Revisiting Targeting in Social Assistance
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...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Online |
| Published: |
Washington, DC: World Bank
2022
|
| Subjects: | |
| Online Access: | https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e https://hdl.handle.net/10986/37228 |
| _version_ | 1866367694319648768 |
|---|---|
| author | Leite, Phillippe Grosh, Margaret Wai-Poi, Matthew Tesliuc, Emil |
| author_facet | Leite, Phillippe Grosh, Margaret Wai-Poi, Matthew Tesliuc, Emil |
| author_sort | Leite, Phillippe |
| collection | Colección Libros - Series (activas) |
| 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 | Online Book |
| id | wb-10986-37228 |
| institution | Banco Mundial |
| publishDate | 2022 |
| publisher | Washington, DC: World Bank |
| record_format | dspace |
| spelling | wb-10986-372282026-04-28T14:34:48Z Revisiting Targeting in Social Assistance A New Look at Old Dilemmas Leite, Phillippe Grosh, Margaret 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 Livre Libro https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e 978-1-4648-1814-1 https://hdl.handle.net/10986/37228 10.1596/978-1-4648-1814-1 Human Development Perspectives; CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank application/pdf Washington, DC: World Bank |
| spellingShingle | POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK Leite, Phillippe Grosh, Margaret Wai-Poi, Matthew Tesliuc, Emil Revisiting Targeting in Social Assistance |
| title | Revisiting Targeting in Social Assistance |
| title_full | Revisiting Targeting in Social Assistance |
| title_fullStr | Revisiting Targeting in Social Assistance |
| title_full_unstemmed | Revisiting Targeting in Social Assistance |
| title_short | Revisiting Targeting in Social Assistance |
| title_sort | revisiting targeting in social assistance |
| topic | POVERTY REDUCTION TAX AUTHORITY FISCAL POLICY FISCAL FRAMEWORK |
| url | https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099300006162240907/p1648760df4c480270bd0b02288943f413e https://hdl.handle.net/10986/37228 |
| work_keys_str_mv | AT leitephillippe revisitingtargetinginsocialassistance AT groshmargaret revisitingtargetinginsocialassistance AT waipoimatthew revisitingtargetinginsocialassistance AT tesliucemil revisitingtargetinginsocialassistance AT leitephillippe anewlookatolddilemmas AT groshmargaret anewlookatolddilemmas AT waipoimatthew anewlookatolddilemmas AT tesliucemil anewlookatolddilemmas |