Original Article
Small area estimation of labour force indicators under a multinomial model with correlated time and area effects
Summary
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.
Citing Literature
Number of times cited according to CrossRef: 14
- Jan Pablo Burgard, María Dolores Esteban, Domingo Morales, Agustín Pérez, Small area estimation under a measurement error bivariate Fay–Herriot model, Statistical Methods & Applications, 10.1007/s10260-020-00515-9, (2020).
- Roberto Benavent, Domingo Morales, Small area estimation under a temporal bivariate area-level linear mixed model with independent time effects, Statistical Methods & Applications, 10.1007/s10260-020-00521-x, (2020).
- María Dolores Esteban, María José Lombardía, Esther López-Vizcaíno, Domingo Morales, Agustín Pérez, Small area estimation of expenditure means and ratios under a unit-level bivariate linear mixed model, Journal of Applied Statistics, 10.1080/02664763.2020.1803809, (1-26), (2020).
- Isabel Molina, Ewa Strzalkowska‐Kominiak, 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), 10.1111/rssa.12498, 183, 1, (281-310), (2019).
- Soraia Pereira, K.F. Turkman, Luís Correia, Håvard Rue, Unemployment estimation: Spatial point referenced methods and models, Spatial Statistics, 10.1016/j.spasta.2019.01.004, (2019).
- María Dolores Esteban, María José Lombardía, Esther López-Vizcaíno, Domingo Morales, Agustín Pérez, Small area estimation of proportions under area-level compositional mixed models, TEST, 10.1007/s11749-019-00688-w, (2019).
- Xin Wang, Emily Berg, Zhengyuan Zhu, Dongchu Sun, Gabriel Demuth, Small Area Estimation of Proportions with Constraint for National Resources Inventory Survey, Journal of Agricultural, Biological and Environmental Statistics, 10.1007/s13253-018-0329-6, 23, 4, (509-528), (2018).
- Hukum Chandra, Nicola Salvati, Ray Chambers, Small area estimation under a spatially non-linear model, Computational Statistics & Data Analysis, 10.1016/j.csda.2018.04.002, 126, (19-38), (2018).
- Tomáš Hobza, Domingo Morales, Laureano Santamaría, Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models, TEST, 10.1007/s11749-017-0545-3, 27, 2, (270-294), (2017).
- Timo Schmid, Fabian Bruckschen, Nicola Salvati, Till Zbiranski, Constructing sociodemographic indicators for national statistical institutes by using mobile phone data: estimating literacy rates in Senegal, Journal of the Royal Statistical Society: Series A (Statistics in Society), 10.1111/rssa.12305, 180, 4, (1163-1190), (2017).
- Miguel Boubeta, María José Lombardía, Domingo Morales, Poisson mixed models for studying the poverty in small areas, Computational Statistics & Data Analysis, 10.1016/j.csda.2016.10.014, 107, (32-47), (2017).
- Domingo Morales, María del Mar Rueda, Dolores Esteban, Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain, Social Indicators Research, 10.1007/s11205-017-1678-1, (2017).
- Ray Chambers, Nicola Salvati, Nikos Tzavidis, Semiparametric small area estimation for binary outcomes with application to unemployment estimation for local authorities in the UK, Journal of the Royal Statistical Society: Series A (Statistics in Society), 10.1111/rssa.12123, 179, 2, (453-479), (2015).
- Miguel Boubeta, María José Lombardía, Domingo Morales, Empirical best prediction under area-level Poisson mixed models, TEST, 10.1007/s11749-015-0469-8, 25, 3, (548-569), (2015).
