We extend the baseline Susceptible-Exposed-Infectious-Recovered (SEIR) infectious disease epidemiology model to understand the role of testing and case-dependent quarantine. During a period of asymptomatic infection, testing can reveal infection that otherwise would only be revealed later when symptoms develop. Along with those displaying symptoms, such individuals are deemed known positive cases. Quarantine policy is case-dependent in that it can depend on whether a case is unknown, known positive, known negative, or recovered. Testing therefore makes possible the identification and quarantine of infected individuals and release of non-infected individuals. We fix a quarantine technology—a parameter determining the differential rate of transmission in quarantine—and compare simple testing and quarantine policies. We start with a baseline quarantine-only policy that replicates the rate at which individuals are entering quarantine in the US in March, 2020. We show that the total deaths that occur under this policy can occur under looser quarantine measures and a substantial increase in random testing of asymptomatic individuals. Testing at a higher rate in conjunction with targeted quarantine policies can (i) dampen the economic impact of the coronavirus and (ii) reduce peak symptomatic infections—relevant for hospital capacity constraints. Our model can be plugged into richer quantitative extensions of the SEIR model of the kind currently being used to forecast the effects of public health and economic policies.

Citation

Berger, D, K Herkenhoff and S Mongey (eds) (2020), “An SEIR Infectious Disease Model with Testing and Conditional Quarantine”, COVID Economics N/A. https://cepr.org/node/390418

We argue that occupations are a key explanatory variable for understanding the early transmission of COVID-19 in New York City, finding that they play a larger role than other key demographics such as race or income. Moreover, we find no evidence that commuting patterns are significant after controlling for occupations. However, racial disparities still persist for Blacks and Hispanics compared to Whites, although their magnitudes are economically small. We perform a daily analysis over a range of one month to evaluate how different channels interact with the progression of the pandemic and the stay-at-home order. While the coefficient magnitudes of many occupations and demographics decrease, we find evidence consistent with higher intra-household contagion over time. Finally, our results also suggest that crowded spaces play a more important role than population density in the spread of COVID-19.

Citation

Almagro, M and A Orane-Hutchinson (eds) (2020), “The determinants of the differential exposure to COVID-19 in New York City and their evolution over time”, COVID Economics N/A. https://cepr.org/node/390419

This article presents a spatial analysis of COVID-19 mortality rates across England and Wales in the early part of the pandemic (3/January/2020 to 27/March/2020). It assesses whether cultural and/or economic discrimination enhanced the vulnerability of groups of people and places. We used data on lung cancer deaths in non-pandemic times as an instrument for mortality rates during the pandemic and explored the relationship between COVID-19 mortalityrates and the Brexit vote. Results suggest that the effects of cultural discrimination on COVID-19-related mortality is five times greater than the economic effect, and deaths were 19 percent higher in pro-Brexit areas

Citation

Boy, F, A Tubadji and D Webber (eds) (2020), “Cultural and Economic Discrimination by the Great Leveller: The COVID-19 Pandemic in the UK”, COVID Economics N/A. https://cepr.org/node/390420

Older adults and those with underlying medical conditions seem especially vulnerable to the COVID-19 pandemic. The U.S. government’s efforts to contain the infection, on the other hand, have a disproportionate impact on the working age population. To be able to capture the impact of the pandemic and the resulting mitigation efforts on a population that is heterogeneous by age, income and health status, we use an overlapping generations model that mimics the U.S. economy along those dimensions in 2020. We introduce an unexpected COVID-19 shock in the economy and examine the resulting impact on aggregate output, labor supply, savings, and consumption behavior of the different agents. We find that mitigation efforts that target certain age and health groups result in significantly smaller disruptions in the economy. Going forward, introducing subsidies to those with underlying health conditions and/or the elderly to self isolate might prove to be a useful path in opening up the economy.

Citation

Bairoliya, N and a imrohoroglu (eds) (2020), “Macroeconomic Consequences of Stay-At-Home Policies During the COVID-19 Pandemic”, COVID Economics N/A. https://cepr.org/node/390421

We investigate the effects of the COVID-19-induced shock in financial markets on aggregate venue selection/market share and market quality. We find that the shock is linked with an economically significant loss of market share by dark pools to lit exchanges. In line with theory, the loss appears linked to an increase in lit market volatility and a search for immediacy by traders active in stocks with dark trading access. The market quality implications of the reduction in dark trading are mixed: while it tempers COVID-19- linked liquidity decline in the lit market, it exacerbates the loss of informational efficiency.

Citation

Ibikunle, G and K Rzayev (eds) (2020), “Volatility, dark trading and market quality: evidence from the 2020 COVID-19 pandemic-driven market volatility”, COVID Economics N/A. https://cepr.org/node/390422

This study investigates the effectiveness of lockdown and testing in curbing the transmission of Covid-19 infection. Using a combination of data from the European Centre for Disease Prevention, Roser et al. (2020) and Hale et al. (2020), we carried cross-country analysis covering 69 countries across the 5 continents. To take care of the fact that the number of Covid-19 cases strongly depend on its own lag values, we used two-step system GMM for the estimations. Unlike prior studies that measure lockdown in terms of a fixed intervention date, we relied on the stringency index from Hale et al. (2020) that accommodates for the gradual lockdown measures in different countries. We found that an exogenous lockdown significantly affects the number of confirmed cases after 7 days of its implementation and its lag effects are intact even after 21 days of its implementation. A one unit change in the lockdown index decreases the total number of confirmed cases by 0.19 percent. Testing has no significant effects for at least 14 days after its implementation. However, after 21 days of its implementation, its effects become significant with ?0.03 to ?0.05 elasticity value.

Citation

Ajala, O and A Ullah (eds) (2020), “Do Lockdown and Testing Help in Curbing Covid-19 Transmission?”, COVID Economics N/A. https://cepr.org/node/390423

The paper uses Google mobility data to identify the determinants of social distancing during the 2020 COVID-19 outbreak. We find for the U.S. that much of the decrease in mobility is voluntary driven by the number of COVID-19 cases and proxying for greater awareness of risk. Non-Pharmaceutical Interventions (NPI) such as closing nonessential business, sheltering in place, school closings are also effective, although with a total contribution dwarfed by the voluntary. This suggests that much social distancing will happen regardless of the presence of NPIs and that restrictions may often function more like a coordinating device among increasingly predisposed individuals than repressive measures per se. These results are consistent across countries income groups with only the poorest (LICs) showing limited effect of NPIs , and no voluntary component, consistent with resistance to abandon sources of livelihood. We also confirm the direct impact of the voluntary component on economic activity by showing that the majority of the fall in restaurant reservations in the U.S., and movie spending in Sweden occurred before the imposition of any NPIs. Widespread voluntary de-mobilization implies that releasing constraints may not yield a V shaped recovery if the reduction in COVID risk not credible.

Citation

Maloney, W and T Taskin (eds) (2020), “Determinants of Social Distancing during COVID-19: A Global View”, COVID Economics N/A. https://cepr.org/node/390424

Early indicators suggest that startup activity is heavily disrupted by the COVID-19 pandemic and the associated lockdown. At the same time, empirical evidence has shown that such disturbances may have long-lasting effects on aggregate employment. This paper presents a calculator which can be used to compute these effects under different scenarios regarding (i) the number of startups, (ii) the growth potential of startups, and (iii) the survival rate of young firms. We find that employment losses can be substantial and last for more than a decade, even when the assumed slump in startup activity is only short-lived.

Citation

Sedlacek, P and V Sterk (eds) (2020), “Startups and Employment Following the COVID-19 Pandemic: A Calculator”, COVID Economics N/A. https://cepr.org/node/391023