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Expectation Shocks and Learning as Drivers of the Business Cycle

  • Fabio Milani

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.

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Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 121 (2011)
Issue (Month): 552 (05)
Pages: 379-401

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Handle: RePEc:ecj:econjl:v:121:y:2011:i:552:p:379-401
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  1. James Bullard & George Evans, 2004. "Near-Rational Exuberance," 2004 Meeting Papers 465, Society for Economic Dynamics.
  2. Adam, Klaus, 2003. "Learning to Forecast and Cyclical Behavior of Output and Inflation," CFS Working Paper Series 2003/01, Center for Financial Studies (CFS).
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  6. Roger E.A. Farmer, 1994. "The Econometrics of Indeterminacy: An Applied Study," UCLA Economics Working Papers 720, UCLA Department of Economics.
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  9. Preston, Bruce, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," MPRA Paper 830, University Library of Munich, Germany.
  10. 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.
  11. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
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  14. 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.
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