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Optimal Experimentation a Comparison of the Perturbation and Dynamic Programming Algorithms

Author

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  • Michael T. Gapen
  • Thomas F. Cosimano

Abstract

Cosimano (2003) uses the perturbation method to approximate optimal experimentation problems in the neighborhood of the augmented linear regulator problem as formulated by Hansen and Sargent (2004) and Anderson, Hansen, McGratten and Sargent (1966). Cosimano and Gapen (2005) develop a computer algorithm which implements the perturbation method for any economic problem within the class specified by Hansen and Sargent. As a result, optimal experimentation problems may be analyzed for any linear quadratic model of the economy. Wieland (2000) has developed a dynamic programming algorithm for solving optimal experimentation problems with four parameters. He has used this algorithm to analyze monetary policy when the central bank is uncertain about the fundamental equations for the economy in Wieland (2002). Wieland's models fit into the Hansan and Sargent class of economies. As a result, this paper examines the cost and benefits of the Perturbation and Dynamic Programming Algorithms for solving optimal experimentation problems in the context of Wieland's (2002) model of the economy. Anderson, E. W., L. P. Hansen, E. R. McGrattan, and T. J. Sargent, 1996. Mechanics of Forming and Estimating Dynamic Linear Economies. In Handbook of computational economics, vol 1, edited by H.M. Amman. D.A. Kendrick and J. Rust, Elsevier, Netherlands. Cosimano, T. F. 2003. Optimal Experimentation and the Perturbation Method around the Augmented Linear Regulator Problem. Working Paper University of Notre Dame. Cosimano, T. F. and M. T. Gapen, (2005). An Algorithm for Simulating Optimal Experimentation Problems using the Perturbation Method around the Augmented Linear Regulator Problem.. Hansen, L. P. and T. J. Sargent, (2004). Recursive LinearModels of Dynamic Economies, University of Chicago manuscript. Wieland, V., 2000. Learning by Doing and the Value of Optimal Experimentation. Journal of Economic Dynamics and Control 24, 501-534. Wieland, V. 2002. Monetary Policy and Uncertainty about the Natural Unemployment Rate. Working Paper University of Frankfurt

Suggested Citation

  • Michael T. Gapen & Thomas F. Cosimano, 2005. "Optimal Experimentation a Comparison of the Perturbation and Dynamic Programming Algorithms," Computing in Economics and Finance 2005 92, Society for Computational Economics.
    • Handle: RePEc:sce:scecf5:92
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    More about this item

    Keywords

    Optimal Experimentation; Learning; Perturbation Method;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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