Factors Affecting Rural Medium-term Loan Repayment: Evidence from a South African Development Finance Institution

Poor loan repayment performance experienced by many development finance institutions (DFls) has placed an increasing financial burden on these agencies and governments, with default rates ranging from 27 to 60 per cent in African countries such as Ghana and Nigeria (Okorie, 1986). Lugemwa and Darroch (1995) reported a default rate of 40 per cent for small-scale seasonal credit borrowers at the Transkei Agricultural Bank. Without an adequate flow of funds, the capacity of the DFis to provide more funds in the future is undermined, as financial success depends on a good loan recovery rate. Past African studies of loan repayment performance have focused on determinants of a binary loan outcome where loans were either current or in default. Loan repayment was positively related to factors such as timeliness of disbursement, enterprise profitability, additional sources of income, established previous loan history and lower client debt-asset ratios (Okorie, 1986; Vigano, 1993; Lugemwa and Darroch, 1995). The above analyses ignore another dimension of the loan repayment problem, namely loans that are repaid in arrears. These can have considerable impacts on DFI liquidity management over time and hence should be considered when analysing loan repayment (Aguilera-Alfred and Gonzalez-Vega, 1993). To date, no research on loan performance in a DFI using multiple loan repayment categories has been done in South Africa. This study therefore aims to use a multiple category response model to estimate factors influencing medium-term loan repayment performance at a South African DFI (which for confidentiality purposes may not be named). This DFI is a parastatal organization financing small business, agricultural/rural development and housing predominantly in the former homeland areas of KwaZulu-Natal, South Africa. It obtains funds primarily from the Development Bank of Southern Africa at concessional interest rates, and has recently also begun actively to mobilize savings. Lenders often have limited information on borrowers and so may select clients who are more risky than they believe, leading to major repayment problems (the adverse selection problem) (Barry et al., 1995). This study will