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Adaptive Learning and Complex Dynamics

Author

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  • Orlando Gomes

    (Instituto Politécnico de Lisboa - Escola Superior de Comunicação Social and UNIDE-ERC)

Abstract

In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady-state. This long term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the innefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and aperiodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. Two macroeconomic models are used to illustrate how the formation of expectations through learning may eventually lead to awkward long term outcomes.

Suggested Citation

  • Orlando Gomes, 2008. "Adaptive Learning and Complex Dynamics," Working Papers Series 1 ercwp2108, ISCTE-IUL, Business Research Unit (BRU-IUL).
  • Handle: RePEc:isc:iscwp1:ercwp2108
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    References listed on IDEAS

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    1. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    2. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
    3. Dieci, Roberto & Foroni, Ilaria & Gardini, Laura & He, Xue-Zhong, 2006. "Market mood, adaptive beliefs and asset price dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 520-534.
    4. Schonhofer, Martin, 1999. "Chaotic Learning Equilibria," Journal of Economic Theory, Elsevier, vol. 89(1), pages 1-20, November.
    5. Honkapohja, Seppo & Mitra, Kaushik, 2003. "Learning with bounded memory in stochastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 27(8), pages 1437-1457, June.
    6. Colucci, D. & Valori, V., 2006. "Ways of learning in a simple economic setting: A comparison," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 653-670.
    7. George William Evans, 2001. "Expectations in Macroeconomics Adaptive versus Eductive Learning," Revue économique, Presses de Sciences-Po, vol. 52(3), pages 573-582.
    8. Bullard James, 1994. "Learning Equilibria," Journal of Economic Theory, Elsevier, vol. 64(2), pages 468-485, December.
    9. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    10. Martin Schonhofer, "undated". "Chaotic Learning Equilibria," Computing in Economics and Finance 1997 121, Society for Computational Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Orlando Gomes, 2010. "Ordinary Least Squares Learning And Nonlinearities In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 52-84, February.
    2. Kostevšek, Anja & Petek, Janez & Čuček, Lidija & Pivec, Aleksandra, 2013. "Conceptual design of a municipal energy and environmental system as an efficient basis for advanced energy planning," Energy, Elsevier, vol. 60(C), pages 148-158.

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    More about this item

    Keywords

    Adaptive Learning; Nonlinear Dynamics; Stability Properties; Economic Models.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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