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Coevolution and stable adjustments in the cobweb model

Author

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  • Reiner Franke

    (Department of Economics, University of Bremen, D-28334 Bremen, Germany)

Abstract

The paper is concerned with genetic algorithm learning in a cobweb economy. Besides discussing several specification details in the genetic operators, the model includes four different types of firm forecasting rules and subjects the demand side to serially correlated random shocks. The main finding of the simulation experiments is that the genetic algorithm is a reasonably good approximation of the moving Walrasian equilibria, and that this process is characterized by the coevolution of different strategies. Accordingly, it is just the persistent heterogeneity of firms, and the persistently changing composition of this heterogeneity, that achieves stability. In this world, convergence is improved by weak, rather than strong, evolutionary pressure.

Suggested Citation

  • Reiner Franke, 1998. "Coevolution and stable adjustments in the cobweb model," Journal of Evolutionary Economics, Springer, vol. 8(4), pages 383-406.
    • Handle: RePEc:spr:joevec:v:8:y:1998:i:4:p:383-406
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    Citations

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    Cited by:

    1. Dawid, Herbert, 1999. "On the convergence of genetic learning in a double auction market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1545-1567, September.

    More about this item

    Keywords

    Behavioural heterogeneity ; Coevolution ; Learning ; Genetic algorithm ; Cobweb model;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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