IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Learning and judgment shocks in U.S. business cycles

  • Murray, James
Registered author(s):

    This paper examines the role of judgment shocks in combination with other structural shocks in explaining post-war economic volatility within the context of a New Keynesian model. Agents form expectations using constant gain learning then augment these forecasts with judgment. These judgments may be interpreted as a reaction to current news stories or policy announcements that would influence people's expectations. I allow for the possibility that these judgments be informatively based on information about structural shocks, but judgment itself may also be subject to its own stochastic shocks. I estimate a standard New Keynesian model that includes these shocks using Bayesian simulation methods. To aid in identifying expectational shocks from other structural shocks I include data on professional forecasts along with data on output gap, inflation, and interest rates. I find judgment is largely not informed by macroeconomic fundamentals; most of the variability in judgment is explained by its own stochastic shocks. Impulse response functions from the estimated model illustrate how shocks to judgment destabilize the economy and explain business cycle fluctuations.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://mpra.ub.uni-muenchen.de/29257/1/MPRA_paper_29257.pdf
    File Function: original version
    Download Restriction: no

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 29257.

    as
    in new window

    Length:
    Date of creation: 02 Mar 2011
    Date of revision:
    Handle: RePEc:pra:mprapa:29257
    Contact details of provider: Postal: Schackstr. 4, D-80539 Munich, Germany
    Phone: +49-(0)89-2180-2219
    Fax: +49-(0)89-2180-3900
    Web page: http://mpra.ub.uni-muenchen.de

    More information through EDIRC

    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.:

    as in new window
    1. James Bullard & George W. Evans & Seppo Honkapohja, 2009. "A Model of Near-Rational Exuberance," CDMA Working Paper Series 200902, Centre for Dynamic Macroeconomic Analysis.
    2. Thomas Lubik & Frank Schorfheide, 2002. "Testing for Indeterminacy:An Application to U.S. Monetary Policy," Economics Working Paper Archive 480, The Johns Hopkins University,Department of Economics, revised Jun 2003.
    3. Smets, Frank & Wouters, Rafael, 2004. "Comparing Shocks and Frictions in US and Euro Area Business Cycles: A Bayesian DSGE Approach," CEPR Discussion Papers 4750, C.E.P.R. Discussion Papers.
    4. George W. Evans & Seppo Honkapohja, 2004. "Adaptive learning and monetary policy design," Macroeconomics 0405008, EconWPA.
    5. Athanasios Orphanides & John C. Williams, 2003. "Inflation scares and forecast-based monetary policy," Working Paper 2003-21, Federal Reserve Bank of Atlanta.
    6. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    7. Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 0722, European Central Bank.
    8. Reifschneider, David L. & Stockton, David J. & Wilcox, David W., 1997. "Econometric models and the monetary policy process," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 1-37, December.
    9. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2006. "Adaptive Learning in Practice," CEPR Discussion Papers 5627, C.E.P.R. Discussion Papers.
    10. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    11. Julio Rotemberg & Michael Woodford, 1997. "An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 297-361 National Bureau of Economic Research, Inc.
    12. Kaushik Mitra & James Bullard, 2004. "Determinacy, Learnability, and Monetary Policy Inertia," Royal Holloway, University of London: Discussion Papers in Economics 04/14, Department of Economics, Royal Holloway University of London, revised Jul 2004.
    13. Marc P. Giannoni & Michael Woodford, 2003. "Optimal Inflation Targeting Rules," NBER Working Papers 9939, National Bureau of Economic Research, Inc.
    14. James Bullard & Stefano Eusepi, 2003. "Did the Great Inflation Occur Despite Policymaker Commitment to a Taylor Rule?," Computing in Economics and Finance 2003 129, Society for Computational Economics.
    15. James B. Bullard & Aarti Singh, 2009. "Learning and the Great Moderation," Working Papers 2007-027, Federal Reserve Bank of St. Louis.
    16. Peter N. Ireland, 2002. "Technology Shocks in the New Keynesian Model," Boston College Working Papers in Economics 536, Boston College Department of Economics.
    17. 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.
    18. James Bullard & Kaushik Mitra, 2002. "Learning about monetary policy rules," Working Papers 2000-001, Federal Reserve Bank of St. Louis.
    19. Kim, Insu & Kim, Minsoo, 2009. "Irrational Bias in Inflation Forecasts," MPRA Paper 16447, University Library of Munich, Germany.
    20. Evans, George W. & Honkapohja, Seppo, 2001. "Expectations and the Stability Problem for Optimal Monetary Policies," CEPR Discussion Papers 2805, C.E.P.R. Discussion Papers.
    21. 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.
    22. McCallum, Bennett T., 1999. "Issues in the design of monetary policy rules," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 23, pages 1483-1530 Elsevier.
    23. James M. Nason & Gregor W. Smith, 2005. "Identifying the New Keynesian Phillips curve," Working Paper 2005-01, Federal Reserve Bank of Atlanta.
    24. Rotemberg, Julio J, 1982. "Sticky Prices in the United States," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1187-1211, December.
    25. James Bullard & George W. Evans & Seppo Honkapohja, 2008. "Monetary Policy, Judgment, and Near-Rational Exuberance," American Economic Review, American Economic Association, vol. 98(3), pages 1163-77, June.
    26. Jeffrey C. Fuhrer, 2000. "Habit Formation in Consumption and Its Implications for Monetary-Policy Models," American Economic Review, American Economic Association, vol. 90(3), pages 367-390, June.
    27. Roberts, John M, 1995. "New Keynesian Economics and the Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 975-84, November.
    28. Sergey Slobodyan & Raf Wouters, 2009. "Learning in an Estimated Medium-Scale DSGE Model," CERGE-EI Working Papers wp396, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    29. Milani, Fabio, 2008. "Learning, monetary policy rules, and macroeconomic stability," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3148-3165, October.
    30. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    31. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-22, December.
    32. Giorgio Primiceri, 2005. "Why Inflation Rose and Fell: Policymakers' Beliefs and US Postwar Stabilization Policy," NBER Working Papers 11147, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:29257. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.