Can network theory-based targeting increase technology adoption?

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Economic Growth Center Discussion Paper ; No. 1062

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Economic Development: Financial Markets; Saving and Capital Investment; Corporate Finance and Governance ; Economic Development: Agriculture; Natural Resources; Energy; Environment; Other Primary Products
• Thema: Social Learning ; Agricultural Technology Adoption ; Complex Contagion ; Malawi

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Beaman, Lori ; Benyishay, Ariel ; Magruder, Jeremy ; Mobarak, Ahmed Mushfiq
• Ereignis: Veröffentlichung
• (wer): Yale University, Economic Growth Center
• (wo): New Haven, CT
• (wann): 2018

Weitere Informationen

• Handle: http://hdl.handle.net/10419/197782
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ