Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect

Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develo...

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Main Authors:	Bedoya, Guadalupe, Bittarello, Luca, Davis, Jonathan, Mittag, Nikolas
Format:	Working Paper
Language:	English en_US
Published:	World Bank, Washington, DC 2017
Subjects:	DISTRIBUTIONAL EFFECTS RANDOMIZED CONTROL TRIAL OUTCOME DISTRIBUTIONS TREATMENT EFFECTS
Online Access:	http://documents.worldbank.org/curated/en/292901499351272899/Distributional-impact-analysis-toolkit-and-illustrations-of-impacts-beyond-the-average-treatment-effect http://hdl.handle.net/10986/27642

id	okr-10986-27642
recordtype	oai_dc
spelling	okr-10986-276422021-06-08T14:42:47Z Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect Bedoya, Guadalupe Bittarello, Luca Davis, Jonathan Mittag, Nikolas DISTRIBUTIONAL EFFECTS RANDOMIZED CONTROL TRIAL OUTCOME DISTRIBUTIONS TREATMENT EFFECTS Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining the distributional impacts of programs and policies. This toolkit reviews methods to do so, focusing on their application to randomized control trials. The paper emphasizes two strands of the literature: estimation of impacts on outcome distributions and estimation of the distribution of treatment impacts. The article then discusses extensions to conditional treatment effect heterogeneity, that is, to analyses of how treatment impacts vary with observed characteristics. The paper offers advice on inference, testing, and power calculations, which are important when implementing distributional analyses in practice. Finally, the paper illustrates select methods using data from two randomized evaluations. 2017-07-19T17:05:08Z 2017-07-19T17:05:08Z 2017-07 Working Paper http://documents.worldbank.org/curated/en/292901499351272899/Distributional-impact-analysis-toolkit-and-illustrations-of-impacts-beyond-the-average-treatment-effect http://hdl.handle.net/10986/27642 English en_US Policy Research Working Paper;No. 8139 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	DISTRIBUTIONAL EFFECTS RANDOMIZED CONTROL TRIAL OUTCOME DISTRIBUTIONS TREATMENT EFFECTS
spellingShingle	DISTRIBUTIONAL EFFECTS RANDOMIZED CONTROL TRIAL OUTCOME DISTRIBUTIONS TREATMENT EFFECTS Bedoya, Guadalupe Bittarello, Luca Davis, Jonathan Mittag, Nikolas Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
relation	Policy Research Working Paper;No. 8139
description	Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining the distributional impacts of programs and policies. This toolkit reviews methods to do so, focusing on their application to randomized control trials. The paper emphasizes two strands of the literature: estimation of impacts on outcome distributions and estimation of the distribution of treatment impacts. The article then discusses extensions to conditional treatment effect heterogeneity, that is, to analyses of how treatment impacts vary with observed characteristics. The paper offers advice on inference, testing, and power calculations, which are important when implementing distributional analyses in practice. Finally, the paper illustrates select methods using data from two randomized evaluations.
format	Working Paper
author	Bedoya, Guadalupe Bittarello, Luca Davis, Jonathan Mittag, Nikolas
author_facet	Bedoya, Guadalupe Bittarello, Luca Davis, Jonathan Mittag, Nikolas
author_sort	Bedoya, Guadalupe
title	Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
title_short	Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
title_full	Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
title_fullStr	Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
title_full_unstemmed	Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect
title_sort	distributional impact analysis : toolkit and illustrations of impacts beyond the average treatment effect
publisher	World Bank, Washington, DC
publishDate	2017
url	http://documents.worldbank.org/curated/en/292901499351272899/Distributional-impact-analysis-toolkit-and-illustrations-of-impacts-beyond-the-average-treatment-effect http://hdl.handle.net/10986/27642
_version_	1764465624726110208

Distributional Impact Analysis : Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect

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