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The Effects of Vocational Rehabilitation for People with Mental Illlness

Author

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  • Steven Stern
  • John Pepper
  • David Dean
  • Robert Schmidt

Abstract

: The public-sector Vocational Rehabilitation (VR) program is a $3 billion federal-state partnership designed to provide employment-related assistance to persons with disabilities. There is, however, relatively little-known about the long-term efficacy of VR programs. This paper utilizes unique and detailed administrative and employment data to examine both short and longer-term employment impacts for all persons diagnosed with mental illness who applied for VR services in the state of Virginia in State Fiscal Year 2000. These data provide quarterly information on VR services and employment outcomes from 1995 to 2010. Estimates from our model of service provision and labor market outcomes reveal that VR services generally have positive long-run labor market outcome effects that appear to substantially exceed the cost of providing services.

Suggested Citation

  • Steven Stern & John Pepper & David Dean & Robert Schmidt, 2011. "The Effects of Vocational Rehabilitation for People with Mental Illlness," Virginia Economics Online Papers 382, University of Virginia, Department of Economics.
  • Handle: RePEc:vir:virpap:382
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    References listed on IDEAS

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    1. Kimmel, Jean & Kniesner, Thomas J., 1998. "New evidence on labor supply:: Employment versus hours elasticities by sex and marital status," Journal of Monetary Economics, Elsevier, vol. 42(2), pages 289-301, July.
    2. Raphael, Steven & Rice, Lorien, 2002. "Car ownership, employment, and earnings," Journal of Urban Economics, Elsevier, vol. 52(1), pages 109-130, July.
    3. Robert Shimer, 2012. "Reassessing the Ins and Outs of Unemployment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(2), pages 127-148, April.
    4. van den Berg, Gerard J & van Ours, Jan C, 1996. "Unemployment Dynamics and Duration Dependence," Journal of Labor Economics, University of Chicago Press, vol. 14(1), pages 100-125, January.
    5. 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.
    6. Geweke, John, 1988. "Antithetic acceleration of Monte Carlo integration in Bayesian inference," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 73-89.
    7. Moffitt, Robert, 1985. "Unemployment insurance and the distribution of unemployment spells," Journal of Econometrics, Elsevier, vol. 28(1), pages 85-101, April.
    8. Olympia Bover & Manuel Arellano & Samuel Bentolila, 2002. "Unemployment Duration, Benefit Duration and the Business Cycle," Economic Journal, Royal Economic Society, vol. 112(479), pages 223-265, April.
    9. Daniel Friedlander & David H. Greenberg & Philip K. Robins, 1997. "Evaluating Government Training Programs for the Economically Disadvantaged," Journal of Economic Literature, American Economic Association, vol. 35(4), pages 1809-1855, December.
    10. Espen Bratberg & Astrid Grasdal & Alf Erling Risa, 2002. "Evaluating Social Policy by Experimental and Nonexperimental Methods," Scandinavian Journal of Economics, Wiley Blackwell, vol. 104(1), pages 147-171, March.
    11. Donald M. Bellante, 1972. "A Multivariate Analysis of a Vocational Rehabilitation Program," Journal of Human Resources, University of Wisconsin Press, vol. 7(2), pages 226-241.
    12. Markus Frölich & Almas Heshmati & Michael Lechner, 2004. "A microeconometric evaluation of rehabilitation of long-term sickness in Sweden," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 375-396.
    13. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    14. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    15. Stern, Steven, 1992. "A Method for Smoothing Simulated Moments of Discrete Probabilities in Multinomial Probit Models," Econometrica, Econometric Society, vol. 60(4), pages 943-952, July.
    16. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
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    Cited by:

    1. Todd Honeycutt & Allison Thompkins & Maura Bardos & Steven Stern, "undated". "State Differences in the Vocational Rehabilitation Experiences of Transition-Age Youth with Disabilities," Mathematica Policy Research Reports 2b57dad5f3aa466db95f12cc8, Mathematica Policy Research.

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    More about this item

    Keywords

    etraining; mental illness; treatment effects;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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