Economic uncertainty before and during the COVID-19 pandemic

• 成果类型: Article
• 署名作者: Altig, Dave; Baker, Scott; Barrero, Jose Maria; Bloom, Nicholas; Bunn, Philip; Chen, Scarlet; Davis, Steven J.; Leather, Julia; Meyer, Brent; Mihaylov, Emil; Mizen, Paul; Parker, Nicholas; Renault, Thomas; Smietanka, Pawel; Thwaites, Gregory
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - Atlanta; Northwestern University; Instituto Tecnologico Autonomo de Mexico; Stanford University; Bank of England; University of Chicago; University of Nottingham; heSam Universite; Universite Pantheon-Sorbonne
• 刊物名称: JOURNAL OF PUBLIC ECONOMICS
• ISSN/ISSBN: 0047-2727
• DOI: 10.1016/j.jpubeco.2020.104274
• 发表日期: 2020
• 关键词: Forward-looking uncertainty measures; volatility; Covid-19; CORONAVIRUS

摘要

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.