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| dc.contributor.author | Fentahun Tadesse | |
| dc.date.accessioned | 2020-10-13T11:25:17Z | |
| dc.date.available | 2020-10-13T11:25:17Z | |
| dc.date.issued | 2020-10-13 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/11353 | |
| dc.description.abstract | ABSTRACT In Bahir Dar city, there is a mortgage repayment problem, almost 30% of mortgage finance is not collected back on time. In addition, the studies undertaken on, factors that affect loan repayment performance of mortgage loans are scarce in the study area.This paper was analyzing the mortgage repayment performance of borrowers in Bahir Dar city. The main specific objectives of this study were the determinants of borrowers’ repayment performance, measure the association of borrowers’ profile and loan contents on borrowers’ outstanding balance, and identify the challenges and prospects of borrowers to make mortgage payments. Two-stage-sampling methods were used to draw representative borrowers. Cross-sectional data were collected using a schedulequestionnaire and secondary data were collected using a structured document review mode. Both descriptive statistics and econometric models (binary logit models) were used to analyze data at a borrower level. The logistic regression model estimated the factors influencing the likelihood of borrowers to default. The results of the Logistic regression model show that the age of the borrowers LTV, marital status, interest rate and educational qualification (high school, and college and above relative to illiterates) were significant at (P<0.05). In addition, the family size was found to be significant at (P<0.01), and educational qualification was (Read and write only and Elementary relative to illiterates) significant at (P<0.10). The correlation test shows an outstanding balance of the borrower has an association with gender, educational qualification, family size, loan amount repaid, LTV, and the interest rate, at least greater than 90% level of confidence. The majority of respondents identified loss of collaterals and denial of future loans as major effects of loan default. Further, this study recommends the lender institution should involve borrowers in reviewing loan repayment terms, effective monitoring of loans, credit training programs and where necessary and available the use of mortgage insurance. Keywords: Mortgage Default, Collateral, LTV, Logistic regression, Loan Repayment, default probability. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | LAND ADMINISTRATION | en_US |
| dc.title | Determinants of Mortgage Repayment Performance: A Case of Three-Selected Institutions in Bahir Dar City | en_US |
| dc.type | Thesis | en_US |
