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Nonparametric Tests for Treatment Effect Heterogeneity

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Author Info

  • Crump, Richard K.

    ()
    (Federal Reserve Bank of New York)

  • Hotz, V. Joseph

    ()
    (Duke University)

  • Imbens, Guido W.

    ()
    (Stanford University)

  • Mitnik, Oscar A.

    ()
    (University of Miami)

Abstract

A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are interested in the effects of programs beyond estimates of the overall average or the average for the subpopulation of treated individuals. It may be of substantive interest to investigate whether there is any subpopulation for which a program or treatment has a nonzero average effect, or whether there is heterogeneity in the effect of the treatment. The hypothesis that the average effect of the treatment is zero for all subpopulations is also important for researchers interested in assessing assumptions concerning the selection mechanism. In this paper we develop two nonparametric tests. The first test is for the null hypothesis that the treatment has a zero average effect for any subpopulation defined by covariates. The second test is for the null hypothesis that the average effect conditional on the covariates is identical for all subpopulations, in other words, that there is no heterogeneity in average treatment effects by covariates. Sacrificing some generality by focusing on these two specific null hypotheses we derive tests that are straightforward to implement.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2091.

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Length: 34 pages
Date of creation: Apr 2006
Date of revision:
Publication status: published in: Review of Economics and Statistics, 2008, 90 (3), 389-405
Handle: RePEc:iza:izadps:dp2091

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Keywords: treatment effect heterogeneity; unconfoundedness; causality; average treatment effects;

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References

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  1. Richard Blundell & Monica Costa Dias, 2002. "Alternative approaches to evaluation in empirical microeconomics," CeMMAP working papers CWP10/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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Citations

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Cited by:
  1. Christian Volpe Martincus & Jerónimo Carballo & Pablo M. García, 2010. "Public Programs to Promote Firms' Exports in Developing Countries: Are There Heterogeneous Effects by Size Categories?," IDB Publications 36764, Inter-American Development Bank.
  2. Manuel S. Santos & Juan Pablo Rincon-Zapatero, 2007. "Moving the Goalposts: Differentiability of the Value Function without Interiority Assumptions," Working Papers 0614, University of Miami, Department of Economics.
  3. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
  4. Sokbae 'Simon' Lee & Yoon-Jae Whang, 2009. "Nonparametric tests of conditional treatment effects," CeMMAP working papers CWP36/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. 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 0330, National Bureau of Economic Research, Inc.
  6. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2004. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Working Papers 0716, University of Miami, Department of Economics, revised 12 Jun 2007.
  7. Guido Imbens & Jeffrey Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. 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 0608, University of Miami, Department of Economics.
  9. 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).
  10. Philip M. Gleason & Alexandra M. Resch & Jillian A. Berk, 2012. "Replicating Experimental Impact Estimates Using a Regression Discontinuity Approach," Mathematica Policy Research Reports 7461, Mathematica Policy Research.
  11. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
  12. 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, vol. 35(3), pages 356-379.
  13. 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, vol. 48(2), pages 269-286, February.

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