Determinants of Loan Repayment Performance in Shashemene City Administration: (The Case of Oromia Credit and Saving Share Company in Shashemene Branch, Oromia Region, Ethiopia)

摘要

Microfinance can be an important element of an effective poverty reduction strategy especially for developing countries. In Ethiopia, there has been a high growing interest in considering micro financing as an important approach for the poor. The services provided by microfinance institutions is needed to enable the poor to reduce their consumption, manage their risks better, build their assets gradually, develop their micro enterprises, improve their income earning capacity, and enjoy an improved quality of life. However, the performance of loan repayment has become a serious problem in the country in general and in the study area in particular. This study was therefore identifying and analyzing the determinants of LRP in MFIs with particular reference to OCSSCO Shashamene branch. A total of 169 respondents were included in the survey and the main data for the study was collected through structured questionnaire administered by trained enumerators. In addition, secondary data was collected from the branch office records. Probit model was employed to analyze the determinants of loan repayment performance of the branch borrowers. A total of sixteen explanatory variables were included in the model’s equation. The result of probit regression confirmed that nine of them; age of the borrowers, level of education, income from activities financed by the loan, suitability of , family size, loan diversion rate, residential area, loan size and grace period were significantly affect LRP while the remaining were found to be insignificant in the model. STATA14.0 software was used to analyze data and t-test and chi-squared test was employed to compare non-defaulters and defaulters with respect to significant explanatory variables. Hence, taking these factors in to account is vital since it provides information enabling to take effective measures aiming at improving LRP in the study area. Equivalently, it would also help the institution and policy makers by providing information on how to exercise their capacity to reduce loan default.