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Estimation of Average Treatment Effect From Cross Sectional Dependent Data
发布时间:2017-12-04     点击次数:
报告题目: Estimation of Average Treatment Effect From Cross Sectional Dependent Data
报 告 人: 艾春荣 教授(中国人民大学大数据学院)
报告时间: 2017年12月10日 8:30--9:30
报告地点: 数学院三楼报告厅
报告摘要:
In this paper, we extend the usual treatment effect model to cross sectionally dependent data. The extension requires new way of modeling as the traditional latent variable framework no longer works. We define the average treatment effect coefficient that includes the direct effect and the indirect effect caused by general equilibrium. Under some sufficient conditions, we derive the asymptotic properties. A small scale simulation study reveals that the proposed estimator has practical value.
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