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A simple data-driven estimator for the semiparametric sample selection model

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dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorEscanciano, Juan Carlos
dc.contributor.authorZhu, Lin
dc.contributor.funderMinisterio de Educación y Ciencia (España)es
dc.date.accessioned2022-06-13T18:13:32Z
dc.date.available2022-06-13T18:13:32Z
dc.date.issued2016-08-26
dc.description.abstractThis paper proposes a simple fully data-driven version of Powell's (2001) two-step semiparametric estimator for the sample selection model. The main feature of the proposal is that the bandwidth used to estimate the infinite-dimensional nuisance parameter is chosen by minimizing the mean squared error of the fitted semiparametric model. We formally justify data-driven inference. We introduce the concept of asymptotic normality, uniform in the bandwidth, and show that the proposed estimator achieves this property for a wide range of bandwidths. The method of proof is different from that in Powell (2001) and permits straightforward extensions to other semiparametric or even fully nonparametric specifications of the selection equation. The results of a small Monte Carlo suggest that our estimator has excellent finite sample performance, comparing well with other competing estimators based on alternative choices of smoothing parameters.en
dc.description.sponsorshipResearch funded by the Spanish Plan Nacional de I+D+I, reference number SEJ2007-62908.en
dc.identifier.bibliographicCitationEscanciano, J. C., & Zhu, L. (2014). A Simple Data-Driven Estimator for the Semiparametric Sample Selection Model.Econometric Reviews, 34 (6-10), pp. 734-762.en
dc.identifier.doihttps://doi.org/10.1080/07474938.2014.956577
dc.identifier.issn0747-4938
dc.identifier.publicationfirstpage733es
dc.identifier.publicationissue1es
dc.identifier.publicationlastpage761es
dc.identifier.publicationtitleEconometric Reviewsen
dc.identifier.publicationvolume34es
dc.identifier.urihttp://hdl.handle.net/10016/35102
dc.identifier.uxxiAR/0000029587
dc.language.isoenges
dc.publisherTaylor & Francisen
dc.relation.projectIDGobierno de España. SEJ2007-62908es
dc.rights© Taylor & Francis Group, LLCen
dc.rightsAtribución-NoComercial 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.subject.ecienciaEconomíaes
dc.subject.jelC13
dc.subject.jelC14
dc.subject.jelC25
dc.subject.otherEmpirical process theoryen
dc.subject.otherSemiparametric sample selection modelsen
dc.subject.otherTwo-step estimatoren
dc.titleA simple data-driven estimator for the semiparametric sample selection modelen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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