Inferring Disability Status from Corrupt Data
Brent Kreider () and
John Pepper
Staff General Research Papers Archive from Iowa State University, Department of Economics
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.
Date: 2003-03-24
New Economics Papers: this item is included in nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Published in Journal of Applied Econometrics, April 2008, vol. 23 no. 3, pp. 329-349
Downloads: (external link)
http://www2.econ.iastate.edu/papers/paper_10228_03007.pdf (application/pdf)
Related works:
Journal Article: Inferring disability status from corrupt data (2008) 
Working Paper: Inferring disability status from corrupt data (2008) 
Working Paper: Inferring Disability Status from Corrupt Data (2001) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:isu:genres:10228
Access Statistics for this paper
More papers in Staff General Research Papers Archive from Iowa State University, Department of Economics Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070. Contact information at EDIRC.
Bibliographic data for series maintained by Curtis Balmer ().