Factors Influencing Participation of Farmer in Contract Farming in Narsingdi District of Bangladesh
A. Taslim, M. R. Karim, M. S. Rahman
Asian Journal of Agricultural Extension, Economics & Sociology · pp. 569–576 · Published 3 Dec 2021
10.9734/ajaees/2021/v39i1130785Abstract
Aims: Contract farming (CF) has been used extensively to integrate agricultural value chain both in the developed and developing countries. Participation in CF is associated with increased farm productivity and farmer income. Therefore, the purpose of this study was to analyze socio-economic factors affecting farmer’s participation in contract farming. Study Design: The selected 15 socio-economic factors were used to determine the impact on farmer’s participation in contract farming. Besides, the socio-demographic profile of the farmers in the study area was discussed. Place and Duration of Study: The study was conducted upon contract and non-contract farmers of Shibpur upazila under Narsingdi district of Bangladesh. The duration of the study was from July, 2019 to December, 2020. Methodology: The study used nationally-representative data of smallholder vegetable farmers in Shibpur upazila of Narsingdi district. The data were collected from 75 contract farmer and 125 non-contract farmer of Shibpur upazila. Binary logistic regression was used to analyze fifteen factors that potentially affected farmers’ decision to participate in CF and descriptive statistics were used to analyze the socio-demographic profile of the farmer. Results: The study found that farmers education, wife’s occupation, family size, labor, fertilizer use, training, savings and income were the significant factors in the model and farmers occupation, other family member's occupation, income source, land type, size of land, experience and storage place were non-significant predictors using P<0.01 and P<0.05 threshold. Conclusion: Farmer’s education, female head's occupation, family size, land type, size of land holdings, labor use, type of fertilizers being used, training or technical knowledge and average monthly income of the respondents had a positive influence on farmer’s decision.
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