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Learning and Time-Varying Macroeconomic Volatility

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  • Fabio Milani

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

Abstract

This paper presents a DSGE model in which agents' learning about the economy can endogenously generate time-varying macroeconomic volatility. Economic agents use simple models to form expectations and need to learn the relevant parameters. Their gain coefficient is endogenous and is adjusted according to past forecast errors. The model is estimated using likelihood-based Bayesian methods. The endogenous gain is jointly estimated with the structural parameters of the system. The estimation results show that private agents appear to have often switched to constant-gain learning, with a high constant gain, during most of the 1970s and until the early 1980s, while reverting to a decreasing gain later on. As a result, the model can generate a pattern of volatility, which is increasing in the 1970s and falling in the second half of the sample, with a decline that can roughly match the magnitude of the Great Moderation. The paper also documents how a failure to incorporate learning into the estimation may lead econometricians to spuriously find time-varying volatility in the exogenous shocks, even when these have constant variance by construction.

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File URL: http://www.economics.uci.edu/files/economics/docs/workingpapers/2007-08/Milani-02.pdf
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Bibliographic Info

Paper provided by University of California-Irvine, Department of Economics in its series Working Papers with number 070802.

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Length: 42 pages
Date of creation: May 2007
Date of revision:
Handle: RePEc:irv:wpaper:070802

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Web page: http://www.economics.uci.edu/
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Related research

Keywords: Adaptive learning; Constant gain; Monetary policy; Macroeconomic volatility; Inflation dynamics;

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Cited by:
  1. James B. Bullard & Aarti Singh, 2009. "Learning and the Great Moderation," Working Papers 2007-027, Federal Reserve Bank of St. Louis.
  2. Evans, George W & Honkapohja, Seppo, 2008. "Robust Learning Stability with Operational Monetary Policy Rules," CEPR Discussion Papers 6641, C.E.P.R. Discussion Papers.
  3. Paul Grauwe, 2011. "Animal spirits and monetary policy," Economic Theory, Springer, vol. 47(2), pages 423-457, June.
  4. Paul De Grauwe, 2010. "Top-Down versus Bottom-Up Macroeconomics," CESifo Working Paper Series 3020, CESifo Group Munich.
  5. De Grauwe, Paul, 2008. "DSGE-Modelling: when agents are imperfectly informed," Working Paper Series 0897, European Central Bank.
  6. Fabio Milani, 2009. "The Effect of Global Output on U.S. Inflation and Inflation Expectations: A Structural Estimation," Working Papers 080920, University of California-Irvine, Department of Economics.
  7. Tim Taylor & Richard Harrison, 2008. "Misperceptions, heterogeneous expectations and macroeconomic dynamics," 2008 Meeting Papers 710, Society for Economic Dynamics.
  8. De Grauwe, Paul, 2012. "Booms and busts in economic activity: A behavioral explanation," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 484-501.
  9. Eric Gaus, 2013. "Time-Varying Parameters and Endogenous Learning Algorithms," Working Papers 13-02, Ursinus College, Department of Economics.
  10. Richard Harrison & Haroon Mumtaz & Tony Yates, . " Using time-varying VARs to diagnose the source of ‘Great Moderations’: a Monte Carlo analysis," CDMA Conference Paper Series 0814, Centre for Dynamic Macroeconomic Analysis.

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