Worst-case estimation for econometric models with unobservable components

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dc.contributor.author Esteban-Bravo, Mercedes
dc.contributor.author Vidal-Sanz, Jose M.
dc.date.accessioned 2010-04-12T13:53:57Z
dc.date.available 2010-04-12T13:53:57Z
dc.date.issued 2007-11
dc.identifier.bibliographicCitation Computational Statistics & Data Analysis, 2007, v. 51, n. 7, pp. 3330–3354
dc.identifier.issn 0167-9473
dc.identifier.uri http://hdl.handle.net/10016/7342
dc.description.abstract A worst-case estimator for econometric models containing unobservable components, based on minimax principles for optimal selection of parameters, is proposed. Worst-case estimators are robust against the averse effects of unobservables. Computing worstcase estimators involves solving a minimax continuous problem, which is quite a challenging task. Large sample theory is considered, and a Monte Carlo study of finite-sample properties is conducted. A financial application is considered
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso eng
dc.publisher Elsevier
dc.rights ©Elsevier
dc.subject.other Worst-case decision
dc.subject.other Robust modelling
dc.subject.other Minimax optimization
dc.title Worst-case estimation for econometric models with unobservable components
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/j.csda.2006.09.023
dc.subject.eciencia Empresa
dc.identifier.doi 10.1016/j.csda.2006.09.023
dc.rights.accessRights openAccess
dc.identifier.publicationfirstpage 3330
dc.identifier.publicationissue 7
dc.identifier.publicationlastpage 3354
dc.identifier.publicationtitle Computational Statistics & Data Analysis
dc.identifier.publicationvolume 51
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