Trend, pattern and determinants of crop diversification of small holders in West Bengal: A district-wise panel data analysis
Author(s) -
Mithiya Debasis,
Mandal Kumarjit,
Datta Lakshmikanta
Publication year - 2018
Publication title -
journal of development and agricultural economics
Language(s) - English
Resource type - Journals
ISSN - 2006-9774
DOI - 10.5897/jdae2018.0921
Subject(s) - diversification (marketing strategy) , agricultural diversification , panel data , agricultural economics , population , geography , crop insurance , agriculture , economics , business , marketing , archaeology , econometrics , demography , sociology
Crop diversification is one of the most important risk management and income enhancing strategies for farmers. The study investigates the pattern, trend, and factors influencing crop diversification in different districts of West Bengal, based on secondary data. The Simpson index has been used to estimate diversification. The results show that all the districts of West Bengal and the state as a whole have exhibited a higher crop diversification during new millennium than the nineties. Both the supply side and demand side variables have been found to influence crop diversification. These variables include rural literacy rate, the percentage of urban population to total population of the district, relative earning from high-value crops (HVC) than cereals, the market density of a particular region, the percentage of small landholders and area under high yielding varieties (HYV) of food grains. The magnitude of rainfall and extension of crop insurance facility also have a significant impact on crop diversification. The government should come forward with suitable policies to encourage crop diversification. These policies may encompass the development of rural infrastructure, enhancement of rural literacy rate, the extension of crop insurance facilities and above all, the development of suitable price policy in favor of high-value crops. Key words: Crop diversification, Simpson’s index, panel data regression, high-value crop, smallholder.
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