Testing Serial Correlation in Partial Linear Errors-in-Variables Models Based on Empirical Likelihood

Abstract

In this article, we propose an empirical likelihood-based test to check the existence of serial correlation in partial linear errors-in-variables models. A nonparametric version of Wilk' theorem is derived, which says that our proposed test has an asymptotic chi-square distribution. Simulation results reveal that the finite sample performance of our proposed test is satisfactory in both size and power.

Keywords:

• Empirical likelihood
• Errors-in-variables
• Partial linear model
• Serial correlation
• Wilk' theorem

Mathematics Subject Classification:

• Primary 62G08
• Secondary 62G10

Acknowledgments

Prof. Min Chen's work is supported by the National Natural Science Foundation of China (NSFC) (No. 70221001, 70331001) and the National Basic Research Program of China (973 Program) (No. 2007CB814902). Dr. Feng Liu's work is supported by the Science and Technology Project of Chongqing Education Committee (No. KJ080609).