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The Sensitivity of Experimental Impact Estimates: Evidence from the National JTPA Study

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  • James J. Heckman
  • Jeffrey A. Smith

Abstract

The recent experimental evaluation of the U.S. Job Training Partnership Act (JTPA) program found negative effects of training on the earnings of disadvantaged male youth and no effect on the earnings of disadvantaged female youth. These findings provided justification for Congress to cut the budget of JTPA's youth component by over 80 percent. In this paper, we examine the sensitivity of the experimental impact estimates along several dimensions of construction and interpretation. We find that the statistical significance of the male youth estimates is extremely fragile and that the magnitudes of the estimates for both youth groups are sensitive to nearly all the factors we consider. In particular, accounting for experimental control group members who substitute training from other providers leads to a much more positive picture regarding the effectiveness of JTPA classroom training. Our study indicates the value of sensitivity analyses in experimental evaluations and illustrates that experimental impact estimates, like those from nonexperimental analyses, require careful interpretation if they are to provide a reliable guide to policymakers.

Suggested Citation

  • James J. Heckman & Jeffrey A. Smith, 1997. "The Sensitivity of Experimental Impact Estimates: Evidence from the National JTPA Study," NBER Working Papers 6105, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:6105
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    1. Howard S. Bloom, 1984. "Accounting for No-Shows in Experimental Evaluation Designs," Evaluation Review, , vol. 8(2), pages 225-246, April.
    2. Robert J. LaLonde, 1995. "The Promise of Public Sector-Sponsored Training Programs," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 149-168, Spring.
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    4. Katherine P. Dickinson & Terry R. Johnson & Richard W. West, 1987. "An Analysis of the Sensitivity of Quasi-Experimental Net Impact Estimates of Ceta Programs," Evaluation Review, , vol. 11(4), pages 452-472, August.
    5. James Heckman & Jeffrey Smith & Christopher Taber, 1994. "Accounting for Dropouts in Evaluations of Social Experiments," NBER Technical Working Papers 0166, National Bureau of Economic Research, Inc.
    6. Bassi, Laurie J, 1984. "Estimating the Effect of Training Programs with Non-Random Selection," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 36-43, February.
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    8. Theresa J. Devine & James J. Heckman, 1996. "The Economics of Eligibility Rules for a Social Program: A Study of the Job Training Partnership Act (JTPA)--A Summary Report," Canadian Journal of Economics, Canadian Economics Association, vol. 29(s1), pages 99-104, April.
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    Cited by:

    1. repec:mpr:mprres:6664 is not listed on IDEAS
    2. Markus Frölich & Michael Lechner, 2004. "Regional treatment intensity as an instrument for the evaluation of labour market policies," University of St. Gallen Department of Economics working paper series 2004 2004-08, Department of Economics, University of St. Gallen.
    3. Dolton, Peter & Smith, Jeffrey A., 2011. "The Impact of the UK New Deal for Lone Parents on Benefit Receipt," IZA Discussion Papers 5491, Institute of Labor Economics (IZA).
    4. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.
    5. Rajeev Dehejia, 2000. "Was There a Riverside Miracle? A Framework for Evaluating Multi-Site Programs," NBER Working Papers 7844, National Bureau of Economic Research, Inc.
    6. Burt S. Barnow & Jeffrey Smith, 2015. "Employment and Training Programs," NBER Chapters, in: Economics of Means-Tested Transfer Programs in the United States, Volume 2, pages 127-234, National Bureau of Economic Research, Inc.
    7. Mitali Das, 2000. "Instrumental Variables Estimation of Nonparametric Models with Discrete Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1008, Econometric Society.
    8. Samina Sattar, "undated". "Evidence Scan of Work Experience Programs," Mathematica Policy Research Reports 685b2a650bdf4437b1de31c2e, Mathematica Policy Research.
    9. Agata Maida & Daniela Sonedda, 2019. "Getting out of the starting gate on the right foot: employment effects of investment in human capital," LABORatorio R. Revelli Working Papers Series 164, LABORatorio R. Revelli, Centre for Employment Studies.
    10. Carlos A. Flores & Oscar A. Mitnik, 2013. "Comparing Treatments across Labor Markets: An Assessment of Nonexperimental Multiple-Treatment Strategies," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1691-1707, December.
    11. Carolyn Heinrich & Jeffrey Wenger, 2002. "The Economic Contributions of James J. Heckman and Daniel L. McFadden," Review of Political Economy, Taylor & Francis Journals, vol. 14(1), pages 69-89.
    12. Smith, Jeffrey A. & Whalley, Alexander & Wilcox, Nathaniel T., 2020. "Are Program Participants Good Evaluators?," IZA Discussion Papers 13584, Institute of Labor Economics (IZA).
    13. Hunt Allcott, 2012. "Site Selection Bias in Program Evaluation," NBER Working Papers 18373, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate

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