UC Davis Agricultural and Resource Economics

Scott McNiven, University of California, Davis
Daniel O. Gilligan, International Food Policy Research Institute, Washington DC

Access and Learning through Information Networks in Agricultural Technology Adoption and Diffusion: Results from a Partial Population Experiment in Uganda

Date and Location

Monday, October 18, 2010, 4:10 PM - 5:30 PM


We examine how Ugandan farmers respond to their information neighbors when deciding to adopt and disadopt a new agricultural technology, the provitamin A-rich orange-fleshed sweet potato (OFSP). The context is a partial population experiment, in which some households within a social network receive propagable OFSP vines and trainings on OFSP cultivation while others do not. We use variation in the extent to which farmers report relying on treated farmers for farming information prior to the intervention – and thus variation in the information content of the farmer's information network – to identify the effect of having more information neighbors on adoption and disadoption. Relative to the literature, strengths of this analysis include a robust validation of the peer group definition, the ability to use community fixed effects and the ability to use peer characteristics to reduce econometric issues common to studies of social interactions. We present results for both treated and untreated farmers. We find that untreated farmers gain access to OFSP through their treated information neighbors, while that the treated farmers likely get information from farmer group meetings – and thus the importance of social links dissipates over time. In contrast, untreated farmer get information from their treated information neighbors – and thus the importance of social links grows over time as their neighbors attend more farmer group meetings. In addition, we find that untreated farmers tend to disadopt when their treated neighbors disadopt. Large-scale programs to distribute new agricultural technologies often rely on such peer-to-peer technology diffusion to be successful. Our work suggests that diffusion is occurring through social connections and thus can be leveraged when designing such programs.

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