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Convergence to Rational Expectations in a Stationary Linear Game

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  • Jordan, J.S.

Abstract

This paper describes several learning processes which converge, with probability one, to the rational expectations (Bayesian-Nash) equilibrium of a stationary linear game. The learning processes include a test for convergence to equilibrium, and a method for changing the parameters of the process when non-convergence is indicated. This self-stabilization property eliminates the need to impose stability conditions on the economic environment. Convergence to equilibrium is proved for two types of self-stabilizing learning mechanisms: a centralized forecasting mechanism and a decentralized strategy adjustment process.
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Suggested Citation

  • Jordan, J.S., 1990. "Convergence to Rational Expectations in a Stationary Linear Game," Papers 258, Minnesota - Center for Economic Research.
    • Handle: RePEc:fth:minner:258
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    Cited by:

    1. Marimon, R. & McGraltan, E., 1993. "On Adaptative Learning in Strategic Games," Papers 190, Cambridge - Risk, Information & Quantity Signals.
    2. Vives, Xavier, 1997. "Learning from Others: A Welfare Analysis," Games and Economic Behavior, Elsevier, vol. 20(2), pages 177-200, August.
    3. Linn, Scott C. & Stanhouse, Bryan E., 1997. "The economic advantage of least squares learning in a risky asset market," Journal of Economics and Business, Elsevier, vol. 49(4), pages 303-319.
    4. Buchanan, Neil H., 2008. "How realistic is the supply/demand equilibrium story: A simple demonstration of false trading and its implications for market equilibrium," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(1), pages 400-415, February.

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