IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpge/0409010.html
   My bibliography  Save this paper

Volatility, Heterogeneous Agents and Chaos

Author

Listed:
  • Orlando Gomes

    (Escola Superior de Comunicação Social)

Abstract

Agent heterogeneity has been used in recent economic literature to justify nonlinear dynamics for the time paths of aggregate economic variables. In this paper, the mechanism through which heterogeneous agents leads to chaotic motion is explained. Adding to a system with initial behavior heterogeneity an adaptive learning rule based on discrete choice theory, one is able to encounter a reasonable explanation for nonlinear motion. The adaptive learning / bounded rationality rule is not the only ingredient necessary for the absence of a long run steady state; heterogeneity must also imply that the several behavior possibilities alternate as the best behavioral choice. Only in such circumstances heterogeneity persists and an unpredictable outcome is likely to arise. The paper develops two models. The first is a generic approach that exemplifies how heterogeneity concerning the volatility of two stochastic processes may lead to chaotic motion; the second is a utility maximization setup, where the source of heterogeneity is investment decisions.

Suggested Citation

  • Orlando Gomes, 2004. "Volatility, Heterogeneous Agents and Chaos," GE, Growth, Math methods 0409010, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:0409010
    Note: Type of Document - pdf; pages: 18
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/ge/papers/0409/0409010.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
    2. Bennett T. McCallum, 2002. "Consistent Expectations, Rational Expectations, Multiple-Solution Indeterminacies, and Least-Squares Learnability," NBER Working Papers 9218, National Bureau of Economic Research, Inc.
    3. Bullard, James & Duffy, John, 1999. "Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 41-60, February.
    4. Paul M. Romer, 2000. "Thinking and Feeling," American Economic Review, American Economic Association, vol. 90(2), pages 439-443, May.
    5. Eran Guse, 2004. "Learning with Heterogeneous Expectations in an Evolutionary World," Computing in Economics and Finance 2004 99, Society for Computational Economics.
    6. Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan & van de Velden, Henk, 2005. "A strategy experiment in dynamic asset pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 823-843, April.
    7. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October.
    8. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
    9. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    10. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
    11. De Grauwe, Paul & Grimaldi, Marianna, 2005. "Heterogeneity of agents, transactions costs and the exchange rate," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 691-719, April.
    12. Kurz, Mordecai, 1994. "On the Structure and Diversity of Rational Beliefs," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 4(6), pages 877-900, October.
    13. Honkapohja, Seppo & Mitra, Kaushik, 2005. "Performance of monetary policy with internal central bank forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 627-658, April.
    14. Evans, George W. & Guesnerie, Roger, 2003. "Coordination On Saddle-Path Solutions: The Eductive Viewpoint Linear Univariate Models," Macroeconomic Dynamics, Cambridge University Press, vol. 7(01), pages 42-62, February.
    15. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
    16. Grandmont, Jean-Michel, 1985. "On Endogenous Competitive Business Cycles," Econometrica, Econometric Society, vol. 53(5), pages 995-1045, September.
    17. Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
    18. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    19. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
    20. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    21. McGough, Bruce, 2003. "Statistical Learning With Time-Varying Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 7(01), pages 119-139, February.
    22. Manzan, Sebastiano & Westerhoff, Frank, 2005. "Representativeness of news and exchange rate dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 677-689, April.
    23. Emilio Barucci, 1999. "Heterogeneous beliefs and learning in forward looking economic models," Journal of Evolutionary Economics, Springer, vol. 9(4), pages 453-464.
    24. Negroni, Giorgio, 2003. "Adaptive expectations coordination in an economy with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 28(1), pages 117-140, October.
    25. Sargent, Thomas J., 1993. "Bounded Rationality in Macroeconomics: The Arne Ryde Memorial Lectures," OUP Catalogue, Oxford University Press, number 9780198288695.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gomes, Orlando, 2012. "Attentiveness cycles: Synchronized behavior and aggregate fluctuations," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 66(3), October.
    2. repec:fgv:epgrbe:v:66:n:3:a:1 is not listed on IDEAS
    3. Gomes, Orlando, 2006. "Heterogeneous Researchers in a Two-Sector Representative Consumer Economy," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 60(2), November.
    4. Orlando Gomes, 2008. "Can interaction contribute to the explanation of business cycles?," International Journal of Social Economics, Emerald Group Publishing, vol. 35(3), pages 159-173, February.
    5. Orlando Gomes, 2007. "The Dynamics of Growth and Migrations with Congestion Externalities," Economics Bulletin, AccessEcon, vol. 15(1), pages 1-8.

    More about this item

    Keywords

    Heterogeneous agents; Bounded rationality; Chaos; Volatility;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:wpa:wuwpge:0409010. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.