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Man-bites-dog business cycles

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Abstract

The newsworthiness of an event is partly determined by how unusual it is and this paper investigates the business cycle implications of this fact. In particular, we analyze the consequences of information structures in which some types of signals are more likely to be observed after unusual events. Such signals may increase both uncertainty and disagreement among agents and when embedded in a simple business cycle model, can help us understand why we observe (i) occasional large changes in macro economic aggregate variables without a correspondingly large change in underlying fundamentals (ii) persistent periods of high macroeconomic volatility and (iii) a positive correlation between absolute changes in macro variables and the cross-sectional dispersion of expectations as measured by survey data. These results are consequences of optimal updating by agents when the availability of some signals is positively correlated with tail-events. The model is estimated by likelihood based methods using individual survey responses and a quarterly time series of total factor productivity along with standard aggregate time series. The estimated model suggests that there have been episodes in recent US history when the impact on output of innovations to productivity of a given magnitude was more than eight times as large compared to other times.

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Bibliographic Info

Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1341.

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Date of creation: Dec 2011
Date of revision: Dec 2013
Handle: RePEc:upf:upfgen:1341

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Web page: http://www.econ.upf.edu/

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  1. Author-Name: Alan S. Blinder & Alan B. Krueger, 2004. "What Does the Public Know about Economic Policy, and How Does It Know It?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 35(1), pages 327-397.
  2. Olivier Coibion & Yuriy Gorodnichenko, 2010. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," NBER Working Papers 16537, National Bureau of Economic Research, Inc.
  3. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649 Elsevier.
  4. Kristoffer Nimark, 2007. "Dynamic Higher Order Expectations," 2007 Meeting Papers 542, Society for Economic Dynamics.
  5. Townsend, Robert M, 1983. "Forecasting the Forecasts of Others," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 546-88, August.
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  7. Nir Jaimovich & Sergio Rebelo, 2006. "Can News About the Future Drive the Business Cycle?," NBER Working Papers 12537, National Bureau of Economic Research, Inc.
  8. Graham, Liam & Wright, Stephen, 2010. "Information, heterogeneity and market incompleteness," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 164-174, March.
  9. Ruediger Bachmann & Giuseppe Moscarini, 2011. "Business Cycles and Endogenous Uncertainty," 2011 Meeting Papers 36, Society for Economic Dynamics.
  10. N. Gregory Mankiw & Ricardo Reis, 2001. "Sticky information versus sticky prices: a proposal to replace the New-Keynesian Phillips curve," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
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  16. Bhar, Ramaprasad & Hamori, Shigeyuki, 2003. "Alternative characterization of the volatility in the growth rate of real GDP," Japan and the World Economy, Elsevier, vol. 15(2), pages 223-231, April.
  17. Leonardo Melosi, 2011. "Public's Inflation Expectations and Monetary Policy," 2011 Meeting Papers 1151, Society for Economic Dynamics.
  18. Guido Lorenzoni, 2006. "A Theory of Demand Shocks," NBER Working Papers 12477, National Bureau of Economic Research, Inc.
  19. George-Marios Angeletos & Jennifer La'O, 2009. "Incomplete Information, Higher-Order Beliefs and Price Inertia," NBER Working Papers 15003, National Bureau of Economic Research, Inc.
  20. Péter Kondor, 2012. "The More We Know about the Fundamental, the Less We Agree on the Price," Review of Economic Studies, Oxford University Press, vol. 79(3), pages 1175-1207.
  21. Nimark, Kristoffer, 2008. "Dynamic pricing and imperfect common knowledge," Journal of Monetary Economics, Elsevier, vol. 55(2), pages 365-382, March.
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  1. Yes, there is a confidence fairy
    by chris dillow in Stumbling and Mumbling on 2014-06-21 12:58:14
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Cited by:
  1. Leonardo Melosi, 2013. "Signaling Effects of Monetary Policy," PIER Working Paper Archive 13-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  2. Laura Veldkamp & Anna Orlik, 2013. "Understanding Uncertainty Shocks," 2013 Meeting Papers 391, Society for Economic Dynamics.
  3. Beaudry, Paul & Portier, Franck, 2013. "News Driven Business Cycles: Insights and Challenges," CEPR Discussion Papers 9624, C.E.P.R. Discussion Papers.

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