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Abstract
Journal of Official Statistics, Vol.15, No.1, 1999. pp. 124

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Organization of Small Area Estimators Using a Generalized Linear Regression Framework.

Abstract:
In this article existing small area estimators are described, including Bayesian ones that have been proposed. Ghosh and Rao (1994) provide an excellent description of many of the techniques found in the current literature, pointing out the importance of the level of aggregation at which the models are developed. In this article a literature review is conducted for the estimators. The estimators are then organized from a general linear regression perspective, summarizing and showing where certain methods can be viewed as minor variations or generalizations of others. This includes a derivation of the conditions under which it is possible to view synthetic estimation as a form of regression. The goal of this article is to pull together the wide range of approaches that have been used for small area estimation. From this review a clearer understanding of the present techniques and their interrelationships is apparent.

Keywords:
Bayes; synthetic estimation; components of variance regression.

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