Bootstrap for estimating the mean squared error of the spatial EBLUP

Isabel Molina, Nicola Salvati and Monica Pratesi

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

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.

Keywords: Spatial; correlation; Simultaneously; autoregressive; process; Parametric; bootstrap; Nonparametric; bootstrap (search for similar items in EconPapers)
Date: 2007-04
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws073408

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