Disability and employment: reevaluating the evidence in light of reporting errors
- Collection:
- Health Policy and Services Research
- Series Title(s):
- Center for Retirement Research working paper
- Contributor(s):
- Kreider, Brent. Pepper, John V. Center for Retirement Research at Boston College.
- Publication:
- Chestnut Hill, MA : Center for Retirement Research at Boston College, c2002
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Disabled Persons Employment -- statistics & numerical data Health Status Indicators Self-Assessment Forecasting Health Surveys Models, Theoretical Retirement -- statistics & numerical data Work Capacity Evaluation Humans United States
- Genre(s):
- Technical Report
- Abstract:
- Long-standing debates about relationships between labor supply behavior and health status among persons nearing retirement age have centered largely on disagreements about the reliability of self-reported health indicators. In light of reporting errors in work capacity, this paper considers the problem of predicting how employment rates vary with disability status when "true" disability is unobserved. Rather than imposing the strong assumptions required to obtain point identification, we take a step back to evaluate what can be inferred under a variety of assumptions that are weaker but arguably more credible than those imposed in the existing literature. Although these assumptions do not identify the conditional employment rates except in special cases, nonparametric bounds for these parameters can be obtained. Using data from the Health and Retirement Study, we estimate a set of bounds that formalize the identifying power of a number of different assumptions that appear to have broad consensus in the literature. Our results suggest that models estimated under the assumption of fully accurate reporting lead to biased inferences. In particular, it appears that non-workers tend to over-report disabilities.
- Copyright:
- Reproduced with permission of the copyright holder. Further use of the material is subject to CC BY license. (More information)
- Extent:
- 37 p.
- Illustrations:
- Illustrations
- NLM Unique ID:
- 101468771 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/101468771