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Economic uncertainty before and during the COVID-19 pandemic

Author

Listed:
  • Dave Altig

    (Atlanta Federal Reserve Bank)

  • Scott Baker

    (Northwestern University [Evanston])

  • Jose Maria Barrero

    (ITAM - Instituto Tecnológico Autónomo de México)

  • Nicholas Bloom

    (Stanford University)

  • Philip Bunn

    (Bank of England - Bank of England)

  • Scarlet Chen

    (Stanford University)

  • Steven Davis

    (University of Chicago)

  • Julia Leather

    (UON - University of Nottingham, UK)

  • Brent Meyer

    (Atlanta Federal Reserve Bank)

  • Emil Mihaylov

    (Atlanta Federal Reserve Bank)

  • Paul Mizen

    (UON - University of Nottingham, UK)

  • Nicholas Parker

    (Atlanta Federal Reserve Bank)

  • Thomas Renault

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Pawel Smietanka

    (Bank of England - Bank of England)

  • Gregory Thwaites

    (UON - University of Nottingham, UK)

Abstract
We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based policy uncertainty, Twitter chatter about economic uncertainty, subjective uncertainty about business growth, forecaster disagreement about future GDP growth, and a model-based measure of macro uncertainty. Four results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatly – from a 35% rise for the model-based measure of US economic uncertainty (relative to January 2020) to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: Implied volatility rose rapidly from late February, peaked in mid-March, and fell back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting differences between Wall Street and Main Street uncertainty measures. Fourth, in Cholesky-identified VAR models fit to monthly U.S. data, a COVID-size uncertainty shock foreshadows peak drops in industrial production of 12–19%.

Suggested Citation

  • Dave Altig & Scott Baker & Jose Maria Barrero & Nicholas Bloom & Philip Bunn & Scarlet Chen & Steven Davis & Julia Leather & Brent Meyer & Emil Mihaylov & Paul Mizen & Nicholas Parker & Thomas Renault, 2020. "Economic uncertainty before and during the COVID-19 pandemic," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205118, HAL.
    • Handle: RePEc:hal:cesptp:hal-03205118
    DOI: 10.1016/j.jpubeco.2020.104274
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Forward-looking uncertainty measures; Volatility; COVID-19; Coronavirus;
    All these keywords.

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General

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