Nonparametric Tests for Treatment Effect Heterogeneity

Richard K. Crump (), V. Joseph Hotz, Guido W. Imbens and Oscar A. Mitnik ()
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V. Joseph Hotz: Department of Economics, Duke University, and NBER
Guido W. Imbens: Department of Economics, Harvard University, and NBER

The Review of Economics and Statistics, 2008, vol. 90, issue 3, pages 389-405

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. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Date: 2008

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Related works:
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity (2006)
Working Paper: Nonparametric Tests for Treatment Effect Heterogeneity (2006)
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