Working Paper Number
WP #03007, August 2006
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 find that inferences are highly sensitive to the maintained assumptions - especially to how one models po- tential inconsistencies between subjective self-assessments of work limitation and more objective measures of functional limitation. We estimate tight bounds under our strongest assumptions but then find that identification deteriorates rapidly as the assumptions are relaxed.
This is a working paper of an article from Journal of Applied Econometrics 23, no. 3 (2008): 329-349. doi: 10.1002/jae.979.
Kreider, Brent and Pepper, John, "Inferring disability status from corrupt data" (2006). Economics Working Papers (2002–2016). 257.