State-Level Economic Policy Uncertainty

We quantify and study state-level economic policy uncertainty. Tapping digital archives for nearly 3,500 local newspapers, we construct three monthly indexes for each state: one that captures state and local sources of policy uncertainty (EPU−S), one that captures national and international sources (EPU−N), and a composite index that captures both. EPU−S rises around gubernatorial elections and own-state episodes like the California electricity crisis of 2000-01 and the Kansas tax experiment of 2012. EPU−N rises around presidential elections and in response to 9-11, Gulf Wars I and II, the 2011 debt-ceiling crisis, the 2012 fiscal cliff episode, and federal government shutdowns. Close elections elevate policy uncertainty much more than the average election. VAR models fit to pre-COVID data imply that upward shocks to own-state EPU foreshadow weaker economic performance in the state, as do upward EPU shocks in contiguous states. The COVID-19 pandemic drove huge increases in policy uncertainty and unemployment, more so in states with stricter government-mandated lockdowns.

Using Disasters to Estimate the Impact of Uncertainty

Uncertainty rises in recessions and falls in booms. But what is the causal relationship? We construct cross-country panel data on stock market levels and volatility and use natural disasters, terrorist attacks, and political shocks as instruments in regressions and VAR estimations. We find that increased volatility robustly lowers growth. We also structurally estimate a heterogeneous firms business cycle model with uncertainty and disasters and use this to analyze our empirical results. Finally, using our VAR results we estimate COVID-19 will reduce US GDP by 9% in 2020 based on the initial stock market returns and volatility response.

The Unprecedented Stock Market Impact of COVID-19

No previous infectious disease outbreak, including the Spanish Flu, has impacted 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 1918-19, 1957-58 and 1968.

Measuring Customer Churn and Interconnectedness

This paper demonstrates that it is possible to construct accurate pictures of firm revenue, growth, geographic dispersion, and customer base characteristics using an increasingly accessible class of consumer financial transaction data. We develop two new measures which characterize firms' customer bases: the rate of churn in a firm's customer base and a metric of the pairwise similarity between firms' customer bases. We show that these measures provide important insights into the behavior of both real firm decisions and firm asset prices. Rates of customer churn affect the level and volatility of firm-level investment, markups, and profits. Churn also affects how quickly firms respond to shocks in the value of their growth options (i.e. Tobin's~Q). Moreover, high churn firms tended to face steeper declines in consumer spending during the recent COVID-19 outbreak. Similarity between firms' customer bases highlights one under-explored type of predictability among stock returns -- we demonstrate that significant alpha can be generated using a trading strategy that exploits our index of customer base similarity across firms.

How Does Household Spending Respond to an Epidemic? Consumption During the 2020 COVID-19 Pandemic

We explore how household consumption responds to epidemics, utilizing transaction-level household financial data to investigate the impact of the COVID-19 virus. As the number of cases grew, households began to radically alter their typical spending across a number of major categories. Initially spending increased sharply, particularly in retail, credit card spending and food items. This was followed by a sharp decrease in overall spending. Households responded most strongly in states with shelter-in-place orders in place by March 29th. We explore heterogeneity across partisan affiliation, demographics and income. Greater levels of social distancing are associated with drops in spending, particularly in restaurants and retail.

Economic Uncertainty Before and During the COVID-19 Pandemic

We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based economic policy uncertainty, twitter chatter about economic uncertainty, subjective uncertainty about future business growth, and disagreement among professional forecasters about future GDP growth. Three 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 rise of around 100% (relative to January 2020) in two-year implied volatility on the S&P 500 and subjective uncertainty around year-ahead sales for UK firms 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 the difference in uncertainty measures between Wall Street and Main Street.

COVID-Induced Economic Uncertainty

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.

How Does Household Spending Respond to an Epidemic? Consumption during the 2020 COVID-19 Pandemic

Utilizing transaction-level financial data, we explore how household consumption responded to the onset of the COVID-19 pandemic. As case numbers grew and cities and states enacted shelter-in-place orders, Americans began to radically alter their typical spending across a number of major categories. In the first half of March 2020, individuals increased total spending by over 40% across a wide range of categories. This was followed by a decrease in overall spending of 25%–30% during the second half of March coinciding with the disease spreading, with only food delivery and grocery spending as major exceptions to the decline. Spending responded most strongly in states with active shelter-in-place orders, though individuals in all states had sizable responses. We find few differences across individuals with differing political beliefs, but households with children or low levels of liquidity saw the largest declines in spending during the latter part of March.

The Unprecedented Stock Market Reaction to COVID-19

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.