Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities

Benitez, Joseph; Courtemanche, Charles; Yelowitz, Aaron

doi:10.3386/w27592

Cited by 15 publications

(6 citation statements)

References 41 publications

(15 reference statements)

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“…Given the crucial role of private beliefs in shaping behavior, an important question is how individual beliefs are formed and whether they reflect reality. Unlike prior work in the context of COVID-19 (Bordalo et al 2020), we find that differences in the perception of risks across demographic subgroups and different geographies generally correlate with known realities of the risk of contracting the disease (Benitez et al 2020; Ford et al 2020; Richardson et al 2020; Polyakova et al 2020; Polyakova et al 2021). This finding of a positive relationship between risk perceptions and protective behaviors in the context of the COVID-19 pandemic is consistent with other contemporaneous studies (Dryhurst et al 2020; Heffetz and Ishai 2021).…”

Section: Discussioncontrasting

confidence: 97%

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*

Bundorf

DeMatteis

Miller

et al. 2022

Preprint

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We analyze data from a survey we administered during the COVID-19 pandemic to investigate the relationship between people’s subjective beliefs about risks and their private protective behaviors. On average, people substantially overestimate the absolute level of risk associated with economic activity, but have correct signals about their relative risk. Subjective risk beliefs are predictive of changes in economic activities independently of government policies. Government mandates restricting economic behavior, in turn, attenuate the relationship between subjective risk beliefs and protective behaviors.

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Section: Discussioncontrasting

confidence: 97%

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*

Bundorf

DeMatteis

Miller

et al. 2022

Preprint

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“…Moving beyond the baseline specification, I introduce a set of additional variables that have been highlighted in the literature as potential drivers of the local COVID-19 toll (Panel B, Table 1). US-based research has found a connection between worse local COVID-19 outcomes and lower schooling levels, or the presence of racial minorities Benitez et al, 2020;Wiemers et al, 2020). These factors could play an even more important role in Brazil, given the country's long history of racial disparities and inequalities in access to higher education.…”

Section: Results At the End Of The First Year Of The Pandemicmentioning

confidence: 99%

Why Does COVID-19 Affect Some Cities More than Others?: Evidence from the First Year of the Pandemic in Brazil

Chauvin¹

2021

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This paper investigates what explains the variation in impacts of COVID-19 across Brazilian cities. I assemble data from over 2,500 cities on COVID-19 cases and deaths, population mobility, and local policy responses. I study how these outcomes correlate with pre-pandemic local characteristics, drawing comparisons with existing US estimates when possible. As in the United States, the connections between city characteristics and outcomes in Brazil can evolve over time, with some early correlations fading as the pandemic entered a second wave. Population density is associated with greater local impact of the disease in both countries. However, in contrast to the United States, the pandemic in Brazil took a greater toll in cities with higher income levels consistent with the fact that higher incomes correlate with greater mobility in Brazil. Socioeconomic vulnerabilities, such as the presence of slums and high residential crowding, correlate with higher death rates per capita. Cities with such vulnerabilities in Brazil suffered higher COVID-19 death rates despite their residents' greater propensity to stay home. Policy responses do not appear to drive these connections.

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“…It also limits our statistical power to detect potentially important differences across subgroups. Future research, with larger sample sizes, could beneficially compare differences in program participation based on residence in areas experiencing higher COVID-19 case rates [28]. Third, as with all surveys on public program participation, there is likely to be some under-identification of program participation [29].…”

Section: Discussionmentioning

confidence: 99%

Access and enrollment in safety net programs in the wake of COVID-19: A national cross-sectional survey

et al. 2020

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The global COVID-19 pandemic is causing unprecedented job loss and financial strain. It is unclear how those most directly experiencing economic impacts may seek assistance from disparate safety net programs. To identify self-reported economic hardship and enrollment in major safety net programs before and early in the COVID-19 pandemic, we compared individuals with COVID-19 related employment or earnings reduction with other individuals. We created a set of questions related to COVID-19 economic impact that was added to a cross-sectional, nationally representative online survey of American adults (age �18, English-speaking) in the AmeriSpeak panel fielded from April 23-27, 2020. All analyses were weighted to account for survey non-response and known oversampling probabilities. We calculated unadjusted bivariate differences, comparing people with and without COVID-19 employment and earnings reductions with other individuals. Our study looked primarily at awareness and enrollment in seven major safety net programs before and since the pandemic (Medicaid, health insurance marketplaces/exchanges, unemployment insurance, food pantries/free meals, housing/renters assistance, SNAP, and TANF). Overall, 28.1% of all individuals experienced an employment reduction (job loss or reduced earnings). Prior to the pandemic, 39.0% of the sample was enrolled in �1 safety net program, and 50.0% of individuals who subsequently experienced COVID-19 employment reduction were enrolled in at least one safety net program. Those who experienced COVID-19 employment reduction versus those who did not were significantly more likely to have applied or enrolled in �1 program (45.9% versus 11.7%, p<0.001) and also significantly more likely to specifically have enrolled in unemployment insurance (29.4% versus 5.4%, p < .001) and SNAP (16.8% versus 2.8%, p = 0.028). The economic devastation from COVID-19 increases the importance of a robust safety net.

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Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities

Cited by 15 publications

References 41 publications

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*

Why Does COVID-19 Affect Some Cities More than Others?: Evidence from the First Year of the Pandemic in Brazil

Access and enrollment in safety net programs in the wake of COVID-19: A national cross-sectional survey

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Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities

Cited by 15 publications

References 41 publications

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic*

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic*

Why Does COVID-19 Affect Some Cities More than Others?: Evidence from the First Year of the Pandemic in Brazil

Access and enrollment in safety net programs in the wake of COVID-19: A national cross-sectional survey

Contact Info

Product

Resources

About

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*

Risk Perceptions and Private Protective Behaviors: Evidence from COVID-19 Pandemic^*