Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas

Targeting is a commonly used, but much debated, policy within global social assistance practice. This book examines the well- known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear. Chapter 1 present...

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Main Authors:	Grosh, Margaret, Leite, Phillippe, Wai-Poi, Matthew, Tesliuc, Emil
Format:	Book
Published:	Washington, DC: World Bank 2022
Subjects:	POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK
Online Access:	https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e http://hdl.handle.net/10986/37228

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recordtype	oai_dc
spelling	okr-10986-372282022-07-06T20:16:22Z Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas Grosh, Margaret Leite, Phillippe Wai-Poi, Matthew Tesliuc, Emil POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK Targeting is a commonly used, but much debated, policy within global social assistance practice. This book examines the well- known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear. Chapter 1 presents a series of essays on the factors that shape choices around why or whether or how narrowly/broadly to target different parts of social assistance. Chapter 2 updates the global empirics around the outcomes and costs of focusing benefits on the poor or vulnerable. Chapter 3 illustrates the options and choices that must be made in moving from an abstract vision of focusing resources on the poor or vulnerable to more specific concepts and implementable definitions and procedures, and how the many choices should be informed by values, empirics and context. Chapter 4 provides a brief treatment of delivery systems and processes showing their importance to distributional outcomes and suggesting the many facets with room for improvement. Chapter 5 discusses the choice between targeting methods, how differences in purposes and contexts shape those. Chapter 6 summarizes and comprehensively updates the know-how with respect to the data and inference used by the different household-specific targeting methods. Chapter 7 contains a primer on measurement issues, going much deeper than usual and explaining how better measurement can lead to clearer understanding of targeting issues. Chapter 8 explores machine learning algorithms for household-specific mechanisms for eligibility determination. 2022-03-29T15:21:03Z 2022-03-29T15:21:03Z 2022-03-31 Book https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e 978-1-4648-1814-1 http://hdl.handle.net/10986/37228 Human Development Perspectives; CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank Washington, DC: World Bank Publications & Research
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
topic	POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK
spellingShingle	POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK Grosh, Margaret Leite, Phillippe Wai-Poi, Matthew Tesliuc, Emil Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
relation	Human Development Perspectives;
description	Targeting is a commonly used, but much debated, policy within global social assistance practice. This book examines the well- known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear. Chapter 1 presents a series of essays on the factors that shape choices around why or whether or how narrowly/broadly to target different parts of social assistance. Chapter 2 updates the global empirics around the outcomes and costs of focusing benefits on the poor or vulnerable. Chapter 3 illustrates the options and choices that must be made in moving from an abstract vision of focusing resources on the poor or vulnerable to more specific concepts and implementable definitions and procedures, and how the many choices should be informed by values, empirics and context. Chapter 4 provides a brief treatment of delivery systems and processes showing their importance to distributional outcomes and suggesting the many facets with room for improvement. Chapter 5 discusses the choice between targeting methods, how differences in purposes and contexts shape those. Chapter 6 summarizes and comprehensively updates the know-how with respect to the data and inference used by the different household-specific targeting methods. Chapter 7 contains a primer on measurement issues, going much deeper than usual and explaining how better measurement can lead to clearer understanding of targeting issues. Chapter 8 explores machine learning algorithms for household-specific mechanisms for eligibility determination.
format	Book
author	Grosh, Margaret Leite, Phillippe Wai-Poi, Matthew Tesliuc, Emil
author_facet	Grosh, Margaret Leite, Phillippe Wai-Poi, Matthew Tesliuc, Emil
author_sort	Grosh, Margaret
title	Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
title_short	Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
title_full	Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
title_fullStr	Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
title_full_unstemmed	Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas
title_sort	revisiting targeting in social assistance : a new look at old dilemmas
publisher	Washington, DC: World Bank
publishDate	2022
url	https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e http://hdl.handle.net/10986/37228
_version_	1764486770189139968

Revisiting Targeting in Social Assistance : A New Look at Old Dilemmas

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