Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/197782
Authors: 
Beaman, Lori
Benyishay, Ariel
Magruder, Jeremy
Mobarak, Ahmed Mushfiq
Year of Publication: 
2018
Series/Report no.: 
Center Discussion Paper 1062
Abstract: 
In order to induce farmers to adopt a productive new agricultural technology, we apply simple and complex contagion diffusion models on rich social network data from 200 villages in Malawi to identify seed farmers to target and train on the new technology. A randomized controlled trial compares these theory-driven network targeting approaches to simpler strategies that either rely on a government extension worker or an easily measurable proxy for the social network (geographic distance between households) to identify seed farmers. Our results indicate that technology diffusion is characterized by a complex contagion learning environment in which most farmers need to learn from multiple people before they adopt themselves. Network theory based targeting can out-perform traditional approaches to extension, and we identify methods to realize these gains at low cost to policymakers.
Subjects: 
Social Learning
Agricultural Technology Adoption
Complex Contagion
Malawi
JEL: 
O16
O13
Document Type: 
Working Paper

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