- Author
- Salvati Nicola (Universita di Pisa), Pratesi Monica (Universita di Pisa), Tzavidis Nikos (University of Manchester), Chambers Ray (University of Wollongong)
- Title
- Spatial M-Quantile Models for Small Area Estimation
- Source
- Statistics in Transition, 2009, vol. 10, nr 2, s. 251-267, rys., tab., bibliogr. s. 265-267
- Keyword
- Statystyka małych obszarów, Korelacja, Metody statystyczne, Modele symulacyjne
Small area estimates, Correlation, Statistical methods, Simulation models - Note
- summ.
- Abstract
- In small area estimation direct survey estimates that rely only on area-specific data can exhibit large sampling variability due to small sample sizes at the small area level. Efficient small area estimates can be constructed using explicit linking models that borrow information from related areas. The most popular class of models for this purpose are models that include random area effects. Estimation for these models typically assumes that the random area effects are uncorrelated. In many situations, however, it is reasonable to assume that the effects of neighbouring areas are correlated. Models that extend conventional random effects models to account for spatial correlation between the small areas have been recently proposed in literature. A new semi-parametric approach to small area estimation is based on the use of M-quantile models. Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumptions and are robust to the presence of outliers. In its current form, however, the M-quantile approach to small area estimation does not allow for spatially correlated area effects. The aim of this paper is to extend the M-quantile approach to account for such spatial correlation between small areas. (original abstract)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of Poznań University of Economics and Business
The Main Library of the Wroclaw University of Economics - Full text
- Show
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- Cited by
- ISSN
- 1234-7655
- Language
- eng