How large is the bias in self-reported disability?

Hugo Benítez-Silva, Moshe Buchinsky, Hiu Man Chan, Sofia Cheidvasser and John Rust
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Hugo Benítez-Silva: Stony Brook University, State University of New York, USA, Postal: Stony Brook University, State University of New York, USA
Moshe Buchinsky: University of California, Los Angeles, USA, National Bureau of Economic Research, USA and CREST-INSEE, France, Postal: University of California, Los Angeles, USA, National Bureau of Economic Research, USA and CREST-INSEE, France
Hiu Man Chan: Charles River Associates, Boston, USA, Postal: Charles River Associates, Boston, USA
Sofia Cheidvasser: Goldman Sachs, New York, USA, Postal: Goldman Sachs, New York, USA
John Rust: University of Maryland, USA, and National Bureau of Economic Research, USA, Postal: University of Maryland, USA, and National Bureau of Economic Research, USA

Journal of Applied Econometrics, 2004, vol. 19, issue 6, pages 649-670

Abstract: A pervasive concern with the use of self-reported health measures in behavioural models is that individuals tend to exaggerate the severity of health problems in order to rationalize their decisions regarding labour force participation, application for disability benefits, etc. We re-examine this issue using a self-reported indicator of disability status from the Health and Retirement Study. We study a subsample of individuals who applied for disability benefits from the Social Security Administration (SSA), for whom we can also observe the SSA's decision. Using a battery of tests, we are unable to reject the hypothesis that self-reported disability is an unbiased indicator of the SSA's decision. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
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