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Estimating within-cluster spillover effects using a cluster randomization with application to knowledge diffusion in rural India

机译:使用聚类随机化估计集群内溢出效应并将其应用于印度农村地区的知识传播

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摘要

Spillover effects within randomized clusters pose a challenge for identifying impacts of an individualized treatment. The paper proposes a solution. Longitudinal and intra-household observations are combined in estimating the direct knowledge gain from watching an info-movie in rural India, while randomized village assignment identifies knowledge sharing. Simulations on synthetic data and econometric tests provide support for the estimation method. We find evidence of information sharing, but far less so for disadvantaged groups, such as illiterate and lower-caste individuals; these groups rely more on actually seeing the movie. Our results are consistent with sizeable biases in ordinary least squares, matching or instrumental variable impact estimators that ignore within-cluster spillovers.
机译:随机簇内的溢出效应对识别个体化治疗的影响提出了挑战。本文提出了一种解决方案。纵向和家庭内部观察相结合,以估计通过观看印度农村的信息电影获得的直接知识,而随机分配的村庄则确定了知识共享。综合数据的模拟和计量经济检验为估算方法提供了支持。我们发现了信息共享的证据,但对于文盲和低种姓的弱势群体却很少。这些群体更多地依赖实际看电影。我们的结果与忽略簇内溢出的普通最小二乘法,匹配或工具变量影响估计量中的可观偏差相一致。

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