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Economic Impact of COVID-19
March 3, 2021

The Evolving Relationship Between COVID-19 and
Financial Distress
Article by: Kartik B. Athreya, José Mustre-del-Río and Juan M. Sanchez

The COVID-19 pandemic has touched every corner of the United States, but some regions
have been hit harder than others. Financially distressed areas of the country in particular
may face tougher challenges, as people who are more nancially vulnerable are less able to
weather adverse events.1 Indeed, nancial distress can be thought of as an "economic
preexisting condition" because it is concentrated among a small proportion of individuals in
persistent trouble and is long-lasting.2
To assess whether the pandemic has spread more in nancially distressed areas, Chart 1
plots the shares of COVID-19 cases in counties in each quintile of nancial distress,
measured by the percentage of individuals in each county who were at least 30 days
delinquent on bank card debt in 2018 (that is, pre-pandemic).3 The lowest quintile of
nancial distress, Q1, contains counties with the smallest fraction of nancially distressed
individuals, while the highest quintile of nancial distress, Q5, contains counties with the
highest fraction of nancially distressed individuals.

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The chart shows that except for the rst few weeks of the pandemic, counties with higher
nancial distress have accounted for a larger share of total COVID-19 infections than
counties with lower nancial distress. For example, in mid-August, counties in Q5 accounted
for nearly 30 percent (1.5 million) of the roughly 5 million recorded cases in the United
States. In contrast, counties in Q1 accounted for only 13 percent (0.65 million). This
represents more than a two-fold di erence in the infection burden of the pandemic across
groups of counties that account for the same share of the U.S. population.
However, Chart 1 also shows that the cumulative case burden of the pandemic appears to
have evened out more recently. As of January 31, counties in Q5 accounted for about 21
percent (5.5 million) of total cases in the United States, while counties in Q1 accounted for
about 18 percent (4.8 million). Across all quintiles, the shares were close to 20 percent,
which is what we would expect if infections were evenly distributed across the United States
regardless of nancial distress.
Measuring the pandemic's burden in terms of deaths shows somewhat more uneven
patterns. Chart 2 shows that through most of the pandemic, regions with higher nancial
distress have shouldered a larger share of COVID-19-related deaths. For example, by midSeptember, counties in Q5 (maroon line) accounted for nearly 30 percent (58,000) of the
roughly 190,000 recorded deaths in the United States. In contrast, counties in Q1 (blue line)
accounted for only 12 percent (23,000) of all deaths in the United States. Again, this is more
than a two-fold di erence in the death burden of the pandemic across groups of counties
with similar population sizes.
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Importantly, Chart 2 shows that deaths across quintiles of nancial distress have not
converged to the same extent as cases. As of January 31, counties in Q5 accounted for
about 23 percent (100,000) of all COVID-19 deaths in the United States, while Q1 accounted
for about 15 percent (67,000). If deaths were evenly distributed across the United States
regardless of nancial distress, we would expect these shares to be closer to 20 percent.
That said, the gap in deaths may narrow still, as deaths tend to lag cases.
A natural question is whether the di erence in mortality across regions may be due to
other variables that correlate with nancial distress. For example, counties in higher
nancial distress also have higher incidences of tobacco usage and adult obesity. Although
di erences in these health metrics among high- and low-distress areas are signi cant, they
are not large enough to explain the di erences in COVID-19-related deaths we observe.
Similarly, di erences in access to health care do not fully explain the mortality di erences,
either.4 Moreover, survey evidence suggests mask usage is actually a bit higher in areas of
higher nancial distress, so di erences in preventative actions cannot explain the mortality
di erences.5
Instead, our results may be indicative of the role that wealth plays in determining life
expectancy in the United States.6 Household income and wealth tend to fall as the
incidence of nancial distress rises.7 Thus, the di erences in COVID-19 mortality we
currently observe may persist, as they do for other causes of death.

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Kartik Athreya is executive vice president and director of research at the Federal Reserve
Bank of Richmond. José Mustre-del-Río is a research and policy o cer at the Federal
Reserve Bank of Kansas City. Juan M. Sánchez is an assistant vice president and Olivia
Wilkinson is a research associate at the Federal Reserve Bank of St. Louis.

1

Athreya, Kartik, Ryan Mather, José Mustre-del-Río, and Juan M. Sánchez. "Household Financial

Distress and the Burden of 'Aggregate' Shocks." Federal Reserve Bank of Kansas City Research
Working Paper No. 20-13, September 2020.
2

Athreya, Kartik, Ryan Mather, José Mustre-del-Río, and Juan M. Sánchez. "The Persistence of

Financial Distress." Review of Financial Studies, February 2019, vol. 32, no. 10, pp. 3851-3883.
3

We combine data from the Federal Reserve Bank of New York Consumer Credit Panel (FRBNY
CCP) and publicly available, county-level data on COVID-19 cases and deaths. Our resulting data
covers 98.4 percent of all COVID-19 cases and 98 percent of all COVID-19 deaths.
4

We measure access to health care by looking at the number of hospitals per 100,000 residents
at the county level.
5

We combine our FRBNY CCP data with mask usage data from the New York Times and Dynata
based on roughly 250,000 interviews conducted by Dynata from July 2 to July 14.
6

Reuell, Peter. "For Life Expectancy, Money Matters." Harvard Gazette, Apr. 11, 2016.

7

Athreya et al. (2020).

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Views expressed in this article are those of the authors and not necessarily those of their
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