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Unit Root Tests and Heavy-Tailed Innovations

Georgiev, I and Rodrigues, PMM and Taylor, AMR (2017) Unit Root Tests and Heavy-Tailed Innovations. UNSPECIFIED. Essex Finance Centre Working Papers.


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We evaluate the impact of heavy-tailed innovations on some popular unit root tests. In the context of a near-integrated series driven by linear-process shocks, we demonstrate that their limiting distributions are altered under in nite variance vis-�-vis finite variance. Reassuringly, however, simulation results suggest that the impact of heavy-tailed innovations on these tests are relatively small. We use the framework of Amsler and Schmidt (2012) whereby the innovations have local-to- nite variances being generated as a linear combination of draws from a thin- tailed distribution (in the domain of attraction of the Gaussian distribution) and a heavy-tailed distribution (in the normal domain of attraction of a stable law). We also explore the properties of ADF tests which employ Eicker-White standard errors, demonstrating that these can yield significant power improvements over conventional tests.

Item Type: Monograph (UNSPECIFIED)
Uncontrolled Keywords: Infinite variance, ?-stable distribution, Eicker-White standard errors, symptotic local power functions, weak dependence
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Jim Jamieson
Date Deposited: 18 Jan 2017 11:12
Last Modified: 04 Dec 2017 22:52

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