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Pandemic Lockdown: The Role of Government Commitment
From the Abstract: "This note studies optimal lockdown policy in a model in which the government can limit a pandemic's impact via a lockdown at the cost of lower economic output. A government would like to commit to limit the extent of future lockdown in order to support more optimistic investor expectations in the present. However, such a commitment is not credible since investment decisions are sunk when the government makes the lockdown decision in the future. The commitment problem is more severe if lockdown is sufficiently effective at limiting disease spread or if the size of the susceptible population is sufficiently large. Credible rules that limit a government's ability to lock down the economy in the future can improve the efficiency of lockdown policy."
National Bureau of Economic Research
Moser, Christian A.; Yared, Pierre
2020-04
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Corporate Immunity to the COVID-19 Pandemic
From the Abstract: "Using data on over 6,000 firms across 56 economies during the first quarter of 2020, we evaluate the connection between corporate characteristics and stock price reactions to COVID-19 [coronavirus disease 2019] cases. We find that the pandemic-induced drop in stock prices was milder among firms with (a) stronger pre-2020 finances (more cash, less debt, and larger profits), (b) less exposure to COVID-19 through global supply chains and customer locations, (c) more CSR [corporate social responsibility] activities, and (d) less entrenched executives. Furthermore, the stock prices of firms with greater hedge fund ownership performed worse, and those of firms with larger non-financial corporate ownership performed better. We believe ours is the first paper to assess international, cross-firm stock price reactions to COVID-19 as functions of these pre-shock corporate characteristics."
National Bureau of Economic Research
Ding, Wenzhi; Levine, Ross; Lin, Chen . . .
2020-04
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Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists
From the Abstract: "This paper provides a critical review of models of the spread of the coronavirus (SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2]) epidemic that have been influential in recent policy decisions. There is tremendous opportunity for social scientists to advance the relevant literature as new and better data becomes available to bolster economic outcomes and save lives."
National Bureau of Economic Research
Avery, Christopher (Christopher N.); Bossert, William H., 1937-; Clark, Adam . . .
2020-04
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Polarization and Public Health: Partisan Differences in Social Distancing During the Coronavirus Pandemic
From the Abstract: "We study partisan differences in Americans' response to the COVID-19 [coronavirus disease 2019] pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engage in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic."
National Bureau of Economic Research
Allcott, Hunt; Boxell, Levi; Conway, Jacob C. . . .
2020-04
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Subways Seeded the Massive Coronavirus Epidemic in New York City
From the Abstract: "New York City's multitentacled subway system was a major disseminator - if not the principal transmission vehicle - of coronavirus infection during the initial takeoff of the massive epidemic that became evident throughout the city during March 2020. The near shutoff of subway ridership in Manhattan - down by over 90 percent at the end of March - correlates strongly with the substantial increase in the doubling time of new cases in this borough. Maps of subway station turnstile entries, superimposed upon zip code-level maps of reported coronavirus incidence, are strongly consistent with subway-facilitated disease propagation. Local train lines appear to have a higher propensity to transmit infection than express lines. Reciprocal seeding of infection appears to be the best explanation for the emergence of a single hotspot in Midtown West in Manhattan. Bus hubs may have served as secondary transmission routes out to the periphery of the city."
National Bureau of Economic Research
Harris, Jeffrey E.
2020-04
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Labor Demand in the Time of COVID-19: Evidence from Vacancy Postings and UI Claims
From the Abstract: "We use job vacancy data collected in real time by Burning Glass Technologies, as well as initial unemployment insurance (UI) claims data to study the impact of COVID-19 [coronavirus disease 2019] on the labor market. Our data allow us to track postings at disaggregated geography and by detailed occupation and industry. We find that job vacancies collapsed in the second half of March and are now 30% lower than their level at the beginning of the year. To a first approximation, this collapse was broad based, hitting all U.S. states, regardless of the intensity of the initial virus spread or timing of stay-at-home policies. UI claims also largely match these patterns. Nearly all industries and occupations saw contraction in postings and spikes in UI claims, regardless of whether they are deemed essential and whether they have work-from-home capability. The only major exceptions are in essential retail and nursing, the 'front line' jobs most in-demand during the current crisis."
National Bureau of Economic Research
Kahn, Lisa B.; Lange, Fabian; Wiczer, David G.
2020-04
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Demographic Perspectives on Mortality of COVID-19 and Other Epidemics
From the Abstract: "What would a hypothetical one million US deaths in the Covid-19 [coronavirus disease 2019] epidemic mean for mortality of individuals at the population level? To put estimates of Covid-19 mortality into perspective, we estimate age-specific mortality for an epidemic claiming for illustrative purposes one million US lives, with results scalable over a broad range of deaths. We calculate the impact on period life expectancy (down 3 years) and remaining life-years (12.3 years per death), which for one million deaths can be valued at six to 10 trillion dollars. The age-patterns of Covid-19 mortality observed in other countries are remarkably similar and exhibit the typical rate of increase by age of normal mortality. The scenario of one million Covid-19 deaths is similar in scale to the decades-long HIV/AIDS and opioid-overdose epidemics but considerably smaller than the Spanish Flu of 1918. Unlike HIV/AIDS and opioid epidemics, the Covid-19 deaths will be concentrated in months rather than spread out over decades."
National Bureau of Economic Research
Goldstein, Joshua R.; Lee, Ronald Demos, 1941-
2020-04
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Optimal Mitigation Policies in a Pandemic: Social Distancing and Working from Home
From the Abstract: "We study the response of an economy to an unexpected epidemic. Households mitigate the spread of the disease by reducing consumption, reducing hours worked, and working from home. Working from home is subject to learning-by-doing and the capacity of the health care system is limited. A social planner worries about two externalities, an infection externality and a healthcare congestion externality. Private agents' mitigation incentives are weak and biased. We show that private safety incentives can even decline at the onset of the epidemic. The planner, on the other hand, implements front-loaded mitigation policies and encourages working from home immediately. In our calibration, assuming a CFR [case fatality rate] of 1% and an initial infection rate of 0.1%, private mitigation reduces the cumulative death rate from 2.5% of the initially susceptible population to about 1.75%. The planner optimally imposes a drastic suppression policy and reduces the death rate to 0.15% at the cost of an initial drop in consumption of around 25%."
National Bureau of Economic Research
Jones, Callum J.; Philippon, Thomas; Venkateswaran, Venky
2020-04
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U.S. Economic Activity During the Early Weeks of the SARS-CoV-2 Outbreak [April 2020]
From the Abstract: "This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the response to the novel Coronavirus in the United States. The WEI shows a strong and sudden decline in economic activity starting in the week ending March 21, 2020. In the most recent week ending March 28, the WEI indicates economic activity has fallen further to -6.19% scaled to 4 quarter growth in GDP [gross domestic product]."
National Bureau of Economic Research
Lewis, Daniel; Mertens, Karel; Stock, James H.
2020-04
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COVID-19 Infection Externalities: Trading Off Lives vs. Livelihoods
From the Abstract: "We analyze the externalities that arise when social and economic interactions transmit infectious diseases such as COVID-19 [coronavirus disease 2019]. Individually rational agents do not internalize that they impose infection externalities upon others when the disease is transmitted. In an SIR [Susceptible, Infected and Recovered] model calibrated to capture the main features of COVID-19 in the US economy, we show that private agents perceive the cost an additional infection to be around $80k whereas the social cost including infection externalities is more than three times higher, around $286k. This misvaluation has stark implications for how society ultimately overcomes the disease: for a population of individually rational agents, the precautionary behavior by the susceptible flattens the curve of infections, but the disease is not overcome until herd immunity is acquired. The resulting economic cost is high; an initial sharp decline in aggregate output followed by a slow recovery over several years. By contrast, the socially optimal approach in our model focuses public policy measures on the infected in order to contain the disease and quickly eradicate it, which produces a much milder recession. If targeting the infected is impossible, the optimal policy in our model is still to aggressively contain and eliminate the disease, and the social cost of an extra infection rises to $586k."
National Bureau of Economic Research
Bethune, Zachary Austin; Korinek, Anton
2020-04
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Tracking Public and Private Responses to the COVID-19 Epidemic: Evidence from State and Local Government Actions
From the Abstract: "This paper examines the determinants of social distancing during the COVID-19 [coronavirus disease 2019] epidemic. We classify state and local government actions, and we study multiple proxies for social distancing based on data from smart devices. Mobility fell substantially in all states, even ones that have not adopted major distancing mandates. There is little evidence, for example, that stay-at-home mandates induced distancing. In contrast, early and information-focused actions have had bigger effects. Event studies show that first case announcements, emergency declarations, and school closures reduced mobility by 1-5% after 5 days and 7-45% after 20 days. Between March 1 and April 11, average time spent at home grew from 9.1 hours to 13.9 hours. We find, for example, that without state emergency declarations, event study estimates imply that hours at home would have been 11.3 hours in April, suggesting that 55% of the growth comes from emergency declarations and 45% comes from secular (non-policy) trends. State and local government actions induced changes in mobility on top of a large response across all states to the prevailing knowledge of public health risks. Early state policies conveyed information about the epidemic, suggesting that even the policy response mainly operates through a voluntary channel."
National Bureau of Economic Research
Gupta, Sumedha; Nguyen, Thuy D.; Rojas, Felipe Lozano . . .
2020-04
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Controlling a Pandemic
From the Abstract: "To slow the spread of COVID-19 [coronavirus disease 2019], many countries are shutting down non-essential sectors of the economy. Older individuals have the most to gain from slowing virus diffusion. Younger workers in sectors that are shuttered have the most to lose. In this paper, we build a model in which economic activity and disease progression are jointly determined. Individuals differ by age (young and retired), by sector (basic and luxury), and by health status. Disease transmission occurs in the workplace, in consumption activities, at home, and in hospitals. We study the optimal economic mitigation policy of a utilitarian government that can redistribute across individuals, but where such redistribution is costly. We show that optimal redistribution and mitigation policies interact, and reflect a compromise between the strongly diverging preferred policy paths of different subgroups of the population. We find that the shutdown in place on April 12 is too extensive, but that a partial shutdown should remain in place through the fall. Finally, people prefer deeper and longer shutdowns if a vaccine is imminent, especially the elderly."
National Bureau of Economic Research
Glover, Andrew; Heathcote, Jonathan; Krueger, Dirk . . .
2020-04
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Which Retail Outlets Generate the Most Physical Interactions?
From the Abstract: "This paper seeks to answer the simple question of what category of retail outlets generates the most physical interactions in the regular course of life. In this way, we aim to bring a marketing perspective to discussions about which businesses may be most risky from the standpoint of spreading contagious disease. We use detailed data from people's mobile devices prior to the implementation of social distancing measures in the United States. With this data, we examine a number of potential indicators of risk of contagion: The absolute number of visits and visitors, how many of the visits are generated by the same people, the median average distance traveled by the visitor to the retailer, and the number of customers from Canada and Mexico. We find that retailers with a single outlet tend to attract relatively few visitors, fewer one-off visitors, and have fewer international customers. For retailers that have multiple stores the patterns are non-linear. Retailers that have such a large number of stores that they are ubiquitous, tend to exhibit fewer visits and visitors and attract customers from a smaller distance. However, retailers that have a large enough footprint to be well known, but not large enough to be ubiquitous tend to attract a large number of visitors who make one-off visits, travel a long distance, and are disproportionately international."
National Bureau of Economic Research
Goldfarb, Avi; Tucker, Catherine (Catherine Elizabeth)
2020-04
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Brazilian Bombshell? The Long-Term Impact of the 1918 Influenza Pandemic the South American Way
From the Abstract: "We analyze the repercussions of the 1918 Influenza Pandemic on demographic measures, human capital formation, and productivity markers in the state of Sao Paulo, Brazil's financial center and the most populous city in South America today. Leveraging temporal and spatial variation in district-level estimates of influenza-related deaths for the period 1917-1920 combined with a unique database on socio-economic, health and productivity outcomes constructed from historical and contemporary documents for all districts in Sao Paulo, we find that the 1918 Influenza pandemic had significant negative impacts on infant mortality and sex ratios at birth in 1920 (the short-run). We find robust evidence of persistent effects on health, educational attainment and productivity more than twenty years later. Our study highlights the importance of documenting the legacy of historical shocks in understanding the development trajectories of countries over time."
National Bureau of Economic Research
Guimbeau, Amanda; Menon, Nidhiya; Musacchio, Aldo
2020-04
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Sequential Lifting of COVID-19 Interventions with Population Heterogeneity
From the Abstract: "This paper analyzes a sequential approach to lifting interventions in the COVID-19 [coronavirus disease 2019] pandemic taking heterogeneity in the population into account. The population is heterogeneous in terms of the consequences of infection (need for hospitalization and critical care, and mortality) and in terms of labor force participation. Splitting the population in two groups by age, a less affected younger group that is more likely to work, and a more affected older group less likely to work, and lifting interventions sequentially (for the younger group first and the older group later on) can substantially reduce mortality, demands on the health care system, and the economic cost of interventions."
National Bureau of Economic Research
Rampini, Adriano A.
2020-04
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Data Gaps and the Policy Response to the Novel Coronavirus
From the Abstract: "This note lays out the basic Susceptible-Infected-Recovered (SIR) epidemiological model of contagion, with a target audience of economists who want a framework for understanding the effects of social distancing and containment policies on the evolution of contagion and interactions with the economy. A key parameter, the asymptomatic rate (the fraction of the infected that are not tested under current guidelines), is not well estimated in the literature because tests for the coronavirus have been targeted at the sick and vulnerable, however it could be estimated by random sampling of the population. In this simple model, different policies that yield the same transmission rate β have the same health outcomes but can have very different economic costs. Thus, one way to frame the economics of shutdown policy is as finding the most efficient policies to achieve a given β, then determining the path of β that trades off the economic cost against the cost of excess lives lost by overwhelming the health care system."
National Bureau of Economic Research
Stock, James H.
2020-03
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What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios
From the Abstract: "This note is intended to introduce economists to a simple SIR [susceptible-infected-recovered] model of the progression of COVID-19 [coronavirus disease 2019] in the United States over the next 12-18 months. An SIR model is a Markov model of the spread of an epidemic in a population in which the total population is divided into categories of being susceptible to the disease (S), actively infected with the disease (I), and recovered (or dead) and no longer contagious (R). How an epidemic plays out over time is determined by the transition rates between these three states. This model allows for quantitative statements regarding the tradeoff between the severity and timing of suppression of the disease through social distancing and the progression of the disease in the population. Example applications of the model are provided. Special attention is given to the question of if and when the fraction of active infections in the population exceeds 1% (at which point the health system is forecast to be severely challenged) and 10% (which may result in severe staffing shortages for key financial and economic infrastructure) as well as the cumulative burden of the disease over an 18 month horizon."
National Bureau of Economic Research
Atkeson, Andrew
2020-03
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Group Testing in a Pandemic: The Role of Frequent Testing, Correlated Risk, and Machine Learning
From the Abstract: "Group testing increases efficiency by pooling patient specimens and clearing the entire group with one negative test. Optimal grouping strategy is well studied in one-off testing scenarios with reasonably well-known prevalence rates and no correlations in risk. We discuss how the strategy changes in a pandemic environment with repeated testing, rapid local infection spread, and highly uncertain risk. First, repeated testing mechanically lowers prevalence at the time of the next test. This increases testing efficiency, such that increasing frequency by x times only increases expected tests by around √x rather than x. However, this calculation omits a further benefit of frequent testing: infected people are quickly removed from the population, which lowers prevalence and generates further efficiency. Accounting for this decline in intra-group spread, we show that increasing frequency can paradoxically reduce the total testing cost. Second, we show that group size and efficiency increases with intra-group risk correlation, which is expected in natural test groupings based on proximity. Third, because optimal groupings depend on uncertain risk and correlation, we show how better estimates from machine learning can drive large efficiency gains. We conclude that frequent group testing, aided by machine learning, is a promising and inexpensive surveillance strategy."
National Bureau of Economic Research
Augenblick, Ned; Kolstad, Jonathan T.; Obermeyer, Ziad . . .
2020
