A class of composite estimators of small area quantities that exploit spatial (distancerelated)
similarity is derived. It is based on a distribution-free model for the areas, but the
estimators are aimed to have optimal design-based properties. Composition is applied also
to estimate some of the global parameters on which the small area estimators depend.
It is shown that the commonly adopted assumption of random effects is not necessary
for exploiting the similarity of the districts (borrowing ...
A class of composite estimators of small area quantities that exploit spatial (distancerelated)
similarity is derived. It is based on a distribution-free model for the areas, but the
estimators are aimed to have optimal design-based properties. Composition is applied also
to estimate some of the global parameters on which the small area estimators depend.
It is shown that the commonly adopted assumption of random effects is not necessary
for exploiting the similarity of the districts (borrowing strength across the districts). The
methods are applied in the estimation of the mean household sizes and the proportions of
single-member households in the counties (comarcas) of Catalonia. The simplest version of
the estimators is more efficient than the established alternatives, even though the extent
of spatial similarity is quite modest.
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