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Job Exit Behavior of Older Men
Abstract
A dynamic programming model of job exit behavior and retirement is constructed and estimated using the method of simulated moments. The model and estimation method allow for both unobserved individual effects and unobserved job-specific "match" effects. The model is estimated using two different assumptions about individual discount factors. First, a static model, with the discount factor equal to zero, is estimated. Then a dynamic model, with the discount factor equal to .95 is estimated. In both models, it is found that bad health, age, and lack of education increase the probability of retirement. The dynamic model performs better than the static model and has different implications for retirement behavior. The job-specific effects are an important source of unobserved heterogeneity. Copyright 1991 by The Econometric Society.
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Citations
Cited by
Discrete Choice Methods with Simulation
Train, K. E. (2001) · doi:10.1017/cbo9780511805271 · Cited by 7,784
Pensions, The Option Value of Work, and Retirement
Stock, J., & Wise, D. (1988) · National Bureau of Economic Research · doi:10.3386/w2686 · Cited by 555
Job Loss and Employment Patterns of Older Workers
Chan, S., & Huff Stevens, A. (2001) · Journal of Labor Economics · doi:10.1086/319568 · Cited by 441
New Developments in Econometric Methods for Labor Market Analysis
(1999) · Handbook of Labor Economics · doi:10.1016/s1573-4463(99)03005-9 · Cited by 152
Metadata
- Authors
- Berkovec, J., & Stern, S.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1991-01
- Volume
- 59
- Issue
- 1
- Pages
- 189
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2040988375
- Cited by
- 290
- References
- 0
- FWCI
- 29.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Berkovec, J., & Stern, S. (1991). Job Exit Behavior of Older Men. Econometrica. https://doi.org/10.2307/2938246
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
