Affiliations: [a] Department of Economics, State University at Stony
Brook, SUNY Stony Brook, Rm. S625, Social Behavioral Science Bldg., Stony Brook,
NY 11794-4384, USA | [b] Credit Policy, Fannie Mae, 3900 Wisconsin Ave., NW,
Washington, DC 20016, USA | [c] Housing and Household Economics Statistics Division,
Bureau of the Census, FOB 3, Room 1473, Washington, DC 20233, USA | [d] Office of Disability and Income Security Policy,
Social Security Administration, 7th floor, 400 Virginia Ave., Washington, DC
20024, USA
Abstract: We develop methodology to identify medical eligibility for Social Security's
Disability programs using publicly available data. Using a structural model of
Social Security's disability determination process estimated on a sample of
applicants, we make out-of-sample predictions of medical eligibility for
non-beneficiaries in the general population aged 18–64. This methodology defines
an observable, publicly-available indicator of disability consistent with Social
Security's definition. This would be useful in a wide number of applications and
may be of particular interest to empirical labor economists. We find that 2.9%
of this population were medically eligible but not receiving disability benefits
early in 1992. Our methodology permits use of publicly available survey data to
analyze medical criteria that determine who receives disability benefits. We
consider effects of sample selection adjustments, sample restrictions, and
several methods of estimating eligibility from continuous probabilities. Our
preferred measure outperforms the conventional single variable model based on
the "prevented" measure.
