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A Model of Boundedly Rational Consumer Choice - An Agent Based Appraoch

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  • Riechmann, Thomas

Abstract

The paper presents an extended version of the consumer choice problem. Different from the standard model, prices are not fixed but arise from Walrasian interactions of total demand and a stylized supply function for each of the goods. Three different types of evolutionary algorithms are set up to answer the question whether agents can learn to solve the problem of extended consumer choice. There are three important answers to this question: a) The quality of the results learned crucially depends on the elasticity of supply, which in turn is shown to be a measure of the degree of state dependency of the economic problem. b) It seems to be relatively easy to adhere to the budget constraint, but relatively difficult to reach an optimum with marginal utility per Dollar being equal for each good. c) Agents equipped with some memory are found to perform notably better than agents without memory.

Suggested Citation

  • Riechmann, Thomas, 2000. "A Model of Boundedly Rational Consumer Choice - An Agent Based Appraoch," Hannover Economic Papers (HEP) dp-232, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-232
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    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    3. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    4. Thomas Riechmann, 1999. "Learning and behavioral stability An economic interpretation of genetic algorithms," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 225-242.
    5. Chris Birchenhall & Nikos Kastrinos & Stan Metcalfe, 1997. "Genetic algorithms in evolutionary modelling," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 375-393.
    6. Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    consumer choice; evolutionary algorithms; state dependency;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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