U.S. Economic Activity During the Early Weeks of the SARS-Cov-2 Outbreak

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.

Reopening Scenarios

We use a five-age epidemiological model, combined with 66-sector economic accounting, to address a variety of questions concerning the economic reopening. We calibrate/estimate the model using contact survey data and data on weekly historical individual actions and non-pharmaceutical interventions in the weeks ending March 8 – May 16, 2020. Going forward, we model a decision-maker (governor) as following reopening guidelines like those proposed by the White House and the CDC. The sectoral accounting, combined with information on personal proximity and ability to work from home by sector, make it possible to construct a GDP-to-Risk index of which sectors provide the greatest increment in GDP per marginal increase in R0. Through simulations, we find that: a strong economic reopening is possible;a “smart” reopening, preferencing some sectors over others, makes only modest improvements over a broad reopening;and all this hinges on retaining strong restrictions on non-work social contacts. If non-work contacts – going to bars, shopping without social distancing and masks, large group gatherings, etc. – return only half-way to the pre-COVID-19 baseline, the current decline in deaths reverses leading to a second wave of business closures.

Identification and Estimation of Undetected COVID-19 Cases Using Testing Data from Iceland

In the early stages of the COVID-19 pandemic, international testing efforts tended to target individuals whose symptoms and/or jobs placed them at a high presumed risk of infection. Testing regimes of this sort potentially result in a high proportion of cases going undetected. Quantifying this parameter, which we refer to as the undetected rate, is an important contribution to the analysis of the early spread of the SARS-CoV-2 virus. We show that partial identification techniques can credibly deal with the data problems that common COVID-19 testing programs induce (i.e. excluding quarantined individuals from testing and low participation in random screening programs). We use public data from two Icelandic testing regimes during the first month of the outbreak and estimate an identified interval for the undetected rate. Our main approach estimates that the undetected rate was between 89% and 93% before the medical system broadened its eligibility criteria and between 80% and 90% after.

Economic Benefits of COVID-19 Screening Tests

We assess the economic value of screening testing programs as a policy response to the ongoing COVID-19 pandemic. We find that the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs far exceed their costs, with the ratio of economic benefits to costs typically in the range of 4-15 (depending on program details), not counting the monetized value of lives saved. Unless the screening test is highly specific, however, the signal value of the screening test alone is low, leading to concerns about adherence. Confirmatory testing increases the net economic benefits of screening tests by reducing the number of healthy workers in quarantine and by increasing adherence to quarantine measures. The analysis is undertaken using a behavioral SIR model for the United States with 5 age groups, 66 economic sectors, screening and diagnostic testing, and partial adherence to instructions to quarantine or to isolate.

Data Gaps and the Policy Response to the Novel Coronavirus

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 ß 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 ß, then determining the path of ß that trades off the economic cost against the cost of excess lives lost by overwhelming the health care system.

Reopening the Coronavirus-Closed Economy

From the Abstract: The COVID-19 [coronavirus disease 2019] pandemic and resulting shutdown of much of the United States to attempt to contain the SARSCoV-2 [severe acute respiratory syndrome coronavirus 2] virus produced a sudden and unprecedented economic contraction. The questions the nation face today are how and when to reopen the economy and get people back to work, while also achieving public health goals. This note briefly reviews the main considerations in answering these questions, drawing from the economic research conducted over the past eight weeks. This research can and should help the public and policymakers evaluate the difficult choices that lie ahead of us so we can avoid the worst case outcome - large numbers of deaths and a prolonged, deep, and painful recession.COVID-19 (Disease);Economic policy;Disaster recovery