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Article: Instrumental variables estimation of heteroskedastic linear models using all lags of instruments

TitleInstrumental variables estimation of heteroskedastic linear models using all lags of instruments
Authors
KeywordsEfficiency
Efficiency Bounds
Instrumental Variables
Optimal Instrument
Stationary Time Series
Issue Date2009
PublisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/07474938.asp
Citation
Econometric Reviews, 2009, v. 28 n. 5, p. 441-467 How to Cite?
AbstractWe propose and evaluate a technique for instrumental variables estimation of linear models with conditional heteroskedasticity. The technique uses approximating parametric models for the projection of right-hand side variables onto the instrument space, and for conditional heteroskedasticity and serial correlation of the disturbance. Use of parametric models allows one to exploit information in all lags of instruments, unconstrained by degrees of freedom limitations. Analytical calculations and simulations indicate that sometimes there are large asymptotic and finite sample efficiency gains relative to conventional estimators (Hansen, 1982), and modest gains or losses depending on data generating process and sample size relative to quasi-maximum likelihood. These results are robust to minor misspecification of the parametric models used by our estimator. [Supplemental materials are available for this article. Go to the publisher's online edition of Econometric Reviews for the following free supplemental resources: two appendices containing additional results from this article.].
Persistent Identifierhttp://hdl.handle.net/10722/177764
ISSN
2015 Impact Factor: 1.817
2015 SCImago Journal Rankings: 1.836
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWest, KDen_US
dc.contributor.authorWong, KFen_US
dc.contributor.authorAnatolyev, Sen_US
dc.date.accessioned2012-12-19T09:39:50Z-
dc.date.available2012-12-19T09:39:50Z-
dc.date.issued2009en_US
dc.identifier.citationEconometric Reviews, 2009, v. 28 n. 5, p. 441-467en_US
dc.identifier.issn0747-4938en_US
dc.identifier.urihttp://hdl.handle.net/10722/177764-
dc.description.abstractWe propose and evaluate a technique for instrumental variables estimation of linear models with conditional heteroskedasticity. The technique uses approximating parametric models for the projection of right-hand side variables onto the instrument space, and for conditional heteroskedasticity and serial correlation of the disturbance. Use of parametric models allows one to exploit information in all lags of instruments, unconstrained by degrees of freedom limitations. Analytical calculations and simulations indicate that sometimes there are large asymptotic and finite sample efficiency gains relative to conventional estimators (Hansen, 1982), and modest gains or losses depending on data generating process and sample size relative to quasi-maximum likelihood. These results are robust to minor misspecification of the parametric models used by our estimator. [Supplemental materials are available for this article. Go to the publisher's online edition of Econometric Reviews for the following free supplemental resources: two appendices containing additional results from this article.].en_US
dc.languageengen_US
dc.publisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/07474938.aspen_US
dc.relation.ispartofEconometric Reviewsen_US
dc.subjectEfficiencyen_US
dc.subjectEfficiency Boundsen_US
dc.subjectInstrumental Variablesen_US
dc.subjectOptimal Instrumenten_US
dc.subjectStationary Time Seriesen_US
dc.titleInstrumental variables estimation of heteroskedastic linear models using all lags of instrumentsen_US
dc.typeArticleen_US
dc.identifier.emailWong, KF: kafuwong@hkucc.hku.hken_US
dc.identifier.authorityWong, KF=rp01111en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1080/07474930802467241en_US
dc.identifier.scopuseid_2-s2.0-66249104320en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-66249104320&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume28en_US
dc.identifier.issue5en_US
dc.identifier.spage441en_US
dc.identifier.epage467en_US
dc.identifier.isiWOS:000276099400003-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridWest, KD=7401596903en_US
dc.identifier.scopusauthoridWong, KF=8872594700en_US
dc.identifier.scopusauthoridAnatolyev, S=9247651500en_US

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