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News shocks and Business cycles: Evidence from forecast data

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  • Thuy Lan Nguyen

    (Columbia University)

  • Wataru Miyamoto

    (Columbia University)

Abstract

This paper proposes the use of data on expectations to identify the role of news shocks in business cycles. This approach exploits the fact that news shocks cause agents to adjust their expectations about the future even when current fundamentals are not affected, therefore, data on expectations are particularly informative about the role of news shocks. Using data on expectations, we estimate a dynamic, stochastic, general equilibrium model that incorporates news shocks for the U.S. between 1955Q1 and 2006Q4. We find that the contribution of news shocks to output is about half of that estimated without data on expectations. The precision of the estimated role of news shocks also greatly improves when data on expectations are used. Moreover, the contribution of news shocks to explaining short run fluctuations is negligible. These results arise because data on expectations show that changes in expectations are not large and do not resemble actual movements of output. Therefore, news shocks cannot be the main driver of business cycles.

Suggested Citation

  • Thuy Lan Nguyen & Wataru Miyamoto, 2014. "News shocks and Business cycles: Evidence from forecast data," 2014 Meeting Papers 259, Society for Economic Dynamics.
    • Handle: RePEc:red:sed014:259
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    References listed on IDEAS

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    Cited by:

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    2. Clements, Michael P. & Galvão, Ana Beatriz, 2021. "Measuring the effects of expectations shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
    3. Kyle Jurado, 2016. "Advance Information and Distorted Beliefs in Macroeconomic and Financial Fluctuations," 2016 Meeting Papers 154, Society for Economic Dynamics.
    4. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    5. Iskrev, Nikolay, 2018. "Are asset price data informative about news shocks? A DSGE perspective," Working Paper Series 2161, European Central Bank.
    6. Deokwoo Nam & Jian Wang, 2019. "Mood Swings and Business Cycles: Evidence from Sign Restrictions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(6), pages 1623-1649, September.
    7. Renato Faccini & Leonardo Melosi, 2022. "Pigouvian Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 281-318, April.
    8. Iskrev, Nikolay, 2019. "On the sources of information about latent variables in DSGE models," European Economic Review, Elsevier, vol. 119(C), pages 318-332.
    9. Ansgar Belke & Steffen Elstner & Svetlana Rujin, 2022. "Growth Prospects and the Trade Balance in Advanced Economies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1209-1234, October.
    10. Renato Faccini & Leonardo Melosi, 2018. "The Role of News about TFP in U.S. Recessions and Booms," Working Paper Series WP-2018-6, Federal Reserve Bank of Chicago.
    11. D’Amico, Stefania & King, Thomas B., 2023. "What does anticipated monetary policy do?," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 123-139.
    12. Yasuo Hirose & Takushi Kurozumi, 2017. "Changes in the Federal Reserve Communication Strategy: A Structural Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(1), pages 171-185, February.
    13. Hirose, Yasuo & Kurozumi, Takushi, 2021. "Identifying News Shocks With Forecast Data," Macroeconomic Dynamics, Cambridge University Press, vol. 25(6), pages 1442-1471, September.
    14. Dongho Song & Jenny Tang, 2023. "News-Driven Uncertainty Fluctuations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 968-982, July.
    15. Claudio, João C. & von Schweinitz, Gregor, 2020. "On the international dissemination of technology news shocks," IWH Discussion Papers 25/2020, Halle Institute for Economic Research (IWH).

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