Local statistical offices often dispose of very rich databases of spatially referenced socio– economic data. The high degree of spatial detail of such information is often not too useful for practical purposes in that firms or local authorities are interested in information aggregated at higher levels. The standard practice usually consists in aggregating the data at some prespecified geographi...

Small area estimation techniques are employed when sample data are insufficient for acceptably precise direct estimation in domains of interest. These techniques typically rely on regression models that use both covariates and random effects to explain variation between domains. However, such models also depend on strong distributional assumptions, require a formal specification of the random p...

Estimation of small area means in the presence of area level auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. The assumptions on the area level regression are considerably weaker than standard small area models. Both the small area mean functions and the between area variance function are modeled as smooth functions of area level covar...

Riassunto: L’esigenza sempre più frequente di ottenere stime relative a zone e domini ridotti che non sono stati considerati tali al momento del disegno dell’indagine, ha determinato lo sviluppo di metodi statistici di stima per piccole aree. Questo lavoro ha lo scopo di valutare la possibilità di migliorare le stime dei parametri di interesse attraverso l’introduzione di un modello spaziale ne...

Valmária Rocha da Silva ∗ Fernando Antônio da Silva Moura † Abstract The main aim of this work is to propose two important connected extensions of the Fay and Heriot (1979) area level small area estimation model that might be of practical and theoretical interests. The first extension allows for the sampling error to be non-symmetrically distributed. This is important for the case that the samp...

Abstract. National statistical offices are often required to provide statistical information about characteristics of the population, such as mean income or unemployment rate, at several administrative or small area levels. Having good area level estimates is important because policies will often be based on this type of information. In this paper we describe how Bayesian hierarchical models ca...