Influence of membership to farmer association on maize yields in Bungoma County: A propensity score matching analysis

  • David Kosgei Department of Management Science, School of Business and Economics, Moi University P.O. BOX 3900 Eldoret 30100
Keywords: Farmer association, propensity score matching, maize yield and income


Limited access to extension services, credit facilities, inputs, and markets are important causes for declining food production in sub-Saharan Africa (SSA).  Farmer associations could be pertinent in solving some of these constraints, for instance, in the provision of extension services, credit, and marketing of farmers’ crops.  However, there is a paucity of empirical evidence on the performance of farmer groups in disseminating technologies and information.  This study investigated the influence of belonging to a farmer association on a farmer’s maize yield and income among smallholder farmers in Bungoma County.  The study employed a descriptive survey design to collect data from the farmers. The target population was all the 498 members of Bungoma Small-Scale Farmers Forum farmer associations who were the experimental group and a similar number of neighbouring farmers who were non-members which formed the control group. Simple random sampling was used to select the 223 respondents.  Propensity score matching was used to minimize selection bias. Farmer associations were dominated by younger, more educated and female members.  The average treatment effect (ATT) for yield and maize income was 325 Kg/ha (z=3.45, p=0.001) and Kshs 15 814 (z=2.46, p=0.014), respectively, showing that membership of farmer associations had a significant influence on the farmers’ maize yield and income.  The study recommends that farmer associations and other cooperative movements should be increased and strengthened in order to boost farmers’ crop yields and incomes by the agriculture department of the county government. 


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How to Cite
Kosgei, D. (2019, September 17). Influence of membership to farmer association on maize yields in Bungoma County: A propensity score matching analysis. African Journal of Education,Science and Technology, 5(2), Pg 101-110. Retrieved from