Adoption of Crop Insurance by Smallholder Farmers: Farm-Level Evidence from India

The paper aims to analyse the extent and determinants of smallholder farmers’ adoption of crop insurance. The study conducted a primary survey and collected data from farmers in a drought-prone area of Karnataka state in India using a structured questionnaire. The study has applied a binary logistic regression model to identify the determinants of crop insurance adoption. Empirical results reveal that though most farmers experienced crop loss, only a small percentage subscribed to crop insurance regularly. Lack of money to pay premiums and lack of information are the most common reasons for not subscribing to crop insurance schemes. Further, farmers feel the premium is expensive and do not receive the promised compensation due to the stringent eligibility rules. Most farmers who received compensation think the money is inadequate to cover the cultivation cost. Farmers feel each farm should be treated as a unit against the area-based insurance concept, and more crops should be brought under insurance. They also highlighted the need to further subsidise the premium. Results of the logistic regression confirm that socially marginalised groups and farmers practising agriculture as an ancestral profession are less likely to insure their crops.

Authors

Publication Details

Journal
Research on World Agricultural Economy
Published
2024-10-16
DOI
https://doi.org/10.36956/rwae.v5i4.1197
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adoption of Crop Insurance by Smallholder Farmers: Farm-Level Evidence from India

Rajesh Acharya H
Research on World Agricultural Economy
Agricultural risk and resilience
article

Adoption of Crop Insurance by Smallholder Farmers: Farm-Level Evidence from India

Rajesh Acharya H
article en

Abstract

The paper aims to analyse the extent and determinants of smallholder farmers’ adoption of crop insurance. The study conducted a primary survey and collected data from farmers in a drought-prone area of Karnataka state in India using a structured questionnaire. The study has applied a binary logistic regression model to identify the determinants of crop insurance adoption. Empirical results reveal that though most farmers experienced crop loss, only a small percentage subscribed to crop insurance regularly. Lack of money to pay premiums and lack of information are the most common reasons for not subscribing to crop insurance schemes. Further, farmers feel the premium is expensive and do not receive the promised compensation due to the stringent eligibility rules. Most farmers who received compensation think the money is inadequate to cover the cultivation cost. Farmers feel each farm should be treated as a unit against the area-based insurance concept, and more crops should be brought under insurance. They also highlighted the need to further subsidise the premium. Results of the logistic regression confirm that socially marginalised groups and farmers practising agriculture as an ancestral profession are less likely to insure their crops.

Research on World Agricultural Economy
Openalex Percentile: Top 76%
Agricultural risk and resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.