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Treatment Effects for Discrete Outcomes when Responses to Treatment Vary Among Observationally Identical Persons: An Application to Norwegian ..

  • Arild Aakvik
  • James J. Heckman
  • Edward J. Vytlacil

This paper formulates an econometric framework for studying the impact of interventions on discrete outcomes when responses to treatment vary among observationally identical persons. Using a latent variable model that can be linked to well-posed economic models, we show how to define and interpret the average treatment effects, the average effect of treatment on the treated, the marginal treatment effect and the distribution of treatment effects for discrete outcomes. To estimate these parameters and the distribution of treatment effects, we formulate and estimate a discrete choice model with unobservables generated by a factor structure model. We apply our methods to evaluate the effect of Norwegian Vocational Rehabilitation training programs on employment outcomes for women. We find that applicants to these programs who participate in active training have a 4.6% higher employment rate than nonparticipants. When we control for the observable characteristics of applicants, we find that the average treatment effects falls to 4.1%. When we control for the unobservables characteristics of applicants, the average treatment effect falls to -1.4% and effect of treatment on the treated is -11%. We also find evidence of substantial heterogeneity in response to training.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0262.

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Date of creation: Sep 2000
Date of revision:
Publication status: published as Aakvik, Arild, James J. Heckman and Edward J. Vytlacil. "Estimating Treatment Effects For Discrete Outcomes When Responses To Treatment Vary: An Application To Norwegian Vocational Rehabilitation Programs," Journal of Econometrics, 2005, v125(1-2,Mar-Apr), 15-51.
Handle: RePEc:nbr:nberte:0262
Note: TWP
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
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  1. Gary Burtless, 1995. "The Case for Randomized Field Trials in Economic and Policy Research," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 63-84, Spring.
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  4. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
  5. Poirier, Dale J., 1980. "Partial observability in bivariate probit models," Journal of Econometrics, Elsevier, vol. 12(2), pages 209-217, February.
  6. Joshua D. Angrist, 2000. "Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice," NBER Technical Working Papers 0248, National Bureau of Economic Research, Inc.
  7. Heckman, James J. & Vytlacil, Edward J., 2000. "The relationship between treatment parameters within a latent variable framework," Economics Letters, Elsevier, vol. 66(1), pages 33-39, January.
  8. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-49, September.
  9. Ridder, G, 1986. "An Event History Approach to the Evaluation of Training, Recruitment and Employment Programmes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 109-26, April.
  10. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
  11. Stephen H. Bell & Larry l. Orr & John D. Blomquist & Glen G. Cain, 1995. "Program Applicants as a Comparison Group in Evaluating Training Programs: Theory and a Test," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number pacg.
  12. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  13. James J. Heckman & Lance Lochner & Christopher Taber, 1998. "Explaining Rising Wage Inequality: Explorations with a Dynamic General Equilibrium Model of Labor Earnings with Heterogeneous Agents," NBER Working Papers 6384, National Bureau of Economic Research, Inc.
  14. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
  15. Card, David & Sullivan, Daniel G, 1988. "Measuring the Effect of Subsidized Training Programs on Movements in and out of Employment," Econometrica, Econometric Society, vol. 56(3), pages 497-530, May.
  16. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May.
  17. 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.
  18. Joshua D. Angrist & Kathryn Graddy & Guido W. Imbens, 1995. "Non-Parametric Demand Analysis with an Application to the Demand for Fish," NBER Technical Working Papers 0178, National Bureau of Economic Research, Inc.
  19. Xiaohong Chen & James J. Heckman & Edward Vytlacil, 2000. "Identification and SQRT N Efficient Estimation of Semiparametric Panel Data Models with Binary Dependent Variables and a Latent Factor," Econometric Society World Congress 2000 Contributed Papers 1567, Econometric Society.
  20. Gritz, R. Mark, 1993. "The impact of training on the frequency and duration of employment," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 21-51.
  21. James J. Heckman & Lance Lochner & Christopher Taber, 1998. "General Equilibrium Treatment Effects: A Study of Tuition Policy," NBER Working Papers 6426, National Bureau of Economic Research, Inc.
  22. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
  23. Burt S. Barnow, 1987. "The Impact of CETA Programs on Earnings: A Review of the Literature," Journal of Human Resources, University of Wisconsin Press, vol. 22(2), pages 157-193.
  24. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
  25. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
  26. Ham, John C & LaLonde, Robert J, 1996. "The Effect of Sample Selection and Initial Conditions in Duration Models: Evidence from Experimental Data on Training," Econometrica, Econometric Society, vol. 64(1), pages 175-205, January.
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