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  4. PROPERTIES OF DOUBLY ROBUST ESTIMATORS WHEN NUISANCE FUNCTIONS ARE ESTIMATED NONPARAMETRICALLY
Please use this identifier to cite or link to this item: https://repositorio.insper.edu.br/handle/11224/4237
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dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.date.accessioned2022-10-11T18:53:06Z-
dc.date.available2022-10-11T18:53:06Z-
dc.date.issued2018-
dc.identifier.issn1469-4360pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4237-
dc.format.extentp. 1048-1087pt_BR
dc.format.mediumDigitalpt_BR
dc.language.isoInglêspt_BR
dc.publisherCambridge University Presspt_BR
dc.relation.ispartofProperties of doubly robust estimators when nuisance functions are estimated nonparametricallypt_BR
dc.relation.urihttps://www.cambridge.org/core/journals/econometric-theory/article/abs/properties-of-doubly-robust-estimators-when-nuisance-functions-are-estimated-nonparametrically/A9BA1449CD982BC35C245BFEE680759F#articlept_BR
dc.titlePROPERTIES OF DOUBLY ROBUST ESTIMATORS WHEN NUISANCE FUNCTIONS ARE ESTIMATED NONPARAMETRICALLYpt_BR
dc.typeArtigo Científicopt_BR
dc.description.otherAn estimator of a finite-dimensional parameter is said to be doubly robust (DR) if it imposes parametric specifications on two unknown nuisance functions, but only requires that one of these two specifications is correct in order for the estimator to be consistent for the object of interest. In this article, we study versions of such estimators that use local polynomial smoothing for estimating the nuisance functions. We show that such semiparametric two-step (STS) versions of DR estimators have favorable theoretical and practical properties relative to other commonly used STS estimators. We also show that these gains are not generated by the DR property alone. Instead, it needs to be combined with an orthogonality condition on the estimation residuals from the nonparametric first stage, which we show to be satisfied in a wide range of models.pt_BR
dc.subject.cnpqCiências Exatas e da Terrapt_BR
dc.identifier.doihttps://doi.org/10.1017/S0266466618000385pt_BR
dc.identifier.issue5pt_BR
dc.identifier.volume35pt_BR
dc.description.notesEvidenciapt_BR
dc.contributor.autorFirpo, Sergio Pinheiro-
dc.contributor.autorRothe, Christoph-
dc.coverage.paisNão Informadopt_BR
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