The finite-sample performance of robust unit root tests
AbstractThis paper investigates the relative small sample performance of several robust unit root tests by means of a simulation study. It is confirmed that the traditional least-squares based Dickey-Fuller test has substantially lower power than several robust alternatives if the error distribution is fat-tailed while its power gain is small at the normal model. Particularly good results are achieved by a quasi-maximum likelihood test. However, all robust tests under consideration exhibit severe size distortions if the disturbances follow a skewed distribution. Moreover, under additive outliers, robust tests fail to produce stable sizes and good power properties. Consequently, the value of using robust unit root tests depends heavily of the type of nonnormality at hand.
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Bibliographic InfoArticle provided by Springer in its journal Statistical Papers.
Volume (Year): 44 (2003)
Issue (Month): 4 (October)
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Web page: http://www.springer.com/statistics/business/journal/362
Other versions of this item:
- Carstensen, Kai, 2003. "The finite-sample performance of robust unit root tests," Munich Reprints in Economics 19943, University of Munich, Department of Economics.
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