Technology Diffusion, Outcome Variability, and Social Learning: Evidence from a Field Experiment in Kenya

Andrew Crane-Droesch

American Journal of Agricultural Economics, 2018, vol. 100, issue 3, 955-974

Abstract: This article explores the mechanisms through which social learning mediates technology diffusion. We exploit an experiment on the dissemination of biochar, a soil amendment that can improve fertility on weathered and/or degraded soils. We find that social networks transmit information about the average benefits of adoption, but also its risk, and that observed variability inhibits uptake to a greater degree than positive average results engender it. Paradoxically, this relationship is stronger among networks that do not discuss farming, but disappears among farmer networks that do. This is resolved with a simple model of social learning about conditional, rather than unconditional benefit distributions. As farmers observe factors associated with outcomes in their networks, they constrain the distribution of their own potential outcomes. This conditional distribution diverges from the unconditional distribution that the econometrician observes. We conclude that social learning is characterized by implicit model-building by sophisticated decision makers, rather than simple herding towards observed good results.

Keywords: Agriculture; development; Kenya; learning; risk; semiparametric econometrics; social networks; technology adoption (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1093/ajae/aax090 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:100:y:2018:i:3:p:955-974.

Access Statistics for this article

American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().