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Estimation of proportions in small areas: application to the labour force using the Swiss Census Structural Survey

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorMolina Peralta, Isabel
dc.contributor.authorStrzalkowska-Kominiak, Ewa
dc.date.accessioned2022-06-01T16:38:38Z
dc.date.available2022-06-01T16:38:38Z
dc.date.issued2020-01-01
dc.description.abstractThe main objectives of this paper are to find efficient but computationally simple estimators for the proportions of people in the labour force (economic activity rates) in Swiss communes and to estimate their mean-squared error (MSE) over the sampling replication mechanism (the design MSE). This will be done by combining survey data with administrative data provided by the Swiss Federal Statistical Office. We find estimators with considerably greater efficiency than currently used direct estimators and that are easy to implement. We show that, under a generalized linear mixed model with logit link, the computationally expensive empirical best predictor does not perform appreciably better than a plug-in estimator. Moreover, for moderate proportions of active workers, the empirical best linear unbiased predictor (EBLUP) based on a much simpler linear mixed model performs similarly to the above estimators. We propose new bootstrap estimators of the design MSE of the EBLUPs, which ‘borrow strength’ similarly to EBLUPs. Realistic simulation studies carried out under both model- and design-based set-ups indicate great gains in efficiency of the selected small area estimators over the traditional direct estimators and acceptable performance of the proposed bootstrap MSE estimators. In the application using the Swiss data, coefficient-of-variation reductions of the estimates obtained for the communes are remarkable.en
dc.identifier.bibliographicCitationMolina, I., & Strzalkowska‐Kominiak, E. (2019). Estimation of proportions in small areas: application to the labour force using the Swiss Census Structural Survey. Journal of the Royal Statistical Society: Series A (Statistics in Society), 183 (1), pp. 281-310.en
dc.identifier.doihttps://doi.org/10.1111/rssa.12498
dc.identifier.publicationfirstpage281es
dc.identifier.publicationissue1es
dc.identifier.publicationlastpage310es
dc.identifier.publicationtitleJournal of the Royal Statistical Society. Series A: Statistics in Societyen
dc.identifier.publicationvolume183es
dc.identifier.urihttps://hdl.handle.net/10016/34972
dc.identifier.uxxiAR/0000025497
dc.language.isoenges
dc.publisherWileyen
dc.rights© 2019 Royal Statistical Societyes
dc.rights.accessRightsopen accessen
dc.subject.otherDesign mean-squared erroren
dc.subject.otherGeneralized linear mixed model logit linken
dc.subject.otherSmall area estimationen
dc.titleEstimation of proportions in small areas: application to the labour force using the Swiss Census Structural Surveyen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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