How Large are the Classification Errors in the Social Security Disability Award Process?
AbstractThis 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.
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Bibliographic InfoPaper provided by Stony Brook University, Department of Economics in its series Department of Economics Working Papers with number 05-02.
Length: 53 pages.
Date of creation: 2005
Date of revision:
Social Security Disability Insurance; Supplemental Security Income; Health and Retirement Study; Classification Errors.;
Other versions of this item:
- 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.
- H5 - Public Economics - - National Government Expenditures and Related Policies
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9712001, EconWPA, revised 16 Feb 1998.
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