Rank tests of unit root hypothesis with infinite variance errors

We consider a family of rank tests based on the regression rank score process introduced by Gutenbrunner and Jurečková (Ann. Statist. 20 (1992) 305) to test the unit root hypothesis under infinite variance innovations. Unlike the finite variance case as studied by Hasan and Koenker (Econometrica 65...

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Bibliographic Details
Published in:Journal of econometrics 2001-08, Vol.104 (1), p.49-65
Main Author: Hasan, Mohammad N.
Format: Article
Language:English
Subjects:
Correlation
Econometrics
Economic models
Exact sciences and technology
Hypotheses
Innovation
Linear inference, regression
Mathematics
Modelling
Parametric inference
Probability and statistics
Quantile regression
Regression analysis
Regression rank score
Sciences and techniques of general use
Statistics
Studies
Time series
Unit root tests
Variance
Variance analysis
α-stable process
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Summary:We consider a family of rank tests based on the regression rank score process introduced by Gutenbrunner and Jurečková (Ann. Statist. 20 (1992) 305) to test the unit root hypothesis under infinite variance innovations. Unlike the finite variance case as studied by Hasan and Koenker (Econometrica 65 (1997) 133) the original rankscore test statistics ( T n ) exhibit a simple Gaussian limiting behavior. However, finite sample investigations suggest a correction similar to what HK proposed. This corrected version ( S ̂ T ) has reliable size, and exhibits remarkable power even in near unit root cases under a variety of α-stable distributions. Also, the test statistics do not depend on the α parameter.
ISSN:0304-4076
1872-6895
DOI:10.1016/S0304-4076(01)00050-1