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Nonparametric Tests for Treatment Effect Heterogeneity

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  • Richard K. Crump

    (Department of Economics, University of California, Berkeley)

  • V. Joseph Hotz

    (Department of Economics, Duke University, and NBER)

  • Guido W. Imbens

    (Department of Economics, Harvard University, and NBER)

  • Oscar A. Mitnik

    (Department of Economics, University of Miami, and IZA)

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.

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Bibliographic Info

Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 90 (2008)
Issue (Month): 3 (August)
Pages: 389-405

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Handle: RePEc:tpr:restat:v:90:y:2008:i:3:p:389-405

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References

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  3. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2006. "Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Reanalysis of the California GAIN Program," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 24(3), pages 521-566, July.
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  14. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, Econometric Society, vol. 71(4), pages 1161-1189, 07.
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  20. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0330, National Bureau of Economic Research, Inc.
  21. V. Joseph Hotz & Guido W. Imbens & Julie H. Mortimer, 1999. "Predicting the Efficacy of Future Training Programs Using Past Experiences," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0238, National Bureau of Economic Research, Inc.
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Citations

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Cited by:
  1. Hotz, V. Joseph & Crump, Richard K. & Mitnik, Oscar A. & Imbens, Guido, 2009. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Scholarly Articles 3007645, Harvard University Department of Economics.
  2. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1740, Cowles Foundation for Research in Economics, Yale University.
  3. Christian Volpe Martincus & Jer�nimo Carballo & Pablo M. Garcia, 2012. "Public programmes to promote firms’ exports in developing countries: are there heterogeneous effects by size categories?," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 44(4), pages 471-491, February.
  4. Manuel S. Santos & Juan Pablo Rincon-Zapatero, 2007. "Moving the Goalposts: Differentiability of the Value Function without Interiority Assumptions," Working Papers, University of Miami, Department of Economics 0614, University of Miami, Department of Economics.
  5. Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute for the Study of Labor (IZA).
  6. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in Estimation of Average Treatment Effects by Changing the Estimand," Working Papers, University of Miami, Department of Economics 0608, University of Miami, Department of Economics.
  7. Paul Ferraro & Merlin Hanauer, 2011. "Protecting Ecosystems and Alleviating Poverty with Parks and Reserves: ‘Win-Win’ or Tradeoffs?," Environmental & Resource Economics, European Association of Environmental and Resource Economists, European Association of Environmental and Resource Economists, vol. 48(2), pages 269-286, February.
  8. Ferraro, Paul J. & Miranda, Juan José, 2013. "Heterogeneous treatment effects and mechanisms in information-based environmental policies: Evidence from a large-scale field experiment," Resource and Energy Economics, Elsevier, Elsevier, vol. 35(3), pages 356-379.
  9. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0330, National Bureau of Economic Research, Inc.
  10. Albrecht, Konstanze & Von Essen, Emma & Parys, Juliane & Szech, Nora, 2011. "Updating, Self-Confidence and Discrimination," IZA Discussion Papers 6203, Institute for the Study of Labor (IZA).
  11. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
  12. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1927, Cowles Foundation for Research in Economics, Yale University.
  13. Philip M. Gleason & Alexandra M. Resch & Jillian A. Berk, 2012. "Replicating Experimental Impact Estimates Using a Regression Discontinuity Approach," Mathematica Policy Research Reports, Mathematica Policy Research 7461, Mathematica Policy Research.

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