The role of microfanance institutions in improving livelihood: In case of Oromia Credit and Saving Share Company in Agaro Town, Jimma Zone

Seminar paper from the year 2013 in the subject Business economics - Operations Research, grade: A, , language: English, abstract: Livelihoods are 'means of making a living', the various activities and resources that allow people to live. It comprises the capabilities, assets (including both material and social) and activities required for a means of living. Thus, microfinance programs have been considered as one of the main instruments in livelihood improvement in recent development agenda. Microfinance comprises the provision of financial services including credit and other facilities like savings, insurance, and transfer services to poor household. The study was conducted in Geniji-Dalecho and Bulbulo kebeles among 35 target kebeles of the OCSSCO. The main objective of the study is to identify the contribution of OCSSCO in improving household livelihood through providing credit. Further, the study used both primary and secondary data sources. The primary data was collected with semi-structured interview and focus group discussion from sampled respondents; whereas, secondary data gathered from different documents of the microfinance institution that exists in the study area. Stratified random sampling was used to select 60 respondents (35 beneficiaries and 25 non-beneficiaries) based on the principle of probability proportional to size (pps). Generally, Microfinance Institutions have an explicit potential that intends to improve the livelihoods of households. While improving livelihood, microfinance (OCSSCO) credit service increases the income of the clients; which, in turn, enable them educating their children and improves their nutritional status. Inferential statistics such as crosstabs; independent sample t-test and custom table are used in data analysis. Descriptive statistics like frequency, percentage, mean and standard deviation were employed to analyze the data. Chi-square (for categorical variables) and t-test (for continuous variables) were used to see