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.