Estimation of mean squared error of model-based small area estimators

Gauri Sankar Datta, Tatsuya Kubokawa, J. N. K. Rao and Isabel Molina
Additional contact information
Gauri Sankar Datta: Department of Statistics, University of Georgia
Tatsuya Kubokawa: Faculty of Economics, University of Tokyo
J. N. K. Rao: School of Mathematics and Statistics, Carleton University
Isabel Molina: Department of Statistics, University Carlos III de Madrid

No CIRJE-F-633, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: Estimation of small area means under a basic area level model is studied, using an empirical Bayes (best) estimator or a weighted estimator with fixed weights. Mean squared errors (MSEs) of the estimators and nearly unbiased (or exactly unbiased) estimators of MSE are derived under three different approaches: design based (approach 1), unconditional model based (approach 2) and conditional model based (approach 3). Performance of MSE estimators under the three approaches with respect to relative bias and coefficient of variation is also studied, using a simulation experiment.

Date: 2009-08

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Persistent link: http://EconPapers.repec.org/RePEc:tky:fseres:2009cf633

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