Economic uncertainty before and during the COVID-19 pandemic

By David E. Altig, Scott R. Baker, Jose Maria Barrero, Nicholas Bloom, P. Bunn, Scarlet Chen, Steven J. Davis, J. Leather, B. Meyer, E. Mihaylov and 5 more. Journal of Public Economics, 2020

873 citations recorded by the source corpus.

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%.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/a381e176f5a8ab4cd60a1b38917bd49550dc6796

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Citations in the corpus

Policies to Support Businesses through the COVID-19 Shock: A Firm Level Perspective (2021, positive): “Recognizing that the COVID-19 crisis has significantly altered firms’ outlook and heightened uncertainty (Altig et al. 2020), the section that follows specifically focuses on the relationship between receiving policy support and firms’ expectations and uncertainty.”
Unmasking the Impact of COVID-19 on Businesses : Firm Level Evidence from across the World (2020, methodology): “Section 6 addresses the issue of uncertainty relying on a novel measure which builds on Altig et al. (2020a) and Barrero et al. (2020).”
A literature review of the economics of COVID‐19 (2020, methodology): “Based on a similar approach, Altig et al. (2020) conduct an analysis of different forward-looking uncertainty measures during the pandemic. Coibion et al. (2020a) use surveys to assess the macroeconomic expectations of households in the United States. They find that it is primarily lockdowns, rather”
Economic Policy Uncertainty in Times of COVID-19 Pandemic (2020, background): “Our finding of a pandemic-induced economic uncertainty in China and Korea echoes the observations that the unprecedented nature of the COVID-19 outbreak spearheaded equally unprecedented policy responses (Iyke, 2020b; Phan & Narayan, 2020), whose paths and impacts are uncertain (Altig et al., 2020).”
The Impact of Covid-19 on Productivity (2020, neutral): “Section 2: The Decision Maker Panel (DMP) during Covid-19 Survey methodology The DMP is a large and representative online survey of Chief Financial Officers in UK businesses.7 It is similar in style to the Survey of Business Uncertainty run in the United States by the Federal Reserve Bank of Atlanta”
Job search during the COVID-19 crisis (2020, positive): “One possible reason for the opposite empirical result is that firms initially underestimate the sharp drop in job search activity and its consequences for job filling rates, as their environment reaches record level of uncertainty (Altig et al., 2020).”