IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/7743.html
   My bibliography  Save this paper

Expectation Shocks and Learning as Drivers of the Business Cycle

Author

Listed:
  • Milani, Fabio

Abstract

Psychological factors, market sentiments, and shifts in beliefs are believed by many to play a nontrivial role in inducing and amplifying economic fluctuations. Yet, these forces are rarely considered in macroeconomic models. This paper provides an attempt to evaluate the empirical role of expectational shocks on business cycle fluctuations. The paper relaxes the conventional assumption of rational expectations to exploit observed data on survey and market expectations in the estimation of a benchmark New Keynesian model. The observed expectations are modeled as formed from a near-rational expectation formation mechanism, which assumes that economic agents use a linear perceived law of motion for economic variables that has the same structural form as the model solution under rational expectations and that they need to learn model coefficients over time. In addition to the typical structural demand, supply, and policy disturbances, the model incorporates expectation shocks, which affect the formation of expectations by the private sector. Both the best-fitting learning process and the expectations shocks are identified from the expectations data and from the interaction between expectations and realized data. The expectations shocks capture waves of optimism and pessimism that lead agents to form forecasts that deviate from those implied by their learning model and by the state of the economy. The empirical results uncover a crucial role for these novel expectations shocks as a major driving force of the U.S. business cycle. Expectation shocks regarding future real activity are the main source of economic fluctuations, since they can account for roughly half of business cycle fluctuations.

Suggested Citation

  • Milani, Fabio, 2010. "Expectation Shocks and Learning as Drivers of the Business Cycle," CEPR Discussion Papers 7743, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7743
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP7743
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stephanie Schmitt‐Grohé & Martín Uribe, 2012. "What's News in Business Cycles," Econometrica, Econometric Society, vol. 80(6), pages 2733-2764, November.
    2. 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.
    3. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    4. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    5. 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.
    6. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    7. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    8. James Bullard & George Evans, 2004. "Near-Rational Exuberance," 2004 Meeting Papers 465, Society for Economic Dynamics.
    9. 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.
    10. Preston, Bruce, 2006. "Adaptive learning, forecast-based instrument rules and monetary policy," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 507-535, April.
    11. Adam, Klaus, 2005. "Learning To Forecast And Cyclical Behavior Of Output And Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 9(1), pages 1-27, February.
    12. Hall, Robert E, 1988. "Intertemporal Substitution in Consumption," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 339-357, April.
    13. 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.
    14. 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.
    15. 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.
    16. Woodford, Michael, 1990. "Learning to Believe in Sunspots," Econometrica, Econometric Society, vol. 58(2), pages 277-307, March.
    17. Milani, Fabio, 2008. "Learning, monetary policy rules, and macroeconomic stability," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3148-3165, October.
    18. Cass, David & Shell, Karl, 1983. "Do Sunspots Matter?," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 193-227, April.
    19. Milani, Fabio, 2014. "Learning and time-varying macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 94-114.
    20. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    21. Jonathan Gruber, 2006. "A Tax-Based Estimate of the Elasticity of Intertemporal Substitution," NBER Working Papers 11945, National Bureau of Economic Research, Inc.
    22. Benhabib, Jess & Farmer, Roger E.A., 1999. "Indeterminacy and sunspots in macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 6, pages 387-448, Elsevier.
    23. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    24. Farmer, Roger E. A. & Jang-Ting, Guo, 1995. "The econometrics of indeterminacy: an applied study," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 43(1), pages 225-271, December.
    25. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    26. Woodford, Michael, 1986. "Stationary sunspot equilibria in a finance constrained economy," Journal of Economic Theory, Elsevier, vol. 40(1), pages 128-137, October.
    27. Farmer, Roger E.A. & Woodford, Michael, 1997. "Self-Fulfilling Prophecies And The Business Cycle," Macroeconomic Dynamics, Cambridge University Press, vol. 1(4), pages 740-769, December.
    28. 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.
    29. 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. Fabio Milani, 2012. "The Modeling of Expectations in Empirical DSGE Models: A Survey," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 3-38, Emerald Group Publishing Limited.
    2. Stephen J. Cole, 2021. "Learning and the Effectiveness of Central Bank Forward Guidance," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 157-200, February.
    3. 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.
    4. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    5. Fabio Milani, 2006. "A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
    6. Milani, Fabio, 2017. "Sentiment and the U.S. business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 289-311.
    7. Hürtgen, Patrick, 2014. "Consumer misperceptions, uncertain fundamentals, and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 279-292.
    8. Stephen J. Cole, 2020. "The Limits of Central Bank forward Guidance under Learning," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 199-250, September.
    9. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    10. Fabio Milani & Ashish Rajbhandari, 2012. "Expectation Formation and Monetary DSGE Models: Beyond the Rational Expectations Paradigm," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 253-288, Emerald Group Publishing Limited.
    11. Kyle Jurado, 2016. "Advance Information and Distorted Beliefs in Macroeconomic and Financial Fluctuations," 2016 Meeting Papers 154, Society for Economic Dynamics.
    12. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    13. Greta Meggiorini & Fabio Milani, 2021. "Behavioral New Keynesian Models: Learning vs. Cognitive Discounting," CESifo Working Paper Series 9039, CESifo.
    14. Vázquez, Jesús & Aguilar, Pablo, 2021. "Adaptive learning with term structure information," European Economic Review, Elsevier, vol. 134(C).
    15. Fabio Milani & John Treadwell, 2012. "The Effects of Monetary Policy “News” and “Surprises”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1667-1692, December.
    16. Aguilar, Pablo & Vázquez, Jesús, 2021. "An Estimated Dsge Model With Learning Based On Term Structure Information," Macroeconomic Dynamics, Cambridge University Press, vol. 25(7), pages 1635-1665, October.
    17. George‐Marios Angeletos & Fabrice Collard & Harris Dellas, 2018. "Quantifying Confidence," Econometrica, Econometric Society, vol. 86(5), pages 1689-1726, September.
    18. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    19. Gáti, Laura, 2023. "Monetary policy & anchored expectations—An endogenous gain learning model," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 37-47.
    20. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.

    More about this item

    Keywords

    Expectation formation; Constant-gain learning; Dsge estimation with survey expectations; Behavioral explanations of the business cycle; Waves of optimism and pessimism; Expectation shocks;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    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:cpr:ceprdp:7743. 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    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.