Small area estimation via unmatched sampling and linking models |
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Authors: | Shonosuke Sugasawa Tatsuya Kubokawa J N K Rao |
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Affiliation: | 1.Risk Analysis Research Center,The Institute of Statistical Mathematics,Tokyo,Japan;2.Faculty of Economics,University of Tokyo,Tokyo,Japan;3.School of Mathematics and Statistics,Carleton University,Ottawa,Canada |
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Abstract: | The authors use an empirical Bayes (EB) approach to small area estimation under area-level unmatched sampling and linking models. Model parameters are estimated by a unified expectation and maximization (EM) algorithm and used to obtain EB estimators of area parameters. Results are extended to a nonparametric linking model based on a spline approximation. Approximate EB estimators that are computationally simpler are also obtained. Different bootstrap approaches to estimating the mean squared error (MSE) of the EB estimators are proposed. Results of a simulation study on the performance of the proposed methods are presented. Proposed methods are applied to data from a survey of family income and expenditure in Japan and poverty rates in Spanish provinces. |
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