Household composition reveals vital aspects of the socioeconomic situation and major changes in developed countries for decision-making and mapping the distribution of single-person households is highly relevant and useful. Driven by the Spanish Household Budget Survey data, we propose a new statistical methodology for small area estimation of proportions and total counts of single-person households. Estimation domains are defined as crosses of province, sex and age group of the main breadwinner of the household. Predictors are based on area-level zero-inflated Poisson mixed models. Model parameters are estimated by maximum likelihood and mean squared errors by parametric bootstrap. Several simulation experiments are carried out to empirically investigate the properties of these estimators and predictors. Finally, the paper concludes with an application to real data from 2016.
Household composition reveals vital aspects of the socioeconomic situation and major changes in developed countries for decision-making and mapping the distribution of single-person households is highly relevant and useful. Driven by the Spanish Household Budget Survey data, we propose a new statistical methodology for small area estimation of proportions and total counts of single-person households. Estimation domains are defined as crosses of province, sex and age group of the main breadwinner of the household. Predictors are based on area-level zero-inflated Poisson mixed models. Model parameters are estimated by maximum likelihood and mean squared errors by parametric bootstrap. Several simulation experiments are carried out to empirically investigate the properties of these estimators and predictors. Finally, the paper concludes with an application to real data from 2016.