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Improved Targeting of Social Programs: An Application to a State Job Coaching Program for Adults with Intellectual Disabilities

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Listed:
  • Melayne Morgan McInnes

    (Department of Economics, Darla Moore School of Business, University of South Carolina, 1014 Greene Street, Columbia, SC 29208, USA)

  • Orgul Demet Ozturk

    (Department of Economics, Darla Moore School of Business, University of South Carolina, 1014 Greene Street, Columbia, SC 29208, USA)

  • Suzanne McDermott

    (Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Discovery 1 Columbia, SC 29208, USA)

  • Joshua Mann

    (Department of Family and Preventive Medicine, School of Medicine, University of South Carolina, 3209 Colonial Drive, Columbia, SC 29203, USA)

Abstract

In a climate of flat or shrinking budgets, can programs reallocate existing resources to improve efficiency? We illustrate the potential for gains from redirecting resources using data from a state job coaching program that is designed to increase employment among adults with intellectual disabilities (IDs). We model selection into the program and employment outcomes for participants and non-participants allowing for potentially heterogeneous response among observationally equivalent individuals. In our simulations, we find that state ID population employment can be increased from 10.7 percent to an upper bound of 16.7 percent by a program administrator who can allocate the job coaches to those with the most to gain. This is a 56 percent increase in the overall employment rate. While we assume that program administrators know more about individual program participants than we do, we can consider an administrator who has only the information available to the econometrician. In this case, targeting gains based only on observable characteristics would lead to 11.8 percent employment, which is an 11 percent increase in the overall employment rate. Surprisingly, a simple rule that only requires administrators to predict employment success when treated (based on observables) will achieve almost the same results.

Suggested Citation

  • Melayne Morgan McInnes & Orgul Demet Ozturk & Suzanne McDermott & Joshua Mann, 2016. "Improved Targeting of Social Programs: An Application to a State Job Coaching Program for Adults with Intellectual Disabilities," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 42(2), pages 252-269, March.
    • Handle: RePEc:pal:easeco:v:42:y:2016:i:2:p:252-269
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    References listed on IDEAS

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    1. James J. Heckman & Carolyn Heinrich & Jeffrey Smith, 2002. "The Performance of Performance Standards," Journal of Human Resources, University of Wisconsin Press, vol. 37(4), pages 778-811.
    2. James J. Heckman & Carolyn J. Heinrich & Pascal Courty & Gerald Marschke & Jeffrey Smith (ed.), 2011. "The Performance of Performance Standards," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number tpps, November.
    3. 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.
    4. Melayne Morgan McInnes & Orgul Demet Ozturk & Suzanne McDermott & Joshua R. Mann, 2010. "Does supported employment work?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 506-525.
    5. 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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    More about this item

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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