As shown in the chart below, the researchers divided counties into five groups, or quintiles, based on a county’s level of financial distress — measured by the proportion of people who become 30 and 90 days delinquent on a credit card payment throughout the year. These quintiles are then plotted by date (x-axis) and number of confirmed COVID-19 cases (y-axis). The dotted vertical lines indicate when a quintile’s rate of infection reached the point of exponential growth — or the “liftoff” point. The chart shows that infections were initially concentrated in areas of lower financial distress and reached liftoff earlier while more distressed areas became infected later but are experiencing faster growth rates in and greater numbers of infections.
Researchers find a similar trend in the liftoff points for death rates, but have not found strong evidence that the death rates are different between areas of low and high financial distress. The authors acknowledge that widespread issues with the accuracy and availability of testing the U.S. have the potential to strongly influence these findings and how they should be interpreted. That is, the authors note that infection numbers in more financially stable areas may be overstated since people there tend to be wealthier, typically have greater access to medical services and information, and are more likely to get themselves tested than financially insecure people. However, given the similarities between the timelines of infections and deaths — which are unlikely to be selectively reported — the researchers expect that their conclusions are not being severely affected by the biases presented through uneven testing.
The research also examines which industries are most vulnerable to disruption from COVID-19 and the distribution of workers from financially distressed areas within them. Researchers categorize sectors based on their level of “socialness” — with highly social sectors such as accommodation and food services consisting of greater face-to-face interaction with customers and clients. Although fundamental to combating coronavirus, social distancing has the potential to disrupt highly social jobs — other than those deemed “essential” such as grocery retailers and medical workers — to a much greater degree than less social jobs like computer programming or farming.
Using the same quintile classification as before, the researchers found that workers from more financially distressed areas are more concentrated in highly social, highly vulnerable industries. Based on their previous research showing that people in areas of higher financial distress decrease their consumption more drastically than people in less distressed areas in reaction to declines in wealth, the researchers conclude that poorer areas are being hit harder by the slowdowns in these vulnerable industries caused by the pandemic. The researchers also conclude that the “essential” nature of several of these highly vulnerable sectors — with higher concentrations of people from financially distressed areas — provides a buffer from the impact of job losses. However, they also speculate that the higher concentrations of financially distressed people working in these essential jobs may lead to disproportionately higher rates of COVID-19 infection.
Another essay from the St. Louis Fed considers this and other research to provide three principles that should guide fiscal policy moving forward:
- Incentivize behavior to align with recognized public health objectives during the outbreak;
- Avoid concentrating the individual financial burden of the outbreak or the policy response to the outbreak; and,
- Implement these policies as quickly as possible, subject to some efficiency considerations.