Nonparametric Tests for Treatment Effect Heterogeneity

Oscar Mitnik, Guido Imbens, V. Joseph Hotz and Richard Crump

Scholarly Articles from Harvard University Department of Economics

Abstract: In this paper we develop two nonparametric tests of treatment effect heterogeneity. The first test is for the null hypothesis that the treatment has a zero average effect for all subpopulations defined by covariates. The second test is for the null hypothesis that the average effect conditional on the covariates is identical for all subpopulations, that is, that there is no heterogeneity in average treatment effects by covariates. We derive tests that are straightforward to implement and illustrate the use of these tests on data from two sets of experimental evaluations of the effects of welfare-to-work programs.

Date: 2008
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Citations: View citations in EconPapers (73)

Published in The Review of Economics and Statistics

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http://dash.harvard.edu/bitstream/handle/1/3039049/imbens_nonparametric.pdf (application/pdf)

Related works:
Journal Article: Nonparametric Tests for Treatment Effect Heterogeneity (2008)
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity (2006)
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity (2006)
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:hrv:faseco:3039049

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