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Economic Impact of COVID-19

March 23, 2020

COVID-19 and Households’ Financial Distress

Part 1: Employment Vulnerability and (Financial) Pre-Existing Conditions

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In this video, the first in a three-part series, Richmond Fed Research Director Kartik Athreya shares research that he and colleagues at the Kansas City and St. Louis Feds have conducted to measure the financial toll COVID-19 is taking on workers in the food and accommodation sectors.

COVID-19, and the public's reaction to pursue social distancing, will inevitably affect different industries in different ways. Some jobs, like computer programming and farming, require little face-to-face interaction with clients and can often be completed from home. Others, however — particularly those that specialize in social services like accommodation and food services (think restaurants) — will face significant challenges in these conditions. And while sectors will be hit unevenly, so too will people: A general feature of our economy is that relatively secure and high-paying jobs are the ones most often easily transferred to remote locations, while already-insecure and relatively low-paying jobs are overwhelmingly less suited to remote delivery.

These features imply that the burden of this illness will not only be borne unevenly across occupations, but that the largest burdens will fall on populations that are already the most vulnerable to economic shocks. In a recent working paper, we showed that communities in which a higher percentage of people are financially distressed will cut their consumption much more in reaction to a given decline in wealth than communities where a lower percentage of people are distressed. Moreover, the reductions in consumption in some geographies will likely create further distress at the community level, as research following the Great Recession suggests. On the scale of an entire economy, then, we would expect that losses to income or wealth that fall most heavily on people who are vulnerable in this way will have a greater overall effect than losses that fall on people who are more financially stable.

To predict how COVID-19 may affect household consumption and balance sheets, we will focus in this post on the Accommodation and Food sector, which, as we note above, is particularly vulnerable to a shock that keeps people from gathering. It is also a large sector, representing close to 10 percent of total employment in the United States and an even larger proportion of the sectors we view as likely to be the most affected by social distancing guidelines. We will examine whether this sector tends to employ people from zip codes with high financial distress. By "financial distress," we mean the percentage of people who go 30 days or more delinquent on a credit card payment over the course of a year.1 Difficulty making timely payments is likely a good indicator of an overall lack of financial capacity and, hence, of vulnerability to temporary shocks, especially severe ones like the one we are experiencing.

To do this, we divide all U.S. zip codes into five evenly sized groups, or "quintiles," defined by their incidence of financial distress. In what follows, we denote the zip codes with the lowest financial distress as group "one" and the zip codes with the highest financial distress as group "five." To obtain data on employment by industry and zip code, we utilize the Census LEHD LODES dataset.2

It is clear from this that, indeed, Accommodation and Food is an area of the U.S. economy where the most financially distressed are most often seen. Comparing the bottom quintile with the top, we see that roughly 11 percent of the most financially distressed group is working in this sector, while among the least financially distressed, the number is up to 40 percent lower (at 7 percent, roughly). The relationship is also systematic: The geographic regions of the country that are more financially distressed have a greater share of their employment located in Accommodation and Food. 

If there is better news, it is that Accommodation and Food — while critical and large in size — is perhaps understandably unique in the "double whammy" it features for workers. We show next that for a variety of other sectors there seems to be only a slight positive relationship between zip-code incidence of financial distress and the share of workers employed in potentially vulnerable industries.

Beginning with Arts, Entertainment, and Recreation, we see that the more financially distressed are not more likely to be part of this sector.


Similarly, we see that this holds also for Construction, Retail Trade, and Other services, in the following three figures.

One way of seeing that Accommodation and Food is especially susceptible is that, overall, 32 percent of workers in the highest quintile of financial distress work in the sectors examined here, while a similar proportion (roughly 27 percent) of workers in the lowest quintile also work in these sectors. Thus, the share of employment in vulnerable sectors taken as whole is not very different across zip codes with different distress levels. But our analysis makes clear that the picture of overall calm" hides the much clearer pattern within the sector that covers businesses whose services are clearly important for our lives and livelihoods.

In the next installment of this series, we will use the facts described here as inputs to a model we have developed to deliver an initial projection of what could be the possible response of household consumption and balance sheets to drops in income.


Katrik Athreya is executive vice president and director of research at the Federal Reserve Bank of Richmond. Ryan Mather is a research associate and Juan M. Sanchez is an assistant vice president at the Federal Reserve Bank of St. Louis. Jose Mustre-del-Rio is a senior economist at the Federal Reserve Bank of Kansas City.

 
1

The data used to construct this measure were used in our aforementioned working paper and came originally from the New York Federal Reserve/Equifax CCP dataset for 2018. It is available for public download here.

2

Importantly, we use data from the LEHD LODES database that are summed to the zip-code level in the area where the workers live, as opposed to the area where they work. Thus, even though a worker from a highly financially distressed zip code may work in a zip code with low financial distress, we will count their job as being filled by someone in the highly financially distressed community. Data are available at the two-digit level in the NAICS framework.


This article may be photocopied or reprinted in its entirety. Please credit the authors, source, and the Federal Reserve Bank of Richmond and include the italicized statement below.

Views expressed in this article are those of the authors and not necessarily those of the Federal Reserve Bank of Richmond or the Federal Reserve System.

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