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Small area estimation-based prediction methods to track poverty : validation and applications, Volume 1
 
Author:Christiaensen, Luc; Lanjouw, Peter; Luoto, Jill; Stifel, David; Country:World;
Date Stored:2011/06/15Document Date:2011/06/01
Document Type:Policy Research Working PaperSubTopics:Regional Economic Development; Achieving Shared Growth; Rural Poverty Reduction; Debt Markets
Language:EnglishMajor Sector:Education; Public Administration, Law, and Justice; Health and other social services
Rel. Proj ID:1W-Equity And Development Research Program -- -- P099861;Region:The World Region
Report Number:WPS5683Sub Sectors:Health; Other social services; General education sector; General public administration sector; Law and justice
Collection Title:Policy Research working paper ; no. WPS 5683Paper is funded by the Knowledge for Change Program (KCP)TF No/Name:TF094629-KCP
Volume No:1  

Summary: Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Price deflators are also often missing or disputed. In response, poverty prediction methods that track consumption correlates as opposed to consumption itself have been developed. These methods typically assume that the estimated relation between consumption and its predictors is stable over time -- an assumption that cannot usually be tested directly. This study analyzes the performance of poverty prediction models based on small area estimation techniques. Predicted poverty estimates are compared with directly observed levels in two country settings where data comparability over time is not a problem. Prediction models that employ either non-staple food or non-food expenditures or a full set of assets as predictors are found to yield poverty estimates that match observed poverty well. This offers some support to the use of such methods to approximate the evolution of poverty. Two further country examples illustrate how an application of the method employing models based on household assets can help to adjudicate between alternative price deflators.

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