Financial Distress and COVID-19
This 10-minute podcast was released April 14, 2020. (This podcast was recorded April 10, 2020.)
“We believe the households with more financial distress will be affected more by COVID-19 in the same way that it happened with the previous recession,” Juan Sanchez, an assistant vice president and economist at the Federal Reserve Bank of St. Louis. He talks with Maria Hasenstab, media relations coordinator at the St. Louis Fed, about COVID-19 related economic shocks and his research on financially distressed Americans. He talks about income declines, social distancing, disease spread and more.
Maria Hasenstab: Welcome to Timely Topics, a podcast series from the Federal Reserve Bank of St. Louis. I’m your host, Maria Hasenstab, and today I’m speaking with Juan Sanchez, an assistant vice president and economist at the St. Louis Fed.
Juan, thanks for joining me today.
Juan Sanchez: Thanks for having me.
Hasenstab: Juan, you’ve authored a couple recent blog posts on the St. Louis Fed’s On the Economy Blog, covering COVID-19 and financial distress. They seem to be an extension of some of your previous research covering financial distress. Why apply that line of research to the effects of COVID-19?
Sanchez: Our first paper with Kartik Athreya of the Richmond Fed and Jose Mustre-del-Rio from Kansas City Fed. So we look at financial distress defined as an individual as being financially distressed if you have used all the available credit. So you have a credit line and have used more than 90 % of the credit line. Or if this individual is late making credit payments. So we use credit record data to look at financial distress. And what we found in the paper is that about 10% of the U.S. population is persistently in financial distress. So the probability of being in financial distress a couple of years after being in financial distress is really high.
So this is financial distress, and so we know that the share of the population is persistently in financial distress. So within our second paper is to look at the information at the ZIP code level. So what we find at the ZIP code level, we see what is the share of the population in a given ZIP code that is in financial distress. What we found there is that there is like a very large dispersion. We have some ZIP codes that about like 5% of the population is in financial distress, and we have another ZIP code in which like 40% of the population is in financial distress. Like in very large dispersions.
So then we sorted the ZIP code according to financial distress, we made like five different groups, and we looked at the Great Recession—at the previous crisis in 2008—and the shock during that time was the declining house prices. So we look at how the declining house prices in the different ZIP code correlated with financial distress. What we found in that case is that the decline in house prices was larger in the areas that were already in financial distress before the crisis. And we used information for 2005 for financial distress, and we find that the decline in house prices between 2006 and 2009 was largely in the areas with more financial distress. So we wrote the paper about that.
And when we had started to look at COVID-19, so the first thing that we found and the reason why we applied that line of research to COVID-19 is that we believe the households with more financial distress will be affected more by COVID-19 in the same way that it happened with the previous recession. So that’s kind of how we got started in this line of research.
Hasenstab: Well that is really interesting. The first of your recent blog posts is titled “COVID-19 and Financial Distress: Employment Vulnerability.”In that piece you define two categories of industry that will be affected by social distancing in different ways. Can you tell us about those categories and how the social distancing from COVID-19 will affect them?
Sanchez: Yeah. So when we were trying to look at the effect on employment or on income, so one of the most obvious sectors that will be affected by social distancing is a sector that is called food and accommodation. So this includes restaurants, bars, so we also include other sectors in leisure and hospitality, and we include amusement parks, casinos. So all this activity will be hit very hard with the social distancing. So with the exercise we do in this blog post is to have the individuals in the different ZIP codes, we compute the share of individuals in the different ZIP code that is working in this food and accommodation sector.
What we find in that blog post is that the share of people, so over all the share people working in food and accommodation is close to 9%. What we find is that in the areas with the least financial distress, the share is lower. So if you take the 20% of the ZIP code with the least financial distress, the share is about 7%. If you take the 20% of ZIP code with the most financial distress, this share is 12%.
So our conclusion there is that through employment or through income, we think that areas with more financial distress will be affected more by COVID-19. So that’s the conclusion of the blog post.
Hasenstab: You write about how communities with a higher percentage of people who are financially distressed cut their consumption more in reaction to a given decline in wealth and communities where a lower percentage of people are considered distressed. Fill me in on what this data may predict related to household consumption and balance sheets.
Sanchez: So what we did in this study is to collect information on balance sheet in these ZIP codes. Information on balance sheet is important because it will predict the reaction of consumption. So basically if you have a reaction in income and you have some savings or equity in your house, you are likely to use those savings to smooth the reaction in consumption. So that means the reaction in consumption is not going to be that large compared to the reaction in income if you are in better financial conditions.
So that’s how we relate declines in income and declines in consumption. Households in financial distress are the households that are going to react more to consumption. They have no savings or very little savings, and they don’t have extra access to credit. Remember that if you’re in financial distress, you are late making credit card payments. Your credit score is going to be very low, so it’s very difficult to find additional credit when you lost your job or your income is reduced.
So what we find is that the reaction in consumption per percentage change in the income is larger than households with more financial distress. So just to give you an idea of the magnitude, if there is a 10% reaction in income, households with less financial distress will respond with a decline in between one-fourth and one-third of consumption. So if income goes down by 10%, it’s going to be 2.5 to 3.5% decline in consumption. Households with more financial distress will react with a larger decline in consumption that what we find is more than 50% of their reaction in income. So if their reaction in income in 10%, their reaction in consumption is going to be 5% or more. So that’s the difference in the reaction in consumption.
So if the shock, as we were talking in the previous post, is going to affect areas with more financial distress more heavily. So we’re going to expect that the aggregate decline in consumption is going to be larger, just because the response of this household is going to be larger.
Hasenstab: In your second post, “COVID-19 and Financial Distress: Vulnerability to Infection and Death,” you discuss economic affects when people get sick. Talk to me about some of those affects.
Sanchez: Well, we’re looking at a similar question that we did in the previous blog post that is how is COVID-19 going to affect areas with different incidents of financial distress? So what we did in this case was to look at infections and death. So unfortunately, we don’t have data at the ZIP code level yet, so we did it at the county level for the entire U.S. So we have the number of infection and death. And we look at if the question was if counties with more financial distress, are those having more or less infections and death?
So we basically plot the curve that everybody is talking about with the numbers of infection, but we break the U.S. in five groups according to the level of financial distress. What we find is that 20% of the counties with the least financial distress in the U.S., the curve starts going up earlier at the beginning of March. So this is probably households in better financial condition, it may be related to traveling. So they are getting more cases of COVID-19.
But what we see when we continue with this curve, and now we are updating this daily in the St. Louis Fed webpage, that the curve for the areas with the most financial distress, it started increasing later, but at a faster pace. So these are a steeper curve and they’re already above the curve for the areas with the least financial distress, so they are increasing faster. So meaning that the areas with more financial distress are getting more cases, more infections and more death than the areas with least financial distress. Although at the beginning of this crisis this was different. So this is very concerning, because we are seeing that, again, areas with more financial distress are going to get more infections and death, and they are going to get more hospital bills, so this is going to be added to their financial distress that they have going into this crisis. So that’s the finding of the second blog post.
Hasenstab: Well, that is really sobering to hear that the areas already in financial distress are likely to get hit harder by this disease. Interesting, but very sobering. Juan, what do you want the listeners of this podcast and the readers of these blog posts to take away from your work?
Sanchez: Well, so in our work, when we are looking at this idea that these aggregate shocks, what macroeconomists we call aggregate shocks, is it effects the population not uniformly, they have like bigger impacts in some groups of the population. And in particular, these two last shocks, what we find is that they affect more areas that had more financial distress going into the crisis. So that’s something that is going to be important because it’s going to affect the aggregate impact, because these areas may react more to the shock, but also because when we look, we have to be aware that there are going to be some areas of the country, so some group of the population, that are going to be particularly affected and it’s going to be much more painful than what we see at the aggregate number.
Hasenstab: Juan, thanks for your time today. To read more about the St. Louis Fed’s research related to COVID-19, visit the St. Louis Fed’s On the Economy Blog at stlouisfed.org/on-the-economy. Thank you, Juan.
Sanchez: Thank you.
Economists and other experts from the St. Louis Fed talk about their research, economics-related topics in the news and issues specifically related to the Fed. Views expressed are not necessarily those of the Federal Reserve Bank of St. Louis or of the Federal Reserve System.