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The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence

  • Keane, Michael P
  • Wolpin, Kenneth I

Over the past decade, a substantial literature on methods for the estimation of discrete choice dynamic programming (DDP) models of behavior has developed. However, the implementation of these methods can impose major computational burdens because solving for agents' decision rules often involves high dimensional integrations that must be performed at each point in the state space. In this paper we develop an approximate solution method that consists of: (1) using Monte Carlo integration to stimulate the required multiple integrals at a subset of the state points, and (2) interpolating the non-simulated values using a regression function. The overall performance of this approximation method appears to be excellent. Copyright 1994 by MIT Press.

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Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 76 (1994)
Issue (Month): 4 (November)
Pages: 648-72

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Handle: RePEc:tpr:restat:v:76:y:1994:i:4:p:648-72
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  1. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
  2. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
  3. Miller, Robert A, 1984. "Job Matching and Occupational Choice," Journal of Political Economy, University of Chicago Press, vol. 92(6), pages 1086-120, December.
  4. Robin L. Lumsdaine & James H. Stock & David A. Wise, 1990. "Three Models of Retirement: Computational Complexity Versus Predictive Validity," NBER Working Papers 3558, National Bureau of Economic Research, Inc.
  5. Hotz, J.V. & Miller, R.A. & Sanders, S. & Smith, J., 1992. "A Simulation Estimator for Dynamic Models of Discrete Choice," GSIA Working Papers 1992-13, Carnegie Mellon University, Tepper School of Business.
  6. Heckman, James J & Sedlacek, Guilherme, 1985. "Heterogeneity, Aggregation, and Market Wage Functions: An Empirical Model of Self-selection in the Labor Market," Journal of Political Economy, University of Chicago Press, vol. 93(6), pages 1077-1125, December.
  7. Wolpin, Kenneth I, 1984. "An Estimable Dynamic Stochastic Model of Fertility and Child Mortality," Journal of Political Economy, University of Chicago Press, vol. 92(5), pages 852-74, October.
  8. V. Joseph Hotz & Robert A. Miller, . "An Empirical Analysis of Life Cycle Fertility and Female Labor Supply," University of Chicago - Population Research Center 86-15, Chicago - Population Research Center.
  9. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
  10. Pakes, Ariel S, 1986. "Patents as Options: Some Estimates of the Value of Holding European Patent Stocks," Econometrica, Econometric Society, vol. 54(4), pages 755-84, July.
  11. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
  12. James H. Stock & David A. Wise, 1988. "Pensions, The Option Value of Work, and Retirement," NBER Working Papers 2686, National Bureau of Economic Research, Inc.
  13. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
  14. Berkovec, James & Stern, Steven, 1991. "Job Exit Behavior of Older Men," Econometrica, Econometric Society, vol. 59(1), pages 189-210, January.
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