Recency, Consistent Learning, and Nash Equilibrium

Drew Fudenberg and David Levine

Scholarly Articles from Harvard University Department of Economics

Abstract: We examine the long-term implication of two models of learning with recency bias: recursive weights and limited memory. We show that both models generate similar beliefs and that both have a weighted universal consistency property. Using the limited-memory model we produce learning procedures that both are weighted universally consistent and converge with probability one to strict Nash equilibrium.

Date: 2014
New Economics Papers: this item is included in nep-mic
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Published in Proceedings of the National Academy of Sciences

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Persistent link: https://EconPapers.repec.org/RePEc:hrv:faseco:13477947

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