Second-order refinement of empirical likelihood ratio tests of nonlinear restrictions

IF 2.9 4区经济学 Q1 ECONOMICS

Econometrics Journal Pub Date : 2016-11-24 DOI:10.1111/ectj.12079

Jun Ma

引用次数: 3

Abstract

In this paper, we investigate the second-order properties of empirical likelihood ratio (ELR) tests of general nonlinear parametric restrictions for over-identified moment restriction models. We derive the stochastic expansion of the ELR statistic for this very large class of testing problems and its formal distributional expansion. We show that we can improve the size properties of the ELR tests via either Bartlett correction or pseudo observation adjustment. Monte Carlo experiments show that tests based on these modified ELR statistics exhibit good finite-sample properties.

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非线性约束的经验似然比检验的二阶改进

本文研究了过辨识矩约束模型的一般非线性参数约束的经验似然比检验的二阶性质。我们导出了这类非常大的检验问题的ELR统计量的随机展开式及其形式分布展开式。通过Bartlett校正或伪观测平差可以改善ELR试验的尺寸特性。蒙特卡罗实验表明，基于这些改进的ELR统计量的测试具有良好的有限样本特性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Econometrics Journal 管理科学-数学跨学科应用

CiteScore

4.20

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： The Econometrics Journal was established in 1998 by the Royal Economic Society with the aim of creating a top international field journal for the publication of econometric research with a standard of intellectual rigour and academic standing similar to those of the pre-existing top field journals in econometrics. The Econometrics Journal is committed to publishing first-class papers in macro-, micro- and financial econometrics. It is a general journal for econometric research open to all areas of econometrics, whether applied, computational, methodological or theoretical contributions.