Small area estimation of proportions and rates under area-level Dirichlet mixed models

Abstract

This paper introduces an area-level Dirichlet mixed model for predicting compositional indicators of small areas. Direct estimators of the domain category proportions of a classification variable are the target variables of the new model. Once the model has been selected and fitted to the data, predictors of proportions, totals and rates of small areas are obtained and their mean square errors are estimated by parametric bootstrap. Several simulation experiments, designed to analyse the behaviour of the fitting algorithm, the small area predictors and the bootstrap procedure, are carried out. An application to real data from the Spanish Labour Force Survey, in the last quarter of 2022, is given. The target is the estimation of proportions of employed, unemployed and inactive people and unemployment rates by province, sex and age group.