报告题目： On the asymptotic non-equivalence of GMM and EL estimators in models with missing data
主讲人：陈雪蓉博士（西南财经大学）
时间：2016年5月23日（周一）10:00 a.m. - 11:30 a.m.
地点：北院卓远楼305
主办单位：统计与数学学院

摘要： The generalized method of moments (GMM) and empirical likelihood (EL) are popular methods for combining sample and auxiliary information. These methods are used in very diverse fields of research where competing theories often suggest variables satisfying different moment conditions. Results in the literature have shown that the efficient GMM (GMME) and maximum EL (MEL) estimators have the same asymptotic distribution to order root-n and both estimators are asymptotically semi-parametric efficient. In this paper, we demonstrate that when data are missing at random from the sample, the utilization of some well-known missing at a handling approaches proposed in the literature can yield GMME and MEL estimators with non-identical properties; in particular, it is shown that the GMME estimator is semiparametric efficient under all the missing data handling approaches considered but the MEL estimator is not always efficient. A thorough examination of the reason for the non-equivalence of the two estimators is presented. A particularly strong feature of our analysis is that we don’t assume smoothness in the underlying moment conditions. Our results are thus relevant to situations involving non-smooth estimating functions including quantile and rank regressions, robust estimation, the estimation of ROC curves, and so on.

陈雪蓉博士简介：统计学博士（中科院和云南大学联合培养），乔治城大学和密苏里大学博士后，现为西南财经大学统计研究中心助理教授，主要研究领域为分位数回归、非光滑估计方程、生存分析、缺失数据、长度偏差数据、纵向数据、变量选择、药物混合、半参数非参数建模推断。在包括顶级统计学期刊Journal of the American Statistical Association和一流统计学期刊Scandinavian Journal of Statistics，Electronic Journal of Statistics, Statistica Sinica等国际期刊上发表论文数十篇，目前主持国家级课题一项，并参与过多项国家级课题和香港研究资助局课题以及美国国家癌症研究所课题的研究工作，担任过Journal of the American statistical Association，Scandinavia Journal of Statistics，Biometrics，Journal of Multivariate Analysis，Journal of Nonparametric Statistics和Statistics, American Journal of Biostatistics等期刊的匿名审稿人。