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How Large are the Classification Errors in the Social Security Disability Award Process?

Author

Listed:
  • Hugo Benitez-Silva

    (Dept. of Economics, SUNY at Stony Brook)

  • Moshe Buchinsky

    (UCLA and NBER)

  • John Rust

    (University of Maryland)

Abstract

This paper presents an .audit. of the multistage application and appeal process that the U.S. Social Security Administration (SSA) uses to determine eligibility for disability benefits from the Disability Insurance (DI) and Supplemental Security Income (SSI) programs. We use a subset of individuals from the Health and Retirement Study who applied for DI or SSI benefits between 1992 and 1996, to estimate classification error rates under the hypothesis that applicants' self-reported disability status and the SSA's ultimate award decision are noisy but unbiased indicators of a latent .true disability status. indicator. We find that approximately 20% of SSI/DI applicants who are ultimately awarded benefits are not disabled, and that 60% of applicants who were denied benefits are disabled. We also construct an optimal statistical screening rule that results in significantly lower classification error rates than does SSA's current award process.

Suggested Citation

  • Hugo Benitez-Silva & Moshe Buchinsky & John Rust, 2005. "How Large are the Classification Errors in the Social Security Disability Award Process?," Department of Economics Working Papers 05-02, Stony Brook University, Department of Economics.
    • Handle: RePEc:nys:sunysb:05-02
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    File URL: http://ms.cc.sunysb.edu/~hbenitezsilv/dice.pdf
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    References listed on IDEAS

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    1. Bound, John & Burkhauser, Richard V., 1999. "Economic analysis of transfer programs targeted on people with disabilities," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 51, pages 3417-3528, Elsevier.
    2. John Bound & Timothy Waidmann, 1992. "Disability Transfers, Self-Reported Health, and the Labor Force Attachment of Older Men: Evidence from the Historical Record," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(4), pages 1393-1419.
    3. Benitez-Silva, Hugo & Buchinsky, Moshe & Chan, Hiu Man & Rust, John & Sheidvasser, Sofia, 1999. "An empirical analysis of the social security disability application, appeal, and award process," Labour Economics, Elsevier, vol. 6(2), pages 147-178, June.
    4. John Rust & Christopher Phelan, 1997. "How Social Security and Medicare Affect Retirement Behavior in a World of Incomplete Markets," Econometrica, Econometric Society, vol. 65(4), pages 781-832, July.
    5. Diamond, P. A. & Mirrlees, J. A., 1978. "A model of social insurance with variable retirement," Journal of Public Economics, Elsevier, vol. 10(3), pages 295-336, December.
    6. Jianting Hu & Kajal Lahiri & Denton R. Vaughan & Bernard Wixon, 2001. "A Structural Model Of Social Security'S Disability Determination Process," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 348-361, May.
    7. Hugo Benítez-Silva & Moshe Buchinsky & Hiu Man Chan & Sofia Cheidvasser & John Rust, 2004. "How large is the bias in self-reported disability?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(6), pages 649-670.
    8. Parsons, Donald O., 1996. "Imperfect 'tagging' in social insurance programs," Journal of Public Economics, Elsevier, vol. 62(1-2), pages 183-207, October.
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    More about this item

    Keywords

    Social Security Disability Insurance; Supplemental Security Income; Health and Retirement Study; Classification Errors.;
    All these keywords.

    JEL classification:

    • H5 - Public Economics - - National Government Expenditures and Related Policies

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