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Article: Asymptotic Theory on the Least Squares Estimation of Threshold Moving-Average Models

TitleAsymptotic Theory on the Least Squares Estimation of Threshold Moving-Average Models
Authors
Issue Date2013
PublisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=ECT
Citation
Econometric Theory, 2013, v. 29 n. 3, p. 482-516 How to Cite?
AbstractThis paper studies the asymptotic theory of least squares estimation in a threshold moving average model. Under some mild conditions, it is shown that the estimator of the threshold is n-consistent and its limiting distribution is related to a two-sided compound Poisson process, whereas the estimators of other coefficients are strongly consistent and asymptotically normal. This paper also provides a resampling method to tabulate the limiting distribution of the estimated threshold in practice, which is the first successful effort in this direction. This resampling method contributes to threshold literature. Simultaneously, simulation studies are carried out to assess the performance of least squares estimation in finite samples. © 2012 Cambridge University Press.
Persistent Identifierhttp://hdl.handle.net/10722/191502
ISSN
2015 Impact Factor: 1.162
2015 SCImago Journal Rankings: 2.219
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, D-
dc.contributor.authorLing, S-
dc.contributor.authorLi, WK-
dc.date.accessioned2013-10-15T07:05:46Z-
dc.date.available2013-10-15T07:05:46Z-
dc.date.issued2013-
dc.identifier.citationEconometric Theory, 2013, v. 29 n. 3, p. 482-516-
dc.identifier.issn0266-4666-
dc.identifier.urihttp://hdl.handle.net/10722/191502-
dc.description.abstractThis paper studies the asymptotic theory of least squares estimation in a threshold moving average model. Under some mild conditions, it is shown that the estimator of the threshold is n-consistent and its limiting distribution is related to a two-sided compound Poisson process, whereas the estimators of other coefficients are strongly consistent and asymptotically normal. This paper also provides a resampling method to tabulate the limiting distribution of the estimated threshold in practice, which is the first successful effort in this direction. This resampling method contributes to threshold literature. Simultaneously, simulation studies are carried out to assess the performance of least squares estimation in finite samples. © 2012 Cambridge University Press.-
dc.languageeng-
dc.publisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=ECT-
dc.relation.ispartofEconometric Theory-
dc.rightsEconometric Theory. Copyright © Cambridge University Press.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleAsymptotic Theory on the Least Squares Estimation of Threshold Moving-Average Models-
dc.typeArticle-
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hk-
dc.identifier.authorityLi, WK=rp00741-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1017/S026646661200045X-
dc.identifier.scopuseid_2-s2.0-84878323024-
dc.identifier.hkuros225258-
dc.identifier.volume29-
dc.identifier.issue3-
dc.identifier.spage482-
dc.identifier.epage516-
dc.identifier.isiWOS:000319286400002-
dc.publisher.placeUnited Kingdom-

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