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Bootstrap for estimating the mean squared error of the spatial EBLUP

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Author Info
Isabel Molina ()
Nicola Salvati ()
Monica Pratesi ()
Abstract

This work assumes that the small area quantities of interest follow a Fay-Herriot model with spatially correlated random area effects. Under this model, parametric and nonparametric bootstrap procedures are proposed for estimating the mean squared error of the EBLUP (Empirical Best Linear Unbiased Predictor). A simulation study compares the bootstrap estimates with an asymptotic analytical approximation and studies the robustness to non-normality. Finally, two applications with real data are described.

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws073408.

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Date of creation: Apr 2007
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Handle: RePEc:cte:wsrepe:ws073408

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