The parameter set in an adaptive control Monte Carlo experiment: Some considerations
AbstractComparisons of various methods for solving stochastic control economic models can be done with Monte Carlo methods. These methods have been applied to simple one-state, one-control quadratic-linear tracking models; however, large outliers may occur in a substantial number of the Monte Carlo runs when certain parameter sets are used in these models. Building on the work of Mizrach (1991) and (Amman and Kendrick, 1994) and (Amman and Kendrick, 1995), this paper tracks the source of these outliers to two sources: (1) the use of a zero for the penalty weights on the control variables and (2) the generation of near-zero initial estimate of the control parameter in the systems equations by the Monte Carlo routine. This result leads to an understanding of why both the unsophisticated optimal feedback (certainty equivalence) and the sophisticated dual methods do poorly in some Monte Carlo comparisons relative to the moderately sophisticated expected optimal feedback method.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 34 (2010)
Issue (Month): 9 (September)
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Web page: http://www.elsevier.com/locate/jedc
Active learning Dual control Optimal experimentation Stochastic optimization Time-varying parameters Numerical experiments;
Other versions of this item:
- Marco P. Tucci & David A. Kendrick & Hans M. Amman, 2007. "The Parameter Set in an Adaptive Control Monte Carlo Experiment: Some Considerations," Department of Economics University of Siena 507, Department of Economics, University of Siena.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 435-445 National Bureau of Economic Research, Inc.
- Marco P. Tucci & David A. Kendrick & Hans M. Amman, 2007.
"Expected optimal feedback with Time-Varying Parameters,"
Department of Economics University of Siena
497, Department of Economics, University of Siena.
- Marco Tucci & David Kendrick & Hans Amman, 2013. "Expected Optimal Feedback with Time-Varying Parameters," Computational Economics, Society for Computational Economics, vol. 42(3), pages 351-371, October.
- M.P. Tucci & D.A. Kendrick & H.M. Amman, 2011. "Expected optimal feedback with Time-Varying Parameters," Working Papers 11-18, Utrecht School of Economics.
- Beck, Gunter W. & Wieland, Volker, 2002. "Learning and control in a changing economic environment," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1359-1377, August.
- Kendrick, David, 1978. "Non-convexities from probing in adaptive control problems," Economics Letters, Elsevier, vol. 1(4), pages 347-351.
- Hans M. Amman & David A. Kendrick, 2003.
"A Classification System for Economic Stochastic Control Models,"
Computing in Economics and Finance 2003
114, Society for Computational Economics.
- David Kendrick & Hans Amman, 2006. "A Classification System for Economic Stochastic Control Models," Computational Economics, Society for Computational Economics, vol. 27(4), pages 453-481, June.
- Tucci, Marco P, 1998. "The Nonconvexities Problem in Adaptive Control Models: A Simple Computational Solution," Computational Economics, Society for Computational Economics, vol. 12(3), pages 203-22, December.
- Mizrach, Bruce, 1991. "Nonconvexities in a stochastic control problem with learning," Journal of Economic Dynamics and Control, Elsevier, vol. 15(3), pages 515-538, July.
- Tucci, Marco P., 1997. "Adaptive control in the presence of time-varying parameters," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 39-47, November.
- MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.
- A.L. Norman & M.R. Norman & C.J. Palash, 1979. "Multiple relative maxima in optimal macroeconomic policy: an illustration," Special Studies Papers 134, Board of Governors of the Federal Reserve System (U.S.).
- Cosimano, Thomas F., 2008. "Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1857-1894, June.
- D.A. Kendrick & H.M. Amman & M.P. Tucci, 2008. "Learning About Learning in Dynamic Economic Models," Working Papers 08-20, Utrecht School of Economics.
- H.M. Amman & D.A. Kendrick, 2012. "Conjectures on the policy function in the presence of optimal experimentation," Working Papers 12-09, Utrecht School of Economics.
- D. Blueschke & V. Blueschke-Nikolaeva & R. Neck, 2013. "Stochastic Control of Linear and Nonlinear Econometric Models: Some Computational Aspects," Computational Economics, Society for Computational Economics, vol. 42(1), pages 107-118, June.
- D.A. Kendrick & H.M. Amman, 2008. "Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks," Working Papers 08-19, Utrecht School of Economics.
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