Advanced Search
MyIDEAS: Login to save this paper or follow this series

Nonparametric Tests for Treatment Effect Heterogeneity

Contents:

Author Info

  • 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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://dash.harvard.edu/bitstream/handle/1/3039049/imbens_nonparametric.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Harvard University Department of Economics in its series Scholarly Articles with number 3039049.

as in new window
Length:
Date of creation: 2008
Date of revision:
Publication status: Published in The Review of Economics and Statistics
Handle: RePEc:hrv:faseco:3039049

Contact details of provider:
Postal: Littauer Center, Cambridge, MA 02138
Phone: 617-495-2144
Fax: 617-495-7730
Web page: http://www.economics.harvard.edu/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Blundell, Richard & Costa Dias, Monica, 2008. "Alternative Approaches to Evaluation in Empirical Microeconomics," IZA Discussion Papers 3800, Institute for the Study of Labor (IZA).
  2. Enno Mammen, . "Comparing nonparametric versus parametric regression fits," Statistic und Oekonometrie 9205, Humboldt Universitaet Berlin.
  3. 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.
  4. Bitler, Marianne P. & Gelbach, Jonah B. & Hoynes, Hilary W., 2005. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," IZA Discussion Papers 1728, Institute for the Study of Labor (IZA).
  5. Hong, Yongmiao & White, Halbert, 1995. "Consistent Specification Testing via Nonparametric Series Regression," Econometrica, Econometric Society, Econometric Society, vol. 63(5), pages 1133-59, September.
  6. Haerdle,Wolfgang & Marron,J., 1987. "Semiparametric comparision of regression curve," Discussion Paper Serie A 93, University of Bonn, Germany.
  7. Chen, Xiaohong & Hong, Han & Tarozzi, Alessandro, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Working Papers, Yale University, Department of Economics 42, Yale University, Department of Economics.
  8. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
  9. Bierens, H.J., 1989. "A consistent conditional moment test of functional form," Serie Research Memoranda, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics 0064, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  10. 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.
  11. Guido W. Imbens & Whitney Newey & Geert Ridder, 2005. "Mean-square-error Calculations for Average Treatment Effects," IEPR Working Papers, Institute of Economic Policy Research (IEPR) 05.34, Institute of Economic Policy Research (IEPR).
  12. Bierens, Herman J., 1982. "Consistent model specification tests," Journal of Econometrics, Elsevier, Elsevier, vol. 20(1), pages 105-134, October.
  13. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 65(2), pages 261-94, April.
  14. Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82.
  15. Joseph Hotz, V. & Imbens, Guido W. & Mortimer, Julie H., 2005. "Predicting the efficacy of future training programs using past experiences at other locations," Journal of Econometrics, Elsevier, Elsevier, vol. 125(1-2), pages 241-270.
  16. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
  17. Alberto Abadie & Joshua D. Angrist & Guido W. Imbens, 1998. "Instrumental Variables Estimation of Quantile Treatment Effects," NBER Technical Working Papers 0229, National Bureau of Economic Research, Inc.
  18. de Jong, R.M. & Bierens, H.J., 1994. "On the Limit Behavior of a Chi-Square Type Test if the Number of Conditional Moments Tested Approaches Infinity," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 10(01), pages 70-90, March.
  19. Guido W. Imbens, 2003. "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," NBER Technical Working Papers 0294, National Bureau of Economic Research, Inc.
  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 0330, National Bureau of Economic Research, Inc.
  21. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 66(2), pages 315-332, March.
  22. V. Joseph Hotz & Guido W. Imbens & Julie H. Mortimer, 1999. "Predicting the Efficacy of Future Training Programs Using Past Experiences," NBER Technical Working Papers 0238, National Bureau of Economic Research, Inc.
  23. Sergio Firpo, 2004. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometric Society 2004 North American Summer Meetings 605, Econometric Society.
  24. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 73(1), pages 245-261, 01.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
  2. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
  3. 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.
  4. 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.
  5. 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.
  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. 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.
  8. Albrecht, Konstanze & von Essen, Emma & Parys, Juliane & Szech, Nora, 2013. "Updating, self-confidence, and discrimination," European Economic Review, Elsevier, Elsevier, vol. 60(C), pages 144-169.
  9. Sokbae 'Simon' Lee & Yoon-Jae Whang, 2009. "Nonparametric tests of conditional treatment effects," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP36/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  10. 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.
  11. 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.
  12. 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.
  13. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:hrv:faseco:3039049. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ben Steinberg).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.