Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T05:56:36.731Z Has data issue: false hasContentIssue false
  • English
  • Français

A CONSISTENT NONPARAMETRIC TEST OF PARAMETRIC REGRESSION MODELS UNDER CONDITIONAL QUANTILE RESTRICTIONS

Published online by Cambridge University Press:  01 February 1998

John Xu Zheng
John Xu Zheng
Affiliation:
University of Texas
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper proposes a nonparametric, kernel-based test of parametric quantile regression models. The test statistic has a limiting standard normal distribution if the parametric quantile model is correctly specified and diverges to infinity for any misspecification of the parametric model. Thus the test is consistent against any fixed alternative. The test also has asymptotic power 1 against local alternatives converging to the null at proper rates. A simulation study is provided to evaluate the finite-sample performance of the test.

Type
Research Article
Information
Econometric Theory , Volume 14 , Issue 1 , February 1998 , pp. 123 - 138
Copyright
© 1998 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)