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Unit Root Tests Based on M Estimators

Published online by Cambridge University Press:  11 February 2009

André Lucas
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Abstract

This paper considers unit root tests based on M estimators. The asymptotic theory for these tests is developed. It is shown how the asymptotic distributions of the tests depend on nuisance parameters and how tests can be constructed that are invariant to these parameters. It is also shown that a particular linear combination of a unit root test based on the ordinary least-squares (OLS) estimator and on an M estimator converges to a normal random variate. The interpretation of this result is discussed. A simulation experiment is described, illustrating the level and power of different unit root tests for several sample sizes and data generating processes. The tests based on M estimators turn out to be more powerful than the OLS-based tests if the innovations are fat-tailed.

Type
Research Article
Information
Econometric Theory , Volume 11 , Issue 2 , February 1995 , pp. 331 - 346
Copyright
Copyright © Cambridge University Press 1995

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