 Robust mean‐squared error estimation for poverty estimates based on the method of Elbers, Lanjouw and LanjouwSumonkanti Das and Ray Chambers Journal of the Royal Statistical Society Series A, 2017, vol. 180, issue 4, 1137-1161 Abstract: The method of Elbers, Lanjouw and Lanjouw (ELL) is the small area estimation method developed by the World Bank for poverty mapping and is widely used in developing countries. However, it has been criticized because of its assumption of negligible between‐area variability when used to calculate small area poverty estimates. In particular, the mean‐squared errors (MSEs) of these estimates are significantly underestimated when this between‐area variability cannot be adequately explained by the model covariates. A method of MSE estimation for ELL‐type estimates is proposed which is robust to significant unexplained between‐area variability. Simulation results show that the method proposed performs better than standard ELL MSE estimators when the area homogeneity assumption is violated. An application to a Bangladesh poverty mapping study provides some empirical evidence for this robustness. Date: 2017 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:180:y:2017:i:4:p:1137-1161 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC. |
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