Chi-Square Tests for Parameter Stability

29 Pages Posted: 8 Jun 2004

See all articles by Marine Carrasco

Marine Carrasco

University of Montreal - Departement de Ciences Economiques

Date Written: May 2004

Abstract

Testing when a nuisance parameter is identified only under the alternative is problematic because the Likelihood Ratio test converges to a nonstandard distribution that may depend on unknown parameters. Examples include testing parameter stability in Structural Change and Threshold models.

Our article proposes a class of tests that have the advantage of having a standard distribution, namely a chi-square. In this class, we focus mostly on a Lagrange Multiplier test in an auxiliary regression. We derive the asymptotic power of this test against alternatives which differ from the implicit alternative of the test. We show that this test can be used as a diagnostic test for parameter stabilility.

A Monte Carlo study compares the performance of our tests with other frequently used tests and shows that they have a similar power.

Keywords: Admissibility, smooth transition, structural change test, Threshold autoregressive models

JEL Classification: C12, C22

Suggested Citation

Carrasco, Marine, Chi-Square Tests for Parameter Stability (May 2004). Available at SSRN: https://ssrn.com/abstract=555708 or http://dx.doi.org/10.2139/ssrn.555708

Marine Carrasco (Contact Author)

University of Montreal - Departement de Ciences Economiques ( email )

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