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Distribution-free and link-free estimation for a multivariate semiparametric sample selection model

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorCHAVENT, Marie
hal.structure.identifierQuality control and dynamic reliability [CQFD]
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
dc.contributor.authorSARACCO, Jérôme
dc.date.issued2007-05
dc.date.conference2007-05
dc.description.abstractEnMost of the prevalent estimation methods for sample selection model rely heavely on parametric assumptions. We consider in this communication a multivariate semiparametric sample selection model and we develop a geometric approach to the estimation of the slope vectors in the outcome equation and in the selection equation. Contrary to most existing methods, we deal symmetrically with both slope vectors. The estimation method is link-free and distribution-free, it works in two main steps: a multivariate Sliced Inverse Regression step, and a Canonical Analysis step. We establish √n-consistency and asymptotic normality of the estimates. We give results from a simulation study in order to illustrate the estimation method.
dc.language.isoen
dc.source.titleProceedings of the XIIth International Symposium of Applied Stochastic Models and Data Analysis
dc.title.enDistribution-free and link-free estimation for a multivariate semiparametric sample selection model
dc.typeCommunication dans un congrès
dc.subject.halStatistiques [stat]/Théorie [stat.TH]
dc.subject.halMathématiques [math]/Statistiques [math.ST]
bordeaux.page-
bordeaux.conference.titleASMDA 2007
bordeaux.countryGR
bordeaux.title.proceedingProceedings of the XIIth International Symposium of Applied Stochastic Models and Data Analysis
bordeaux.conference.cityChania, Crète
bordeaux.peerReviewedoui
hal.identifierhal-00278290
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceNon spécifiée
dc.subject.itMultivariate Sliced Inverse Regression
dc.subject.itCanonical Analysis
dc.subject.itSemipara- metric Regression Models
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00278290v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Proceedings%20of%20the%20XIIth%20International%20Symposium%20of%20Applied%20Stochastic%20Models%20and%20Data%20Analysis&rft.date=2007-05&rft.spage=-&rft.epage=-&rft.au=CHAVENT,%20Marie&SARACCO,%20J%C3%A9r%C3%B4me&rft.genre=unknown


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