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Expectations, Learning and Business Cycle Fluctuations

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Author Info
Stefano Eusepi
Bruce Preston

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Abstract

This paper develops a theory of expectations-driven business cycles based on learning. Agents have incomplete knowledge about how market prices are determined and shifts in expectations of future prices affect dynamics. In a real business cycle model, the theoretical framework amplifies and propagates technology shocks. Improved correspondence with data arises from dynamics in beliefs being themselves persistent and because they generate strong intertemporal substitution effects in consumption and leisure. Output volatility is comparable with a rational expectations analysis with a standard deviation of technology shock that is 20 percent smaller, and has substantially more volatility in investment and hours. Persistence in these series is captured, unlike in standard models. Inherited from real business cycle theory, the benchmark model suffers a comovement problem between consumption, hours, output and investment. An augmented model that is consistent with expectations-driven business cycles, in the sense of Beaudry and Portier (2006), resolves these counterfactual predictions.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14181.

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Date of creation: Jul 2008
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Handle: RePEc:nbr:nberwo:14181

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Find related papers by JEL classification:
D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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References listed on IDEAS
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  2. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May. [Downloadable!] (restricted)
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Cited by:
(explanations, 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.)

  1. Kevin X.D. Huang & Zheng Liu & Tao Zha, 2008. "Learning, adaptive expectations, and technology shocks," Working Paper 2008-20, Federal Reserve Bank of Atlanta. [Downloadable!]
    Other versions:
  2. George W. Evans & Seppo Honkapohja, 2008. "Learning and Macroeconomics," University of Oregon Economics Department Working Papers 2008-3, University of Oregon Economics Department. [Downloadable!]
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