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  • Working Paper: To Mask or Not to Mask
    Published: Thursday July 23, 2020, 02:45:49 PM
    Author(s): Travis Ng
    Abstract: Some governments implement mandatory mask policies partly based on the scientific studies that show mask-wearing helps "flatten the curve." Taking mask-wearing as exogenous behaviors makes these studies unable to tell when and why people would comply. I endogenize individuals' mask-wearing decision in a model in which selfish individuals know that masks protect others more. Their equilibrium decisions exhibit inter-dependence. A parameter that proxies the population density determines whether mask-wearing are substitutes or complements among individuals. Without relying on behavioral assumptions and ad hoc differences, the model offers a rational explanation of the polar opposite cases among equally-crowded cities: some in which almost everyone wears masks, but few do so in others. Comparing social and private incentives, the model identifies the scenarios wherein mandatory mask policies benefit the society and wherein people comply with such policies. It highlights how economics differs from science in calculating the effectiveness of mask-wearing in containing the virus.
    Keywords: COVID-19, Infection, Mask, Population Density
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  • Working Paper: Causal impact of masks, policies, behavior on early Covid-19 pandemic in the U.S.
    Published: Thursday July 2, 2020, 12:00:20 PM
    Author(s): Victor Chernozhukov, Hiroyuki Kasahara, Paul Schrimpf
    Abstract: This paper evaluates the dynamic impact of various policies adopted by US states on the growth rates of confirmed Covid-19 cases and deaths as well as social distancing behavior measured by Google Mobility Reports, where we take into consideration people’s voluntary behavioral response to new information of transmission risks. Our analysis finds that both policies and information on transmission risks are important determinants of Covid-19 cases and deaths and shows that a change in policies explains a large fraction of observed changes in social distancing behavior. Our counterfactual experiments suggest that nationally mandating face masks for employees on April 1st could have reduced the growth rate of cases and deaths by more than 10 percentage points in late April, and could have led to as much as 17 to 55 percent less deaths nationally by the end of May, which roughly translates into 17 to 55 thousand saved lives. Our estimates imply that removing non-essential business closures (while maintaining school closures, restrictions on movie theaters and restaurants) could have led to -20 to 60 percent more cases and deaths by the end of May. We also find that, without stay-at-home orders, cases would have been larger by 25 to 170 percent, which implies that 0.5 to 3.4 million more Americans could have been infected if stay-at-home orders had not been implemented. Finally, not having implemented any policies could have led to at least a 7 fold increase with an uninformative upper bound in cases (and deaths) by the end of May in the US, with considerable uncertainty over the effects of school closures, which had little cross-sectional variation.
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  • Working Paper: Political polarization and cooperation during a pandemic
    Published: Tuesday June 23, 2020, 10:29:06 AM
    Author(s): Kirsten Cornelson, Boriana Miloucheva
    Abstract: In this paper, we examine the relationship between political polarization and individuals' willingness to contribute to the public good by engaging in preventative behaviors against COVID-19. Using a sample of individuals from states where the last gubernatorial election was close, we first show that individuals engage in fewer preventative behaviors when the governor of their state is from the opposite party. We also show that this effect is concentrated among moderate individuals who live in polarized states, and that it is strongest when the state has been relatively forceful in combating COVID-19. The results appear to be driven by opposite-party supporters reducing compliance, rather than own-party supporters increasing compliance. We estimate that the opposite-party effect increased COVID cases by around 1%.
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  • Working Paper: The Effect of Social Distancing Mandates on Small Commercial Electricity Users across Ontario
    Published: Monday June 8, 2020, 12:03:06 PM
    Author(s): Abdelrahman Amer, Angelo Melino, Aloysius Siow
    Abstract: Social distancing mandates were and are used to slow the dffusion of Covid-19 in Ontario. With the exception of Toronto, these mandates are uniform across the province. Electricity consumption is highly correlated with socioeconomic activity. We used the year over year decline in electricity usage of small businesses as a proxy for voluntary and mandated social distancing. Our identification of voluntary social distancing relies on infrequent changes in province wide government mandates. We use both within and across Public Health Units changes in daily electricity usage in response to same day news about disease dffusion to measure the extent of voluntary social distancing, while holding mandates constant. Our estimates show that residents change how they practice social distancing based on same day reports of new infections in their community. In areas with low infection rates, most of their behavior are determined by the provincial wide mandates. These findings suggest that public health units should also provide accurate and timely public information on the diffusion of the disease because residents adjust quickly to that information. Easing social distancing mandates in locations with few cases would lead to increased economic activity in a safer way than uniformly lifting social distancing practices across the province.
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  • Working Paper: Estimates of COVID-19 Cases Across Canadian Provinces
    Published: Monday June 8, 2020, 11:50:42 AM
    Author(s): David Benatia, Raphael Godefroy, Joshua Lewis
    Abstract: This paper estimates population infection rates from coronavirus disease 2019 (COVID-19) across four Canadian provinces from late March to early May 2020. The analysis combines daily data on the numbers of conducted tests and diagnosed cases with a sample selection model that corrects for non-random testing. The estimated population infection rates were 1.7 - 2.6 percent in Quebec, 0.7 - 1.4 in Ontario, 0.5 - 1.2 percent in Alberta, and 0.2 - 0.4 percent in B.C over the sample period. The results suggest widespread undiagnosed COVID-19 infection. For each identified case by mid-April, we estimate that there were roughly 12 population infections.
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