Bayesian Estimation of Dynamic Discrete Choice Models
AbstractWe propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters simultaneously. As a result, the computational burden of estimating a dynamic model becomes comparable to that of a static model. Another feature of our algorithm is that even though per solution-estimation iteration, the number of grid points on the state variable is small, the number of effective grid points increases with the number of estimation iterations. This is how we help ease the "Curse of Dimensionality". We simulate and estimate several versions of a simple model of entry and exit to illustrate our methodology. We also prove that under standard conditions, the parameters converge in probability to the true posterior distribution, regardless of the starting values.
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Bibliographic InfoPaper provided by Society for Economic Dynamics in its series 2005 Meeting Papers with number 432.
Date of creation: 2005
Date of revision:
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Postal: Society for Economic Dynamics Christian Zimmermann Economic Research Federal Reserve Bank of St. Louis PO Box 442 St. Louis MO 63166-0442 USA
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Structural estimation; Dynamic programming; MCMC;
Other versions of this item:
- Susumu Imai & Neelam Jain & Andrew Ching, 2009. "Bayesian Estimation of Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 77(6), pages 1865-1899, November.
- Susumu Imai & Neelam Jain & Andrew Ching, 2006. "Bayesian Estimation of Dynamic Discrete Choice Models," Working Papers 1118, Queen's University, Department of Economics.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- L00 - Industrial Organization - - General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-12-01 (All new papers)
- NEP-DCM-2005-12-01 (Discrete Choice Models)
- NEP-DGE-2005-12-01 (Dynamic General Equilibrium)
- NEP-ECM-2005-12-01 (Econometrics)
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- Siddhartha Chib & Edward Greenberg, 1994.
"Markov Chain Monte Carlo Simulation Methods in Econometrics,"
9408001, EconWPA, revised 24 Oct 1994.
- Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
- Victor Aguirregabiria & Pedro Mira, 2002.
"Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models,"
Econometric Society, vol. 70(4), pages 1519-1543, July.
- Victor Aguirregabiria & Pedro Mira, 1999. "Swapping the Nested Fixed-Point Algorithm: a Class of Estimators for Discrete Markov Decision Models," Computing in Economics and Finance 1999 332, Society for Computational Economics.
- V. Joseph Hotz & Robert A. Miller & Seth Sanders & Jeffrey Smith, 1992.
"A Simulation Estimator for Dynamic Models of Discrete Choice,"
9205, Harris School of Public Policy Studies, University of Chicago.
- Hotz, V Joseph & Robert A. Miller & Seth Sanders & Jeffrey Smith, 1994. "A Simulation Estimator for Dynamic Models of Discrete Choice," Review of Economic Studies, Wiley Blackwell, vol. 61(2), pages 265-89, April.
- 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.
- Härdle,Wolfgang, 1992. "Applied Nonparametric Regression," Cambridge Books, Cambridge University Press, number 9780521429504, October.
- Lancaster, Tony, 1997. "Exact Structural Inference in Optimal Job-Search Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(2), pages 165-79, April.
- Susumu Imai & Michael P. Keane, 2004. "Intertemporal Labor Supply and Human Capital Accumulation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 601-641, 05.
- Susumu Imai & Kala Krishna, 2001.
"Employment, Dynamic Deterrence and Crime,"
NBER Working Papers
8281, National Bureau of Economic Research, Inc.
- McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
- repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
- Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
- Andriy Norets, 2009. "Inference in Dynamic Discrete Choice Models With Serially orrelated Unobserved State Variables," Econometrica, Econometric Society, vol. 77(5), pages 1665-1682, 09.
- Houser, Daniel, 2003. "Bayesian analysis of a dynamic stochastic model of labor supply and saving," Journal of Econometrics, Elsevier, vol. 113(2), pages 289-335, April.
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