The Parameter Set in an Adaptive Control Monte Carlo Experiment: Some Considerations

Marco P. Tucci (), David Andrew Kendrick () and Hans Amman ()

Department of Economics University of Siena from Department of Economics, University of Siena

Abstract: 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.

Keywords: Adaptive control; Monte Carlo experiment; uncertain parameters; outliers. (search for similar items in EconPapers)
JEL-codes: C63 E61 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp
Date: 2007-07

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Persistent link: http://EconPapers.repec.org/RePEc:usi:wpaper:507

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