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Convergence Of Adaptive Learning And Expectational Stability: The Case Of Multiple Rational-Expectations Equilibria

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  • Heinemann, Maik
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    Abstract

    This paper analyzes the relationship between the expectational stability of rational expectations solutions and the possible convergence of adaptive learning processes.Both concepts are used as selection criteria in the case of multiple rational expectations solutions.Results obtained using recursive least squares lead to the conjecture that there exists a general one-to-one correspondence between these two selection criteria.On the basis of a simple linear model and a stochastic gradient algorithm as an alternative learning procedure, it is demonstrated that such a conjecture would be incorrect:There are cases in which stochastic gradient learning converges to rational expectations solutions that are not expectationally stable.

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    File URL: http://journals.cambridge.org/abstract_S1365100500016011
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    Bibliographic Info

    Article provided by Cambridge University Press in its journal Macroeconomic Dynamics.

    Volume (Year): 4 (2000)
    Issue (Month): 03 (September)
    Pages: 263-288

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    Handle: RePEc:cup:macdyn:v:4:y:2000:i:03:p:263-288_01

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    Cited by:
    1. Seonghoon Cho & Antonio Moreno, 2006. "Expectational Stability in Multivariate Models," Faculty Working Papers 06/08, School of Economics and Business Administration, University of Navarra.
    2. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.
    3. Eran A. Guse, 2008. "Heterogeneous Expectations, Adaptive Learning, and Evolutionary Dynamics," Working Papers 09-01, Department of Economics, West Virginia University.

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