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How Large is the Bias is Self-Reported Disability?

  • Hugo Benitez-Silva
  • Moshe Buchinsky
  • Hiu Man Chan
  • Sofia Cheidvasser
  • John Rust

A pervasive concern with the use of self-reported health and disability measures in behavioral models is that they are biased and endogenous. A commonly suggested explanation is that survey respondents exaggerate the severity of health problems and incidence of disabilities in order to rationalize labor force non-participation, application for disability benefits and/or receipt of those benefits. This paper re-examines this issue using a self-reported indicator of disability status from the Health and Retirement Survey. Using a bivariate probit model we test and are unable to reject the hypothesis that the self-reported disability measure is an exogenous explanatory variable in a model of individual's decision to apply for DI benefits or Social Security Administration's decision to award benefits. We further study a subsample of individuals who applied for Disability Insurance and Supplemental Security Income benefits from the Social Security Administration (SSA) for whom we can also observe SSA's award/deny decision. For this subsample we test and are unable to reject the hypothesis that self-reported disability is health and socio-economic characteristics similar to the information used by the SSA in making its award decisions. The unbiasedness restriction implies that these two variables have the same conditional probability distributions. Thus, our results indicate that disability applicant do not exaggerate their disability status at least in anonymous surveys such as the HRS. Indeed, our results are consistent with the hypothesis that disability applicants are aware of the criteria and decision rules that SSA uses in making awards and act as if they were applying these same criteria and rules when reporting their own disability status.

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File URL: http://www.nber.org/papers/w7526.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 7526.

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Date of creation: Feb 2000
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Publication status: published as Benitez-Silva, Hugo, Moshe Buchinsky, Hiu Man Chan, Sofia Cheidvasser, and John P. Rust. "How Large is the Bias is Self-Reported Disability?" Journal of Applied Econometrics 19 (2004): 649-670.
Handle: RePEc:nbr:nberwo:7526
Note: AG LS
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  1. Bierens, H.J., 1989. "A consistent conditional moment test of functional form," Serie Research Memoranda 0064, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  2. John Rust & Christopher Phelan, 1994. "How Social Security and Medicare Affect Retirement Behavior in a World of Incomplete Markets," Public Economics 9406005, EconWPA, revised 06 Jul 1994.
  3. Debra S. Dwyer & Olivia S. Mitchell, . "Health Problems as Determinants of Retirement: Are Self-Rated Measures Endogenous?," Pension Research Council Working Papers 98-7, Wharton School Pension Research Council, University of Pennsylvania.
  4. Hugo Benitez-Silva & Moshe Buchinsky & Hiu Man Chan & Sofia Cheidvasser & John Rust, 2000. "How Large is the Bias is Self-Reported Disability?," NBER Working Papers 7526, National Bureau of Economic Research, Inc.
  5. 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.
  6. Donald W. K. Andrews & Moshe Buchinsky, 2000. "A Three-Step Method for Choosing the Number of Bootstrap Repetitions," Econometrica, Econometric Society, vol. 68(1), pages 23-52, January.
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