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    Title: Modeling the Expectations of Inflation in the OLG Model with Genetic Programming
    Authors: 陳樹衡;葉佳炫
    Chen,Shu-Heng;Yeh,Chia-Hsuan
    Contributors: 政大經濟系
    Keywords: Genetic programming;overlapping generations models;bounded rationality;agent-based computational economics;Pareto-superior equilibrium
    Date: 1999-09
    Issue Date: 2009-01-09 12:19:44 (UTC+8)
    Abstract: In this paper, genetic programming (GP) is employed to model learning and adaptation in the overlapping generations model, one of the most popular dynamic economic models. Using a model of inflation with multiple equilibria as an illustrative example, we show that our GP-based agents are able to coordinate their actions to achieve the Pareto-superior equilibrium (the low-inflation steady state) rather than the Pareto inferior equilibrium (the high-inflation steady
    state). We also test the robustness of this result with different initial conditions, economic parameters, GP control parameters, and the selection mechanism. We find that as long
    as the survival-of-the-fittest principle is maintained, the evolutionary operators are only secondarily important. However, once the survival-of-the-fittest principle is absent, the well-coordinated economy is also gone and the inflation rate can jump quite wildly. To some extent, these results shed light on the biological foundations of economics.
    Relation: Soft Computing,3(2),53-62
    Data Type: article
    DOI link: http://dx.doi.org/10.1007/s005000050053
    DOI: 10.1007/s005000050053
    Appears in Collections:[Department of Economics] Periodical Articles

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