IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v45y2015i2p337-358.html
   My bibliography  Save this article

Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction

Author

Listed:
  • Sylvain Barde

Abstract

This paper shows that signal restoration methodology is appropriate for predicting the equilibrium state of certain economic systems. A formal justification for this is provided by proving the existence of finite improvement paths in object allocation problems under weak assumptions on preferences, linking any initial condition to a Nash equilibrium. Because a finite improvement path is made up of a sequence of systematic best-responses, backwards movement from the equilibrium back to the initial condition can be treated like the realisation of a noise process. This underpins the use of signal restoration to predict the equilibrium from the initial condition, and an illustration is provided through an application of maximum entropy signal restoration to the Schelling model of segregation. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Sylvain Barde, 2015. "Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 337-358, February.
    • Handle: RePEc:kap:compec:v:45:y:2015:i:2:p:337-358
    DOI: 10.1007/s10614-014-9422-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-014-9422-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-014-9422-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Abdelkader Sbihi, 2007. "A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem," Journal of Combinatorial Optimization, Springer, vol. 13(4), pages 337-351, May.
    2. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
    3. Grauwin, Sébastian & Goffette-Nagot, Florence & Jensen, Pablo, 2012. "Dynamic models of residential segregation: An analytical solution," Journal of Public Economics, Elsevier, vol. 96(1), pages 124-141.
    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. 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.
    6. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    7. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    8. Sebastian Grauwin & Florence Goffette-Nagot & Pablo Jensen, 2012. "Dynamic models of residential segregation: An analytical solution," Post-Print halshs-00733842, HAL.
    9. Harris, Milton & Raviv, Artur, 1981. "Allocation Mechanisms and the Design of Auctions," Econometrica, Econometric Society, vol. 49(6), pages 1477-1499, November.
    10. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    11. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 265-290, October.
    12. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    13. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
    14. 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).
    15. Hurwicz, Leonid, 1973. "The Design of Mechanisms for Resource Allocation," American Economic Review, American Economic Association, vol. 63(2), pages 1-30, May.
    16. Yew-Kwang Ng, 1975. "Bentham or Bergson? Finite Sensibility, Utility Functions and Social Welfare Functions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(4), pages 545-569.
    17. 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.
    18. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    19. M Hifi & M Michrafy & A Sbihi, 2004. "Heuristic algorithms for the multiple-choice multidimensional knapsack problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1323-1332, December.
    20. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.
    2. Trevor Kollmann & Simone Marsiglio & Sandy Suardi & Marco Tolotti, 2021. "Social interactions, residential segregation and the dynamics of tipping," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1355-1388, September.
    3. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046.
    5. Gräbner, Claudius, 2016. "From realism to instrumentalism - and back? Methodological implications of changes in the epistemology of economics," MPRA Paper 71933, University Library of Munich, Germany.
    6. Furtado, Bernardo Alves & Eberhardt, Isaque Daniel Rocha, 2015. "Modelo espacial simples da economia: uma proposta teórico-metodológica [A simple spatial economic model: a proposal]," MPRA Paper 67005, University Library of Munich, Germany.
    7. Khamdamov, T., 2022. "A brief overview of the evolution of computer simulations in economic research," Journal of the New Economic Association, New Economic Association, vol. 54(2), pages 189-207.
    8. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    9. Sylvain Barde, 2011. "Ignorance is bliss: rationality, information and equilibrium," Sciences Po publications 2011-04, Sciences Po.
    10. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    11. Schuster, Stephan, 2012. "Applications in Agent-Based Computational Economics," MPRA Paper 47201, University Library of Munich, Germany.
    12. Francis Tseng & Fei Liu & Bernardo Alves Furtado, 2017. "Humans of Simulated New York (HOSNY): an exploratory comprehensive model of city life," Papers 1703.05240, arXiv.org, revised Mar 2017.
    13. Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.
    14. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    15. Chiarella Carl & Di Guilmi Corrado, 2015. "The limit distribution of evolving strategies in financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 137-159, April.
    16. Richard Wallick, 2012. "Agent-based modeling, public choice, and the legacy of Gordon Tullock," Public Choice, Springer, vol. 152(1), pages 223-244, July.
    17. Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.
    18. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    19. David C. Earnest & Ian F. Wilkinson, 2018. "An agent based model of the evolution of supplier networks," Computational and Mathematical Organization Theory, Springer, vol. 24(1), pages 112-144, March.
    20. Bernardo Alves Furtado & Isaque Daniel Rocha Eberhardt, 2016. "A Simple Agent-Based Spatial Model of the Economy: Tools for Policy," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-12.

    More about this item

    Keywords

    Information entropy; Self-organisation; Potential function; Schelling segregation; C02; C11; C63; D80;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:45:y:2015:i:2:p:337-358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.