Purpose: Evaluating a portfolio of agricultural loans has become an important issue in recent years primarily due to a large number of loan defaults. The purpose of this paper is to investigate the factors influencing credit repayment behavior of farmers in Karnataka. Design/methodology/approach: The study is based on secondary data of 590 farmers collected from a private bank in the state of Karnataka, India. Binary logistic regression and multinomial regression analysis was carried out to estimate the probability of non-payment of a loan. Findings: The results of the regression confirm a significant relationship between non-repayment of agricultural credit and characteristics of borrowers such as the age, years of banking relationship, yield of the crop, distance to bank branch, size and tenure of the loan, farm size and leverage and efficiency ratio. Practical implications: The factors predicted by the model do certainly help in improving the decision-making process in agricultural lending. A rigorous assessment of family responsibilities, farm size, credit-to-asset ratio, interest burden on the farmers and farm income is suggested to reduce the probability of doubtful assets. Originality/value: The studies that predict default risk in agricultural loan are limited in India. This is one of the few studies that estimate the determinants of substandard and doubtful categories of credit in a private sector bank.
All Science Journal Classification (ASJC) codes
- Agricultural and Biological Sciences (miscellaneous)
- Economics and Econometrics
- Strategy and Management