标题： 基于网络理论的靶向能否促进技术采用？ 显示英文标题

标题： Can Network Theory-based Targeting Increase Technology Adoption?

摘要： 为了促使农民采用一种有生产性的新农业技术，我们在马拉维200个村庄的丰富社交网络数据上应用了简单和复杂的传染扩散模型，以确定要针对和培训的种子农民。 随机对照试验将这些理论驱动的网络定位方法与更简单的策略进行比较，这些策略要么依赖于政府的推广工作人员，要么依赖于社交网络的易于测量的代理（家庭之间的地理距离）来识别种子农民。 我们的结果表明，技术扩散具有一个复杂的传染学习环境，在这种环境中，大多数农民在自己采用之前需要从多个人那里学习。 基于网络理论的定位可以优于传统的推广方法，我们还找到了以低成本实现这些收益的方法。 关键词：社会学习，农业技术采用，复杂传染，马拉维 JEL 分类代码：O16，O13 显示英文摘要

摘要： 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. Keywords: Social Learning, Agricultural Technology Adoption, Complex Contagion, Malawi JEL Classification Codes: O16, O13