Credit constraints and rural farmers' welfare in an agrarian economy

This study aims to determine the impact of credit constraints on wheat farmers' welfare. For this study, data on 575 wheat farmers were collected through a simple random sampling technique. The treatment-effect model was used to find the effect of credit constraints on the farmers' welfare. In addition, to control for the problem of endogeneity, ordinary least squares and logistic regressions were employed. Farmers' welfare was measured by as consumption. The results show that constrained farmers cultivate 2.8-4.1% more area of land than unconstrained farmers but that the spending and income per capita of credit-constrained farmers are 18.9 to 13.8% lower, respectivley, than those of unconstrained farmers. Moreover, the results indicate that the welfare and income of credit-constrained farmers are influenced by age, the interest rate, area of land, and family size. An increase in the area of land enhances wellbeing and returns for the constrained farmer, which is in contrast to the unconstrained farmer. The results show that credit constraints have a negative impact on farmers' welfare and income. Better welfare may only be achieved if credit is supplied to credit-constrained farmers. Furthermore, this study has potentially significant implications. First, the negative impact of the interest rate suggests that the State Bank of Pakistan should modify agricultural credit policies, particularly to design a flexible interest rate for farmers. Second, the central bank should amend the agricultural credit limits based on the current financial needs of the agricultural market when the rate of inflation is high and the impact of agricultural crises is long and drawn-out. Third, the government should launch an agricultural Islamic bank in the study area. This Islamic bank would support religious farmers who are constrained due to objections to interest, and it would relax the farmers' credit constraints as well as help them to increase welfare and income.