时间：2019年06月12日（星期三）13:30-16:30

地点：学院南路，主教楼 107

报告题目：Propensity Score-basedSpline Approach for  Average Causal Effects

报告人：童行伟，北京师范大学统计学院教授、博士生导师。

报告摘要：hen estimating the averagecausal effect in observational studies, researchers have to tackle bothself-selection of treatment and outcome modeling. This is difficult sinceusually there are a large number of covariates that affect people's treatmentdecision and the true functional form in the model is not known. Propensity scoreis a popular approach for dimension reduction in causal inference. We propose anew semiparametric estimation strategy using B-spline based on the propensityscore, which does not rely on parametric model specification. We furtherimprove the efficiency of the estimator by addressing the errorheteroscedasticity. We also establish the asymptotic properties of bothestimators. The simulation studies show that our methods compare favorably withmany competing estimators.  Our methods are advantageous over weightingestimators as it is not affected by extreme weights. We apply the proposedmethods to data from the Ohio Medicaid Assessment Survey (OMAS) 2012,estimating the effect of having health insurance on self-reported health statusfor a population with subsidized insurance plan choices under the AffordableCare Act.

报告人简介：童行伟，北京师范大学统计学院教授、博士生导师。2003年毕业于北京大学概率统计系获统计学博士学位。2003-至今，在北京师范大学工作。2005-2006年在美国密苏里大学Columbia分校从事博士后研究。现为中国现场统计研究会高维数据统计分会秘书长、北京师范大学彩票研究中心研究员。主要从事生物统计、金融统计、稳健统计等领域的教学和研究工作，在Biometrika、Biometrics、Statistica Sinica等国内外知名期刊发表学术论文60余篇，其中SCI论文40余篇，出版教材《高等统计学》1部，译著两部。主持研究国家自然科学基金面上项目、国家自然科学基金重点项目子课题以及教育部科学技术研究重大项目等10余项。

本次活动受中央财经大学2019专题学术讲座项目资助。