Small area estimation of poverty proportions under area-level time models
The unit-level small area estimation approach has no standard procedure and each case needs separate modeling when the domain parameters are not linear or the target variable is not normally distributed. Area-level linear mixed models can be generally applied to produce EBLUP estimates of linear and non linear parameters because direct estimates are weighted sums, so that the assumption of normality may be acceptable. The problem of estimating small area non linear parameters is treated, with special emphasis on the estimation of poverty proportions. Borrowing strength from time by using area-level linear time models is proposed. Four time-dependent area-level models are considered and the behavior of the two basic ones is empirically investigated. The developed model-based methodology for estimating poverty proportions is applied in the Spanish Living Conditions Survey.
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- Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST- An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-96, June.
- González-Manteiga, W. & Lombardia, M.J. & Molina, I. & Morales, D. & Santamaria, L., 2008. "Analytic and bootstrap approximations of prediction errors under a multivariate Fay-Herriot model," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5242-5252, August.
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