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Adaptive Learning and Inflation Persistence

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Author Info
Fabio Milani (Princeton University)

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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 inflation, 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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Paper provided by EconWPA in its series Macroeconomics with number 0506013.

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Length: 34 pages
Date of creation: 19 Jun 2005
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Handle: RePEc:wpa:wuwpma:0506013

Note: Type of Document - pdf; pages: 34
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Web page: http://129.3.20.41

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Related research
Keywords: adaptive learning; inflation persistence; sticky prices; best- fitting constant gain; learning speed; expectations.;

Other versions of this item:

Find related papers by JEL classification:
D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    Other versions:
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Fanelli, Luca, 2008. "Evaluating the New Keynesian Phillips Curve under VAR-Based Learning," Economics Discussion Papers 2008-15, Kiel Institute for the World Economy. [Downloadable!]
    Other versions:
  2. Marco Lombardi & Silvia Sgherri, 2007. "(Un)naturally Low? Sequential Monte Carlo Tracking of the US Natural Interest Rate," DNB Working Papers 142, Netherlands Central Bank, Research Department. [Downloadable!]
    Other versions:
  3. Evans , George W & Honkapohja, Seppo, 2007. "Robust learning stability with operational monetary policy rules," Research Discussion Papers 31/2007, Bank of Finland. [Downloadable!]
    Other versions:
  4. Kevin J. Lansing, 2006. "Time-Varying U.S. Inflation Dynamics and the New Keynesian Phillips Curve," Computing in Economics and Finance 2006 488, Society for Computational Economics. [Downloadable!]
    Other versions:
  5. Fabio Milani, 2005. "A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?," Working Papers 060703, University of California-Irvine, Department of Economics. [Downloadable!]
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  6. Emiliano Santoro & Damjan Pfajfar, 2006. "Heterogeneity and learning in inflation expectation formation: an empirical assessment," Department of Economics Working Papers 0607, Department of Economics, University of Trento, Italia. [Downloadable!]
  7. J. Huston McCulloch, 2005. "The Kalman Foundations of Adaptive Least Squares: Applications to Unemployment and Inflation," Computing in Economics and Finance 2005 239, Society for Computational Economics. [Downloadable!]
  8. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2006. "Adaptive Learning in Practice," CEPR Discussion Papers 5627, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  9. Fabio Milani, 2006. "The Evolution of the Fed's Inflation Target in an Estimated Model under RE and Learning," Working Papers 060704, University of California-Irvine, Department of Economics. [Downloadable!]
  10. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Working Papers 050608, University of California-Irvine, Department of Economics. [Downloadable!]
    Other versions:
  11. Fanelli, Luca, 2008. "Evaluating New Keynesian Phillips Curve under VAR-Based Learning," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 2(33), pages 1-24. [Downloadable!]
  12. Evans , George W & Honkapohja, Seppo, 2007. "Expectations, learning and monetary policy: an overview of recent research," Research Discussion Papers 32/2007, Bank of Finland. [Downloadable!]
    Other versions:
  13. Fabio Milani, 2005. "Learning, Monetary Policy Rules, and Macroeconomic Stability," Macroeconomics 0508019, EconWPA. [Downloadable!]
    Other versions:
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