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@article{192768,
author = {Dr Muneer Hasan},
title = {Cost–Benefit Analysis of Institutional Credit and Subsidy Schemes on Small and Marginal Farmers in Madhya Pradesh},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {9},
pages = {2842-2848},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=192768},
abstract = {Institutional agricultural credit and subsidy schemes are among the most important public interventions for supporting small and marginal farmers (SMFs) in India. Madhya Pradesh has experienced expanded coverage of formal credit (crop loans/KCC/term loans) and multiple subsidy-linked supports (input subsidy components, capital subsidy, insurance premium support, interest subvention, and DBT-routed benefits). However, evidence on the net economic benefit to SMFs, after accounting for transaction costs, delays, repayment burden, and scheme-access frictions, remains limited at the state level. This study conducts a cost–benefit analysis (CBA) of institutional credit and subsidy schemes on SMFs in Madhya Pradesh using primary survey data from 240 farmers across six districts, combined with secondary scheme parameters. A CBA framework is operationalized through Net Benefit (NB), Benefit–Cost Ratio (BCR), and Net Present Value (NPV) under alternative scenarios (timely vs delayed benefits; low vs high transaction costs; normal vs stress year). Results indicate that while subsidies and interest subvention improve short-term liquidity and reduce effective cost of capital, net benefits vary significantly by irrigation access, market distance, and administrative friction. The average BCR exceeds 1 for most SMFs under timely delivery, but falls toward unity in remote blocks due to higher transaction costs and delayed receipts. The study proposes policy interventions for improving last-mile inclusion and maximizing welfare impacts.},
keywords = {Cost–Benefit Analysis, Institutional Credit, Subsidy Schemes, Small and Marginal Farmers, NPV, BCR, Madhya Pradesh.},
month = {February},
}
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