Generalized method of moments, efficient bootstrapping, and improved inference

被引：77

作者：

Brown, BW ^{[1
]}

Newey, WK

机构：

[1] Rice Univ, Dept Econ, Houston, TX 77005 USA

[2] MIT, Dept Econ, Cambridge, MA 02139 USA

来源：

JOURNAL OF BUSINESS & ECONOMIC STATISTICS | 2002年 / 20卷 / 04期

基金：

美国国家科学基金会;

关键词：

bootstrapping; empirical likelihood; panel data;

D O I：

10.1198/073500102288618649

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Generalized method of moments (GMM) has been an important innovation in econometrics. Its usefulness has motivated a search for good inference procedures based on GMM. This article presents a novel method of bootstrapping for GMM based on resampling from the empirical likelihood distribution that imposes the moment restrictions. We show that this approach yields a large-sample improvement and is efficient, and give examples. We also discuss the development of GMM and other recent work on improved inference.

引用

页码：507 / 517

页数：11

共 81 条

[1] ON THE COVARIANCE STRUCTURE OF EARNINGS AND HOURS CHANGES [J].