Covid-Induced Economic Uncertainty

By Scott R. Baker, Nicholas Bloom, Steven J. Davis, Stephen J. Terry. 2020

1,175 citations recorded by the source corpus.

Assessing the economic impact of the COVID-19 pandemic is essential for policymakers, but challenging because the crisis has unfolded with extreme speed. We identify three indicators – stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys – that provide real-time forward-looking uncertainty measures. We use these indicators to document and quantify the enormous increase in economic uncertainty in the past several weeks. We also illustrate how these forward-looking measures can be used to assess the macroeconomic impact of the COVID-19 crisis. Specifically, we feed COVID-induced first-moment and uncertainty shocks into an estimated model of disaster effects developed by Baker, Bloom and Terry (2020). Our illustrative exercise implies a year-on-year contraction in U.S. real GDP of nearly 11 percent as of 2020 Q4, with a 90 percent confidence interval extending to a nearly 20 percent contraction. The exercise says that about half of the forecasted output contraction reflects a negative effect of COVID-induced uncertainty.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4c71803aeb55cb4bd25365cab630b3e9916f3140

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In Economics and Econometrics

  1. Efrem Castelnuovo
  2. Giovanni Caggiano
  3. Steven J. Davis
  4. L. Yarovaya
  5. Scott R. Baker
  6. Boqiang Lin
  7. Tong-Yaa Su
  8. Nicholas Bloom

In Management Science and Operations Research

  1. L. Yarovaya
  2. Afees A. Salisu
  3. O. Adekoya
  4. J. Oliyide
  5. Boqiang Lin
  6. Idris A. Adediran
  7. Tong-Yaa Su
  8. Sikiru Abidemi Abdulsalam

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