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Back to the future: economic rationality and maximum entropy prediction

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  • Sylvain Barde

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Abstract

An information-theoretic thought experiment is developed to clarify why the maximum entropy methodology is appropriate for predicting the equilibrium state of economic systems. As a first step, object allocation problems, modeled as knapsack problems, are shown to be equivalent to congestion games under weak assumptions. This proves the existence of finite improvement paths linking initial conditions and Nash equilibria. The existence of these improvement paths is precisely what enables the use of maximum entropy to make predictions concerning the equilibrium state. Finally an illustration of this predictive power is provided through an application to the Schelling model of segregation.

Suggested Citation

  • Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.
  • Handle: RePEc:ukc:ukcedp:1202
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    File URL: ftp://ftp.ukc.ac.uk/pub/ejr/RePEc/ukc/ukcedp/1202.pdf
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    References listed on IDEAS

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    1. Mhand Hifi & Slim Sadfi & Abdelkader Sbihi, 2004. "An exact algorithm for the multiple-choice multidimensional knapsack problem," Cahiers de la Maison des Sciences Economiques b04024, Université Panthéon-Sorbonne (Paris 1).
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    3. Hurwicz, Leonid, 1973. "The Design of Mechanisms for Resource Allocation," American Economic Review, American Economic Association, vol. 63(2), pages 1-30, May.
    4. Castaldi, Carolina & Milakovic, Mishael, 2007. "Turnover activity in wealth portfolios," Journal of Economic Behavior & Organization, Elsevier, vol. 63(3), pages 537-552, July.
    5. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    6. Tutino, Antonella, 2011. "Rationally inattentive macroeconomic wedges," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 344-362, March.
    7. Chakrabarti, Anindya S. & Chakrabarti, Bikas K., 2009. "Microeconomics of the ideal gas like market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4151-4158.
    8. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    9. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    10. Gallegati, Mauro & Keen, Steve & Lux, Thomas & Ormerod, Paul, 2006. "Worrying trends in econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 1-6.
    11. Christopher A. Sims, 2006. "Rational Inattention: Beyond the Linear-Quadratic Case," American Economic Review, American Economic Association, vol. 96(2), pages 158-163, May.
    12. Sylvain Barde, 2012. "Of Ants and Voters. Maximum Entropy Prediction of Agent-Based Models with Recruitment," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 147-175.
    13. Alexis Toda, 2010. "Existence of a statistical equilibrium for an economy with endogenous offer sets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 45(3), pages 379-415, December.
    14. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
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    Citations

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    Cited by:

    1. Zakaria Babutsidze, 2012. "Comments on the paper. "Of Ants and Voters: Maximum entropy prediction of agent-based models with recruitment" by S. Barde," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 33-36.
    2. Sylvain Barde, 2012. "Of ants and voters maximum entropy prediction and agent based models with recruitment," Post-Print hal-01071853, HAL.

    More about this item

    Keywords

    Information entropy; knapsack problem; potential function; Schelling segregation.;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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