ARTICLE
TITLE

On the Simulation Study of Jackknife and Bootstrap MSE Estimators of a Domain Mean Predictor for Fay-Herriot Model

SUMMARY

 We consider the problem of the estimation of the mean squared error (MSE) of some domain mean predictor for Fay-Herriot model. In the simulation study we analyze properties of eight MSE estimators including estimators based on the jackknife method (Jiang, Lahiri, Wan, 2002; Chen, Lahiri, 2002; 2003) and parametric bootstrap (Gonzalez-Manteiga et al., 2008; Buthar, Lahiri, 2003). In the standard Fay-Herriot model the independence of random effects is assumed, and the biases of the MSE estimators are small for large number of domains. The aim of the paper is the comparison of the properties of MSE estimators for different number of domains and the misspecification of the model due to the correlation of random effects in the simulation study. 

PAGES
pp. 169 - 183
COLLECTIONS
Economy

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