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Bootstrap for estimating the mean squared error of the spatial EBLUP

  • Molina, Isabel
  • Salvati, Nicola
  • Pratesi, Monica
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    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 de Madrid. Departamento de Estadística in its series DES - Working Papers. Statistics and Econometrics. WS with number ws073408.

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