Convergence to Rational Expectations in Learning Models: A Note of Caution

YiLi Chien, Inkoo Cho and B Ravikumar

Review, 2021, vol. 103, issue 3, 366 pages

Abstract: We show in a simple monetary model that the learning dynamics do not converge to the rational expectations monetary steady state. We then show it is necessary to restrict the learning rule to obtain convergence. We derive an upper bound on the gain parameter in the learning rule, based on economic fundamentals in the monetary model, such that gain parameters above the upper bound would imply that the learning dynamics would diverge from the rational expectations monetary steady state.

Keywords: monetary; learning models (search for similar items in EconPapers)
JEL-codes: C60 D84 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Working Paper: Convergence to Rational Expectations in Learning Models: A Note of Caution (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlrv:92881

DOI: 10.20955/r.103.351-65

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