DETERMINANTS OF LOAN REPAYMENT PERFORMANCE OF INDUSTRIAL PROJECTS: THE CASE OF DEVELOPMENT BANK OF ETHIOPIA

Abstract

Once the loan is extended to establishment of projects, getting back the money is challenging in project financing. To address this problem, various studies have been undertaken on loan repayment performance of agricultural projects at Development Bank of Ethiopia. However, previous studies did not specifically carried out loan repayment performance of industrial projects. To address this research gap, the study outlined general objectives to investigate factors affecting loan repayment performance of industrial projects financed by DBE. From a total of 270 industrial projects, 116 industrial projects were taken as a sample. Linked with objectives, the study employed descriptive analysis to evaluate the statistical association of factors affecting loan repayment performance. On top of this, likelihood maximization logit model as well as heteroscedasticity and multicollinearity test were applied to analyze the relative importance of factors on loan repayment performance. In doing so, twenty one variables were used in the model. According to the results from the analysis, age of the borrowers, regional distribution of the project location (project location of Oromia and Addis Ababa), and ratio expatriates to local employees, education level of the general manger (Secondary school), work experience of the general manager, and market destination (Both imported and domestic market destinations) and loan scheme, collateral values and loan size are important factors which significantly affect loan repayment performance. Hence, it is recommended that organizing regular discussion mechanism, recruit expatriates for high-tech projects, comprehensive due diligence assessment on educational level and work experience of existing management staffs , design sound and appropriate marking strategy, improve appraisal planning quality, protect strategic default through reasonable collateral coverage ratio, and properly determine the loan size of the project