We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence—including human readings of 12,000 newspaper articles—indicate that our index proxies for movements in policy-related economic uncertainty. Our U.S. index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt ceiling dispute, and other major battles over fiscal policy. Using firm-level data, we find that policy uncertainty is associated with greater stock price volatility and reduced investment and employment in policy-sensitive sectors like defense, health care, finance, and infrastructure construction. At the macro level, innovations in policy uncertainty foreshadow declines in investment, output, and employment in the United States and, in a panel vector autoregressive setting, for 12 major economies. Extending our U.S. index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upward since the 1960s.

We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence -including human readings of 12,000 newspaper articlesindicate that our index proxies for movements in policy-related economic uncertainty. Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy. Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction. At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies. Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s.

This study measures the heterogeneity of establishment-level employment changes in the U.S. manufacturing sector over the 1972 to 1986 period. We measure this heterogeneity in terms of the gross creation and destruction of jobs and the rate at which jobs are reallocated across plants. Our measurement efforts enable us to quantify the connection between job reallocation and worker reallocation, to evaluate theories of heterogeneity in plant-level employment dynamics, and to establish new results related to the cyclical behavior of the labor market.

No previous infectious disease outbreak, including the Spanish Flu, has affected the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with respect to large daily stock market moves back to 1900 and with respect to overall stock market volatility back to 1985. We also evaluate potential explanations for the unprecedented stock market reaction to the COVID-19 pandemic. The evidence we amass suggests that government restrictions on commercial activity and voluntary social distancing, operating with powerful effects in a service-oriented economy, are the main reasons the U.S. stock market reacted so much more forcefully to COVID-19 than to previous pandemics in 1918–1919, 1957–1958, and 1968.

We thank the U.S. National Science Foundation, the Sloan Foundation, and the University of Chicago Booth School of Business for financial support. We also thank Steve Tadelis and Wolfgang Keller for valuable comments on the paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w26983.ack NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We gratefully acknowledge financial support from the U.S. National Science Foundation (SES 1324257) and the University of Chicago Booth School of Business. We thank the editor and an anonymous referee for helpful comments on an earlier draft. Data on our newspaper-based classifications of daily stock market jumps are available at https://stockmarketjumps.com. Data for our newspaper-based Equity Market Volatility Tracker and Infectious Disease Equity Market Volatility Tracker are available at http://www.policyuncertainty.com. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w26945.ack NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence -including human readings of 12,000 newspaper articlesindicate that our index proxies for movements in policy-related economic uncertainty. Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy. Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction. At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies. Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s.

We thank Marios Michaelides for excellent research assistance and the Kauffman Foundation for financial support. The views expressed in the paper are those of the authors and do not necessarily represent those of the Census Bureau. The paper has been screened to ensure that it does not disclose any confidential information. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.