Summary
A Fay-Herriot model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a small subset of domains where direct estimates of the variable of interest cannot be described in the same way as in its complementary subset of domains. Algorithms and formulas to fit the model, to calculate EBLUPs and to estimate mean squared errors are given. A Monte Carlo simulation experiment is carried out to investigate the gain of precision obtained by using the proposed model. An application to Spanish Labour Force Survey data is also given.
The research in this paper was done in memory of our beloved friend María Luisa Menéndez. It was a great honor to coauthor papers and to live beautiful moments with her.
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Esteban, M.D., Herrador, M., Hobza, T., Morales, D. (2011). An Area-Level Model with Fixed or Random Domain Effects in Small Area Estimation Problems. In: Pardo, L., Balakrishnan, N., Gil, M.Á. (eds) Modern Mathematical Tools and Techniques in Capturing Complexity. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20853-9_21
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DOI: https://doi.org/10.1007/978-3-642-20853-9_21
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