The paper by Scott R. Baker, Nicholas Bloom, Steven J. Davis, and Stephen J. Terry assesses the economic impact of the COVID-19 pandemic, focusing on the unprecedented level of uncertainty it has introduced. The authors identify three key indicators—stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys—to measure real-time forward-looking uncertainty. They document and quantify the significant increase in economic uncertainty over the past several weeks and illustrate how these measures can be used to assess the macroeconomic impact of the pandemic. Using an estimated model of disaster effects developed by the authors, they find that the COVID-19 crisis could lead to a year-on-year contraction in U.S. real GDP of nearly 11 percent by the fourth quarter of 2020, with a 90 percent confidence interval extending to a nearly 20 percent contraction. The study suggests that about half of the forecasted output contraction is due to the negative effect of COVID-induced uncertainty. The authors highlight the challenges in quantifying uncertainty, including the rapid onset of the crisis, the lack of historical parallels, and the timeliness of data. They discuss various measures of uncertainty, such as stock market volatility, newspaper-based indices, business expectation surveys, forecaster disagreement, and statistical forecast uncertainty. The paper concludes by emphasizing the magnitude of the uncertainty shock caused by the pandemic, which is larger than that associated with the 2008 financial crisis but similar to the uncertainty levels during the Great Depression.The paper by Scott R. Baker, Nicholas Bloom, Steven J. Davis, and Stephen J. Terry assesses the economic impact of the COVID-19 pandemic, focusing on the unprecedented level of uncertainty it has introduced. The authors identify three key indicators—stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys—to measure real-time forward-looking uncertainty. They document and quantify the significant increase in economic uncertainty over the past several weeks and illustrate how these measures can be used to assess the macroeconomic impact of the pandemic. Using an estimated model of disaster effects developed by the authors, they find that the COVID-19 crisis could lead to a year-on-year contraction in U.S. real GDP of nearly 11 percent by the fourth quarter of 2020, with a 90 percent confidence interval extending to a nearly 20 percent contraction. The study suggests that about half of the forecasted output contraction is due to the negative effect of COVID-induced uncertainty. The authors highlight the challenges in quantifying uncertainty, including the rapid onset of the crisis, the lack of historical parallels, and the timeliness of data. They discuss various measures of uncertainty, such as stock market volatility, newspaper-based indices, business expectation surveys, forecaster disagreement, and statistical forecast uncertainty. The paper concludes by emphasizing the magnitude of the uncertainty shock caused by the pandemic, which is larger than that associated with the 2008 financial crisis but similar to the uncertainty levels during the Great Depression.