Testing the Information Matrix Equality with Robust Estimators

Testing the Information Matrix Equality
with Robust Estimators

March 18, 2003

Abstract

We study the behaviour of the information matrix (IM) test when
maximum likelihood estimators are replaced with robust estimators.
The latter may unmask outliers and hence improve the power of the
test. We investigate in detail the local asymptotic power of the IM
test in the normal model, for various estimators and under a range
of local alternatives. These local alternatives include contamination
neighbourhoods, Student’s t (with degrees of freedom approaching in-
finity), skewness, and a tilted normal. Simulation studies for fixed
alternatives confirm that in many cases the use of robust estimators
substantially increases the power of the IM test.

JEL classification: C12, C15

Key-words: information matrix test, robustness

* Corresponding author. Address: K.U.Leuven, Department of Economics, Naamses-
traat 69, 3000 Leuven, Belgium. Tel. +32 16 326652. Fax +32 16 326796. Email:
[email protected]

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