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Adaptive Learning and Inflation Persistence

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  • Fabio Milani

    ()
    (Department of Economics, University of California-Irvine)

Abstract

What generates persistence in inflation? Is inflation persistence structural? This paper investigates learning as a potential source of persistence in inflation. The paper focuses on the price-setting problem of firms and presents a model that nests structural sources of persistence (indexation) and learning. Indexation is typically necessary under rational expectations to match the inertia in the data and to improve the fit of estimated New Keynesian Phillips curves. The empirical results show that when learning replaces the assumption of fully rational expectations, structural sources of persistence in in?ation, such as indexation, become unsupported by the data. The results suggest learning behavior as the main source of persistence in inflation. This finding has implications for the optimal monetary policy. The paper also shows how one's results can heavily depend on the assumed learning speed. The estimated persistence and the model fit, in fact, vary across the whole range of constant gain values. The paper derives the best-fitting constant gains in the sample and shows that the learning speed has substantially changed over time.

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File URL: http://www.economics.uci.edu/files/economics/docs/workingpapers/2005-06/Milani-07.pdf
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Bibliographic Info

Paper provided by University of California-Irvine, Department of Economics in its series Working Papers with number 050607.

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Length: 40 pages
Date of creation: Jun 2005
Date of revision:
Handle: RePEc:irv:wpaper:050607

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Postal: Irvine, CA 92697-3125
Phone: (949) 824-5788
Web page: http://www.economics.uci.edu/
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Related research

Keywords: Adaptive learning; Inflation persistence; Sticky prices; Best-fitting constant gain; Learning speed; Expectations;

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