期刊
JOURNAL OF PUBLIC ECONOMICS
卷 191, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jpubeco.2020.104274
关键词
Forward-looking uncertainty measures; Volatility; COVID-19; Coronavirus
类别
资金
- US National Science Foundation
- Sloan Foundation
- University of Chicago Booth School of Business
- Economic and Social Research Council
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 - froma 35% rise for the model-basedmeasure 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 lossesmounted, highlighting differences betweenWall Street andMain Street uncertaintymeasures. 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%. Crown Copyright (c) 2020 Published by Elsevier B.V. All rights reserved.
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