A Correction factor for unit root test statistics
A Correction factor for unit root test statistics
Despite the fact that it is not correct to speak of Bartlett corrections in the case of non-stationary time series, this paper shows that a Bartlett-type correction to the likelihood ratio test for a unit root can be an effective tool in order to control size distortions. Using well-known formulae, we obtain second order (numerical) approximations to the moments and cumulants of the likelihood ratio, which makes it possible to calculate a Bartlett type factor. It turns out that the cumulants of the corrected statistic are closer to their asymptotic value than the original one. A simulation study is then carried out to assess the quality of these approximations for the first four moments; the size and power of the original and the corrected statistic are also simulated. Our results suggest that the proposed correction reduced the size of the distortion without affecting the power too much.
University of Southampton
Bravo, F.
0c550398-dddb-4868-ae65-1a12708bee02
January 1998
Bravo, F.
0c550398-dddb-4868-ae65-1a12708bee02
Bravo, F.
(1998)
A Correction factor for unit root test statistics
(Discussion Papers in Economics and Econometrics, 9809)
Southampton, UK.
University of Southampton
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Monograph
(Discussion Paper)
Abstract
Despite the fact that it is not correct to speak of Bartlett corrections in the case of non-stationary time series, this paper shows that a Bartlett-type correction to the likelihood ratio test for a unit root can be an effective tool in order to control size distortions. Using well-known formulae, we obtain second order (numerical) approximations to the moments and cumulants of the likelihood ratio, which makes it possible to calculate a Bartlett type factor. It turns out that the cumulants of the corrected statistic are closer to their asymptotic value than the original one. A simulation study is then carried out to assess the quality of these approximations for the first four moments; the size and power of the original and the corrected statistic are also simulated. Our results suggest that the proposed correction reduced the size of the distortion without affecting the power too much.
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Published date: January 1998
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Local EPrints ID: 33162
URI: http://eprints.soton.ac.uk/id/eprint/33162
PURE UUID: eeb5d280-58ba-4311-a389-08e6d8e989ad
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Date deposited: 05 Feb 2008
Last modified: 11 Dec 2021 15:19
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Author:
F. Bravo
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