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Robustness of computer algorithms to simulate optimal experimentation problems

Author

Listed:
  • Thomas Cosimano

    () (University of Notre Dame)

  • Michael Gapen

    (International Monetary Fund)

  • David Kendrick

    (University of Texas)

  • Volker Wieland

    (Goethe University of Frankfurt)

Abstract

Three methods have been developed by the authors for solving optimal experimentation problems. David Kendrick (1981, 2002, Ch.10) uses quadratic approximation of the value function and linear approximation of the equation of motion to simulate general optimal experimentation (active learning) problems. Beck and Volker Wieland (2002) use dynamic programming methods to develop an algorithm for optimal experimentation problems. Cosimano (2003) and Cosimano and Gapen (2005) use the Perturbation method to develop an algorithm for solving optimal experimentation problems. The perturbation is in the neighborhood of the augmented linear regulator problems of Hansen and Sargent (2004). In this paper we take an example from Beck and Wieland which fits into the setup of all three algorithms. Using this example we examine the cost and benefits of the various algorithms for solving optimal experimentation problems.

Suggested Citation

  • Thomas Cosimano & Michael Gapen & David Kendrick & Volker Wieland, 2006. "Robustness of computer algorithms to simulate optimal experimentation problems," Computing in Economics and Finance 2006 32, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:32
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    File URL: http://repec.org/sce2006/up.28241.1137610390.pdf
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    More about this item

    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
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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