Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches

The performance of the Simple Poverty Scorecard is compared against the performance of established regression-based estimators. All estimates are benchmarked against observed poverty status based on household expenditure (or income) data from house...

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Main Authors:	Diamond, Alexis, Gill, Michael, Rebolledo Dellepiane, Miguel, Skoufias, Emmanuel, Vinha, Katja, Xu, Yiqing
Format:	Working Paper
Language:	English en_US
Published:	World Bank, Washington, DC 2016
Subjects:	simple poverty scorecard PPI headcount poverty rate
Online Access:	http://documents.worldbank.org/curated/en/2016/08/26695758/estimating-poverty-rates-target-populations-assessment-simple-poverty-scorecard-alternative-approaches http://hdl.handle.net/10986/25038

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spelling	okr-10986-250382021-04-23T14:04:28Z Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches Diamond, Alexis Gill, Michael Rebolledo Dellepiane, Miguel Skoufias, Emmanuel Vinha, Katja Xu, Yiqing simple poverty scorecard PPI headcount poverty rate The performance of the Simple Poverty Scorecard is compared against the performance of established regression-based estimators. All estimates are benchmarked against observed poverty status based on household expenditure (or income) data from household socioeconomic surveys that span nearly a decade and are representative of subnational populations. When the models all adopt the same "one-size-fits-all" training approach, there is no meaningful difference in performance and the Simple Poverty Scorecard is as good as any of the regression-based estimators. The findings change, however, when the regression-based estimators are "trained" on "training sets" that more closely resemble potential subpopulation test sets. In this case, regression-based models outperform the nationally calculated Simple Poverty Scorecard in terms of bias and variance. These findings highlight the fundamental trade-off between simplicity of use and accuracy. 2016-09-12T20:22:31Z 2016-09-12T20:22:31Z 2016-08 Working Paper http://documents.worldbank.org/curated/en/2016/08/26695758/estimating-poverty-rates-target-populations-assessment-simple-poverty-scorecard-alternative-approaches http://hdl.handle.net/10986/25038 English en_US Policy Research Working Paper;No. 7793 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English en_US
topic	simple poverty scorecard PPI headcount poverty rate
spellingShingle	simple poverty scorecard PPI headcount poverty rate Diamond, Alexis Gill, Michael Rebolledo Dellepiane, Miguel Skoufias, Emmanuel Vinha, Katja Xu, Yiqing Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
relation	Policy Research Working Paper;No. 7793
description	The performance of the Simple Poverty Scorecard is compared against the performance of established regression-based estimators. All estimates are benchmarked against observed poverty status based on household expenditure (or income) data from household socioeconomic surveys that span nearly a decade and are representative of subnational populations. When the models all adopt the same "one-size-fits-all" training approach, there is no meaningful difference in performance and the Simple Poverty Scorecard is as good as any of the regression-based estimators. The findings change, however, when the regression-based estimators are "trained" on "training sets" that more closely resemble potential subpopulation test sets. In this case, regression-based models outperform the nationally calculated Simple Poverty Scorecard in terms of bias and variance. These findings highlight the fundamental trade-off between simplicity of use and accuracy.
format	Working Paper
author	Diamond, Alexis Gill, Michael Rebolledo Dellepiane, Miguel Skoufias, Emmanuel Vinha, Katja Xu, Yiqing
author_facet	Diamond, Alexis Gill, Michael Rebolledo Dellepiane, Miguel Skoufias, Emmanuel Vinha, Katja Xu, Yiqing
author_sort	Diamond, Alexis
title	Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
title_short	Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
title_full	Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
title_fullStr	Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
title_full_unstemmed	Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches
title_sort	estimating poverty rates in target populations : an assessment of the simple poverty scorecard and alternative approaches
publisher	World Bank, Washington, DC
publishDate	2016
url	http://documents.worldbank.org/curated/en/2016/08/26695758/estimating-poverty-rates-target-populations-assessment-simple-poverty-scorecard-alternative-approaches http://hdl.handle.net/10986/25038
_version_	1764458207878578176

Estimating Poverty Rates in Target Populations : An Assessment of the Simple Poverty Scorecard and Alternative Approaches

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