The Parameter Set in an Adaptive Control Monte Carlo Experiment: Some Considerations
Comparisons 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 quadraticlinear 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. 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 nearzero 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.
|Date of creation:||Jul 2007|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.deps.unisi.it/
More information through EDIRC
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.:
- Marco Tucci & David Kendrick & Hans Amman, 2013.
"Expected Optimal Feedback with Time-Varying Parameters,"
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.
- 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.
- 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.
- 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.).
- Kendrick, David, 1978. "Non-convexities from probing in adaptive control problems," Economics Letters, Elsevier, vol. 1(4), pages 347-351.
- MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.
- Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 437-447 National Bureau of Economic Research, Inc.
- Amman, Hans M & Kendrick, David A, 1995. "Nonconvexities in Stochastic Control Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 455-75, May.
- 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.
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:usi:wpaper:507. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Fabrizio Becatti)
If references are entirely missing, you can add them using this form.