COVID-19 Uncertainty: A Tale of Two Tails (preprint)

Uncertainty about own-firm sales growth rates over the year ahead roughly doubled in reaction to the COVID shock, according to our surveys of U.S. and U.K. business executives. Firm-level uncertainty receded after spring 2020 but remains much higher than pre-COVID levels. Moreover, the nature of firm-level uncertainty has shifted greatly since the pandemic struck: Initially, business executives perceived an enormous increase in downside uncertainty, which has now dissipated. As of October 2021, almost all of the extra firm-level uncertainty is to the upside. In short, economic uncertainty associated with the pandemic has morphed from a tale of the lower tail into a tale about the upper tail.

Internet Access and its Implications for Productivity, Inequality, and Resilience (preprint)

About one-fifth of paid workdays will be supplied from home in the post-pandemic economy, and more than one-fourth on an earnings-weighted basis. In view of this projection, we consider some implications of home internet access quality, exploiting data from the new Survey of Working Arrangements and Attitudes. Moving to high-quality, fully reliable home internet service for all Americans (“universal access”) would raise earnings-weighted labor productivity by an estimated 1.1% in the coming years. The implied output gains are $160 billion per year, or $4 trillion when capitalized at a 4% rate. Estimated flow output payoffs to universal access are nearly three times as large in economic disasters like the COVID-19 pandemic. Our survey data also say that subjective well-being was higher during the pandemic for people with better home internet service conditional on age, employment status, earnings, working arrangements, and other controls. In short, universal access would raise productivity, and it would promote greater economic and social resilience during future disasters that inhibit travel and in-person interactions.

Impact of lockdowns and winter temperatures on natural gas consumption in Europe (preprint)

As the COVID-19 virus spread over the world, governments restricted mobility to slow transmission. Public health measures had different intensities across European countries but all had significant impact on peoples daily lives and economic activities, causing a drop of CO2 emissions of about 10% for the whole year 2020. Here, we analyze changes in natural gas use in the industry and built environment sectors during the first half of year 2020 with daily gas flows data from pipeline and storage facilities in Europe. We find that reductions of industrial gas use reflect decreases in industrial production across most countries. Surprisingly, natural gas use in buildings also decreased despite most people being confined at home and cold spells in March 2020. Those reductions that we attribute to the impacts of COVID-19 remain of comparable magnitude to previous variations induced by cold or warm climate anomalies in the cold season. We conclude that climate variations played a larger role than COVID-19 induced stay-home orders in natural gas consumption across Europe.

COVID-19 Is a Persistent Reallocation Shock (preprint)

Drawing on data from the firm-level Survey of Business Uncertainty, we present three pieces of evidence that COVID-19 is a persistent reallocation shock. First, rates of excess job and sales reallocation over 24-month periods have risen sharply since the pandemic struck, especially for sales. We compute these rates by aggregating over monthly firm-level observations that look back 12 months and ahead 12 months. Second, as of December 2020, firm-level forecasts of sales revenue growth over the next year imply a continuation of recent changes, not a reversal. Third, COVID-19 shifted relative employment growth trends in favor of industries with a high capacity of employees to work from home and against those with a low capacity.

COVID-19 Is a Persistent Reallocation Shock (preprint)

Drawing on data from the firm-level Survey of Business Uncertainty, we present three pieces of evidence that COVID-19 is a persistent reallocation shock. First, rates of excess job and sales reallocation over 24-month periods have risen sharply since the pandemic struck, especially for sales. We compute these rates by aggregating over monthly firm-level observations that look back 12 months and ahead 12 months. Second, as of December 2020, firm-level forecasts of sales revenue growth over the next year imply a continuation of recent changes, not a reversal. Third, COVID-19 shifted relative employment growth trends in favor of industries with a high capacity of employees to work from home, and against those with a low capacity.

Why Working From Home Will Stick (preprint)

COVID-19 drove a mass social experiment in working from home (WFH). We survey more than 30,000 Americans over multiple waves to investigate whether WFH will stick, and why. Our data say that 20 percent of full workdays will be supplied from home after the pandemic ends, compared with just 5 percent before. We develop evidence on five reasons for this large shift: better-than-expected WFH experiences, new investments in physical and human capital that enable WFH, greatly diminished stigma associated with WFH, lingering concerns about crowds and contagion risks, and a pandemic-driven surge in technological innovations that support WFH. We also use our survey data to project three consequences: First, employees will enjoy large benefits from greater remote work, especially those with higher earnings. Second, the shift to WFH will directly reduce spending in major city centers by at least 5-10 percent relative to the pre-pandemic situation. Third, our data on employer plans and the relative productivity of WFH imply a 5 percent productivity boost in the post-pandemic economy due to re-optimized working arrangements. Only one-fifth of this productivity gain will show up in conventional productivity measures, because they do not capture the time savings from less commuting.

Stock Prices, Lockdowns, and Economic Activity in the Time of Coronavirus (preprint)

Stock prices and workplace mobility trace out striking clockwise paths in daily data from mid-February to late May 2020. Global stock prices fell 30 percent from 17 February to 12 March, before mobility declined. Over the next 11 days, stocks fell another 10 percentage points as mobility dropped 40 percent. From 23 March to 9 April, stocks recovered half their losses and mobility fell further. From 9 April to late May, both stocks and mobility rose modestly. This dynamic plays out across the 35 countries in our sample, with a few notable exceptions. We also find that stricter lockdown policies, both in-country and globally, drove larger declines in national stock prices conditional on pandemic severity, workplace mobility, and income support and debt relief policies. Looking more closely at the two largest economies, the pandemic had greater effects on stock market levels and volatilities in the U.S. than in China. Narrative evidence confirms the dominant – and historically unprecedented – role of pandemic-related developments for stock prices in both countries. The size of the global stock market crash in reaction to the pandemic is many times larger than a standard asset-pricing model implies.

Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19 (preprint)

Firm-level stock returns differ enormously in reaction to COVID-19 news. We characterize these reactions using the Risk Factors discussions in pre-pandemic 10-K filings and two text-analytic approaches: expert-curated dictionaries and supervised machine learning (ML). Bad COVID-19 news lowers returns for firms with high exposures to travel, traditional retail, aircraft production and energy supply – directly and via downstream demand linkages – and raises them for firms with high exposures to healthcare policy, e-commerce, web services, drug trials and materials that feed into supply chains for semiconductors, cloud computing and telecommunications. Monetary and fiscal policy responses to the pandemic strongly impact firm-level returns as well, but differently than pandemic news. Despite methodological differences, dictionary and ML approaches yield remarkably congruent return predictions. Importantly though, ML operates on a vastly larger feature space, yielding richer characterizations of risk exposures and outperforming the dictionary approach in goodness-of-fit. By integrating elements of both approaches, we uncover new risk factors and sharpen our explanations for firm-level returns. To illustrate the broader utility of our methods, we also apply them to explain firm-level returns in reaction to the March 2020 Super Tuesday election results.

COVID-19 Shifted Patent Applications Toward Technologies that Support Working from Home (preprint)

We examine the text content of U.S. patent applications, identifying those that advance technologies in support of video conferencing, telecommuting, remote interactivity, and working from home (collectively, WFH). The share of new patent applications that advance WFH technologies more than doubles from January to September of 2020, greatly surpassing its previous peak, and following an upward trajectory since the onset of the pandemic. This evidence suggests that (re-)directed technical change in reaction to COVID-19 will raise the quality and efficiency of remote work, thereby reinforcing a shift to working from home even after the pandemic ends.

Economic Uncertainty Before and During the COVID-19 Pandemic (preprint)

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.

Economic Uncertainty Before and During the Covid-19 Pandemic (preprint)

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.

Global economic footprint of the COVID-19 pandemic (preprint)

Countries around the world have sought to stop the spread of the 2019 novel coronavirus (COVID-19) by severely restricting travel and in-person commercial activities. Here, we analyse the economic footprint of such “lockdowns” using detailed datasets of global supply chains and a set of pandemic scenarios. We find that COVID-related economic losses are largely dependent on the number of countries imposing lockdowns, and that losses are more sensitive to the duration of a lockdown that its strictness—suggesting that more severe restrictions can reduce economic damages if they successfully shorten the duration of a lockdown. Our results also highlight several key vulnerabilities in global supply chains: Even countries that are not directly affected by COVID-19 can experience large losses (e.g., >20% of their GDP)—with such cascading impacts often occurring in low- and middle-income countries. Open and highly-specialized economies suffer particularly large losses (e.g., energy-exporting Central Asian countries or tourism-focused Caribbean countries). Supply bottlenecks and declines in consumer demand lead to especially large losses in globalized sectors such as electronics (production decreases of 13-53% across our scenarios) and automobiles (2-49%). Although retrospective analyses will undoubtedly provide further policy-relevant insights, our findings already imply that earlier, stricter, and thus shorter lockdowns are likely to minimize overall economic damages, and that global supply chains will magnify economic losses in some countries and industry sectors regardless of direct effects of the coronavirus.