New important developments in small area estimation
Pfeffermann, Danny (2013) New important developments in small area estimation. Statistical Science, 28, (1), 40-68. (doi:10.1214/12-STS395).
The problem of small area estimation (SAE) is how to produce reliable estimates of characteristics of interest such as means, counts, quantiles, etc., for areas or domains for which only small samples or no samples are available, and how to assess their precision. The purpose of this paper is to review and discuss some of the new important developments in small area estimation methods. Rao (2003) wrote a very comprehensive book, which covers all the main developments in this topic until that time. A few review papers have been written after 2003 but they are limited in scope. Hence, the focus of this review is on new developments in the last 7-8 years but to make the review more self-contained, I also mention shortly some of the older developments. The review covers both design-based and model-dependent methods, with the latter methods further classified into frequentist and Bayesian methods. The style of the paper is similar to the style of my previous review on SAE published in 2002, explaining the new problems investigated and describing the proposed solutions, but without dwelling on theoretical details, which can be found in the original articles. I hope that this paper will be useful both to researchers who like to learn more on the research carried out in SAE and to practitioners who might be interested in the application of the new methods.
|Keywords:||benchmarking, calibration, design-based methods, empirical likelihood, informative sampling, matching priors, measurement errors, model checking, m-quantile, ordered means, outliers, poverty mapping, prediction intervals, prediction mse, spline regression, two part model|
|Subjects:||H Social Sciences > HA Statistics
H Social Sciences > HN Social history and conditions. Social problems. Social reform
|Divisions:||University Structure - Pre August 2011 > School of Social Sciences
Faculty of Social and Human Sciences > Southampton Statistical Sciences Research Institute
|Date Deposited:||28 Jun 2011 15:05|
|Last Modified:||27 Mar 2014 19:43|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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