A Dynamic Programming Model of Retirement Behavior / John Rust.

By:

Rust, John

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w2470.Publication details: Cambridge, Mass. National Bureau of Economic Research 1987.Description: 1 online resource: illustrations (black and white)Subject(s):

C - Mathematical and Quantitative Methods

Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: This paper formulates a model of retirement behavior based on the solution to a stochastic dynamic programming problem. The workers objective is to maximize expected discounted utility over his remaining lifetime. At each time period the worker chooses how much to consume and whether to work full-time, part-time, or exit the labor force. The model accounts for the sequential nature f the retirement decision problem, and the role of expectations of uncertain future variables such as the worker's future lifespan, health status, marital and family status, employment status, as well as earnings from employment, assets, and social security retirement, disability and medicare payments. This paper applies a "nested fixed point" algorithm that converts the dynamic programming problem into the problem of repeatedly recomputing the fixed point to a contraction mapping operator as a subroutine of a standard nonlinear maximum likelihood program. The goal of the paper is to demonstrate that a fairly complex and realistic formulation of the retirement problem can be estimated using this algorithm and a current generation supercomputer, the Cray-2.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w2470 (Browse shelf(Opens below))	Not For Loan

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December 1987.

This paper formulates a model of retirement behavior based on the solution to a stochastic dynamic programming problem. The workers objective is to maximize expected discounted utility over his remaining lifetime. At each time period the worker chooses how much to consume and whether to work full-time, part-time, or exit the labor force. The model accounts for the sequential nature f the retirement decision problem, and the role of expectations of uncertain future variables such as the worker's future lifespan, health status, marital and family status, employment status, as well as earnings from employment, assets, and social security retirement, disability and medicare payments. This paper applies a "nested fixed point" algorithm that converts the dynamic programming problem into the problem of repeatedly recomputing the fixed point to a contraction mapping operator as a subroutine of a standard nonlinear maximum likelihood program. The goal of the paper is to demonstrate that a fairly complex and realistic formulation of the retirement problem can be estimated using this algorithm and a current generation supercomputer, the Cray-2.