IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/809.html
   My bibliography  Save this paper

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

Author

Listed:
  • Milani, Fabio

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 to be a crucial determinant of inflation inertia.

Suggested Citation

  • Milani, Fabio, 2006. "A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?," MPRA Paper 809, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:809
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/809/1/MPRA_paper_809.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bullard, James & Mitra, Kaushik, 2002. "Learning about monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1105-1129, September.
    2. Frank Smets & Raf Wouters, 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.
    3. Orphanides, Athanasios & Williams, John C., 2005. "The decline of activist stabilization policy: Natural rate misperceptions, learning, and expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1927-1950, November.
    4. Preston, Bruce, 2006. "Adaptive learning, forecast-based instrument rules and monetary policy," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 507-535, April.
    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. Bruce Preston, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    7. 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.
    8. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    9. Milani, Fabio, 2008. "Learning, monetary policy rules, and macroeconomic stability," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3148-3165, October.
    10. Athanasios Orphanides & John Williams, 2004. "Imperfect Knowledge, Inflation Expectations, and Monetary Policy," NBER Chapters, in: The Inflation-Targeting Debate, National Bureau of Economic Research, Inc.
    11. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
    12. 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.
    13. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
    14. Honkapohja, Seppo & Mitra, Kaushik & Evans, George W., 2011. "Notes on Agents’ Behavioral Rules Under Adaptive Learning and Studies of Monetary Policy," SIRE Discussion Papers 2011-04, Scottish Institute for Research in Economics (SIRE).
    15. 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.
    16. 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.
    17. 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.
    18. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    19. 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.
    20. Marc Giannoni & Michael Woodford, 2004. "Optimal Inflation-Targeting Rules," NBER Chapters, in: The Inflation-Targeting Debate, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    2. Milani, Fabio, 2008. "Learning, monetary policy rules, and macroeconomic stability," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3148-3165, October.
    3. Fabio Milani, 2005. "Adaptive Learning and Inflation Persistence," Working Papers 050607, University of California-Irvine, Department of Economics.
    4. 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.
    5. Cars Hommes & Kostas Mavromatis & Tolga Ozden & Mei Zhu, 2019. "Behavioral learning equilibria in the New Keynesian model," DNB Working Papers 654, Netherlands Central Bank, Research Department.
    6. Fabio Milani, 2011. "Expectation Shocks and Learning as Drivers of the Business Cycle," Economic Journal, Royal Economic Society, vol. 121(552), pages 379-401, May.
    7. Mele, Antonio & Molnár, Krisztina & Santoro, Sergio, 2020. "On the perils of stabilizing prices when agents are learning," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 339-353.
    8. George W. Evans & Seppo Honkapohja, 2009. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 2, pages 027-076, Central Bank of Chile.
    9. Murray, James, 2011. "Learning and judgment shocks in U.S. business cycles," MPRA Paper 29257, University Library of Munich, Germany.
    10. George W. Evans & Seppo Honkapohja, 2009. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 2, pages 027-076, Central Bank of Chile.
    11. Thorvardur Tjörvi Ólafsson, 2006. "The New Keynesian Phillips Curve: In Search of Improvements and Adaptation to the Open Economy," Economics wp31_tjorvi, Department of Economics, Central bank of Iceland.
    12. Hommes, C.H. & Zhu, M., 2016. "Behavioral Learning Equilibria, Persistence Amplification & Monetary Policy," CeNDEF Working Papers 16-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    13. Cars Hommes & Kostas Mavromatis & Tolga Özden & Mei Zhu, 2023. "Behavioral learning equilibria in New Keynesian models," Quantitative Economics, Econometric Society, vol. 14(4), pages 1401-1445, November.
    14. repec:bla:jcmkts:v:47:y:2009:i::p:579-599 is not listed on IDEAS
    15. Ascari, Guido & Florio, Anna & Gobbi, Alessandro, 2017. "Transparency, expectations anchoring and inflation target," European Economic Review, Elsevier, vol. 91(C), pages 261-273.
    16. Fabio Milani, 2009. "Adaptive Learning and Macroeconomic Inertia in the Euro Area," Journal of Common Market Studies, Wiley Blackwell, vol. 47(3), pages 579-599, June.
    17. Raf Wouters & Sergey Slobodyan, 2009. "Estimating a medium–scale DSGE model with expectations based on small forecasting models," 2009 Meeting Papers 654, Society for Economic Dynamics.
    18. Lombardi, Marco J. & Sgherri, Silvia, 2007. "(Un)naturally low? Sequential Monte Carlo tracking of the US natural interest rate," Working Paper Series 794, European Central Bank.
    19. Lombardi, Marco J. & Sgherri, Silvia, 2007. "(Un)naturally low? Sequential Monte Carlo tracking of the US natural interest rate," Working Paper Series 794, European Central Bank.
    20. repec:zbw:bofrdp:2007_032 is not listed on IDEAS
    21. Gelfer, Sacha, 2020. "The effects of professional forecast dissemination on macroeconomic volatility," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 131-156.
    22. Vitor Gaspar & Frank Smets & David Vestin, 2006. "Optimal Monetary Policy under Adaptive Learning," Computing in Economics and Finance 2006 183, Society for Computational Economics.

    More about this item

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G0 - Financial Economics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:809. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.