Paper #1105

Title:

Small-area estimation with spatial similarity

Author:

Nicholas Longford

Date:

July 2008 (Revised: September 2009)

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.

Keywords:

Auxiliary information, composite estimation, design-based estimator, exploiting similarity, model-based estimator, multivariate shrinkage, small-area estimation, spatial similarity

JEL codes:

C1, C13, C14, C15, C4, C42

Area of Research:

Statistics, Econometrics and Quantitative Methods

Published in:

Computational Statistics and Data Analysis, 10.1016/j.csda.2009.09.005

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