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Do mood swings drive business cycles and is it rational?

  • Paul Beaudry
  • Deokwoo Nam
  • Jian Wang

This paper provides new evidence in support of the idea that bouts of optimism and pessimism drive much of US business cycles. In particular, we begin by using sign-restriction based identification schemes to isolate innovations in optimism or pessimism and we document the extent to which such episodes explain macroeconomic fluctuations. We then examine the link between these identified mood shocks and subsequent developments in fundamentals using alternative identification schemes (i.e., variants of the maximum forecast error variance approach).> ; We find that there is a very close link between the two, suggesting that agents' feelings of optimism and pessimism are at least partially rational as total factor productivity (TFP) is observed to rise 8–10 quarters after an initial bout of optimism. While this later finding is consistent with some previous findings in the news shock literature, we cannot rule out that such episodes reflect self-fulfilling beliefs. Overall, we argue that mood swings account for over 50 percent of business-cycle fluctuations in hours and output.

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File URL: http://www.dallasfed.org/assets/documents/institute/wpapers/2011/0098.pdf
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Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 98.

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Date of creation: 2011
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Handle: RePEc:fip:feddgw:98
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  1. Mountford, A.W. & Uhlig, H.F.H.V.S., 2002. "What are the Effects of Fiscal Policy Shocks?," Discussion Paper 2002-31, Tilburg University, Center for Economic Research.
  2. Benhabib Jess & Farmer Roger E. A., 1994. "Indeterminacy and Increasing Returns," Journal of Economic Theory, Elsevier, vol. 63(1), pages 19-41, June.
  3. G. Peersman & R. Straub, 2005. "Technology Shocks and Robust Sign Restrictions in a Euro Area SVAR," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/288, Ghent University, Faculty of Economics and Business Administration.
  4. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 638-647, October.
  5. Martial Dupaigne & Franck Portier & Paul Beaudry, 2007. "The International Propagation of News Shocks," 2007 Meeting Papers 251, Society for Economic Dynamics.
  6. Robert B. Barsky & Eric R. Sims, 2009. "News Shocks," NBER Working Papers 15312, National Bureau of Economic Research, Inc.
  7. Farmer Roger E. A. & Guo Jang-Ting, 1994. "Real Business Cycles and the Animal Spirits Hypothesis," Journal of Economic Theory, Elsevier, vol. 63(1), pages 42-72, June.
  8. Deokwoo Nam & Jian Wang, 2010. "Understanding the effect of productivity changes on international relative prices: the role of news shocks," Globalization and Monetary Policy Institute Working Paper 61, Federal Reserve Bank of Dallas.
  9. Enders, Zeno & Müller, Gernot J. & Scholl, Almuth, 2011. "How do fiscal and technology shocks affect real exchange rates?: New evidence for the United States," Journal of International Economics, Elsevier, vol. 83(1), pages 53-69, January.
  10. Paul Beaudry & Bernd Lucke, 2009. "Letting Different Views about Business Cycles Compete," NBER Working Papers 14950, National Bureau of Economic Research, Inc.
  11. George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
  12. Deokwoo Nam & Jian Wang, 2010. "The effects of news about future productivity on international relative prices: an empirical investigation," Globalization and Monetary Policy Institute Working Paper 64, Federal Reserve Bank of Dallas.
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