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Small area estimation with spatial similarity

Authors: Nicholas Longford;

Small area estimation with spatial similarity

Abstract

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.

Country
Spain
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Keywords

multivariate shrinkage, exploiting similarity, composite estimation, Auxiliary information, composite estimation, design-based estimator, exploiting similarity, model-based estimator, multivariate shrinkage, small-area estimation, spatial similarity, spatial similarity, model-based estimator, small-area estimation, auxiliary information, design-based estimator, Statistics, Econometrics and Quantitative Methods, Sampling theory, sample surveys, Computational methods for problems pertaining to statistics, jel: jel:C42, jel: jel:C13, jel: jel:C14, jel: jel:C15, jel: jel:C1, jel: jel:C4

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
Green
hybrid
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