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An Applied Comparison of Area-Level Linear Mixed Models in Small Area Estimation |
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| Authors: | Luis Nobre Pereira Pedro Simões Coelho |
| Affiliation: | 1. Escola Superior de Gest?o, Hotelaria e Turismo, Universidade do Algarve , Faro , Portugal;2. Centro de Investiga??o sobre o Espa?o e as Organiza??es, Universidade do Algarve , Faro , Portugal;3. Instituto Superior de Estatística e Gest?o de Informa??o, Universidade Nova de Lisboa , Lisboa , Portugal;4. Faculty of Economics, Ljubljana University , Ljubljana , Slovenia |
| Abstract: | This article reviews four area-level linear mixed models that borrow strength by exploiting the possible correlation among the neighboring areas or/and past time periods. Its main goal is to study if there are efficiency gains when a spatial dependence or/and a temporal autocorrelation among random-area effects are included into the models. The Fay–Herriot estimator is used as benchmark. A design-based simulation study based on real data collected from a longitudinal survey conducted by a statistical office is presented. Our results show that models that explore both spatial and chronological association considerably improve the efficiency of small area estimates. |
| Keywords: | Empirical best linear unbiased prediction Linear mixed model Small area estimation Spatial correlation Temporal autocorrelation |