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Inferring Disability Status from Corrupt Data

Journal of Applied Econometrics (JAE), 23(3), April 2008, 329-49

Brent Kreider and John Pepper

Abstract. In light of widespread concerns about the reliability of self-reported disability, we investigate what can be learned
about the prevalence of work disability under various assumptions on the reporting error process. Developing a nonparametric
bounding framework, we provide tight inferences under our strongest assumptions but then find that identification deteriorates
rapidly as the assumptions are relaxed. For example, we find that inferences are highly sensitive to how one models potential
inconsistencies between subjective self-assessments of work limitation and more objective measures of functional limitation.
These two indicators appear to measure markedly different aspects of health status.