Small area estimation of proportions under area-level compositional mixed models

• María Dolores Esteban ^[1] ; María José Lombardía ^[2] ; Esther López-Vizcaíno ^[3] ; Domingo Morales ^[1] ; Agustín Pérez ^[1]
  1. [1] Universidad Miguel Hernández de Elche

     Universidad Miguel Hernández de Elche

     Elche, España

     
  2. [2] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
  3. [3] Instituto Galego de Estatística, Santiago de Compostela, Spain

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 29, Nº. 3, 2020, págs. 793-818
• Idioma: inglés
• DOI: 10.1007/s11749-019-00688-w
• Texto completo no disponible (Saber más ...)
• Resumen

  • This paper introduces area-level compositional mixed models by applying transformations to a multivariate Fay–Herriot model. Small area estimators of the proportions of the categories of a classification variable are derived from the new model, and the corresponding mean squared errors are estimated by parametric bootstrap. Several simulation experiments designed to analyse the behaviour of the introduced estimators are carried out. An application to real data from the Spanish Labour Force Survey of Galicia (north-west of Spain), in the first quarter of 2017, is given. The target is the estimation of domain proportions of people in the four categories of the variable labour status: under 16 years, employed, unemployed and inactive.

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