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Semiparametric estimation of average treatment effect through a random coefficient dummy endogenous variable model

Science China Mathematics 2014年第11期57卷 2415-2428页

作者： ZHOU YaHong WANG LiMing HE XiaoDan School of Economics Shanghai University of Finance and EconomicsKey Laboratory of Mathematical Economics (SUFE) School of Statistics and Management Shanghai University of Finance and Economics School of Economics Shanghai University of Finance and Economics

This paper provides an estimation procedure for average treatment effect through a random coefficient dummy endogenous variable model. A leading example of the model is estimating the effect of a training program on earnings. The model is composed of two equations:an outcome equation and a decision *** the linear restriction in outcome and decision equations,Chen(1999) provided a distribution-free estimation procedure under conditional symmetric error distributions. In this paper we extend Chen's estimator by relaxing the linear index into a nonparametric function,which greatly reduces the risk of model misspecification. A two-step approach is proposed:the first step uses a nonparametric regression estimator for the decision variable,and the second step uses an instrumental variables approach to estimate average treatment effect in the outcome equation. The proposed estimator is shown to be consistent and asymptotically normally distributed. Furthermore,we investigate the finite performance of our estimator by a Monte Carlo study and also use our estimator to study the return of college education in different periods of China. The estimates seem more reasonable than those of other commonly used estimators.

关键词：模型参数估计治疗效果随机系数平均渐近正态分布培训项目分布自由模型假设

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A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data

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Science China Mathematics 2013年第11期56卷 2367-2380页

作者： LIU XiaoYu ZHANG WeiPing Department of Statistics and Finance School of ManagementUniversity of Science and Technology of China

Modeling the mean and covariance simultaneously is a common strategy to efciently estimate the mean parameters when applying generalized estimating equation techniques to longitudinal *** this article,using generalized estimation equation techniques,we propose a new kind of regression models for parameterizing covariance *** a novel Cholesky factor,the entries in this decomposition have moving average and log innovation interpretation and are modeled as linear functions of *** resulting estimators for the regression coefcients in both the mean and the covariance are shown to be consistent and asymptotically normally *** studies and a real data analysis show that the proposed approach yields highly efcient estimators for the parameters in the mean,and provides parsimonious estimation for the covariance structure.

关键词：协方差结构移动平均线均值参数纵向数据子模型渐近正态分布回归模型回归系数

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一类线性结构模型参数的极大似然估计及拟极大似然估计的渐近性质

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系统科学与数学 1984年第2期 128-135页

作者：王成名广西师范大学数学系

不少作者探讨过参数的极大似然估计（以下简记为 MLE）的渐近性质.一些统计工作者还把极大似然估计方法用于估计部分参数.即在参数为θ=（θ′1,θ′2）′的模型中,当不易求出θ的 MLE,而我们的目的是估计 θ2时,可将似然函数中其余的... 详细信息

不少作者探讨过参数的极大似然估计（以下简记为 MLE）的渐近性质.一些统计工作者还把极大似然估计方法用于估计部分参数.即在参数为θ=（θ′1,θ′2）′的模型中,当不易求出θ的 MLE,而我们的目的是估计 θ2时,可将似然函数中其余的参数θ1用它们的估计（?）来代替,然后极大化这个经代换后的似然函数来求得 θ2的估计.这就是所谓拟极大似然估计（以下简记为 PMLE）.

关键词：极大似然估计渐近性质模型参数线性结构参数θ 似然函数渐近正态分布极大化相合性统计工作者

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常见概率分布间的逻辑关系

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南方冶金学院学报 1982年第Z2期 102-115页

作者：邹建国贺軼凡戴盛优江西冶金学院 82届毕业生指导教师

大家知道,概率分布完全描述了随机变量的统计规律性,许多常见的概率分布在不同的理论和实际问题中扮演着极其重要的角色。然而这些概率分布彼此不是耳相孤立的,他们之间都具有一定的联系。探讨各个概率分布间的逻辑关系,不仅在计算应用... 详细信息

大家知道,概率分布完全描述了随机变量的统计规律性,许多常见的概率分布在不同的理论和实际问题中扮演着极其重要的角色。然而这些概率分布彼此不是耳相孤立的,他们之间都具有一定的联系。探讨各个概率分布间的逻辑关系,不仅在计算应用中非常需要,而且在理论研究上也很重要。本文主要给出了常见概率分布间的逻辑关系以及他们的严格证明(对于某些在书籍上常见的证明从略)。