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光华讲坛——社会名流与企业家论坛第3211期

发布时间:2014-03-13

查看次数:6813

时间: 2014年03月14日02:30-04:00

地点:柳林校区颐德楼H513

主题:Estimating Conditional Average Treatment Effects

主讲人:台湾中央研究院助理研究员 许育进

主持人:西南财经大学 郭萌萌副教授

时间:2014年3月14日下午2:30-4点

地点:柳林校区颐德楼H513

主讲人简介:

许育进,2010年毕业于美国德州大学奥斯汀分校经济系,现为台湾中央研究院助理研究员。他的主要研究方向为计量经济学理论。他在Journal of Econometrics, Journal of Business and Economic Statistics, Econometrics Journal, Economics Letters, Journal of Financial Econometrics, Journal of Empirical Finance, 等英文期刊上发表论文多篇。

内容提要:

This paper considers a functional parameter called the conditional average treatment effect (CATE), designed to capture heterogeneity of a treatment effect across subpopulations when the unconfoundedness assumption applies. In contrast to quantile regressions, the subpopulations of interest are defined in terms of the possible values of a set of continuous covariates rather than the quantiles of the potential outcome distributions. We show that the CATE parameter is nonparametrically identified under the unconfoundedness assumption and propose inverse probability weighted estimators for it. Under regularity conditions, some of which are standard and some of which are new in the literature, we show (pointwise) consistency and asymptotic normality of a fully nonparametric and a semiparametric estimator. We apply our methods to estimate the average effect of a first-time mother's smoking during pregnancy on the baby's birth weight as a function of per capita income in the mother's zip code. For non-white mothers, the average effect of smoking is predicted to become stronger (more negative) as a function of income.