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Decoding India's Low Covid-19 Case Fatality Rate
From the Abstract: "India's case fatality rate (CFR) under covid-19 [coronavirus disease 2019] is strikingly low, trending from 3% or more, to a current level of around 2.2%. The world average rate is far higher, at around 4%. Several observers have noted that this difference is at least partly due to India's younger age distribution. In this paper, we use age-specific fatality rates from 14 comparison countries, coupled with India's distribution of covid-19 cases to 'predict' what India's CFR would be with those age-specific rates. In most cases, those predictions are lower than India's actual performance, suggesting that India's CFR is, if anything, too high rather than too low. We supplement the prediction exercises with the application of a decomposition technique, and we additionally account for time lags between case incidence and death, for a more relevant cross-country perspective in the growth phase of the pandemic."
National Bureau of Economic Research
Subramanian, S. (Sreenivasan), 1953-; Ray, Debraj; Philip, Minu
2020-08
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Nursing Home Staff Networks and COVID-19
From the Abstract: "Nursing homes and other long term-care facilities account for a disproportionate share of COVID-19 [coronavirus disease 2019] cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes---and the crucial role these connections serve in spreading a highly contagious respiratory infection---is currently unknown given the lack of centralized data on cross-facility nursing home employment. In this paper, we perform the first large-scale analysis of nursing home connections via shared staff using device-level geolocation data from 30 million smartphones, and find that 7 percent of smartphones appearing in a nursing home also appeared in at least one other facility---even after visitor restrictions were imposed. We construct network measures of nursing home connectedness and estimate that nursing homes have, on average, connections with 15 other facilities. Controlling for demographic and other factors, a home's staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Results suggest that eliminating staff linkages between nursing homes could reduce COVID-19 infections in nursing homes by 44 percent."
National Bureau of Economic Research
Chevalier, Judith A.; Chen, M. Keith; Long, Elisa F.
2020-07
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COVID-19 Prevention and Air Pollution in the Absence of a Lockdown
From the Abstract: "Recent studies demonstrate that air quality improved during the coronavirus pandemic due to the imposition of social lockdowns. We investigate the impact of COVID-19 [coronavirus disease 2019] on air pollution in the two largest cities in Taiwan, which were not subject to economic or mobility restrictions. Using a generalized difference-in-differences approach and real-time data on air quality and transportation, we estimate that levels of sulfur dioxide, nitrogen dioxide and particulate matter increased 5 - 12 percent relative to 2017 - 2019. We demonstrate that this counterintuitive finding is likely due to a shift in preferences for mode of transport away from public transportation and towards personal automobiles. Similar COVID-19 prevention behaviors in regions or countries emerging from lockdowns could likewise result in an increase in air pollution."
National Bureau of Economic Research
Chang, Hung-Hao; Meyerhoefer, Chad D.; Yang, Feng-An
2020-07
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Dynamic Trade-Offs and Labor Supply Under the Cares Act
From the Abstract: "The CARES [Coronavirus Aid, Relief, and Economic Security] Act resulted in many unemployed workers receiving benefits that exceeded wages at their previous job. Given this, would an unemployed worker reject an offer to return to their former job at the same wage? Qualitatively, we provide a very simple dynamic model that incorporates four reasons the answer could be 'no': (i) the temporary nature of the CARES Act, (ii) uncertainty that their return-to-work offer might expire, (iii) search frictions, and (iv) wage losses out of unemployment in a recession. Quantitatively, when evaluated under empirically relevant parameters, we find it unlikely a worker would reject an offer to return to work at the same wage. We show special cases where this is not true and relate these to anecdotal evidence."
National Bureau of Economic Research
Boar, Corina; Mongey, Simon
2020-08
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Collaborating During Coronavirus: The Impact of COVID-19 on the Nature of Work
From the Abstract: "We explore the impact of COVID-19 [coronavirus disease 2019] on employee's digital communication patterns through an event study of lockdowns in 16 large metropolitan areas in North America, Europe and the Middle East. Using de- identified, aggregated meeting and email meta-data from 3,143,270 users, we find, compared to pre- pandemic levels, increases in the number of meetings per person (+12.9 percent) and the number of attendees per meeting (+13.5 percent), but decreases in the average length of meetings (-20.1 percent). Collectively, the net effect is that people spent less time in meetings per day (-11.5 percent) in the post- lockdown period. We also find significant and durable increases in length of the average workday (+8.2 percent, or +48.5 minutes), along with short-term increases in email activity. These findings provide insight from a novel dataset into how the nature of work has changed for a large sample of knowledge workers. We discuss these changes in light of the ongoing challenges faced by organizations and workers struggling to adapt and perform in the face of a global pandemic."
National Bureau of Economic Research
Polzer, Jeffrey T.; Sadun, Raffaella; DeFilippis, Evan . . .
2020-07
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Racial Disparity in COVID-19 Deaths: Seeking Economic Roots with Census Data
From the Abstract: "This note seeks the socioeconomic roots of racial disparities in COVID-19 [coronavirus disease 2019] mortality, using county-level mortality, economic, and demographic data from 3,140 counties. For all minorities, the minority's population share is strongly correlated with total COVID-19 deaths. For Hispanic/ Latino and Asian minorities those correlations are fragile, and largely disappear when we control for education, occupation, and commuting patterns. For African Americans and First Nations populations, the correlations are very robust. Surprisingly, for these two groups the racial disparity does not seem to be due to differences in income, poverty rates, education, occupational mix, or even access to healthcare insurance. A significant portion of the disparity can, however, be sourced to the use of public transit."
National Bureau of Economic Research
McLaren, John, 1962-
2020-06
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Longer-Run Economic Consequences of Pandemics
From the Abstract: "What are the medium- to long-term effects of pandemics? How do they differ from other economic disasters? We study major pandemics using the rates of return on assets stretching back to the 14th century. Significant macroeconomic after-effects of pandemics persist for about decades, with real rates of return substantially depressed, in stark contrast to what happens after wars. Our findings are consistent with the neoclassical growth model: capital is destroyed in wars, but not in pandemics; pandemics instead may induce relative labor scarcity and/or a shift to greater precautionary savings."
National Bureau of Economic Research
Jorda, Oscar, 1967-; Singh, Sanjay R.; Taylor, Alan M., 1964-
2020-06
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Global Supply Chains in the Pandemic
From the Abstract: "We study the role of global supply chains in the impact of the Covid-19 [coronavirus disease 2019] pandemic on GDP [gross domestic product] growth for 64 countries. We discipline the labor supply shock across sectors and countries using the fraction of work in the sector that can be done from home, interacted with the stringency with which countries imposed lockdown measures. Using the quantitative framework and methods developed in Huo, Levchenko and Pandalai-Nayar (2020), we show that the average real GDP downturn due to the Covid-19 shock is expected to be -31.5%, of which -10.7% (or one-third of the total) is due to transmission through global supply chains. However, 'renationalization' of global supply chains does not in general make countries more resilient to pandemic-induced contractions in labor supply. The average GDP drop would have been -32.3% in a world without trade in inputs and final goods. This is because eliminating reliance on foreign inputs increases reliance on the domestic inputs, which are also subject to lockdowns. Whether renationalizing supply chains insulates a country from the pandemic depends on whether it plans to impose a more or less stringent lockdown than its trading partners. Finally, unilateral lifting of the lockdowns in the largest economies can contribute as much as 6-8% to GDP growth in some of their smaller trade partners."
National Bureau of Economic Research
Bonadio, Barthélémy; Huo, Zhen (College teacher); Levchenko, Andrei A. . . .
2020-05
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Determinants of Disparities in COVID-19 Job Losses
From the Abstract: "We make several contributions to understanding how the COVID-19 [coronavirus disease 2019] epidemic and policy responses have affected U.S. labor markets, benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April 2020 (relative to February) for Hispanics, workers aged 20 to 24, and those with high school degrees and some college. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Pre-epidemic sorting into occupations with more potential for remote work and industries that are currently essential explain a large share of gaps in recent unemployment for key racial, ethnic, age, and education sub-populations. However, there is a larger unexplained component to the gender employment gaps. We also address measurement issues known to have affected the March and April 2020 CPS. In particular, non-response increased dramatically, especially among the incoming rotation groups. Some of the increase appears non-random, but is not likely to be driving our conclusions. We also demonstrate the importance of tracking workers who report having a job but being absent, in addition to tracking employed and unemployed workers. We conclude with a discussion of policy priorities implied by the disparities in labor market losses from the COVID-19 crisis that we identify."
National Bureau of Economic Research
Montenovo, Laura; Jiang, Xuan; Lozano Rojas, Felipe . . .
2020-05
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Social Interactions in Pandemics: Fear, Altruism, and Reciprocity
From the Abstract: "In SIR [susceptible-infected-removed] models, homogeneous or with a network structure, infection rates are assumed to be exogenous. However, individuals adjust their behavior. Using daily data for 89 cities worldwide, we document that mobility falls in response to fear, as approximated by Google search terms. Combining these data with experimentally validated measures of social preferences at the regional level, we find that stringency measures matter less if individuals are more patient and altruistic preference traits, and exhibit less negative reciprocity community traits. We modify the homogeneous SIR and the SIR-network model to include agents' optimizing decisions on social interactions. Susceptible individuals internalize infection risk based on their patience, infected ones do so based on their altruism, and reciprocity matters for internalizing risk in SIR networks. A planner further restricts interactions due to a static and a dynamic inefficiency in the homogeneous SIR model, and due to an additional reciprocity inefficiency in the SIR-network model. We show that partial or targeted lockdown policies are efficient only when it is possible to identify infected individuals."
National Bureau of Economic Research
Alfaro, Laura; Faia, Ester; Lamersdorf, Nora . . .
2020-05
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Reopening Under COVID-19: What to Watch For
From the Abstract: "We critically analyze the currently available status indicators of the COVID-19 [coronavirus disease 2019] epidemic so that state governors will have the guideposts necessary to decide whether to further loosen or instead retighten controls on social and economic activity. Overreliance on aggregate, state-level data in Wisconsin, we find, confounds the effects of the spring primary elections and the outbreak among meat packers. Relaxed testing standards in Los Angeles may have upwardly biased the observed trend in new infection rates. Reanalysis of New Jersey data, based upon the date an ultimately fatal case first became ill rather than the date of death, reveals that deaths have already peaked in that state. Evidence from Cook County, Illinois shows that trends in the percentage of positive tests can be wholly misleading. Trends on emergency department visits for influenza-like illness, advocated by the White House Guidelines, are unlikely to be informative. Data on hospital census counts in Orange County, California suggest that healthcare system-based indicators are likely to be more reliable and informative. An analysis of cumulative infections in San Antonio, Texas, shows how mathematical models intended to guide decisions on relaxation of social distancing are severely limited by untested assumptions. Universal coronavirus testing may not on its own solve difficult problems of data interpretation and causal inference."
National Bureau of Economic Research
Harris, Jeffrey E.
2020-05
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Economic Policy Incentives to Preserve Lives and Livelihoods
From the Abstract: "The Covid-19 [coronavirus disease 2019] pandemic has motivated a myriad of studies and proposals on how economic policy should respond to this colossal shock. But in this debate it is seldom recognized that the health shock is not entirely exogenous. Its magnitude and dynamics themselves depend on economic policies, and the explicit or implicit incentives those policies provide. To illuminate the feedback loops between medical and economic factors we develop a minimal economic model of pandemics. In the model, as in reality, individual decisions to comply (or not) with virus-related public health directives depend on economic variables and incentives, which themselves respond to current economic policy and expectations of future policies. The analysis yields several practical lessons: because policies affect the speed of virus transmission via incentives, public health measures and economic policies can complement each other, reducing the cost of attaining desired social goals; expectations of expansionary macroeconomic policies during the recovery phase can help reduce the speed of infection, and hence the size of the health shock; the credibility of announced policies is key to rule out both self-fulfilling pessimistic expectations and time inconsistency problems."
National Bureau of Economic Research
Chang, Roberto; Velasco, Andrés
2020-04
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Statistical Decision Properties of Imprecise Trials Assessing COVID-19 Drugs
From the Abstract: "As the COVID-19 [coronavirus disease 2019] pandemic progresses, researchers are reporting findings of randomized trials comparing standard care with care augmented by experimental drugs. The trials have small sample sizes, so estimates of treatment effects are imprecise. Seeing imprecision, clinicians reading research articles may find it difficult to decide when to treat patients with experimental drugs. Whatever decision criterion one uses, there is always some probability that random variation in trial outcomes will lead to prescribing sub-optimal treatments. A conventional practice when comparing standard care and an innovation is to choose the innovation only if the estimated treatment effect is positive and statistically significant. This practice defers to standard care as the status quo. To evaluate decision criteria, we use the concept of near optimality, which jointly considers the probability and magnitude of decision errors. An appealing decision criterion from this perspective is the empirical success rule, which chooses the treatment with the highest observed average patient outcome in the trial. Considering the design of recent and ongoing COVID-19 trials, we show that the empirical success rule yields treatment results that are much closer to optimal than those generated by prevailing decision criteria based on hypothesis tests."
National Bureau of Economic Research
Manski, Charles F.; Tetenov, Aleksey
2020-06
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Macroeconomics of a Pandemic: A Minimalist Model
From the Abstract: "We build a minimalist model of the macroeconomics of a pandemic, with two essential components. The first is productivity-related: if the virus forces firms to shed labor beyond a certain threshold, productivity suffers. The second component is a credit market imperfection: because lenders cannot be sure a borrower will repay, they only lend against collateral. Expected productivity determines collateral value; in turn, collateral value can limit borrowing and productivity. As a result, adverse shocks have large magnification effects, in an unemployment and asset price deflation doom loop. There may be multiple equilibria, so that pessimistic expectations can push the economy to a bad equilibrium with limited borrowing and low employment and productivity. The model helps identify policies to fight the effects of the pandemic. Traditional expansionary fiscal policy has no beneficial effects, while cutting interest rates has a limited effect if the initial real interest rate is low. By contrast, several unconventional policies, including wage subsidies, helicopter drops of liquid assets, equity injections, and loan guarantees, can keep the economy in a full-employment, high-productivity equilibrium. Such policies can be fiscally expensive, so their implementation is feasible only with ample fiscal space or emergency financing from abroad."
National Bureau of Economic Research
Céspedes, Luis Felipe; Chang, Roberto; Velasco, Andrés
2020-05
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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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Trading Off Consumption and COVID-19 Deaths
From the Abstract: "This note develops a framework for thinking about the following question: What is the maximum amount of consumption that a utilitarian welfare function would be willing to trade off to avoid the deaths associated with the pandemic? The answer depends crucially on the mortality rate associated with the coronavirus. If the mortality rate averages 0.81%, taken from the Imperial College London study, our answer is 41% of one year's consumption. If the mortality rate instead averages 0.44% across age groups, our answer is 28%."
National Bureau of Economic Research
Hall, Robert E.; Jones, Charles I. (Charles Irving); Klenow, Peter J.
2020-06
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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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Estimating Probabilities of Success of Vaccine and Other Anti-Infective Therapeutic Development Programs
From the Abstract: "A key driver in biopharmaceutical investment decisions is the probability of success of a drug development program. We estimate the probabilities of success (PoSs) of clinical trials for vaccines and other anti-infective therapeutics using 43,414 unique triplets of clinical trial, drug, and disease between January 1, 2000, and January 7, 2020, yielding 2,544 vaccine programs and 6,829 nonvaccine programs targeting infectious diseases. The overall estimated PoS for an industry-sponsored vaccine program is 39.6%, and 16.3% for an industry-sponsored anti=infective therapeutic. Among industry-sponsored vaccines programs, only 12 out of 27 disease categories have seen at least one approval, with the most successful being against monkeypox (100%), rotavirus (78.7%), and Japanese encephalitis (67.6%). The three infectious diseases with the highest PoSs for industry-sponsored nonvaccine therapeutics are smallpox (100%), cytomegalovirus (CMV) infection (31.8%), and onychomycosis (29.8%). Non-industry-sponsored vaccine and nonvaccine development programs have lower overall PoSs: 6.8% and 8.2%, respectively. Viruses involved in recent outbreaks--Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS), Ebola, and Zika--have had a combined total of only 45 nonvaccine development programs initiated over the past two decades, and no approved therapy to date. These estimates offer guidance both to biopharma investors as well as to policymakers seeking to identify areas most likely to be underserved by private sector engagement and in need of public sector support."
National Bureau of Economic Research
Lo, Andrew W. (Andrew Wen-Chuan); Siah, Kien Wei; Wong, Chi Heem
2020-05
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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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Effects of Social Distancing Policy on Labor Market Outcomes
From the Abstract: "This paper examines the impact of the social distancing policies states adopted between March and April of 2020 in response to the COVID-19 [coronavirus disease 2019] epidemic. These actions, together with voluntary social distancing, appear to have reduced the rate of new COVID-19 cases and deaths, but raised concerns about the costs experienced by workers and businesses. Estimates from difference-indifference models that leverage cross-state variation in the timing of business closures and stay-at-home mandates suggest that the employment rate fell by about 1.7 percentage points for every extra 10 days that a state experienced a stay-at-home mandate during the period March 12-April 12, 2020; select business closure laws were associated with similar employment effects."
National Bureau of Economic Research
Gupta, Sumedha; Montenovo, Laura; Nguyen, Thuy D. . . .
2020-05
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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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Supply and Demand in Disaggregated Keynesian Economies with an Application to the COVID-19 Crisis
From the Abstract: "We study supply and demand shocks in a general disaggregated model with multiple sectors, factors, and input-output linkages, as well as downward nominal wage rigidities and a zero lower bound constraint. We use the model to understand how the Covid-19 [coronavirus disease 2019] crisis, an omnibus of supply and demand shocks, affects output, unemployment, inflation, and leads to the coexistence of tight and slack labor markets. Under some conditions, the details of the production network can be summarized by simple sufficient statistics that we use to conduct global comparative statics. Negative sectoral supply shocks and sectoral demand shocks are stagflationary, whereas negative intertemporal demand shocks are deflationary. Complementarities magnify Keynesian spillovers for the former shocks but mitigate them for the latter. We illustrate the intuition using a nonlinear AS-AD [aggregate supply-aggregate demand] representation. In a quantitative model of the US calibrated to current disaggregated data, sectoral supply and demand shocks on their own generate more than 10% inflation, and negative intertemporal demand shocks on their own generate 7% deflation. Both types of shocks are necessary to capture the disaggregated data, each explains about half the reduction in real GDP [gross domestic product], and putting both together results in 0:3% inflation and as much as 10% Keynesian unemployment in April 2020. Nevertheless, aggregate demand stimulus is only about a third as effective as in a typical recession where all labor markets are slack. More targeted forms of demand stimulus are more effective."
National Bureau of Economic Research
Baqaee, David Rezza; Farhi, Emmanuel
2020-05
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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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Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey
From the Abstract: "In order to understand the impact of the COVID-19 [coronavirus disease 2019] pandemic on higher education, we surveyed approximately 1,500 students at one of the largest public institutions in the United States using an instrument designed to recover the causal impact of the pandemic on students' current and expected outcomes. Results show large negative effects across many dimensions. Due to COVID-19: 13% of students have delayed graduation, 40% lost a job, internship, or a job offer, and 29% expect to earn less at age 35. Moreover, these effects have been highly heterogeneous. One quarter of students increased their study time by more than 4 hours per week due to COVID-19, while another quarter decreased their study time by more than 5 hours per week. This heterogeneity often followed existing socioeconomic divides; lower-income students are 55% more likely to have delayed graduation due to COVID-19 than their higher-income peers. Finally, we show that the economic and health related shocks induced by COVID-19 vary systematically by socioeconomic factors and constitute key mediators in explaining the large (and heterogeneous) effects of the pandemic."
National Bureau of Economic Research
Aucejo, Esteban; French, Jacob F.; Ugalde Araya, Maria Paola . . .
2020-06
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What Does and Does Not Correlate with COVID-19 Death Rates
From the Abstract: "We correlate county-level COVID-19 [coronavirus disease 2019] death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates."
National Bureau of Economic Research
Knittel, Christopher R.; Ozaltun, Bora
2020-06
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Social Distancing and Social Capital: Why U.S. Counties Respond Differently to COVID-19
From the Abstract: "Since social distancing is the primary strategy for slowing the spread of many diseases, understanding why U.S. counties respond differently to COVID-19 [coronavirus disease 2019] is critical for designing effective public policies. Using daily data from about 45 million mobile phones to measure social distancing we examine how counties responded to both local COVID-19 cases and statewide shelter-in-place orders. We find that social distancing increases more in response to cases and official orders in counties where individuals historically (1) engaged less in community activities and (2) demonstrated greater willingness to incur individual costs to contribute to social objectives. Our work highlights the importance of these two features of social capital-- community engagement and individual commitment to societal institutions--in formulating public health policies."
National Bureau of Economic Research
Ding, Wenzhi; Levine, Ross; Lin, Chen . . .
2020-06
