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Models of Macroeconomic Systems using Genetic Algorithms

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  • Nora Mihail

    (Academia de Studii Economice, Bucuresti)

Abstract

AG represents only one, it’s true that it is very fashionable today, of the new instruments which began to be used lately in the macroeconomic modelling. Here, it may also be mentioned the classification systems, the genetic programming, the models based on agents, the evolutionist games etc. The characteristics of all these methods consist in the effort to detect the internal dynamic processes of the modelled macroeconomic systems and not only the answer of these to external chocks and perturbations. Among these internal dynamic processes maybe the most interesting is that one of continuous adapting of the modelled macroeconomic system to the environment. In the macroeconomic environment are included different systems made of subsystems and heterogene agents and the decisions adopted by these affect both the systems as such and other subsystems and processes from the environment. This general independency, neglected several times in the macroeconomic modelling due to the lack of instruments and methods able to detect it, may be however approached with enough rigour resorting to new modelling methods as the one described in this chapter. In order to illustrate such a tendency, we shall present further on some of the most recent macroeconomic models which have been reformulated and studied using AG.

Suggested Citation

  • Nora Mihail, 2007. "Models of Macroeconomic Systems using Genetic Algorithms," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 12(12(517)), pages 49-54, December.
  • Handle: RePEc:agr:journl:v:12(517):y:2007:i:12(517):p:49-54
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