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Unit Root Tests and Heavy-Tailed Innovations

Georgiev, Iliyan and Rodrigues, Paulo MM and Taylor, AM Robert (2017) 'Unit Root Tests and Heavy-Tailed Innovations.' Journal of Time Series Analysis, 38 (5). pp. 733-768. ISSN 0143-9782

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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 infinite variance vis-à-vis finite variance. Reassuringly, however, simulation results suggest that the impact of heavy-tailed innovations on these tests is relatively small. We use the framework of Amsler and Schmidt () whereby the innovations have local-to-finite 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 augmented Dickey–Fuller tests that employ Eicker–White standard errors, demonstrating that these can yield significant power improvements over conventional tests.

Item Type: Article
Uncontrolled Keywords: Infinite variance; α‐stable distribution; Eicker–White standard errors; asymptotic local power functions
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Divisions: Faculty of Social Sciences
Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 18 Jan 2017 11:08
Last Modified: 06 Jan 2022 14:44

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