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A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?

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  • Fabio Milani

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

Abstract

This paper estimates a monetary DSGE model with learning introduced from the primitive assumptions. The model nests infinite-horizon learning and features, such as habit formation in consumption and inflation indexation, that are essential for the model fit under rational expectations. I estimate the DSGE model by Bayesian methods, obtaining estimates of the main learning parameter, the constant gain, jointly with the deep parameters of the economy. The results show that relaxing the assumption of rational expectations in favor of learning may render mechanical sources of persistence superfluous. In particular, learning appears a crucial determinant of inflation inertia.

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File URL: http://www.economics.uci.edu/files/economics/docs/workingpapers/2006-07/Milani-03.pdf
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Bibliographic Info

Paper provided by University of California-Irvine, Department of Economics in its series Working Papers with number 060703.

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Length: 19 pages
Date of creation: Dec 2005
Date of revision:
Handle: RePEc:irv:wpaper:060703

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Keywords: Infinite-horizon learning; DSGE model; Bayesian estimation; Non-rational expectations; Inflation persistence; Habit formation;

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References

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  1. Raf Wouters & Frank Smets, 2005. "Comparing shocks and frictions in US and euro area business cycles: a Bayesian DSGE Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 161-183.
  2. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  3. Athanasios Orphanides & John C. Williams, 2003. "Inflation scares and forecast-based monetary policy," Finance and Economics Discussion Series 2003-41, Board of Governors of the Federal Reserve System (U.S.).
  4. Marc P. Giannoni & Michael Woodford, 2003. "Optimal Inflation Targeting Rules," NBER Working Papers 9939, National Bureau of Economic Research, Inc.
  5. Sungbae An & Frank Schorfheide, 2006. "Bayesian analysis of DSGE models," Working Papers 06-5, Federal Reserve Bank of Philadelphia.
  6. Fabio Milani, 2005. "Learning, Monetary Policy Rules, and Macroeconomic Stability," Macroeconomics 0508019, EconWPA.
  7. Orphanides, Athanasios & Williams, John C., 2003. "Imperfect knowledge, inflation expectations, and monetary policy," CFS Working Paper Series 2003/40, Center for Financial Studies (CFS).
  8. Kaushik Mitra & James Bullard, . "Learning About Monetary Policy Rules," Discussion Papers 00/41, Department of Economics, University of York.
  9. Frank Smets & Raf Wouters, 2002. "Monetary policy in an estimated stochastic dynamic general equilibrium model of the Euro area," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  10. Bruce Preston, 2003. "Learning about monetary policy rules when long-horizon expectations matter," Working Paper 2003-18, Federal Reserve Bank of Atlanta.
  11. Preston, Bruce, 2008. "Adaptive learning and the use of forecasts in monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3661-3681, November.
  12. Preston, Bruce, 2006. "Adaptive learning, forecast-based instrument rules and monetary policy," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 507-535, April.
  13. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
  14. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
  15. Frank Smets & Raf Wouters, 2004. "Forecasting with a Bayesian DSGE Model: An Application to the Euro Area," Journal of Common Market Studies, Wiley Blackwell, vol. 42(4), pages 841-867, November.
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Citations

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Cited by:
  1. 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.
  2. Harrison, Richard & Taylor, Tim, 2012. "Misperceptions, heterogeneous expectations and macroeconomic dynamics," Bank of England working papers 449, Bank of England.
  3. 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.
  4. Milani, Fabio, 2011. "The impact of foreign stock markets on macroeconomic dynamics in open economies: A structural estimation," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 111-129, February.
  5. Slobodyan, Sergey & Wouters, Raf, 2012. "Learning in an estimated medium-scale DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 26-46.
  6. Fazzari, Steven M. & Ferri, Piero & Greenberg, Edward, 2010. "Investment and the Taylor rule in a dynamic Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2010-2022, October.
  7. John M. Roberts, 2007. "Learning, Sticky Inflation, and the Sacrifice Ratio," Kiel Working Papers 1365, Kiel Institute for the World Economy.
  8. Bask, Mikael & Selander, Carina, 2007. "Robust Taylor rules in an open economy with heterogeneous expectations and least squares learning," Research Discussion Papers 6/2007, Bank of Finland.
  9. Krisztina Molnár & Sergio Santoro, 2010. "Optimal Monetary Policy when Agents are Learning," CESifo Working Paper Series 3072, CESifo Group Munich.
  10. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
  11. Milani, Fabio, 2009. "Expectations, learning, and the changing relationship between oil prices and the macroeconomy," Energy Economics, Elsevier, vol. 31(6), pages 827-837, November.
  12. Claudio Borio & Piti Disyatat & Mikael Juselius, 2014. "A parsimonious approach to incorporating economic information in measures of potential output," BIS Working Papers 442, Bank for International Settlements.
  13. Chevillon, Guillaume & Massmann, Michael & Mavroeidis, Sophocles, 2010. "Inference in models with adaptive learning," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 341-351, April.

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