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

  • Milani, Fabio

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 to be a crucial determinant of inflation inertia.

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File URL: http://mpra.ub.uni-muenchen.de/809/1/MPRA_paper_809.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 809.

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Date of creation: 28 Jun 2006
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Publication status: Published in International Journal of Central Banking Number 3.Volume(2006): pp. 87-106
Handle: RePEc:pra:mprapa:809
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  1. Athanasios Orphanides & John C. Williams, 2002. "Imperfect knowledge, inflation expectations, and monetary policy," Working Paper Series 2002-04, Federal Reserve Bank of San Francisco.
  2. Frank Smets & Raf Wouters, 2004. "Comparing shocks and frictions in US and euro area business cycles: a Bayesian DSGE approach," Working Paper Research 61, National Bank of Belgium.
  3. Frank Smets & Raf Wouters, 2004. "Forecasting with a Bayesian DSGE Model: an application to the euro area," Working Paper Research 60, National Bank of Belgium.
  4. Jean Boivin & Marc P. Giannoni, 2003. "Has Monetary Policy Become More Effective?," NBER Working Papers 9459, National Bureau of Economic Research, Inc.
  5. Athanasios Orphanides & John C. Williams, 2005. "Inflation scares and forecast-based monetary policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 498-527, April.
  6. Preston, Bruce, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," MPRA Paper 830, University Library of Munich, Germany.
  7. Marc P. Giannoni & Michael Woodford, 2003. "Optimal Inflation Targeting Rules," NBER Working Papers 9939, National Bureau of Economic Research, Inc.
  8. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
  9. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
  10. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
  11. Preston, Bruce, 2006. "Adaptive learning, forecast-based instrument rules and monetary policy," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 507-535, April.
  12. Milani, Fabio, 2008. "Learning, monetary policy rules, and macroeconomic stability," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3148-3165, October.
  13. An, Sungbae & Schorfheide, Frank, 2005. "Bayesian Analysis of DSGE Models," CEPR Discussion Papers 5207, C.E.P.R. Discussion Papers.
  14. Seppo Honkapohja & Kaushik Mitra & George W. Evans, 2011. "Notes on Agents¡¯ Behavioral Rules Under Adaptive Learning and Studies of Monetary Policy," CDMA Working Paper Series 201102, Centre for Dynamic Macroeconomic Analysis.
  15. 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.
  16. 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.
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