Parametric transformed Fay-Herriot model for small area estimation

被引:6
作者
Sugasawa, Shonosuke [1 ]
Kubokawa, Tatsuya [2 ]
机构
[1] Univ Tokyo, Grad Sch Econ, Bunkyo Ku, Tokyo 1130033, Japan
[2] Univ Tokyo, Fac Econ, Bunkyo Ku, Tokyo 1130033, Japan
基金
日本学术振兴会;
关键词
Asymptotically unbiased estimator; Box-Cox transformation; Dual power transformation; Fay-Herriot model; Linear mixed model; Mean squared error; Parametric bootstrap; Small area estimation; MEAN-SQUARED ERROR; PREDICTION;
D O I
10.1016/j.jmva.2015.04.001
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Motivated from analysis of positive data such as income, revenue, harvests and production, the paper suggests the parametric transformed Fay-Herriot model in small-area estimation. When the dual power transformation is used as the parametric transformation, we provide consistent estimators of the transformation parameter, the regression coefficients and the variance component. The empirical best linear unbiased predictors which plug in those consistent estimators are suggested, and their mean squared errors (MSE) are asymptotically evaluated. A second-order unbiased estimator of the MSE is also given through the parametric bootstrap. Finally, performances of the suggested procedures are investigated through simulation and empirical studies. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:295 / 311
页数:17
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