Finite sample behavior of two step estimators in selection models

The problem of specification errors in sample selection models has received considerable attention both theoretically and empirically. However, very few is known about the finite sample behavior of two step estimators. In this paper we investigate by simulations both bias and finite sample distribut...

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Autores: Fernández Sáinz, Ana Isabel, Rodríguez-Poo, Juan M.|||0000-0001-8751-3025, Villanúa Martín, Inmaculada
Formato: artículo
Fecha de publicación:1999
País:España
Recursos:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/4642
Acesso em linha:http://hdl.handle.net/10902/4642
Access Level:acceso abierto
Palavra-chave:Sample selection models
Semiparametric models
Finite sample analysis
Misspecification error
Heteroskedasticity
Heckman two step estimator
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spelling Finite sample behavior of two step estimators in selection modelsFernández Sáinz, Ana IsabelRodríguez-Poo, Juan M.|||0000-0001-8751-3025Villanúa Martín, InmaculadaSample selection modelsSemiparametric modelsFinite sample analysisMisspecification errorHeteroskedasticityHeckman two step estimatorThe problem of specification errors in sample selection models has received considerable attention both theoretically and empirically. However, very few is known about the finite sample behavior of two step estimators. In this paper we investigate by simulations both bias and finite sample distribution of these estimators when ignoring heteroskedasticity in the sample selection mechanism. It turns out that under conditions traditionally faced by practitioners, the misspecified parametric two step estimator (Heckman, 1979) performs better, in finite sample sizes, than the robust semiparametric one (Ahn and Powell, 1993). Moreover, under very general conditions, we show that the asymptotic bias of the parametric two step estimator is linear in the covariance between the sample selection and the participation equation.Universidad del País VascoUniversidad de Cantabria19991999-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttp://hdl.handle.net/10902/4642Documentos de Trabajo BILTOKI, 1999, 6reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/46422026-06-02T12:39:31Z
dc.title.none.fl_str_mv Finite sample behavior of two step estimators in selection models
title Finite sample behavior of two step estimators in selection models
spellingShingle Finite sample behavior of two step estimators in selection models
Fernández Sáinz, Ana Isabel
Sample selection models
Semiparametric models
Finite sample analysis
Misspecification error
Heteroskedasticity
Heckman two step estimator
title_short Finite sample behavior of two step estimators in selection models
title_full Finite sample behavior of two step estimators in selection models
title_fullStr Finite sample behavior of two step estimators in selection models
title_full_unstemmed Finite sample behavior of two step estimators in selection models
title_sort Finite sample behavior of two step estimators in selection models
dc.creator.none.fl_str_mv Fernández Sáinz, Ana Isabel
Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
Villanúa Martín, Inmaculada
author Fernández Sáinz, Ana Isabel
author_facet Fernández Sáinz, Ana Isabel
Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
Villanúa Martín, Inmaculada
author_role author
author2 Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
Villanúa Martín, Inmaculada
author2_role author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Sample selection models
Semiparametric models
Finite sample analysis
Misspecification error
Heteroskedasticity
Heckman two step estimator
topic Sample selection models
Semiparametric models
Finite sample analysis
Misspecification error
Heteroskedasticity
Heckman two step estimator
description The problem of specification errors in sample selection models has received considerable attention both theoretically and empirically. However, very few is known about the finite sample behavior of two step estimators. In this paper we investigate by simulations both bias and finite sample distribution of these estimators when ignoring heteroskedasticity in the sample selection mechanism. It turns out that under conditions traditionally faced by practitioners, the misspecified parametric two step estimator (Heckman, 1979) performs better, in finite sample sizes, than the robust semiparametric one (Ahn and Powell, 1993). Moreover, under very general conditions, we show that the asymptotic bias of the parametric two step estimator is linear in the covariance between the sample selection and the participation equation.
publishDate 1999
dc.date.none.fl_str_mv 1999
1999-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10902/4642
url http://hdl.handle.net/10902/4642
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidad del País Vasco
publisher.none.fl_str_mv Universidad del País Vasco
dc.source.none.fl_str_mv Documentos de Trabajo BILTOKI, 1999, 6
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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