What is it about?
World Bank produces poverty estimates with their accuracy measures for a number of developing countries based on two-level regression model considering household and cluster as the two levels under the assumption of no between area (target small area) variability. However, area-level variation can not be explained always by the explanatory variables specified in the regression model. In such case, the World Bank method (the ELL method) produces more accuracy than the expected one. The article has dealt with such a problem and showed a way to resolve such problem.
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Why is it important?
Accuracy measurements (mean squared errors) help the policy makers in finding the more vulnerable area and hence help to take decision in aid-distribution. So the article is important for policy makers and stake-holders in planning of aid-distribution.
Perspectives
Preparing the article takes about three and half years after presenting different parts of this article in different national and international conferences. I got scope to meet with the small area estimation research group, that actually help me to improve my work. Finally I can publish the work which is a real pleasure to me.
Dr. Sumonkanti Das
Shahjalal University of Science and Technology
Read the Original
This page is a summary of: Robust mean-squared error estimation for poverty estimates based on the method of Elbers, Lanjouw and Lanjouw, Journal of the Royal Statistical Society Series A (Statistics in Society), August 2017, Wiley,
DOI: 10.1111/rssa.12311.
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