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A HYBRID BOOTSTRAP APPROACH TO UNIT ROOT TESTS

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  • This article was published online on May 3, 2013. In order to update the review of the published literature provided, a new version was published in Early View last April 24, 2014. This notice is included in the online and print versions to indicate that both have been corrected.

Abstract

This article proposes a hybrid bootstrap approach to approximate the augmented Dickey–Fuller test by perturbing both the residual sequence and the minimand of the objective function. Since innovations can be dependent, this allows the inclusion of conditional heteroscedasticity models. The new bootstrap method is also applied to least absolute deviation-based unit root test statistics, which are efficient in handling heavy-tailed time-series data. The asymptotic distributions of resulting bootstrap tests are presented, and Monte Carlo studies demonstrate the usefulness of the proposed tests.

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