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Small area estimation of labour force indicators under a multinomial model with correlated time and area effects


  • Esther López-Vizcaíno
  • María José Lombardía
  • Domingo Morales


type="main" xml:id="rssa12085-abs-0001"> The aim of the paper is the estimation of small area labour force indicators like totals of employed and unemployed people and unemployment rates. Small area estimators of these quantities are derived from four multinomial logit mixed models, including a model with correlated time and area random effects. Mean-squared errors are used to measure the accuracy of the estimators proposed and they are estimated by analytic and bootstrap methods. The methodology introduced is applied to real data from the Spanish Labour Force Survey of Galicia.

Suggested Citation

  • Esther López-Vizcaíno & María José Lombardía & Domingo Morales, 2015. "Small area estimation of labour force indicators under a multinomial model with correlated time and area effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 535-565, June.
  • Handle: RePEc:bla:jorssa:v:178:y:2015:i:3:p:535-565

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    Cited by:

    1. repec:spr:soinre:v:138:y:2018:i:3:d:10.1007_s11205-017-1678-1 is not listed on IDEAS
    2. Schmid, Timo & Bruckschen, Fabian & Salvati, Nicola & Zbiranski, Till, 2016. "Constructing socio-demographic indicators for National Statistical Institutes using mobile phone data: Estimating literacy rates in Senegal," Discussion Papers 2016/9, Free University Berlin, School of Business & Economics.
    3. Miguel Boubeta & María José Lombardía & Domingo Morales, 2016. "Empirical best prediction under area-level Poisson mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 548-569, September.
    4. Boubeta, Miguel & Lombardía, María José & Morales, Domingo, 2017. "Poisson mixed models for studying the poverty in small areas," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 32-47.
    5. repec:spr:testjl:v:27:y:2018:i:2:d:10.1007_s11749-017-0545-3 is not listed on IDEAS
    6. repec:eee:csdana:v:126:y:2018:i:c:p:19-38 is not listed on IDEAS

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