Small area estimation: new developments and directions

Pfeffermann, Danny (2002) Small area estimation: new developments and directions. International Statistical Review, 70, (1), 125-143. (doi:10.1111/j.1751-5823.2002.tb00352.x).


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The purpose of this paper is to provide a critical review of the main advances in small area
estimation (SAE) methods in recent years. We also discuss some of the earlier developments,
which serve as a necessary background for the new studies. The review focuses on model
dependent methods with special emphasis on point prediction of the target area quantities,
and mean square error assessments. The new models considered are models used for discrete
measurements, time series models and models that arise under informative sampling. The
possible gains from modeling the correlations among small area random effects used to
represent the unexplained variation of the small area target quantities are examined. For
review and appraisal of the earlier methods used for SAE, see Ghosh and Rao (1994).

Item Type: Article
Digital Object Identifier (DOI): doi:10.1111/j.1751-5823.2002.tb00352.x
ISSNs: 0306-7734 (print)
Related URLs:
Keywords: best linear unbiased prediction, cross-sectional correlations, empirical bayes, hierarchical bayes, informative sampling, mixed models, time series models
Subjects: H Social Sciences > HA Statistics
Divisions : University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
ePrint ID: 38494
Accepted Date and Publication Date:
Date Deposited: 19 Jun 2006
Last Modified: 31 Mar 2016 12:08

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