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News, Noise, and Fluctuations: An Empirical Exploration

  • Olivier J. Blanchard
  • Jean-Paul L'Huillier
  • Guido Lorenzoni

We explore empirically models of aggregate fluctuations in which consumers form anticipations about the future based on noisy sources of information and these anticipations affect output in the short run. Our objective is to separate fluctuations due to changes in fundamentals (news) from those due to temporary errors in agents' estimates (noise). We show that structural VARs cannot be used to identify news and noise shocks, but identification is possible via a method of moments or maximum likelihood. Next, we estimate our model on US data. Our results suggest that noise shocks explain a sizable fraction of short-run consumption fluctuations.

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Article provided by American Economic Association in its journal American Economic Review.

Volume (Year): 103 (2013)
Issue (Month): 7 (December)
Pages: 3045-3070

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Handle: RePEc:aea:aecrev:v:103:y:2013:i:7:p:3045-70
Note: DOI: 10.1257/aer.103.7.3045
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  7. Danny Quah, 1991. "The Relative Importance of Permanent and Transitory Components: Identification and Some Theoretical Bounds," FMG Discussion Papers dp126, Financial Markets Group.
  8. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2009. "Fiscal Foresight and Information Flows," NBER Working Papers 14630, National Bureau of Economic Research, Inc.
  9. Lippi, Francesco & Neri, Stefano, 2003. "Information Variables for Monetary Policy in a Small Structural Model of the Euro Area," CEPR Discussion Papers 4125, C.E.P.R. Discussion Papers.
  10. Nir Jaimovich & Sergio Rebelo, 2006. "Can News About the Future Drive the Business Cycle?," NBER Working Papers 12537, National Bureau of Economic Research, Inc.
  11. Emine Boz & Christian Daude & C. Bora Durdu, 2011. "Emerging Market Business Cycles Revisited: Learning about the Trend," Koç University-TUSIAD Economic Research Forum Working Papers 1110, Koc University-TUSIAD Economic Research Forum.
  12. Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996. "Mechanics of forming and estimating dynamic linear economies," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 4, pages 171-252 Elsevier.
  13. Guido Lorenzoni, 2011. "News and Aggregate Demand Shocks," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 537-557, 09.
  14. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
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  16. Quah, Danny, 1990. "Permanent and Transitory Movements in Labor Income: An Explanation for "Excess Smoothness" in Consumption," Journal of Political Economy, University of Chicago Press, vol. 98(3), pages 449-475, June.
  17. Christopher A. Sims & Tao Zha, 1998. "Does monetary policy generate recessions?," FRB Atlanta Working Paper 98-12, Federal Reserve Bank of Atlanta.
  18. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2011. "Foresight and Information Flows," NBER Working Papers 16951, National Bureau of Economic Research, Inc.
  19. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
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  21. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-77, June.
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