Technology Diffusion, Outcome Variability, and Social Learning: Evidence from a Field Experiment in Kenya
通过肯尼亚生物炭推广实验，研究发现社会网络不仅传递平均收益信息，还传递风险信息，且观察到的结果变异对技术采纳的抑制作用强于正面平均结果的促进作用，但这一关系在农民网络中消失，表明社会学习是决策者基于条件分布的复杂建模过程。
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.