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.
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Find related papers by JEL classification: C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - 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
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