Covid-Induced Economic Uncertainty

S. Baker, N. Bloom, S. Davis, S. Terry
{"title":"Covid-Induced Economic Uncertainty","authors":"S. Baker, N. Bloom, S. Davis, S. Terry","doi":"10.3386/w26983","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":155479,"journal":{"name":"Econometric Modeling: Macroeconomics eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"873","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: Macroeconomics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3386/w26983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 873

Abstract

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.
新冠病毒引发的经济不确定性
评估COVID-19大流行的经济影响对政策制定者至关重要,但由于危机以极快的速度展开,因此具有挑战性。我们确定了三个指标-股票市场波动,基于报纸的经济不确定性,以及商业预期调查中的主观不确定性-提供了实时前瞻性不确定性措施。我们使用这些指标来记录和量化过去几周经济不确定性的大幅增加。我们还说明了如何使用这些前瞻性措施来评估2019冠状病毒病危机的宏观经济影响。具体来说,我们将新冠病毒引发的第一时刻冲击和不确定性冲击输入到Baker、Bloom和Terry(2020)开发的灾害影响估计模型中。我们的说明性计算表明,截至2020年第四季度,美国实际GDP同比收缩近11%,90%的置信区间延伸至近20%的收缩。该演习表明,约一半的预测产出收缩反映了新冠肺炎引发的不确定性的负面影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信