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Gendered Social Networks, Agricultural Innovations, and Farm Productivity in Ethiopia

Daniel Ayalew Mekonnen, Nicolas Gerber and Julia Matz ()

World Development, 2018, vol. 105, issue C, 321-335

Abstract: This paper examines the existence of social learning in agriculture in Ethiopia. To be specific, we use a “random matching within sample” technique to collect data on social networks and to elicit details of the relationships and information exchange between network members. We find that shared kinship or membership in certain groups, informal forms of mutual insurance, and having frequent meetings with network members are all associated with a higher probability of forming an information link with a network member. Furthermore, we find evidence for a statistically significant and positive relationship between networks and the adoption of row-planting as well as yields for both male and female networks. However, the evidence for an inverse U-shaped relationship of social learning, that is, between the number of adopters in the network and the adoption of row-planting, is strongest for female networks. Our results, thus, suggest that extension services and other programs that promote agricultural innovations and seek yield improvement can benefit from social networks but that their success depends on identifying the “right” networks, such as those of female household members in the case of row-planting.

Keywords: social networks; gender; innovations; agriculture; Ethiopia; Africa (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1016/j.worlddev.2017.04.020

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