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Simulating economic transition processes by genetic programming

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  • Shu-Heng Chen
  • Chia-Hsuan Yeh

Abstract

Recently, genetic programming has been proposed to model agents' adaptive behavior in a complex transition process where uncertainty cannot be formalized within the usual probabilistic framework. However, this approach has not been widely accepted by economists. One of the main reasons is the lack of the theoretical foundation of using genetic programming to model transition dynamics. Therefore, the purpose of this paper is two-fold. First, motivated by the recent applications of algorithmic information theory in economics, we would like to show the relevance of genetic programming to transition dynamics given this background. Second, we would like to supply two concrete applications to transition dynamics. The first application, which is designed for the pedagogic purpose, shows that genetic programming can simulate the non-smooth transition, which is difficult to be captured by conventional toolkits, such as differential equations and difference equations. In the second application, genetic programming is applied to simulate the adaptive behavior of speculators. This simulation shows that genetic programming can generate artificial time series with the statistical properties frequently observed in real financial time series. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Shu-Heng Chen & Chia-Hsuan Yeh, 2000. "Simulating economic transition processes by genetic programming," Annals of Operations Research, Springer, vol. 97(1), pages 265-286, December.
    • Handle: RePEc:spr:annopr:v:97:y:2000:i:1:p:265-286:10.1023/a:1018972006990
    DOI: 10.1023/A:1018972006990
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    Cited by:

    1. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    2. Tongkui Yu & Shu-Heng Chen, 2021. "Realizable Utility Maximization as a Mechanism for the Stability of Competitive General Equilibrium in a Scarf Economy," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 133-167, June.

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