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dc.contributor.authorMoretti, Angelo; orcid: 0000-0001-6543-9418; email: angelo.moretti@manchester.ac.uk
dc.contributor.authorShlomo, Natalie
dc.contributor.authorSakshaug, Joseph W.
dc.date.accessioned2021-10-02T17:11:54Z
dc.date.available2021-10-02T17:11:54Z
dc.date.issued2019-02-13
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/626019/10.1177_0049124119826160.pdf?sequence=2
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/626019/10.1177_0049124119826160.xml?sequence=3
dc.identifier.citationSociological Methods & Research, volume 50, issue 4, page 1660-1693
dc.identifier.urihttp://hdl.handle.net/10034/626019
dc.descriptionFrom SAGE Publishing via Jisc Publications Router
dc.descriptionHistory: epub 2019-02-13
dc.descriptionPublication status: Published
dc.descriptionFunder: Economic and Social Research Council; FundRef: https://doi.org/10.13039/501100000269; Grant(s): ES/J500094/1
dc.description.abstractSmall area estimation (SAE) plays a crucial role in the social sciences due to the growing need for reliable and accurate estimates for small domains. In the study of well-being, for example, policy makers need detailed information about the geographical distribution of a range of social indicators. We investigate data dimensionality reduction using factor analysis models and implement SAE on the factor scores under the empirical best linear unbiased prediction approach. We contrast this approach with the standard approach of providing a dashboard of indicators or a weighted average of indicators at the local level. We demonstrate the approach in a simulation study and a real data application based on the European Union Statistics for Income and Living Conditions for the municipalities of Tuscany.
dc.languageen
dc.publisherSAGE Publications
dc.rightsLicence for this article starting on 2019-02-13: http://creativecommons.org/licenses/by/4.0/
dc.rightsEmbargo: ends 2019-02-13
dc.sourcepissn: 0049-1241
dc.sourceeissn: 1552-8294
dc.subjectArticles
dc.subjectcomposite estimation
dc.subjectdirect estimation
dc.subjectEBLUP
dc.subjectfactor analysis
dc.subjectfactor scores
dc.subjectmodel-based estimation
dc.titleSmall Area Estimation of Latent Economic Well-being
dc.typearticle
dc.date.updated2021-10-02T17:11:54Z


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