Improving small area estimation by combining surveys: new perspectives in regional statistics

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devise...

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Detalhes bibliográficos
Autores: Satorra, Albert, Ventura, Eva, Costa Saenz de San Pedro, Alex
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2006
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/46301
Acesso em linha:http://hdl.handle.net/10230/46301
http://dx.doi.org/10.2139/ssrn.1002507
Access Level:Acceso aberto
Palavra-chave:Composite estimator
Complementary survey
Mean squared error
Official statistics
Regional statistics
Small area
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spelling Improving small area estimation by combining surveys: new perspectives in regional statisticsSatorra, AlbertVentura, EvaCosta Saenz de San Pedro, AlexComposite estimatorComplementary surveyMean squared errorOfficial statisticsRegional statisticsSmall areaA national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.Institut d'Estadística de Catalunya (IDESCAT)202120212006info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/46301http://dx.doi.org/10.2139/ssrn.1002507reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésSORT Statistics and Operations Research Transactions. 2007 Jul 24;30(1):101-22Document subjecte a una llicència de Creative Commons https://creativecommons.org/licenses/by-nc-nd/3.0/https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/463012026-05-29T05:05:01Z
dc.title.none.fl_str_mv Improving small area estimation by combining surveys: new perspectives in regional statistics
title Improving small area estimation by combining surveys: new perspectives in regional statistics
spellingShingle Improving small area estimation by combining surveys: new perspectives in regional statistics
Satorra, Albert
Composite estimator
Complementary survey
Mean squared error
Official statistics
Regional statistics
Small area
title_short Improving small area estimation by combining surveys: new perspectives in regional statistics
title_full Improving small area estimation by combining surveys: new perspectives in regional statistics
title_fullStr Improving small area estimation by combining surveys: new perspectives in regional statistics
title_full_unstemmed Improving small area estimation by combining surveys: new perspectives in regional statistics
title_sort Improving small area estimation by combining surveys: new perspectives in regional statistics
dc.creator.none.fl_str_mv Satorra, Albert
Ventura, Eva
Costa Saenz de San Pedro, Alex
author Satorra, Albert
author_facet Satorra, Albert
Ventura, Eva
Costa Saenz de San Pedro, Alex
author_role author
author2 Ventura, Eva
Costa Saenz de San Pedro, Alex
author2_role author
author
dc.subject.none.fl_str_mv Composite estimator
Complementary survey
Mean squared error
Official statistics
Regional statistics
Small area
topic Composite estimator
Complementary survey
Mean squared error
Official statistics
Regional statistics
Small area
description A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.
publishDate 2006
dc.date.none.fl_str_mv 2006
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/46301
http://dx.doi.org/10.2139/ssrn.1002507
url http://hdl.handle.net/10230/46301
http://dx.doi.org/10.2139/ssrn.1002507
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv SORT Statistics and Operations Research Transactions. 2007 Jul 24;30(1):101-22
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institut d'Estadística de Catalunya (IDESCAT)
publisher.none.fl_str_mv Institut d'Estadística de Catalunya (IDESCAT)
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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