Publication Type

Journal Article

Version

Preprint

Publication Date

4-2015

Abstract

A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey–Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey–Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic.

Keywords

Nonstationary volatility, Lag selection, Information criteria, Wild bootstrap, Unit root test

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Reviews

Volume

34

Issue

4

First Page

512

Last Page

536

ISSN

0747-4938

Identifier

10.1080/07474938.2013.808065

Publisher

Taylor and Francis

Embargo Period

7-17-2017

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1080/07474938.2013.808065

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Econometrics Commons

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