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

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  • Hugo Benitez-Silva
  • Moshe Buchinsky
  • John Rust

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 study a subset of individuals from the Health and Retirement Study (HRS) who applied for DI or SSI benefits between 1992 and 1996. We compare the SSA's ultimate award decision (i.e. after allowing for appeals) to the applicant's self-reported disability status. We use these data 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. Our analysis also yields insights into the patterns of self-selection induced by varying delays and award probabilities at various levels of the application and appeal process. We construct an optimal statistical screening rule using a subset of objective health indicators that the SSA uses in making award decisions that results in significantly lower classification error rates than does SSA's current award process.

Suggested Citation

  • Hugo Benitez-Silva & Moshe Buchinsky & John Rust, 2004. "How Large are the Classification Errors in the Social Security Disability Award Process?," NBER Working Papers 10219, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:10219
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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, Oxford University Press, 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 BenĂ­tez-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.
    9. Haveman, Robert & Wolfe, Barbara, 2000. "The economics of disability and disability policy," Handbook of Health Economics,in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 18, pages 995-1051 Elsevier.
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    JEL classification:

    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

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