IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1202.6647.html
   My bibliography  Save this paper

Chaos and Nonlinear Dynamics in a Quantum Artificial Economy

Author

Listed:
  • Carlos Pedro Gonc{c}alves

Abstract

Chaos and nonlinear economic dynamics are addressed for a quantum coupled map lattice model of an artificial economy, with quantized supply and demand equilibrium conditions. The measure theoretic properties and the patterns that emerge in both the economic business volume dynamics' diagrams as well as in the quantum mean field averages are addressed and conclusions are drawn in regards to the application of quantum chaos theory to address signatures of chaotic dynamics in relevant discrete economic state variables.

Suggested Citation

  • Carlos Pedro Gonc{c}alves, 2012. "Chaos and Nonlinear Dynamics in a Quantum Artificial Economy," Papers 1202.6647, arXiv.org.
    • Handle: RePEc:arx:papers:1202.6647
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1202.6647
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard H. Day, 2000. "Complex Economic Dynamics - Vol. 2: An Introduction to Macroeconomic Dynamics," MIT Press Books, The MIT Press, edition 1, volume 2, number 0262041723, December.
    2. Richard H. Day, 1994. "Complex Economic Dynamics - Vol. 1: An Introduction to Dynamical Systems and Market Mechanisms," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262041413, December.
    3. Edward W. Piotrowski & Jan Sladkowski, "undated". "Quantum-Like Approach to Financial Risk: Quantum Anthropic Principle," Departmental Working Papers 8, University of Bialtystok, Department of Theoretical Physics.
    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. Neugart, Michael, 2004. "Complicated dynamics in a flow model of the labor market," Journal of Economic Behavior & Organization, Elsevier, vol. 53(2), pages 193-213, February.
    2. Witt, Ulrich & Worch, Hagen, 2023. "Growth-induced crises and transitions in the governance of firm organizations," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 1182-1191.
    3. Viktor Avrutin & Iryna Sushko & Fabio Tramontana, 2014. "Bifurcation Structure in a Bimodal Piecewise Linear Business Cycle Model," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-12, November.
    4. Citera, Emanuele & Sau, Lino, 2019. "Complexity, Conventions and Instability: the role of monetary policy," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201924, University of Turin.
    5. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    6. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    7. Tuinstra, Jan & Wegener, Michael & Westerhoff, Frank, 2014. "Positive welfare effects of trade barriers in a dynamic partial equilibrium model," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 246-264.
    8. Faggini, Marisa & Parziale, Anna, 2011. "Fitness landscape and tax planning: NK model for fiscal federalism," MPRA Paper 33770, University Library of Munich, Germany.
    9. Guevara Hidalgo, Esteban, 2006. "Quantum Replicator Dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 393-407.
    10. J. Barkley Rosser & Marina V. Rosser, 2017. "Complexity and institutional evolution," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 415-430, December.
    11. Piotrowski, Edward W. & Sładkowski, Jan, 2005. "Quantum diffusion of prices and profits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(1), pages 185-195.
    12. Kumaraswamy Velupillai, 2003. "Economics and the complexity vision: chimerical partners or elysian adventurers," Department of Economics Working Papers 0307, Department of Economics, University of Trento, Italia.
    13. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    14. Fontana, Magda, 2010. "Can neoclassical economics handle complexity? The fallacy of the oil spot dynamic," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 584-596, December.
    15. Khrennikov, Andrei, 2008. "Quantum-like microeconomics: Statistical model of distribution of investments and production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5826-5843.
    16. Teglio, Andrea & Catalano, Michele & Petrovic, Marko, 2014. "Myopic households on a stable path: the neoclassical growth model with rule-based expectations," MPRA Paper 120253, University Library of Munich, Germany.
    17. Pakuła, Ireneusz & Piotrowski, Edward W. & Sładkowski, Jan, 2007. "Universality of measurements on quantum markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 397-405.
    18. Edward Piotrowski & Jan Sładkowski, 2004. "Quantum games in finance," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 61-67.
    19. Dawid, Herbert, 2000. "On the emergence of exchange and mediation in a production economy," Journal of Economic Behavior & Organization, Elsevier, vol. 41(1), pages 27-53, January.
    20. Laurent Cellarier & Richard Day, 2011. "Structural instability and alternative development scenarios," Journal of Population Economics, Springer;European Society for Population Economics, vol. 24(3), pages 1165-1180, July.

    More about this item

    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:arx:papers:1202.6647. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.