The Sensitivity of Experimental Impact Estimates (Evidence from the National JTPA Study)
In: Youth Employment and Joblessness in Advanced Countries
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.
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- Heckman, J. & Smith, J. & Taber, C., 1994.
"Accounting for Dropouts in Evaluations of Social Experiments,"
University of Chicago - Economics Research Center
94-3, Chicago - Economics Research Center.
- 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.
- repec:mpr:mprres:2737 is not listed on IDEAS
- 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.
- 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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