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Improving the performance of an economic system: Controlling chaos

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Author Info

  • Michael Kopel

    ()
    (University of Technology, Department of Managerial Economics and Industrial Organization, Theresianumgasse 27/330, A-1040 Wien, Austria)

Abstract

In this paper we use a simple model of evolutionary market dynamics to illustrate how chaotic behavior can be controlled by making small changes in a parameter that is accessible to the decision makers. This approach is commonly referred to as `targeting' - one can easily switch from a chaotic evolution of the market to any desired regular motion. We show that complex dynamics leads to inferior performance in our model and that an application of such a correction mechanism by the decision makers of the firms yields a considerable improvement in the system's economical properties in terms of profits and profitability. We present numerical simulations in order to illustrate the effectiveness of this method.

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Bibliographic Info

Article provided by Springer in its journal Journal of Evolutionary Economics.

Volume (Year): 7 (1997)
Issue (Month): 3 ()
Pages: 269-289

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Handle: RePEc:spr:joevec:v:7:y:1997:i:3:p:269-289

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Related research

Keywords: Cobweb models ; Bounded rationality ; Controlling chaos;

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Cited by:
  1. Xue-Zhong He & Frank H. Westerhoff, 2004. "Commodity Markets, Price Limiters and Speculative Price Dynamics," Research Paper Series 136, Quantitative Finance Research Centre, University of Technology, Sydney.
  2. Matsumoto, Akio & Nonaka, Yasuo, 2006. "Statistical dynamics in a chaotic Cournot model with complementary goods," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 769-783, December.
  3. J. Barkley Rosser, 1999. "On the Complexities of Complex Economic Dynamics," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 169-192, Fall.
  4. Athanasiou, George & Kotsios, Stelios, 2008. "An algorithmic approach to exchange rate stabilization," Economic Modelling, Elsevier, vol. 25(6), pages 1246-1260, November.
  5. Frank Westerhoff & Cristian Wieland, . "Exchange rate dynamics, central bank interventions and chaos control methods," Modeling, Computing, and Mastering Complexity 2003 22, Society for Computational Economics.
  6. Huang, Weihong & Zhang, Yang, 2007. "Distributional dynamics of cautious economic adjustment processes," Journal of Economic Behavior & Organization, Elsevier, vol. 62(3), pages 389-407, March.
  7. Chen, Liang & Chen, Guanrong, 2007. "Controlling chaos in an economic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 349-358.
  8. Matsumoto, Akio, 2005. "Density function of piecewise linear transformation," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 631-653, April.
  9. Vivaldo M. Mendes & Diana A. Mendes, 2007. "Controlling Endogenous Cycles in an OLG Economy by the OGY Method," Working Papers Series 1 ercwp0808, ISCTE-IUL, Business Research Unit (BRU-IUL).
  10. Salarieh, Hassan & Alasty, Aria, 2008. "Delayed feedback control via minimum entropy strategy in an economic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 851-860.
  11. Vivaldo M. Mendes & Diana A. Mendes, 2006. "Active Interest Rate Rules and the Role of Stabilization Policy R&D Tax Credits," Working Papers Series 1 ercwp0208, ISCTE-IUL, Business Research Unit (BRU-IUL).
  12. Barkley Rosser, J. Jr., 2001. "Complex ecologic-economic dynamics and environmental policy," Ecological Economics, Elsevier, vol. 37(1), pages 23-37, April.
  13. Huang, Weihong, 2008. "The long-run benefits of chaos to oligopolistic firms," Journal of Economic Dynamics and Control, Elsevier, vol. 32(4), pages 1332-1355, April.
  14. Kaas, Leo, 1998. "Stabilizing chaos in a dynamic macroeconomic model," Journal of Economic Behavior & Organization, Elsevier, vol. 33(3-4), pages 313-332, January.

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