Determinants of Successful Loan Repayment Performance in Project Financing:The Case of the Development Bank of Ethiopia

Masters Thesis from the year 2018 in the subject Business economics - Investment and Finance, language: English, abstract: This study assesses the determinants of successful loan repayment performance of project financing in the case of Development Bank of Ethiopia. The study uses explanatory design and quantitative research approach. Secondary data was used. The collected data were taken from individual borrowers files. Hence, the total sample size was seventy-five (75), of which 40 (53%) were successful financed projects (non-defaulters), whereas the rest 35 (47%) were non-successful ones (defaulters). The data was analysed via correlation followed by logistic regression model using SPSS version 20. The independent variables used in the study are accessibility of market, amount of loan, availability of raw material, distance from project location to raw material destination, distance from project location to output product market, educational level, equity debt ratio, loan processing time, managerial experience of project manager, number of project follow-up, project implementation period, type of management and type of market for the commodity financed. In the study, a logistic regression model was used to identify variables which determine successful loan repayment performance. The paper reveals that the managerial experience of project managers, loan processing time, educational level, number of project supervisions/ follow-ups by the bank, delay in project implementation period and type of management for the financed projects were statistically significant determinant of loan repayment performance of DBEs financed projects. This study suggests that Development Bank of Ethiopia better intensify its project monitoring and follow-up work in order to make well-informed decisions and provide technical assistance for its credit-assisted projects; give due attention to minimize the bureaucracy that delays the loan processing time; critically analyse the