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Acceptance of Bengal Fasal Bima Yojona by the Farmers: A Study of Purba Burdwan District of West Bengal, India

Acceptance of Bengal Fasal Bima Yojona by the Farmers: A Study of Purba Burdwan District of West Bengal, India

Partha Mukhopadhyay, Partha Pratim Sengupta
Copyright: © 2019 |Volume: 10 |Issue: 2 |Pages: 17
ISSN: 1947-9638|EISSN: 1947-9646|EISBN13: 9781522565994|DOI: 10.4018/IJABIM.2019040107
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MLA

Mukhopadhyay, Partha, and Partha Pratim Sengupta. "Acceptance of Bengal Fasal Bima Yojona by the Farmers: A Study of Purba Burdwan District of West Bengal, India." IJABIM vol.10, no.2 2019: pp.126-142. http://doi.org/10.4018/IJABIM.2019040107

APA

Mukhopadhyay, P. & Sengupta, P. P. (2019). Acceptance of Bengal Fasal Bima Yojona by the Farmers: A Study of Purba Burdwan District of West Bengal, India. International Journal of Asian Business and Information Management (IJABIM), 10(2), 126-142. http://doi.org/10.4018/IJABIM.2019040107

Chicago

Mukhopadhyay, Partha, and Partha Pratim Sengupta. "Acceptance of Bengal Fasal Bima Yojona by the Farmers: A Study of Purba Burdwan District of West Bengal, India," International Journal of Asian Business and Information Management (IJABIM) 10, no.2: 126-142. http://doi.org/10.4018/IJABIM.2019040107

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Abstract

Due to weak logistics, the price of potato has been observed volatile since 2011, at Burdwan, West Bengal, India. Burdwan becomes news headlines for the farmer suicide rate in 2015. The Hon'ble Prime Minister has called for doubling of farmers' income by 2022. In Bengal, it is known as Bengal Fasal Bima Yojona (BFBY). BFBY is free to farmers and the Government of West Bengal pays the premium. Insurance premiums price moves from a government account to account of insurance companies but farmers are remaining cashless and fall into a debt trap due to the low selling price. To bridge the gap and to find the result, data was collected from 701 farmers of 16 Blocks of Purba Burdwan. Eight estimators are considered. The authors continue the study on the basis of analysis done by Mukhopadhyay et al.. Using multinomial logistic regression to analyse the data they observe income, marital status, age, and education which are significant to the loan ‘defaulter' group.

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