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dc.contributor.authorLombardía, María José
dc.contributor.authorLópez Vizcaíno, María Esther
dc.contributor.authorRueda, Cristina
dc.date.accessioned2023-12-12T14:47:46Z
dc.date.available2023-12-12T14:47:46Z
dc.date.issued2022-01
dc.identifier.citationM. J. Lombardía, E. López-Vizcaíno, y C. Rueda, «A New Approach to the Gender Pay Gap Decomposition by Economic Activity», Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 185, n.º 1, pp. 219-245, ene. 2022, doi: 10.1111/rssa.12742.es_ES
dc.identifier.issn1467-985X
dc.identifier.urihttp://hdl.handle.net/2183/34463
dc.descriptionThis is a pre-copyedited, author-produced version of an article accepted for publication in Journal of the Royal Statistical Society Series A: Statistics in Society, following peer review. The version of record [M. J. Lombardía, E. López-Vizcaíno, y C. Rueda, «A New Approach to the Gender Pay Gap Decomposition by Economic Activity», Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 185, n.º 1, pp. 219-245, ene. 2022] is available online at: https://doi.org/10.1111/rssa.12742.es_ES
dc.description.abstract[Abstract]: The aim of this paper is to present an original approach to estimate the gender pay gap (GPG). We propose a model-based decomposition, similar to the most popular approaches, where the first component measures differences in group characteristics and the second component measures the unexplained effect; the latter being the real gap. The novel approach incorporates model selection and bias correction. The pay gap problem in a small area context is considered in this paper, although the approach is flexible to be applied to other contexts. Specifically, the methodology is validated for analysing wage differentials by economic activities in the region of Galicia (Spain) and by analysing simulated data from an experimental design that imitates the generation of real data. The good performance of the proposed estimators is shown in both cases, specifically when compared with those obtained from the widely used Oaxaca–Blinder approach.es_ES
dc.description.sponsorshipSupported by the MINECO grants MTM2017-82724-R, MTM2015-71217-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C 2020/14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2020/14es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.language.isoenges_ES
dc.publisherOxford University Presses_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSIONes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Programa Estatal de I+D+I Orientada a los Retos de la Sociedad/MTM2015-71217-R/ES/DISEÑO E IMPLEMENTACION DE NUEVOS PROCEDIMENTOS DE INFERENCIA ESTADISTICA CON RESTRICCIONES PARA RESOLVER APLICACIONES EN BIOMEDICINA Y OTROS AMBITOSes_ES
dc.relation.urihttps://doi.org/10.1111/rssa.12742es_ES
dc.rights© 2021 Royal Statistical Societyes_ES
dc.subjectGender pay gapes_ES
dc.subjectModel selectiones_ES
dc.subjectNested error regression modeles_ES
dc.subjectSmall area estimationes_ES
dc.subjectOxaca-blinder decompositiones_ES
dc.titleA New Approach to the Gender Pay Gap Decomposition by Economic Activityes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleJournal of the Royal Statistical Society Series A: Statistics in Societyes_ES
UDC.volume185es_ES
UDC.issue1es_ES
UDC.startPage219es_ES
UDC.endPage245es_ES


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