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Estimation of unemployment rates in small areas of Portugal: a best linear unbiased prediction approach versus a hierarchical Bayes approach

2011Conference object Open access
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dc.contributor.authorPereira, Luis Nobre
dc.contributor.authorMendes, J.
dc.contributor.authorCoelho, Pedro S.
dc.date.accessioned2012-02-29T11:38:07Z
dc.date.available2012-02-29T11:38:07Z
dc.date.issued2011
dc.date.updated2012-02-24T12:46:12Z
dc.description.abstractThe high level of unemployment is one of the major problems in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Labour Force Survey (LFS) conducted by the Portuguese Statistical Office is the main source of official statistics on the labour market at the macro level (e.g. NUTS2 and national level). However, the LFS was not designed to produce reliable statistics at the micro level (e.g. NUTS3, municipalities or further disaggregate level) due to small sample sizes. Consequently, traditional design-based estimators are not appropriate. A solution to this problem is to consider model-based estimators that "borrow information" from related areas or past samples by using auxiliary information. This paper reviews, under the model-based approach, Best Linear Unbiased Predictors and an estimator based on the posterior predictive distribution of a Hierarchical Bayesian model. The goal of this paper is to analyze the possibility to produce accurate unemployment rate statistics at micro level from the Portuguese LFS using these kinds of stimators. This paper discusses the advantages of using each approach and the viability of its implementation.por
dc.identifier.citationEuropean Young Statisticians Meeting, 17th , Lisbon, 2011.por
dc.identifier.issn978-972-8893-27-9
dc.identifier.otherAUT: LMP01693;
dc.identifier.urihttp://hdl.handle.net/10400.1/914
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherUniversidade Nova de Lisboapor
dc.subjectSmall Area Estimationpor
dc.subjectEmpirical Best Linear Unbiased Predictorpor
dc.subjectHierarchical Bayespor
dc.subjectUnemployment Ratepor
dc.titleEstimation of unemployment rates in small areas of Portugal: a best linear unbiased prediction approach versus a hierarchical Bayes approachpor
dc.typeconference object
dspace.entity.typePublication
person.familyNameNobre Pereira
person.givenNameLuis
person.identifier.ciencia-id6114-E329-972E
person.identifier.orcid0000-0003-0917-7163
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication090a6604-b604-414b-a8d2-c4dc731b7b51
relation.isAuthorOfPublication.latestForDiscovery090a6604-b604-414b-a8d2-c4dc731b7b51

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