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News or Noise? The Missing Link

Author

Listed:
  • Ryan Chahrour

    (Boston College)

  • Kyle Jurado

    (Duke University)

Abstract
The macroeconomic literature on belief-driven business cycles treats news and noise as distinct representations of people's beliefs about economic fundamentals. We prove that these two representations are actually observationally equivalent. This means that the decision to use one representation or the other must be made on theoretical, and not empirical, grounds. Our result allows us to determine the importance of beliefs as an independent source of fluctuations. Using three prominent models from this literature, we show that existing research has understated the importance of independent shocks to beliefs. This is because representations with anticipated and unanticipated shocks mix the fluctuations due independently to beliefs with the fluctuations due to fundamentals. We also argue that the observational equivalence of news and noise representations implies that structural vector auto-regression analysis is equally appropriate for recovering both news and noise shocks.

Suggested Citation

  • Ryan Chahrour & Kyle Jurado, 2016. "News or Noise? The Missing Link," Boston College Working Papers in Economics 917, Boston College Department of Economics, revised 02 Nov 2017.
    • Handle: RePEc:boc:bocoec:917
    as

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    References listed on IDEAS

    as
    1. Stephanie Schmitt‐Grohé & Martín Uribe, 2012. "What's News in Business Cycles," Econometrica, Econometric Society, vol. 80(6), pages 2733-2764, November.
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    5. Guido Lorenzoni, 2011. "News and Aggregate Demand Shocks," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 537-557, September.
    6. Born, Benjamin & Peter, Alexandra & Pfeifer, Johannes, 2013. "Fiscal news and macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2582-2601.
    7. Andr? Kurmann & Christopher Otrok, 2013. "News Shocks and the Slope of the Term Structure of Interest Rates," American Economic Review, American Economic Association, vol. 103(6), pages 2612-2632, October.
    8. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
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    14. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noisy News in Business Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 122-152, October.
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    16. Ryo Jinnai, 2014. "R&D Shocks and News Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1457-1478, October.
    17. 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 1343-1377, June.
    18. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2014. "Risk Shocks," American Economic Review, American Economic Association, vol. 104(1), pages 27-65, January.
    19. James D. Hamilton, 2017. "Why You Should Never Use the Hodrick-Prescott Filter," NBER Working Papers 23429, National Bureau of Economic Research, Inc.
    20. Robert B. Barsky & Susanto Basu & Keyoung Lee, 2015. "Whither News Shocks?," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 225-264.
    21. Sims, Eric, 2016. "What׳s news in News? A cautionary note on using a variance decomposition to assess the quantitative importance of news shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 41-60.
    22. Paul Beaudry & Bernd Lucke, 2010. "Letting Different Views about Business Cycles Compete," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 413-455, National Bureau of Economic Research, Inc.
    23. Chris Woolston, 2014. "Rice," Nature, Nature, vol. 514(7524), pages 49-49, October.
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    More about this item

    Keywords

    News; noise; business cycles; structural vector autoregression;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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