Three Models of Retirement: Computational Complexity Versus Predictive Validity

62 Pages Posted: 28 Jan 2002 Last revised: 23 Sep 2010

See all articles by Robin L. Lumsdaine

Robin L. Lumsdaine

American University - Department of Finance and Real Estate; Erasmus University Rotterdam (EUR) - Department of Econometrics; National Bureau of Economic Research (NBER)

James H. Stock

Harvard University - Department of Economics; National Bureau of Economic Research (NBER); Harvard University - Harvard Kennedy School (HKS)

David A. Wise

National Bureau of Economic Research (NBER); Harvard University - Harvard Kennedy School (HKS)

Date Written: December 1990

Abstract

Empirical analysis often raises questions of approximation to underlying individual behavior. Closer approximation may require more complex statistical specifications, On the other hand, more complex specifications may presume computational facility that is beyond the grasp of most real people and therefore less consistent with the actual rules that govern their behavior, even though economic theory may push analysts to increasingly more complex specifications. Thus the issue is not only whether more complex models are worth the effort, but also whether they are better. We compare the in-sample and out-of-sample predictive performance of three models of retirement -- "option value," dynamic programming, and probit -- to determine which of the retirement rules most closely matches retirement behavior in a large firm. The primary measure of predictive validity is the correspondence between the model predictions and actual retirement under the firm's temporary early retirement window plan. The "option value" and dynamic programming models are considerably more successful than the less complex probit model in approximating the rules individuals use to make retirement decisions, but the more complex dynamic programming rule approximates behavior no better than the simpler option value rule.

Suggested Citation

Lumsdaine, Robin L. and Stock, James H. and Wise, David A., Three Models of Retirement: Computational Complexity Versus Predictive Validity (December 1990). NBER Working Paper No. w3558. Available at SSRN: https://ssrn.com/abstract=226824

Robin L. Lumsdaine (Contact Author)

American University - Department of Finance and Real Estate ( email )

Kogod School of Business
4400 Massachusetts Ave., N.W.
Washington, DC 20016-8044
United States

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

National Bureau of Economic Research (NBER) ( email )

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James H. Stock

Harvard University - Department of Economics ( email )

Littauer Center
Cambridge, MA 02138
United States
617-496-0502 (Phone)
617-496-5960 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States

David A. Wise

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Harvard University - Harvard Kennedy School (HKS)

79 John F. Kennedy Street
Cambridge, MA 02138
United States

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