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Applications, Denials, and Appeals for Social Security Disability Insurance

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Listed:
  • Olivia S. Mitchell

    (University of Pennsylvania and NBER)

  • John W.R. Phillips

    (Social Security Administration)

Abstract

This project explores the process by which older workers apply for, and are awarded, Social Security Disability Insurance (DI) benefits. Our focus is on how and whether DI serves as a path out of the labor market at older ages. This research is important to the extent that proposals to raise the early retirement age under Social Security alter the opportunity set available to older workers. Identifying the characteristics of older workers who apply for DI under current rules, those who are rejected after application, and those who then go on to appeal, can provide policymakers with insight regarding the potential well-being of the “at risk” population if the early retirement age were to rise. We use data from the Health and Retirement Study to compare older workers prior to application, and use these characteristics to predict future DI application and award patterns. The findings indicate that older people initially in poor health and with low economic status are more likely to apply for DI thereafter, as compared to those reporting no health problems and with more assets. Nevertheless few factors distinguish statistically between applicants awarded versus denied benefits, and between those who appeal rejected applications versus those who do not.

Suggested Citation

  • Olivia S. Mitchell & John W.R. Phillips, 2002. "Applications, Denials, and Appeals for Social Security Disability Insurance," Working Papers wp032, University of Michigan, Michigan Retirement Research Center.
  • Handle: RePEc:mrr:papers:wp032
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    File URL: http://mrdrc.isr.umich.edu/publications/Papers/pdf/wp032.pdf
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    References listed on IDEAS

    as
    1. Parsons, Donald O, 1980. "The Decline in Male Labor Force Participation," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 117-134, February.
    2. F. Thomas Juster & Richard Suzman, 1995. "An Overview of the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 7-56.
    3. Phillip B. Levine & Olivia S. Mitchell & John W. Phillips, "undated". "A Benefit of One's Own: Older Women's Retirement Entitlements Under Social Security," Pension Research Council Working Papers 99-21, Wharton School Pension Research Council, University of Pennsylvania.
    4. Olivia S. Mitchell & John W.R. Phillips, 2001. "Eligibility for Social Security Disability Insurance," Working Papers wp011, University of Michigan, Michigan Retirement Research Center.
    5. Olivia S. Mitchell & John W. R. Phillips, 2000. "Retirement Responses to Early Social Security Benefit Reductions," Working Papers wp006, University of Michigan, Michigan Retirement Research Center.
    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. 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.
    8. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    9. Kreider, Brent, 1999. "Social Security Disability Insurance: Applications, Awards, and Lifetime Income Flows," Journal of Labor Economics, University of Chicago Press, vol. 17(4), pages 784-827, October.
    10. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
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    Cited by:

    1. Naoko Akashi-Ronquest & Paul Carrillo & Bruce Dembling & Steven Stern, 2011. "Measuring the biases in self-reported disability status: evidence from aggregate data," Applied Economics Letters, Taylor & Francis Journals, vol. 18(11), pages 1053-1060.

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