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                <text>Faculty Publications</text>
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    <name>Article</name>
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              <text>Keerthikumara, S.M.; Saikia, Bondita; Hiremath, Channaveerayya</text>
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          <name>Title</name>
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              <text>Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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              <text>Asian Journal of Agriculture;Volume;9;Issue;2;pp.377-390</text>
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              <text>&lt;a href="https://doi.org/10.13057/asianjagric/g090205" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.13057/asianjagric/g090205&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105018127663?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105018127663?origin=resultslist&lt;/a&gt;</text>
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              <text>Keerthikumara S.M., School of Commerce, Christ University, Karnataka, Bengaluru, 560029, India; Saikia B., Centre for Economic Studies and Policy, Institute for Social and Economic Change, Karnataka, Bengaluru, 560072, India; Hiremath C., School of Commerce and Management, Garden City University, Karnataka, Bengaluru, 560049, India</text>
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              <text>Keerthikumara SM, Saikia B, Hiremath C. 2025. Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment. Asian J Agric 9: 377-390. Indian farmers continue to face structural distress driven by low income, high indebtedness, and inadequate risk protection. This study investigates the interrelationship between landholding size, agricultural credit, indebtedness, and crop insurance uptake using state-level secondary data from 2016 to 2023, drawn from Agricultural Statistics at a Glance, PMFBY/RWBCIS dashboards, and NCRB reports. Using descriptive statistics, linear regression, and paired t-tests, we identify key macro-level trends across 20 major Indian states. Results show that marginal and small farmers (less than 2 hectares) account for over 62.7% of all indebted farm households, but receive only 38.5% of total institutional agricultural credit. A bivariate regression reveals that a ?1,000 increase in monthly farm income is associated with a reduction of 1,314 indebted households (?=-0.445, p=0.016). Despite substantial credit disbursal in high-debt states like Andhra Pradesh and Telangana, farmer debt remains elevated, underscoring that credit alone does not reduce vulnerability. Crop insurance enrollment increased after the 2020 policy shift from mandatory to optional participation among loanee farmers, yet the change was not statistically significant (p=0.099). Actuarial analysis reveals that in several states, claim settlement ratios remain below 50%, with high premiums and delayed payouts fueling distrust. The study recommends fully subsidized premiums for marginal farmers, region-specific pricing, improved claim transparency, and financial literacy integration with agricultural extension. Effective risk mitigation in agriculture must go beyond insurance and integrate income and credit reforms to ensure equitable protection for Indias most vulnerable farmers.  2025, Smujo International. All rights reserved.</text>
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              <text>Actuarial performance; crop insurance; farmer indebtedness; landholding size; regression analysis</text>
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              <text>Smujo International</text>
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              <text>ISSN: 25804537;</text>
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              <text>All Open Access; Gold Open Access</text>
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