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%.
Original language | English (US) |
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Article number | 104274 |
Journal | Journal of Public Economics |
Volume | 191 |
DOIs | |
State | Published - Nov 2020 |
Funding
We thank the US National Science Foundation , the Sloan Foundation , the University of Chicago Booth School of Business , and the Economic and Social Research Council for financial support. We thank our editor Owen Zidar and an anonymous referee for useful comments, Mike Clements and Martin Weale for feedback on an earlier draft, Ian Dew-Becker for supplying data on the 24-month VIX, and Niall Ferguson for pointers to the literature on excess mortality in previous pandemics.
Keywords
- COVID-19
- Coronavirus
- Forward-looking uncertainty measures
- Volatility
ASJC Scopus subject areas
- Finance
- Economics and Econometrics