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摘要翻译：
为了引导农民采用一种新的农业技术，我们在马拉维200个村庄丰富的社会网络数据上应用简单和复杂的传染扩散模型来识别种子农民，并对其进行新技术的培训。一项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了比较，这些策略要么依赖于政府推广人员，要么依赖于社会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。我们的研究结果表明，技术扩散是一个复杂的传染学习环境，在这种环境中，大多数农民在采用自己之前需要向多个人学习。基于网络理论的目标定位可以比传统的扩展方法更有效，我们确定了政策制定者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，马拉维果冻分类代码:O16，O13
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英文标题：
《Can Network Theory-based Targeting Increase Technology Adoption?》
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作者：
Lori Beaman, Ariel BenYishay, Jeremy Magruder, Ahmed Mushfiq Mobarak
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：General Economics 一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
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
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PDF链接：
https://arxiv.org/pdf/1808.01205
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