同时方程系统中单项式系数的斯坦式收缩估计器

IF 2 Q2 ECONOMICS
A, l, i, , M, e, h, r, a, b, a, n, i
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引用次数: 0

摘要

本文引入了两个类似于斯坦因收缩的估计器,用于修正同时方程组中单个方程系数的 2SLS 和 LIML 估计器。所提出的估计器是 2SLS/LIML 估计器和 OLS 估计器的加权平均值。缩减权重取决于吴-豪斯曼(Wu-Hausman)失范检验统计量,该统计量针对内生性的替代假设评估外生性的零假设。利用小扰动近似法获得了斯坦因类收缩估计器的近似有限样本偏差、均方误差和密度函数。在均方误差和集中概率下,得到了斯坦因类收缩估计器相对于 2SLS/LIML 估计器的优势条件。模拟研究进一步说明了所提出的方法,证明该方法具有良好的有限样本性能,并将其应用于教育回报的实证应用中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stein-Like Shrinkage Estimators for Coefficients of a Single-Equation in Simultaneous Equation Systems
Two stein-like shrinkage estimators are introduced to modify the 2SLS and the LIML estimators for coefficients of a single equation in a simultaneous system of equations. The proposed estimators are weighted averages of the 2SLS/LIML estimators and the OLS estimator. The shrinkage weight depends on the Wu-Hausman misspecification test statistic which evaluates the null of exogeneity against the alternative hypothesis of endogeneity. The approximate finite sample bias, mean squared errors, and density functions of the Stein-like shrinkage estimators are obtained using small-disturbance approximations. The dominance conditions of the Stein-like shrinkage estimators over the 2SLS/LIML estimator under the mean squared error and the concentration probability are obtained. The proposed method is further illustrated by simulation studies which demonstrate the good finite sample performance of the method, and is also applied to an empirical application of returns to education.
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
84
期刊介绍: Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.
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