Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/185323
Authors: 
Bedoya, Guadalupe
Bittarello, Luca
Davis, Jonathan
Mittag, Nikolas
Year of Publication: 
2018
Series/Report no.: 
IZA Discussion Papers No. 11863
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
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.
Subjects: 
distribution of treatment effects
impacts on outcome distributions
heterogeneous treatment effects
distributional impact analysis
policy evaluation
random control trials
JEL: 
C18
C21
C54
C93
D39
Document Type: 
Working Paper

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