -0.6325327 and the p-value 0.0262 (which is significant) that leads to reject the null hypothesis that there is no difference between the groups in family size (i.e. clients have less family size than non-clients) (see Table 4 in the appendix).

Others* indicate that decision is made mostly by their husbands or family Respondents asked to explain the impact of OMFI as very-high, high, medium and low. Accordingly 10.84% and 45.78% of the clients explained OMFI has very-high and high impact in improving their saving habits respectively. While 42.17% of clients elucidate that OMFI has medium impact in improving their level of saving. Only two observations reported OMFI has low impact on their decision making. The result is similar with the findings of (Tesfay, 2003;Haymanot, 2007;Gebru and Paul, 2011;Balamurugan, 2012;Gebrat, 2013 andMohamed, 2013;Kato and Kratzer, 2013).

In general, the descriptive statistics indicates that, OMFI increased women's average income, improved their saving habits and improved their participation in major decision making process in the family than those non-clients in the study area. Regarding asset ownership and capital formation, OMFI has limited impact on its clients compared with non-participants. The overall descriptive result depict that OMFI has positively affected its clients in increasing their involvement in major decision making process, improved their level of confidence, self esteem and reduce their poverty than non-program participants.

The result of the above descriptive statistics was strengthened from the interview explanation held. According to sub-branch manger currently OMFI has given special attention to women and efforts are made to benefit women's from our services. As a result, women were benefited from the loan program during the last years and they improved their overall living status. Loan officer explained that,<<I believe that,women were benefited from our loan program and as much as we can we are supporting and encouraging them and many of our member had improved their living condition. Their income is increased. If you see their saving account, for sure, you will understand about their awareness on their saving habits improvement. Generally, I can say that, they are benefited from the loan program in many ways>>.

Source: Own computation, 2016

Concerning the main occupation, the sample result depicts that more than three-fourth of the respondents (79.7%) were engaged in the agriculture sector. Agriculture, being the main occupation in the study area, it is followed by trade activities which accounts about 14.72% of occupation activities in the area. The remain 4.57 % of respondents reply that they are engaged in government sectors like agricultural and health extension workers, teachers and 1.02% were engaged in different works. Separately, 77.11% of client respondents' main occupation is agriculture while for non-client respondent it accounts 81.42%. Trade accounts 19.28% and 11.5% for both client and non-clients respectively. Three clients responded that their main occupation is government employers. Six nonclients occupation is government employee while two of them are engaged in different activities.

Among the total sample, one observation reported that she has been client of OMFI since its establishment which is the maximum period for 15 years. Of the total samples 30% of the respondents were clients since 2000 E.c, while more than 72% of the respondents were been clients since 2004 E.c. The majority of clients' loan size lie between 3000 -5000. The maximum and minimum loan size is 9000 and 1500 during the last five years from recent to back loan cycles. The maximum loan size is determined by OMFI while the minimum size is determined by client request or demand. The descriptive statistics depict that, when the loan cycles increases, the average amount of loan is also increase.

Of the sample taken, 34% of the clients reply that, they take the loan for the purpose of buying ox for their farm activities. On the other hand, 22.78%, 20.25% and 16.46% of clients take their loan for the purpose of buying agricultural input, for fattening (sheep and goat) and to small trade respectively. The remaining 12.66% of the clients use the loan for different purpose like to build/repair their house and for household consumption. Regarding loan repayment, 77.79% of clients reported that they didn't face loan repayment problem. But 22.21% of the client's reply that during the last five loan periods either in one or two loan period they face loan repayment due to die and stolen of ox, sheep, use of their loan for household expenses and illness. They repaid their loan by selling household assets and by borrowing from relatives and neighbors. Regarding group formation, the minimum size of the group is five clients.

The result of all the above tests indicate that the matching algorithm being chosen and used is comparatively best for this data and thus, now it is possible to estimate ATT for clients of OMFI.

Effect on Asset Ownership

Among sampled clients 78% of them have at least one ox and 90% of them have more than two sheep with five maximum sheep. Regarding household utensils, 83% of clients reported that they have cooking utensils and radio while 17% of clients answered that they have full household materials and Radios, Television and DVD player.

Regarding home ownership 9.64% client respondents said that they didn't have house, they are being living in rent-house. These clients are those health extension workers, agricultural extension workers and teachers. 44.58% of clients have ''Sar bet'' while 45.78% of them have ''Korkoro bet''. The client respondents explained that, they owned their house mostly after they were being OMFI client. Regarding house improvements, 19.51%clients' house was not improved while 43.37% are able to build additional houses and 24.39% of clients were able to decorate their house. 12.73% of clients reported that they don't know whether there is improvement or not. Accordingly, 10.84% of the respondents explained that OMFI has ''very-high'' impact on their access and control over assets while 39.76 % of clients reported that the impact is 'high'. 46.99% of clients explained that the impact of OMFI on their access and control over assets is 'medium' and 2.41% answered it has 'low' impact.

Out of 112 non-clients, 7.96% of them have no house and 59.29%, 28.32% and 4.42% of future clients have owned 'Sar bet', 'Korkoro bet' and both 'Sar bet' and 'Korkoro bet' respectively. Of these nonclients 45.28% have no improvement in their house, 14.15% and 6.6% of them have been able to built better house and built additional rooms. 22.64% of respondents were able to decorate their house while 11.32% of them reported that they don't know whether there is improvement or not.

Of 112 future clients 39.82% are very-high interested and 45.13% highly interested to participate in the loan program of OMFI. 14.16% of non-clients have medium level of interest to participate in OMFI loan program while one observation confirms that low level of interest to participate in the program, only for the sake of her neighbors she is going to participate.

The t-test result indicates that, the mean difference on asset ownership between client and non-clients is 0.0803571 and the p-value is 0.1233 which is insignificant at 10% significance level. This leads us to accept the null hypothesis that there is no difference between clients and non-clients in asset ownership (see Table 7 in the appendix).

In general, the above descriptive and t-test analysis depict that OMF has limited impact on access and control over asset between program participants and non-participants. This is because of their unwise use of loan for consumption expenditures and their limited entrepreneurship on the use of loan.

Effect on Income

In order to see the impact on income, respondents' average yearly income was asked. Accordingly, client respondents reported that 8.34 % of them estimate their average yearly income lie between 10001 to 20000 and 1.19 % of the clients earn estimated average yearly income in between 20001 to 30000. The remain 23.8 %, 3.57 % clients income falls between 5001 to 10000 and 30001 to 40000 respectively while 60.71% of clients reported that their income falls under 5000. Their minimum and maximum income is 1000 and 80000 with the mean income of 6131.311.

Similarly, 10.71 %, 11.6% and 2.68 % of non-clients explained that their estimated average yearly income falls between 10001 to 20000, 5001 to 10000 and 20001 to 30000 respectively.75 % of nonclients reported that their average income was less than 5000. The minimum and maximum income of non-clients is 900 and 30000 with the mean income of 7957.619. 92.96% of clients reported that their income was increased because of adequate market for their business, good agricultural season and profitability of their business and 2.77% of clients explained that their income was greatly increased while 4.33% of clients explain that, their income has no change because of illness of the family and dead of livestock like ox and sheep.

Accordingly, 50% of the respondents explains that OMFI has high impact in increasing their income while only 7.32% of clients report that the impact is very high in increasing their average yearly income. 39.02% of clients explained that the impact of OMFI on increasing their income is medium and 2.44% answered it has low impact. A single observation states that OMFI has very low impact in affecting her income. Compared with clients, non-clients income was not increased. Only 32.14% of non-clients reported that their income has shown improvement due to good agricultural season and adequate market.

The t-test result for average yearly household income depict that, the mean difference between clients and non-clients average yearly income is -59094.64 and the p-value is 0.0000 which is highly significant at 1% significance level (see Table 5 in the appendix). This leads to reject the null hypothesis that there is no difference between clients and non-clients average yearly household income. The implication is that clients of OMFI earn better average yearly household income than non-clients. The result is consistent with the findings of (Tesfay, 2003

Effect on Saving

Sampled respondents explained their saving experience before they were client of OMFI as follows. Among 84 clients 92.77 % of respondents explained that they didn't have saving account at any institution before they join OMFI. Only 7.23% of clients reported that they have saving account in CBE with their male partner. 80.52% of clients explained that they haven't knowhow or awareness about saving while 14.29% and 5.19% of the clients indicated that lack of money and distance of financial institutions affect them not to save.

On the other hand, 92.86% of non-clients explained that they haven't saving account at any institution. They said that we opened saving account after the selection or recruit of OMFI agent in the near past decision making to sell/buy land between client and non-clients is 0.4244567 and the p-value is 0.0001 which is significant at 1% significance level. This leads us to reject the null hypothesis that there is no difference between clients and non-clients in decision making (clients are better decision makers than non-clients)(see the table 7.1 in the appendix).

Similarly, the t-test result on decision making to sell/buy ox (domestic animals) indicates that, the mean difference on decision making to sell/buy ox between client and non-clients is 0.8922952 and the p-value is 0.0093 which is significant at 1% significance level. This leads us to reject the null hypothesis that there is no difference between clients and non-clients in decision making to sell/buy ox (domestic animals) (i.e. clients are better decision makers) (see the table 7.1 in the appendix).

From the above descriptive statistics it can be concluded that, clients are better decision makers than non-clients. Thus, their improved or better decision making ability of clients was the result of the loan program which increases their income, saving habits and their overall confidence and status at all.

Estimation Econometric Model

Under this sub-section, the logistic regression model and propensity scores for matching of clients and non-clients were presented. To estimate the effect of propensity scores, logit model is employed because there is no difference on result between logit and probit model (Caliendo and Kopeinig, 2005).

Before looking the econometric regression result, it is better to check the fitness of the model usually the problem of heteroscedascity and multicollinearity. Accordingly, the problem of heteroscedascity which is common in cross-sectional data was checked and solved by robustness of standard error before the estimation of the model.

The problem multicollinearity which is the relationship between continuous explanatory variables and coefficient of contingency (the association between discrete variable) was checked by different tests. To detect multicollinearity problem, variance inflation factor (VIF) was calculated and the result depict that the data had no problems of multicollinearity (see Table 9 in the appendix). Likewise the contingency coefficients were computed to check the association among discrete variables. The value of contingency coefficients lies between 0 and 1 in which 0 indicating no association between the variables and values close to 1 indicates high degree of association. Since contingency coefficient is not greater than 0.75 all discrete variables can be used in the regression analysis (see Table 8 in the appendix). The Pseudo R 2 indicates the overall significance of the model. The model was estimated by STATA 13.0 software using propensity score matching method of analysis.

Determinants of Women's Involvement in Decision Making

The logistic regression model used nine explanatory variables such as age, marital status, head of the household, women's level of education, spouse level of education, number of household size, being member of other microfinance institutions, ecology and amount of initial wealth. The dependent variable is a binary variable taking a value of 1 if a woman is client and 0 if not.

The logistic regression estimate was made to identify factors that affect women's involvement in major decision making in the family. Accordingly the logit regression estimate depict that women's involvement in major decision making is significantly affected by age, women's spouse level of education, number of family size, head of the household, being member of other MFI and amount of initial wealth. But variables like women's level of education, marital status and ecology were insignificant in affecting women's economic empowerment. The result of women's level of education is consistent with Haymanot, (2007)and marital status is consistent with the finding of Gebrat, (2013) in affecting women's involvement in major decision making process.

The result of the model indicates that age of respondents is significantly affects women empowerment at 1% significant level. This is may be because of aged women's relatively can't decide on the household issues and dominate by their husband. The positive relationship between age of respondents and women empowerment is consistent with the finding of Ahmed (2013). If women are head of their family they are better chance to involve and decide on their asset and other family issues. Therefore, the variable head of the household affects women involvement in major decision making significantly at 1% significance level.

Respondent's spouse level of education significantly affects women's involvement in major decision making at 1% significant level. As the spouse's level of education increases their awareness and attitudes towards their wife changes and husbands start to consult their wife on major decision issues in the household.

Number of household size of respondents affects women's empowerment significantly at 10% significant level. The justification is that as family size increases their income will increase by engaging in various income generating activities.

The variable being member of other microfinance institution (credit experience) affects women's empowerment significantly at 1% significance level. The justification is that, women who have member of other microfinance institution have better knowledge how to use the loan and invest and it is positively related with women empowerment. Amount of initial wealth also significantly affects women's empowerment at 5% significant level. Women who have initial wealth have the opportunity to start their business earlier and when combined with their loan, they may have better capital to engage in a better business (see Table 10 in the appendix).

Propensity Scores

From the total sample, propensity score matching estimation result discards three observations from clients but it doesn't discard any observation from non clients. As indicated from table 11 below, 112 of non-clients (untreated) are on common support region and 81 of the clients (treated) are on common support region (see Table 13 in the appendix). The minima and maxima criterion deletes all observations whose propensity score is smaller than the minimum and larger than the maximum propensity scores (Caliendo and Kopeing, 2005 Accordingly, the result of estimated propensity score varies in between 0.000 to 0.998 with the mean of 0.103 for untreated and from 0.119 to 0.999 with the mean of 0.85 for the treated. That is, clients whose estimated propensity scores less than 0.119 and larger than 0.998 are not included in the matching exercise. That is [0.119, 0.999] and [0, 0.998] are propensity scores for treated and untreated respectively. Therefore, by minima and maxima criterion, taking the minimum propensity score from the treated and the maximum score from the untreated forms the common support region. Thus, the common support regions lie between [0.119, 0.998] which show none of observations was dropped from non-clients in the sample (see Table 11 in the appendix). The above graphs depicts that there is wide area in which the propensity score of clients are similar to those non-clients.

Choosing Matching Algorithm

Testing the Balance of Propensity Score and Covariates

After matching, every covariates mean between the two groups in the matched sampled has been reduced and pseudo-R 2 should be relatively low (Caliendo and Kopeinig, 2005). The major aim of propensity score estimation is to balance the distributions of relevant variables in both groups. Below from table 13 before matching age, women level of education (wle), number of household size (nhsize), being member of other microfinance institutions (bmofi), and amount of initial wealth (amtinw) were significantly different for the two groups of respondents. But after matching these significant variables were insignificant which indicates that the differences in covariates mean between the treated and untreated groups was eliminated and now the covariates between the groups is balanced (see Table 14 in the appendix). *** and ** show level of significance at 1% and 5% respectively (before matching ).

The fairly low pseudo-R 2 and the insignificant likelihood ratio tests supports the hypothesis that both treated and non-treated groups have similar distribution in covariates X after matching (i.e. there is complete balance in the characteristics in both groups). After this procedure, we can compare observed outcomes for participants with control groups that lie in the common support region (see Table 14 in the appendix).

Estimating Average Treatment Effect on Treated (ATT)

To meet the objectives of this study, this part evaluates the program's impact on the outcome variable (i.e. average yearly income, personal cash saving and asset ownership) for their significant effect on women clients (participant), after pre-intervention differences were controlled (See table 12 in the appendix). Table 4.16 depict the estimation result of the outcome variables in which out of the three outcome variables two of them (i.e. average yearly income and personal cash saving) are statistically significant while one variable (asset ownership) is statistically insignificant but positive ATT.

Thus, the program intervention has resulted in a positive and statistically significant mean difference between the client and non-clients women in terms of increase in income and cash saving. From the above table, the result of ATT is positive indicating that average yearly income, personal cash saving and owning asset has been improved because of microfinance program in the study area.

Therefore, microfinance program in the study area has been improved women's economic empowerment as shown from table 4.15 and the mean difference value of the outcome variables between client and non-clients women was positive.

Sensitivity Analysis

Since PSM cannot alleviate the potential problem of unobservable variables, sensitivity analysis must be carried out to check the robustness. The sensitivity analysis was carried out on the estimated average treatment effect for the outcome variables and the matching estimator result depict that there is significant effect on the program participants. The sensitivity analysis result (i.e. at e γ =1 up to 1.6) indicates that there was no unobserved variable that affect estimates of ATT or programme participants.

Thus, it can be concluded that the impact estimates of ATT are insensitive to unobserved selection bias and clearly indicates that OMFI has positive impact on its clients (see Table 15 in the appendix).

V. CONCLUSION AND RECOMMENDATION

Summary

Due to the widespread of inequalities, gender discrimination and deprivation of rights, women were vulnerable to poverty and they were denied from various socio-economic activities particularly in LDCs. To end this ignorance, gender equality is a way to promote growth, reduce poverty, equal access to resources and involve in decision making process at different levels which empowers their economic capacity.

Credit is one means of empowering women's economic capacity. MF provision to poor women is taken as a mechanism to reduce poverty and empower women economically. Microfinance provides social cohesion in poor communities, gives opportunity to escape from poverty for the poor particularly women.

The main aim of this study was to analyze the economic impact of Omo microfinance institution in empowering women with a case study in Gimbo woreda, South nation nationalities and peoples region (SNNPR), Ethiopia. Using multi-stage sampling technique, the input data was collected from 6 rural kebeles of which 84 microfinance clients and 112 non-clients with structured questionnaires. Semiinterviews were used to get additional information and cross check information provided in the questionnaire. Control groups were those loan applicants to take loan after they meet the selection criteria of the institution.

The data was analyzed by using both descriptive statistics and econometric models. The econometric model was carried out using propensity score matching method of analysis.

The result of descriptive statistics reveal that 9.64% of clients and 7.96% of non-clients didn't have house, 44.58% of clients and 59.29% of non-clients have Sar bet while 45.78% of clients and 28.32% of non-clients owned Korkoro bet. 10.84% and 39.76 % of client respondents explains that OMFI has ''very-high'' and "high" impact on their access and control over assets. While almost half of clients (46.99%) and (2.41%) clients explained that the impact of OMFI on their access and control over assets was "medium" and "low" respectively. It clearly shows Omo microfinance has limited impact on access and control over their asset or slight differences between program participants and non-participants.

OMFI has significant impact in increasing their average yearly income. 92.96% of client's income is increased duet their participation in the program.Similarly saving has significant impact on the savings of respondents showing difference on their saving habits. 92.92% of non-clients didn't have any saving account at any institution due to their lack of awareness.

The finding of this study on the impact OMFI in improving women's decision making was found significant. 12.05%of clients and 53.1%)of non-clients explained that they didn't participate on decisions to sell or buy land and house. They indicated that the decision is made by their spouse. Thus, clients are better decision makers than non-clients.

The logistic regression result indicate that out of nine explanatory variables six variables were significantly affects women's involvement in major decision making. Age, women's spouse level of education, number of family size, head of the household, being member of MFI and amount of initial wealth were significant variables. Women's level of education, marital status and ecology were insignificant in affecting women's economic empowerment (involvement in major decision making). The estimation of propensity score matching result discards only three observations from clients and none from non-clients. The common support region lies between [0.113, 0.998] which show none of observations was dropped from non-clients in the sample.

From the existing matching algorithm kernel 0.5 was chosen based on low pseudo-R 2 , more insignificant balancing test and by looking better number of observations in the common support region.

The propensity score matching estimation result reveals that out of the three outcome variables average yearly income and personal cash saving are statistically significant in affecting women's economic empowerment, but access and control over asset (asset ownership) was statistically insignificant with positive ATT. Therefore, the program intervention has resulted in a positive and statistically significant mean difference between the client and non-clients women in terms of increase in income and cash saving. ATT is positive indicating that average yearly income, personal cash saving and owning asset has been improved.

Summing up, the findings of this study explicitly depict that, with its limitation, OMFI had a positive impact on women's economic empowerment in the study area.

Recommendations

As a policy indicator, the intervention of microfinance program is expected to improve and empower the living standard of the poor's particularly women at the grass root level and hence reduces poverty. As such the economic status of women and their level of participation in decision making will significantly improve.

Descriptive statistics of this study reveals that there is little difference between clients and non-clients in accessing, owning and control over resources. Similarly the econometric result depict ATT has statistically insignificant effect on women's accesses to resources and control over asset. Thus, it can be concluded that, OMFI has limited impact on women's accesses to resources and control over asset.

Therefore credit provision of OMFI should give priority in asset formation, access to resources, acquire asset and able to control it. Taking these actions reduces their level of poverty and empowers women's economic capacity.

OMFI should take appropriate measures to ensure its organizational mandates, objectives and commit to benefit women from its services by providing training, advisory services and continuous follow-up to assist women's economic empowerment. Linkages with other governmental organizations like women and children offices and agricultural offices should be made to work cooperatively and address problems.

Though, the impact of OMFI on women's average yearly income is significant, efforts should continue to increase access to resources and accumulation of assets that eventually help to wipeout or eliminate poverty and empower them.

In conclusion, additional researches should be carried out to acquire more empirical findings on the impact of OMFIs on women's access to resources, own asset and control over their resources.

Table 3 .