WHEN DOES DETERMINACY IMPLY EXPECTATIONAL STABILITY?

Authors

  • JAMES BULLARD,

    1. Federal Reserve Bank of St. Louis, U.S.A.
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  • STEFANO EUSEPI

    Corresponding author
    1. Federal Reserve Bank of New York, U.S.A.
    • Please address correspondence to: Stefano Eusepi, Department of Research and Statistics, Federal Reserve Bank of New York, 33 Liberty Street, New York, NY 10045. E-mail: stefano.eusepi@ny.frb.org.

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    • We thank Bruce Preston, three anonymous referees, and the participants at Learning Week for helpful comments on early versions of this work. Any views expressed are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of St. Louis, the Federal Reserve Bank of New York, or the Federal Reserve.


Abstract

Since the introduction of rational expectations, there have been issues with multiple equilibria and equilibrium selection. We study the connections between determinacy of rational expectations equilibrium and learnability of that equilibrium in a general class of purely forward-looking models. Our framework is sufficiently flexible to encompass lags in agents' information and either finite horizon or infinite horizon approaches to learning. We are able to isolate conditions under which determinacy does and does not imply learnability and also conditions under which long-horizon forecasts make a clear difference for learnability. Finally, we apply our result to a relatively general New Keynesian model.

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