Abstract
Credit is used as an instrument to raise the capital required to increase farm productivity, income and welfare of farmers, particularly small and marginal farmers who lack the capital to buy necessary inputs in time for agricultural operation. But the question of whether the goals of credit policies were met still remains unanswered. This study, therefore, attempted to estimate the effect of farm credit on investment, input expenditure, income and other welfare indicators using national-level farm household survey data. We used the logit function to estimate the determinants of credit access and the propensity score matching algorithm to estimate the effect of credit policies. Results revealed that only 33% of farmers have access to credit facilities and that middle-aged farmers and farmers with a larger farm size have shown a higher probability of accessing credit facilities, whereas farmers from underprivileged castes have shown the least probability of credit access. Nevertheless, credit access, overall, has significant positive effects on farm investments, such as land-building, livestock and machinery. It also has a significant positive effect on the farm revenue expenditure, including the expenditure on seeds, machinery, labour, irrigation, plant protection chemicals and livestock inputs. As a result, credit access has an incremental effect on farm income per hectare, livestock income and monthly consumption expenditure. The results imply that although farm credit policies have improved the welfare of beneficiary farmers, the credit distribution system seems to be inefficient as more than 60% of farmers do not have access to credit. This demonstrates that there is a need for inclusive and holistic policy interventions to include all farmers in the credit system, specifically offering term loans to small and marginal farmers. Apart from this, it is also suggested that simplified crop loan and Kisan Credit Card facilities be made available to tenant farmers.
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Notes
A confounding variable is a variable other than desired one being studied that is associated with both the output variables and the factor being studied. In this study, confounding variables (e.g., age, education, farm size, etc.,) may distort the effects of credit access on the output variables in question (Austin, 2011).
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Ramasamy, P., Malaiarasan, U. Agricultural credit in India: determinants and effects. Ind. Econ. Rev. 58, 169–195 (2023). https://doi.org/10.1007/s41775-023-00187-8
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DOI: https://doi.org/10.1007/s41775-023-00187-8