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Nonparametric Tests for Treatment Effect Heterogeneity

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  • Mitnik, Oscar K.
  • Imbens, Guido
  • Hotz, V. Joseph
  • Crump, Richard K.

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.

Suggested Citation

  • Mitnik, Oscar K. & Imbens, Guido & Hotz, V. Joseph & Crump, Richard K., 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," Scholarly Articles 3039049, Harvard University Department of Economics.
    • Handle: RePEc:hrv:faseco:3039049
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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