论文标题
网络倾向分数：溢出，同质和选择治疗
The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment
论文作者
论文摘要
我在一个具有异质治疗效果，溢出效应，选择后选择和网络形成的连贯模型中建立了原始条件。我确定在最小的交换性条件下的平均部分影响。如果社交互动也是匿名的，我将获得三维网络倾向分数，表征其支持条件，将其与网络伪对象的最新工作相关联和研究扩展。我为随机系数模型提出了一个两步半参数估计器，该模型是一致且渐近地正常的，随着网络的数量和大小的增长。我将估计量应用于乌干达的政治参与干预措施和印度的小额信贷申请。
I establish primitive conditions for unconfoundedness in a coherent model that features heterogeneous treatment effects, spillovers, selection-on-observables, and network formation. I identify average partial effects under minimal exchangeability conditions. If social interactions are also anonymous, I derive a three-dimensional network propensity score, characterize its support conditions, relate it to recent work on network pseudo-metrics, and study extensions. I propose a two-step semiparametric estimator for a random coefficients model which is consistent and asymptotically normal as the number and size of the networks grows. I apply my estimator to a political participation intervention Uganda and a microfinance application in India.
