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Article: A Hybrid Bootstrap Approach To Unit Root Tests

TitleA Hybrid Bootstrap Approach To Unit Root Tests
Authors
Issue Date2014
PublisherWiley.
Citation
Journal of Time Series Analysis, 2014, v. 35, p. 299-321 How to Cite?
AbstractThis 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.
Persistent Identifierhttp://hdl.handle.net/10722/200924
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Gen_US
dc.contributor.authorLeng, Cen_US
dc.contributor.authorTsai, C-Len_US
dc.date.accessioned2014-08-21T07:07:11Z-
dc.date.available2014-08-21T07:07:11Z-
dc.date.issued2014en_US
dc.identifier.citationJournal of Time Series Analysis, 2014, v. 35, p. 299-321en_US
dc.identifier.urihttp://hdl.handle.net/10722/200924-
dc.description.abstractThis 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.en_US
dc.languageengen_US
dc.publisherWiley.en_US
dc.relation.ispartofJournal of Time Series Analysisen_US
dc.titleA Hybrid Bootstrap Approach To Unit Root Testsen_US
dc.typeArticleen_US
dc.identifier.emailLi, G: gdli@hku.hken_US
dc.identifier.authorityLi, G=rp00738en_US
dc.identifier.doi10.1111/jtsa.12019en_US
dc.identifier.hkuros234790en_US
dc.identifier.volume35en_US
dc.identifier.spage299en_US
dc.identifier.epage321en_US
dc.identifier.isiWOS:000338033600001-

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