Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/8447 |
Resumo: | In this paper we use two alternative approaches to study the extent of gender wage discrimination in Portugal. Both methods involve the estimation of wage equations for males and females and the Blinder [1973] and Oaxaca [1973] decomposition. However, to take into account possible sample selection bias, we consider both parametric and semi-parametric methods. First, we consider a parametric approach that relies on distributional assumptions about the distribution of the error terms in the model (Vella (1992, 1998) and Wooldridge (1998)). Within this approach, if the distributional assumption is not satisfied, the parameters’ estimates may be inconsistent. Secondly, we apply Li and Wooldridge [2002] semi-parametric estimator, which does not assume any known distribution on the joint distribution of the errors of the wage equation and of the sample selection equation; the distribution has an unknown form and is estimated through non-parametric kernel techniques.We employ micro data for Portugal from the European Community Household Panel (ECHP). The results from both approaches provide evidence in favour of the existence of gender wage discrimination in Portugal. However, the extent of labour market discrimination decreases when sample selection bias corrections are taken into account. |
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Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approacheswage differentialsdiscriminationsample selectionsemi-parametric estimationIn this paper we use two alternative approaches to study the extent of gender wage discrimination in Portugal. Both methods involve the estimation of wage equations for males and females and the Blinder [1973] and Oaxaca [1973] decomposition. However, to take into account possible sample selection bias, we consider both parametric and semi-parametric methods. First, we consider a parametric approach that relies on distributional assumptions about the distribution of the error terms in the model (Vella (1992, 1998) and Wooldridge (1998)). Within this approach, if the distributional assumption is not satisfied, the parameters’ estimates may be inconsistent. Secondly, we apply Li and Wooldridge [2002] semi-parametric estimator, which does not assume any known distribution on the joint distribution of the errors of the wage equation and of the sample selection equation; the distribution has an unknown form and is estimated through non-parametric kernel techniques.We employ micro data for Portugal from the European Community Household Panel (ECHP). The results from both approaches provide evidence in favour of the existence of gender wage discrimination in Portugal. However, the extent of labour market discrimination decreases when sample selection bias corrections are taken into account.2013-04-03T11:29:50Z2013-04-032006-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/8447http://hdl.handle.net/10174/8447engGalego, A. e J. Pereira (2006), Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches, Documento de Trabalho nº 2006/13, Universidade de Évora, Departamento de Economia.17agalego@uevora.ptjpereira@uvevora.ptJ31, J71, C1413_2006Department of Economics, University of ÉvoraDepartment of Economics, University of ÉvoraGalego, AuroraPereira, Joãoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-08T03:58:59ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
title |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
spellingShingle |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches Galego, Aurora wage differentials discrimination sample selection semi-parametric estimation |
title_short |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
title_full |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
title_fullStr |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
title_full_unstemmed |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
title_sort |
Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches |
author |
Galego, Aurora |
author_facet |
Galego, Aurora Pereira, João |
author_role |
author |
author2 |
Pereira, João |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Galego, Aurora Pereira, João |
dc.subject.por.fl_str_mv |
wage differentials discrimination sample selection semi-parametric estimation |
topic |
wage differentials discrimination sample selection semi-parametric estimation |
description |
In this paper we use two alternative approaches to study the extent of gender wage discrimination in Portugal. Both methods involve the estimation of wage equations for males and females and the Blinder [1973] and Oaxaca [1973] decomposition. However, to take into account possible sample selection bias, we consider both parametric and semi-parametric methods. First, we consider a parametric approach that relies on distributional assumptions about the distribution of the error terms in the model (Vella (1992, 1998) and Wooldridge (1998)). Within this approach, if the distributional assumption is not satisfied, the parameters’ estimates may be inconsistent. Secondly, we apply Li and Wooldridge [2002] semi-parametric estimator, which does not assume any known distribution on the joint distribution of the errors of the wage equation and of the sample selection equation; the distribution has an unknown form and is estimated through non-parametric kernel techniques.We employ micro data for Portugal from the European Community Household Panel (ECHP). The results from both approaches provide evidence in favour of the existence of gender wage discrimination in Portugal. However, the extent of labour market discrimination decreases when sample selection bias corrections are taken into account. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-01-01T00:00:00Z 2013-04-03T11:29:50Z 2013-04-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/8447 http://hdl.handle.net/10174/8447 |
url |
http://hdl.handle.net/10174/8447 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Galego, A. e J. Pereira (2006), Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches, Documento de Trabalho nº 2006/13, Universidade de Évora, Departamento de Economia. 17 agalego@uevora.pt jpereira@uvevora.pt J31, J71, C14 13_2006 Department of Economics, University of Évora Department of Economics, University of Évora |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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1777304586858528768 |