Published In

Macroeconomic Dynamics

Document Type

Article

Publication Date

2012

Subjects

Inflation (Finance) -- Mathematical models, Macroeconomics

Abstract

An adaptive step-size algorithm [Kushner and Yin, Stochastic Approximation and Recursive Algorithms and Applications, 2nd ed., New York: Springer-Verlag (2003)] is used to model time-varying learning, and its performance is illustrated in the environment of Marcet and Nicolini [American Economic Review 93 (2003), 1476–1498]. The resulting model gives qualitatively similar results to those of Marcet and Nicolini, and performs quantitatively somewhat better, based on the criterion of mean squared error. The model generates increasing gain during hyperinflations and decreasing gain after hyperinflations end, which matches findings in the data. An agent using this model behaves cautiously when faced with sudden changes in policy, and is able to recognize a regime change after acquiring sufficient information.

Description

This is the publisher's final pdf. Article appears in Macroeconomic Dynamics (http://journals.cambridge.org) and is copyrighted by Cambridge University Press. This article may be downloaded for personal use only.

DOI

10.1017/S136510051000088X

Persistent Identifier

http://archives.pdx.edu/ds/psu/10211

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