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Activity Number: 213
Type: Invited
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #303852
Title: Semi-parametric Small Area Estimation Based Prediction Methods to Track Poverty: Validation and Applications
Author(s): Roy van der Weide*+ and Chris Elbers
Companies: The World Bank and Vrije Universiteit Amsterdam
Address: , , ,
Keywords: Small Area Statistics ; Poverty ; Inequality ; Survey Methods ; Semi-Parametric Empirical Best Estimation

A small area estimation technique for producing "Poverty Maps", developed by Elbers, Lanjouw and Lanjouw (2002, 2003), has seen application in a large number of countries. Opportunities to formally test small area estimation methods remain rare due to lack of appropriate detailed data. This paper compares a set of predicted welfare estimates based on a generalized ELL methodology against their true values, in a setting where these true values are known. The new approach accommodates Empirical Best estimation but does not make restrictive assumptions about the distribution functions of the errors. We will present a unique empirical application using population census data from Denmark and/or the state of Minas Gerais, Brazil, which include unit record income data.

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