How did inflation affect families last year? Did trends shift in the use of emerging financial products?
On July 13, 2023, the Federal Reserve Board of Governors hosted a Connecting Communities webinar exploring findings from the Survey of Household Economics and Decisionmaking (SHED). For the past decade, the SHED has provided insights into financial challenges families face. The latest report on the Economic Well-Being of U.S. Households in 2022 uncovers compelling data around various aspects of people’s financial lives. Keep reading for a full transcript.
- Jeff Larrimore, Chief, Consumer & Community Research, Federal Reserve Board of Governors
- Alicia Lloro, Principal Economist, Consumer & Community Research, Federal Reserve Board of Governors
- Ellen Merry, Principal Economist, Consumer & Community Research, Federal Reserve Board of Governors
- Jennie Blizzard, Communications Advisor, Fed Communities, moderator
Connecting Communities The Economic Well-Being of U S Households in 2022 (video, 57:41).
Good afternoon, everyone. My name is Jennie Blizzard. I’m the communications advisor with Fed Communities. We would like to welcome you to the July Connecting Communities webinar, the Economic Well-Being of U.S. Households in 2022. Today, you’ll hear more about research from the Federal Reserve Board’s recently released Survey of Household Economics and Decisionmaking. This survey also known as the SHED monitors the financial circumstances of US families with an emphasis on how low and middle income individuals are faring.
Today’s panelists will share insights from the survey that was conducted with more than 11,000 adults in October 2022.
Before we get started, we would like to share a few housekeeping items. Today’s session is being recorded and will be available within two weeks.
Views expressed during this session are those of the speakers and are intended for informational purposes. They do not necessarily represent the views of Fed Communities or the Federal Reserve System.
Microphones have been muted. Please use the Q&A feature throughout the session to submit questions. We promise to get to as many of them as possible. And finally, feel free to keep the conversation going and engage with us on Twitter using the hashtag #connectingcommunities.
Before moving to the content of today’s event, I would like to briefly introduce Jeff Larrimore, who’s going to kick off today’s session. Jeff is the section Chief of Consumer and Community Research at the Federal Reserve Board. He oversees the SHED report, so now without further ado, I’ll turn it over to Jeff.
Great. Good afternoon, everyone, and thank you for joining us. It’s great to be able to discuss the results of the SHED with all of you today. Being able to share these findings is always one of the highlights of my year and it’s especially exciting this year since it’s the 10th year that we’ve fielded the survey. Today, we’re going to be focusing on four topics from the survey, overall financial well-being, inflation, employment and credit. But we’re also going to leave plenty of time for questions and discussion on other areas of the survey that you’re interested in as well. With that, I’m happy to turn things over to my colleagues, Ellen Merry and Alicia Lloro. They’re both principal economists at the Federal Reserve and are the ones who lead the survey, so they’ll be the ones who are sharing the results with you. Ellen, I’ll pass the floor over to you.
Thank you, Jeff. Turning to the next slide. We’re happy to share the results from the 10th year of our survey with you today. And so turning to the following slide, I would just want to give you a little bit of an overview about SHED and the survey itself. So we began the survey in 2013 and this particular year, 2022, that we’ll be talking about or focusing on today, we surveyed over 11,000 adults, ages 18 or older. Our responses are nationally representative of the US adult population and we include a variety of topics on the survey including employment, banking, credit, savings, education, retirement, so quite a range of topics and we’ll just touch on some of those today. The goals of SHED, there’s some distinctives about the nature of the survey. One is that we combine both subjective self-assessments about how people are doing along with objective outcomes of their financial circumstances.
A second distinctive is we ask people directly how they make these financial decisions. For example, why they’re renting or why they’re using a new product like buy now, pay later, which we’ll talk about a little bit today. Another distinctive is we have some flexibility to cover new and emerging issues and so as an example of that, this year we added some questions related to inflation and people’s experiences of that. So those are some of the things that are distinctive about the survey. I also just want to highlight the last point on this slide that the report that summarizes the findings we’ll be putting out, talking about today as well as the underlying data is publicly available on the board’s website, at the link that we share there. And it’s not just this year’s 2022 report, but the reports and data sets from all the prior years are available there as well.
So we hope you’ll check it out if you’re interested in learning more. Okay, so turning to slide 6, I want to start by giving some context for the timing of the survey. So as Jennie mentioned, it was fielded in October 2022, and you can see that timing reflected by the yellow line on the right side of this graph. Now, financial conditions and people’s circumstances evolve over time and so these results kind of show us a picture of how families were faring coming into the new year. But since that time, you can see that inflation has kind of come down somewhat while unemployment has remained low. So this just is helpful to keep in mind when you’re thinking about how SHED results may fit in with other economic indicators.
So turning to slide 7, as Jeff mentioned, I’m going to focus on two topics, financial well-being and we have a number of metrics about that and broadly speaking, we see declines across several well-being metrics and broadly across different population groups. And when we look at the changes over the past year. And then a second topic I’m going to touch on is inflation and we have a couple of different ways of looking at how that’s impacting families. So turning to slide 8, since we first started fielding SHED in 2013, we’ve asked people how well they’re managing financially. So, looking at the right of the picture, 73% of adults said that they were doing at least okay, doing okay or living comfortably, which we combine into a measure we call doing at least okay financially.
Now, this share fell five percentage points from 2021 and was among the lowest level we’ve observed since 2016. So turning to the next slide, we look here at how this financial well-being measure has changed over the past year by different education groups. So it declined among people with all levels of education except for those with less than a high school degree who are shown at the bottom in yellow. Now, adults with at least a bachelor’s degree who are shown in the top in dark blue, saw a decrease in financial well-being for the first time since the survey began in 2013. Now, that said, the gap in financial well-being between those with at least a bachelor’s degree at the top and those with a less than a high school degree in yellow at the bottoms, remain large. They’re not shown here, declines in financial well-being were broadly evident across the population, broken out by other demographics as well. For example, we saw declines in the same financial well-being measure across all income groups and across all racial and ethnic groups.
Okay, turning to slide 11. Another metric we have in the survey to assess people’s financial circumstances is a question that asks people whether they were better off, the same or worse off financially compared to 12 months ago. Now, measuring well-being in this way helps track changes in perceived well-being over time. For example, some individuals may be doing okay overall but still feel like they’re worse off financially than they were a year prior. So, the lighter blue line in this graph shows the share of adults who are worse off, which jumped to 35%, the highest level that since we began asking this question in 2014. And as you can see, the shares saying they were better off decline somewhat.
So turning to slide 12. To understand who’s driving this increase in the share saying they’re worse off, we look here at some subgroups of the population. The spike in those doing worse off financially occurred across educational groups consistent with the broad declines in well-being that we saw in the other well-being metric that I shared earlier. But as you can see at the bottom of that left column, adults with higher levels of education saw a larger change. For example, as with the bachelor’s degree or higher, an additional 17% said that they were doing worse off compared to the year before.
This pattern may reflect the fact that those with a bachelor’s degree not only faced rising prices, but because they’re more likely to have exposure to the stock market and investments more generally, they may have been more affected by the declines in the value of investments last year. And think particularly about that graph that I started with, the timing of the survey was in October and we saw some lows in some markets valuations and stock market in the fall of last year. So consistent with that possibility as it’s shown in the right column, adults with more investible assets also showed larger increases in the shares saying they were worse off in 2022. So it seems to suggest that may be a factor.
Okay, turning to slide 13. On this slide, we look at one of the most well-known measures in the SHED. That is the share of adults who said that they would cover a $400 expense exclusively using cash, savings or a credit card paid off at the next statement. So we call this cash or it’s equivalent. Now, consistent with the declines in the other measures of well-being that I’ve already shown, this share fell five percentage points down to 63% and this decline may reflect people having spent down some savings buffers they’d accrued during the pandemic. So turning to slide 14, this year, we brought back onto the survey an open-ended question asking people about their main financial challenges or concerns and they were able to write in a text response. So I’m going to just focus first on the dark blue bars which show these results from 2022.
Now, we’ve used text analysis to classify the responses in this open-ended question based on whether or not they included keywords in various categories. The inflation responses that we’ve grouped here could include the word inflation, but also terms like paying more, prices, expensive and costs. The next category over, the one titled basic living expenses, has to do with making ends meet and include keywords like bill, utilities, heat, food, and necessities. And the categories are neither exclusive, mutually exclusive or exhaustive. So people could have a response that fit into more than one of them or into none of the categories, but inflation was the most commonly cited concern last fall followed by basic living expenses. Now, respondents also had the option to check a box that said none if they didn’t have any financial concerns to report. And you can see that over on the far right that 28% chose this option in 2022.
Now, the last time we asked this question was in 2016. So we’ve included those results on this slide as well. Those are in the lighter blue bars and comparing the two years, you can see a sharp increase in 2022 and the share mentioning words related to inflation or prices and also in the share siding basic living expenses, those are the two sets of bars on the left side of the slide. Over there on the right, you can see a sharp decline in the share saying none, that is, they didn’t have any main financial challenges to report, but most of the other categories are relatively steady between these two years.
Now, turning to slide 15. When we look at the results for this open-ended question for different income groups, you can see over there on the left that inflation was the most common challenge mentioned by people in all income groups in 2022, suggesting a widespread in impact of higher prices. Now, it’s a bit surprising that the lowest income group, the group in yellow, was somewhat less likely to cite inflation as a challenge. But in part this pattern of response may reflect how low income adults are talking about challenges. If you are frequently struggling with expenses, more generally reflecting in the high; which may be reflected in the higher share citing basic living expenses is a challenge. The next category over people may be less likely to talk about price changes when given the open-ended question.
Also, people who have lower incomes may be more likely to be out of work and in that case employment may be more front of mind and you can see that maybe a possibility from the results for employment over there at the right which are higher share of low income adults, the ones in yellow are likely to mention employment. Now, focusing for a moment on the higher income adults, the people in dark blue, higher income adults were more likely than lower income adults to mention financial challenges related to retirement and savings. And you can see that in the middle set of bars and that may be related to what I mentioned earlier about some of the stock market and investment declines last year.
Okay, turning to slide 16. In addition to the open-ended question I just discussed where inflation was a common theme, we also asked people if they experienced increases in the prices of various products they purchased and while that’s not shown here, almost everyone said yes to having paid higher prices on one or more products last year. What is shown here is a follow-up question we asked about whether their family budget was affected by these price increases and most people said their budget was affected at least somewhat. Here we’re going to focus on those who said their family budget was affected a lot.
And down there at the bottom in yellow, you can see that 54% of adults said that their budget had been affected a lot. Adults with a family income of over a hundred thousand were less likely to say their budget had been affected a lot by higher prices relative to those with lower income. So just to recap this slide with what we talked about earlier. While the lower income adults on the open-end question cited challenges with inflation and somewhat lower rate than those with higher incomes, this question about impact on family budgets does suggest that lower income adults were feeling the impact of higher prices last year.
So turning to slide 17. We also asked people about what actions they had taken in response to higher prices and spending responses were the most common. Those are the dark blue responses bars at the top. Two thirds of adults had said that they cut back on spending and almost as many had switched to cheaper products, about half had delayed a major purchase and also about half had reduced savings. That’s in the lighter blue bars in the middle. But less common responses were people who said that they had searched for a new job or had asked for a raise, down there at the bottom in the medium blue. So that concludes my portion of the presentation. But before I turn things over to Alicia, I just wanted to offer a quick reminder that we’ll be taking questions at the end and you could submit questions to this event Attendee Hub. So with that, Alicia, I’ll turn things over to you.
Thanks, Ellen. So, next I’m going to talk about some of the findings from our questions on employment and in particular I’m going to focus on workers’ experiences in the labor market. Turning to slide 19. So one important aspect of workers’ experiences in the labor market is the strength of the labor market that they’re facing. And some indicators we have of labor market strength remain strong in 2022, even strengthening a bit from what we saw in 2021. The share of adults who received a raise or promotion increased slightly from 2021 to 2022. And so did the share who asked for a raise or promotion. Looking at job changes, we see that the share who applied for a new job, the share who started a new job and the share who voluntarily left a job also went up. Conversely, the share who were laid off or lost a job slightly declined.
So these are all indications that in at least as of the survey in 2022, we were still seeing a strong labor market. Turning to the next slide. The next two slides, I’m going to focus on another aspect of the worker experience and that is around autonomy and choice at work. So on this first slide we’re going to look at working from home and before turning to the figure, I’d like to first share some overall results that we have on working from home and how that’s changed before and after the pandemic. So at the time of the survey in October of 2022, about one in five employees said that they worked entirely from home in the week before the survey. This share was down from its peak in 2020, but well above the 7% who worked mostly from home in 2019 before the start of the pandemic.
So now I’m going to turn to the figure on this slide where we take those working from home shares and break them down by education level. So as you can see on the top set of bars, it shows those with a bachelor’s degree and they were the most likely to say they worked from home either all of the time or some of the time. And those with a high school degree or less shown on the bottom bar, were the least likely to work from home. At least in part we think this reflects the types of jobs that people have and whether those jobs actually allow the work to be done from home. So we asked a follow-up question asking people like if your employer would let you, could your work be done from home? And we also see large splits by education that matched this question. So that gives us some evidence that some of these differences are really about the job type. Next slide.
So another aspect of the worker experience that we asked about in the survey and that we also saw large differences by education was something we’re calling autonomy at work. So we measure that by two different questions. So on the left set of bars here it shows the share of employees who said that they often or always chose what tasks that they worked on. And then on the right set of bars, we show those who said they often or always chose how to complete tasks at work. So if we compare these two sets of bars, one thing we notice is that fewer employees felt that they had control over what tasks that they worked on compared with control over how to complete those tasks. So those are some overall results. And then if we look at these splits here by education for both of the measures we see that shares were higher for those with at least a bachelor’s degree and that’s shown by the dark blue bar on both sets of bars.
Another notable thing we noticed is that for the other education groups, so that’s a high school degree or GED, at least less than high school, some college or technical or associate’s degree, they all kind of had the same shares of control over what tasks they work on and then similar shares for how to complete those tasks. So this was a bit surprising before looking at the data I might’ve expected to see as the education level increased the control or autonomy increases, but that’s not what we saw. It remained pretty much flat until we got to at least a bachelor’s degree. So next slide, slide 22.
So with that, I’d now like to switch gears a bit and talk about some of the results from the credit section of the survey. So next slide, slide 23. So to help give us a sense of how people’s access to and use of credit had changed from 2021 to 2022 and also to provide some context for the later results I’m going to talk about on buy now, pay later, here we’re going to look at rates of credit card ownership, so that’s shown by the full length of the bar and then also the share of adults carrying a balance on their credit card.
So that’s shown by the yellow portion. So starting on the bottom, overall, 82% of adults had a credit card in 2022. This was down from 84% shown by the top bar in 2021. One thing I do want to note quickly is that in the SHED, the overall rates of credit card ownership we think are a little bit high. They’re higher than for example the FDIC survey of unbanked and underbanked households. And we think that’s because our SHED question might be capturing some debit cards. But that said, the general trends that we see are very similar to other surveys and that’s true when we look both over time and when we break things down by different demographic groups.
So the last thing I wanted to point out on this slide is the yellow portion of the bar, which shows that in both 2022 and 2021, 40% of adults said they carried a balance at least once in the past 12 months. So it was a bit surprising that that was the same from 2021 to 2022. But if we dig a little bit deeper, we see that the share who said they carried a balance often that did increase over this time. And we also see that the share who said that the amount of their credit card debt rose, that they were carrying more debt than they were a year ago. Next slide.
So on this slide we break out those overall rates of credit card ownership and the share carrying of balance by both income and race and ethnicity. So starting at the top set of bars, we look at income and if you follow the numbers there at the end of the bar, you can see that those with higher incomes were more likely to have a credit card than those with lower incomes, particularly while nearly everyone with an income of a hundred thousand or more had a credit card, only 57% of those with an income less than $25,000 did. If we focus on the yellow portion of the bar, again that’s showing the share who carried a balance on their credit card. We see that it was those with the middle incomes that were the most likely to carry a balance. And we see that for two reasons.
One is that they’re more likely than the higher income folks to carry a balance and then if we compare them with the lower income people, they’re more likely to have a credit card in general. So that contributes to them being more likely to carry a balance. Turning to the bottom set of bars, we look by race and ethnicity and we can see that Black and Hispanic adults were less likely than white and Asian adults to have a credit card. But if we look at the share carrying a balance, we can see that Black and Hispanic adults were much more likely to carry a balance on their credit card even considering the fact that they’re less likely to have a credit card to begin with.
Turning to slide 24, oh, sorry, I guess 25. So now I’d like to shift the focus to use of buy now, pay later products. Buy now, pay later is a relatively new product that typically provides consumers the option to pay for a purchase with a small number of equal payments. Not always, but often this is the case and often consumers are not charged interest but they may incur other fees such as late charges. So there’s a lot to understand in the buy now pay later space and it’s changing it seems day by day. But over the next couple of slides I’m going to focus again on the consumer experience. So on the SHED we ask about overall incidents, we also ask people why they use buy now, pay later. And then we’re going to look at which groups, demographic groups and different credit profiles are most likely to use buy now, pay later.
So turning to this slide now, the figure on the left shows that the share of adults who use buy now, pay later in 2022 was 12% and this was up slightly from 10% in 2021. The bars on the right show among people who used buy now, pay later what share paid late. So we can see that was up slightly from 2021 as well. So 17% in 2022 compared with 15% in 2021. So to put that paying late in context just a little bit, it’s kind of hard to compare buy now, pay later to other products. But one thing we did was we looked in the consumer credit panel and we looked at people with risk scores below seven 20 and compared. We looked at credit card holders that were at 30 days past due at least once during this time period and we found that the share paying late on buy now, pay later was slightly higher than those 30 days past due on credit cards.
In the most recent survey, we also asked about late fees and while not shown here, we found that among those who paid late, so among that 17% who paid late, a little more than half said they were charged extra for being late. Next slide. So here we look at the reasons that people said they used buy now, pay later. The top two reasons were wanting to spread out payments cited by 87% of buy now, pay later users and convenience cited by 83%. Other reasons that were cited by more than half of buy now, pay later users were to avoid interest charges. It was the only way I could afford it and did not want to use a credit card.
The choice or the response, the reason avoiding interest charges was more likely among higher income adults, whereas lower income adults were more likely to say that it was the only way they could afford it as a reason for using buy now, pay later. And then finally about 20% of buy now, pay later users cited that it was the only accepted payment method I had, though, this share was nearly 40% among those buy now pay later users who didn’t have a credit card. Next slide.
So here we look at some of the characteristics of people who use buy now, pay later. And here we’re looking at their credit profiles. So people differed in their use of buy now pay later by their self-reported credit rating. So our survey vendor asks people for what they think their credit rating is and they provide a response which we show here as don’t know, very poor, poor, fair, good or excellent. I should note in the past we’ve done some work and these self-reported credit ratings actually match up with actual credit ratings fairly well. So that gives us some confidence there that these credit ratings are aligning with actual credit ratings.
But nonetheless, I still think it’s interesting how people self-reported credit ratings line up. So to get to the punchline, those who rated their credit as fair were the most likely to use buy now, pay later, followed by those rating their credit as either poor or very poor. And then turning to the light blue bars on the right, we see that use of buy now, pay later was equally common among those who had a credit card and those who didn’t have a credit card. And I think this finding is particularly interesting because there’s a lot of talk about how buy now, pay later is used by people that don’t have access to credit or don’t have a credit card, but really we see incidences the same among both groups.
So next slide, slide 28. So here we see use of buy now, pay later by different demographic characteristics. Starting again by income at the top, we see that use of buy now, pay later was more common among people with low and middle incomes, whereas those with the highest income level in our survey, that’s a hundred thousand or more were less likely to use it. We also see that use of buy now, pay later differed by race and ethnicity. Black and Hispanic adults in particularly were much more likely to use buy now, pay later than white or Asian adults, about twice as likely. And then we also saw that women were more likely to use buy now, pay later than men. One thing that I often get asked about but I didn’t have space here to include on the graph was differences by age. And those we see a similar pattern to income where use is pretty much the same among all age groups except for the oldest age group, those age 60 and older, which had lower use rates. So next slide.
So that wraps up the content that I have for you today, but I would like to note that the full report, as others have said, covers many topics that we have not had time to cover today. So things like housing, we have a big section on rental information which is somewhat unique to the SHED. We also ask about higher education, both attainment and student loans. We have a section on retirement. And then just to reiterate what Ellen said earlier, our report is available on our website, which the link’s at the beginning of the presentation and on our website you’re also available to download the raw data in case you want to play around with the data and run some things for yourself. So with that, I would now like to pass things back over to Jeff for some questions and discussion.
Alicia, Ellen, if you want to also join us on camera, we have quite a good amount of time for questions and I just want to put a plug to remind everyone, if you have questions, please enter them into the Q&A option in your Attendee Hub and we’re going to try to answer as many questions as we can over the next 25 minutes or so.
Ellen, I’ll start with a question that’s coming for you, which is that you showed some differences in the effects of inflation by income and I’m curious whether there were any other notable differences in terms of which demographic groups were most affected by higher prices and by inflation?
Yes, we did see some other demographic groups that showed more of effect. One group was parents. We defined parents here as adults who are living with their own children who are under the age of 18. So they had a higher impact. Black and Hispanic adults also were more likely to say they have been affected a lot by inflation and also those with a disability indicated that.
Thanks. Alicia, this question is for you. How do the job actions that you talked about, so asking for higher pay, voluntarily leaving a job, being laid off, et cetera? You showed results for 2021 and 2022, how do those compare to earlier years, particularly thinking back before the pandemic?
Yeah. Thanks, Jeff. So if we look back to 2019, the shares look similar to 2022, although not quite as high. I can’t comment on statistical significance, but we did see quite a big dip in 2020 after the onset of the pandemic and then a recovery in 2021 and further increase in ’22. But generally I would say that in 2022 all those indicators are slightly higher than what we were seeing in 2019.
Thank you. Actually, this might be a question for either of you, but in terms of the results that you’re seeing in the survey, particularly thinking, I think, about the open-ended question, does food access or food security show up in any of the survey results?
I think that that was one of the food terms. Food was one of the terms that we used for the basic living expenses category. So yes, people were mentioning food along with other things, necessities, bills, that sort of thing. And that’s one place we saw food show up.
Yeah, I would add too, that when we looked at differences in the words people use by income, it tended to be the lowest income group that used words around food more often, like they pointed to food costs, whereas the higher income groups talked about inflation more generally. So I think part of that may be pointing to the differences that Ellen mentioned as to why when we look at the inflation category itself, we didn’t see the lowest income group as prominently because of the way they talked about their struggles was a little bit different and food was one of those things that really popped for that group.
Okay, thanks. This is another question that I think you really can be for both of you, which is whether we analyze any of the findings by geography and by cost of living. So this person was particularly interested in credit card data for people living in higher cost areas, but I think more broadly just interested in what sort of geographic differences you’re finding.
Sure. I guess I can start since it referred to credit cards, but Ellen please feel free to chime in. We can break down our results by state but we do include state in the public data, internally we’re able to look at census tracked. We didn’t discuss any of those results and we typically don’t put that in the report, but it’s something we can look at and cost of living, again, it’s not something that we sort of tied to credit cards. We haven’t done that analysis, but it is something that we could do. Jeff or Ellen, if you want to add anything?
Yeah, I’ll add just a note about geography, not about credit cards specifically. There are a few places in the reports where we do highlight some geographic differences. We don’t do it everywhere, but we have some census region breakouts on things like being affected by natural disasters or rent and mortgage differences. We’ve got metropolitan area differences I think in several places. MSA, non-MSA for things like well-being and some other places. And we also have an indicator for neighborhood income level. So I think that we have a number of things, but as Alicia mentioned, there’s a lot you can do with the publicly available data, different cuts including by state if you wanted to match up to outside data sources.
Yeah, that’s a good point. Thanks for mentioning that, Ellen, for example, for the overall well-being, we do break that out for LMI communities versus non-LMI communities, which doesn’t quite get at cost of living, but anyhow.
So, Alicia, this is a question for you, I believe, which is whether you’re able to cut the data by LGBTQ+ status, in particular, this person’s really interested in how the LGBTQ+ community is faring financially and do you see any notable differences there?
Yeah. Thanks, Jeff. So for the past several years in the SHED, well, quite a while now, we’ve included differences by LGBTQ+ and one notable thing we found when we were looking at well-being was the LGBTQ+ community had lower self-reported financial well-being than those not in the community. And when we dug a little bit further, if we look specifically at those identifying as transgender or non-binary, we see even lower levels of self-reported financial well-being, quite a bit lower than the overall population. So these results were striking and I think areas for future research. But yeah, in general, our vendor asks questions about sexual orientation and gender identity. So we’re able to break those out really for any of the questions that we have on the survey.
Excellent. Ellen, coming back to you, does the difficulty accessing or paying for childcare come up in the survey at all?
In our expenses question or the categories of expenses where prices change. We didn’t ask specifically about childcare, but that’s a really interesting point and something maybe we might want to consider for the future.
I think just to add one quick thing on that, when we were looking at the responses to the open-ended question, I did kind of pay attention to see if childcare cost was coming through and we did see some, but it certainly wasn’t frequent enough to take over any of the other general inflation concerns. So that’s really the, I guess this year, the only measure we would have that could try to get at that.
Alicia, I will stay with you. You mentioned at the end the other areas of the survey including rental housing being a particularly interesting one, can you talk a little bit about the findings for housing and for rental housing in particular?
Sure. Yeah. So we ask kind of a lot on renters I think because one area where we tend to know less than we do for about homeowners. So one thing that we ask renters is why they’re renting and some people rent out of a preference or convenience, but we did find that the most sided reason for renting was an inability to afford a down payment. I think another area for the renters, which is interesting with the SHED is people who are having challenges with their rental payments. So we saw in the SHED, I forget the exact numbers, but somewhere around like 20% of renters were behind on rent in the past year, and this was about the same as the prior year, but we also saw that Black and Hispanic renters were more likely to be behind on their payments than white or Asian renters. And this continued a pre-pandemic pattern. So that’s just a sampling of some of the information that we have on renters, which I would point people to. I think it’s a really good source.
Excellent. So we have a very engaged audience that’s also asking some technical questions about the way that the survey is fielded and conducted. So one question asked 11,000 respondents is a lot of respondents to reach out to and they’re curious how we go about collecting the responses and what that outreach looks like. Alicia, since you’re already off mute, I’ll pass it to you for that.
Oh, okay, sure. And Jeff please feel free to chime in. Jeff’s worked on the survey for a lot longer than I have, so I may miss some important details. So we work with a survey vendor called Ipsos and they maintain an internet panel of survey respondents and we survey the respondents of this panel.
So really we kind of delegate that work over to Ipsos. So the way their panel is designed, if it’s an online internet panel, if someone doesn’t have a device to access the internet, they’re given a device and they try really hard to make sure that they’re not leaving people behind who don’t otherwise have internet access. I believe they do address based sampling so that the panel is as representative as it can be of the national population. As Ellen mentioned, it’s adults 18 or over and then we sample from their panel to get our 11,000 respondents.
Ellen, did you have anything else you want to add there?
No, I was just going to make sure we said it was address based, the way that they put the panel together.
I should also note that we do benchmark our SHED results with other surveys to make sure that they’re sort of in line with what we think. For example, I mentioned the credit card question. We look at that compared to others, but we do it for a lot of different measures and generally it matches up well.
For those who are technically inclined, we do have a chapter in the report that describes more about the sampling, the weighting, the fielding and all of that. It’s the last chapter in the report, so check it out.
While we’re thinking about the methodology, another question we received is, are we able to follow any of the same people over time to see how people’s financial well-being has changed from one year to the next? Ellen.
Yeah. We are. Every year we have a subset of respondents who took the prior year’s survey.
In the 2022 survey, I believe we had about 3,700 people out of that 11,000 who had taken the prior year’s survey. And so it is possible in the public data to match those folks up. There’s a variable that allows you to match them and weight that allows you to use them as a panel. So that’s been a feature for a while, that there’s a group that you can follow from year to year.
Thank you. Another question sort of going back to the content of the survey. Was transportation access or expenses considered in the survey? Is there anything in the survey understanding people’s access to cars and various public transit, et cetera, Ellen?
We did have not public transit, but we did add a question this year about whether or not people had access to a car. It’s not discussed in the main body of the report, but we do have that in the public data.
And this is a chance to do a shout-out for the appendices. So we have on the public website you can find an appendix that has the text of the instrument that we used and what was fielded to people as well as a tabulation of all responses for each question. So you could find this in the appendix, I believe it’s whether or not they owned or had a regular access to a car.
If the questioner is asking, did we take that into account when we did? We did have a question about whether or not people had faced higher gasoline prices, for example. We didn’t condition on having a car when we tabulated that response as we just end the report, it’s just published for the US adult population is the way we tabulated it. But you could tabulate it that way, it’s available.
This question I think could be for either of you, how do you anticipate the findings the survey are being used? Are there any findings in the survey that you’re looking at and thinking this could be used by either the Federal Reserve or outside organizations to be helpful for understanding how household finances and affecting those decisions?
I think we do share our results internally and externally. So the fact that we have a combination of both objective and subjective measures, it’s really helpful for seeing how the evolving economic conditions are impacting people. And I think if you read just the executive summary of the report, you can see this in the way we frame some of the results and trying to talk about what’s been going on over the year and how that context may be affecting people. So that’s what I particularly find helpful about working on this.
Yeah, I don’t know. I think the whole thing is helpful and useful depending on what you’re interested in. I think for me, one really important point that came out of the survey this year, which we saw through the inflation stuff that Ellen presented. And also just the overall financial well-being, is that usually we don’t see widespread declines in well-being across the whole population. And pretty much if you looked at each group this year, you saw a decline in financial well-being and that was striking and I think informative for policy makers and also for the inflation piece, we saw well up the income gradient, people were saying inflation is my biggest financial challenge. And I think that was also really important to see that we hear in the media inflation affects everyone, but here we’re seeing it when we directly ask people, what’s their challenge?
So I think that was really useful. There’s also some smaller topics that maybe don’t get as much overall attention when you’re thinking about the economy, but that I also think it highlights what Ellen said was a goal of SHED is to like, we’re nimble and we can include things that maybe are new or emerging, so those kind of to me relate around the banking and credit. On SHED, we ask about cryptocurrency and we’re one of the few sources for people using cryptocurrency for transactions, which I didn’t talk about today, but we see that those who use check cashing and money order and Black and Hispanic adults are all more likely to use crypto for transactions. So that was a really interesting finding that has financial inclusion implications and then also the buy now, pay later stuff. It’s an emerging area and we’re still collecting data and I think that’s also a very useful piece that we have on the SHED. Really, like I said, everything, but those are some notable to me from the areas that I work in.
I’ll take my privilege as the moderator. I have one additional place I see the survey being used, which is I think that if you look at the survey over for the past 10 years of public discourse around people’s handling of emergency expenses and the $400 question has really made people think more about how those small financial emergencies affect people’s lives. And I think that’s something that we have certainly seen in a number of discussions coming out of the survey and is a way that people have used these findings.
Another question that has come in, and I think this one is best suited for Ellen, is the survey does ask about a number of different aspects of people’s financial lives. One area that’s really important for some people is health expenses and challenges with medical bills. Is that something that we cover in the survey and can you share anything on that?
Sure. Yes, we do have several different measures that relate to healthcare expenses. And you can find this in the expenses chapter of the report. We ask whether or not people had a major unexpected medical expense that they had to pay for out of pocket in the past year and if they had unpaid medical debt and if so, how much? And whether or not they have health insurance. So a number of different questions like that. One that we highlighted this year, which is whether or not people have skipped medical care in the past year due to cost. And we did see an uptick in that series. We’ve been tracking that since 2013 and we did see an uptick in that this year.
Alicia, this is another survey methodology question that I think is best suited for you, which is, we talked in the presentation today about how white, Black, Hispanic, and Asian adults were doing, but Native Americans aren’t mentioned. Can you share anything on why that is and how the demographic groups that we’re including are chosen?
Yeah, thanks. So we would love to have enough data to report on Native Americans, but really it’s a sample size issue. So we don’t have a large enough sample to produce estimates that are precise for Native Americans. In fact, we have finally added enough samples so we can report on Asian adults, which was new last year or the before. But yeah, so unfortunately we don’t have a large enough sample to report on Native Americans.
This question I think probably either of you could take, so I’ll put it out there for either of you. So the survey take into account burdens of cost of elder care that younger workers are facing as their parents are aging, so how are we thinking about these various care responsibility in both directions, not just childcare but also elder care?
I think we have more available right now on the childcare question, but this is a point well taken. We’ve got a question about people’s living arrangements and whether or not they’re living with others to help out with caregiving responsibilities, but we also recognize that. And when you get to the retirement question, this isn’t quite what the question are asked, but we ask why people retired and whether or not caring for family members was a part of that. I mean, we also ask their health shocks were a part of that. So there’s some places on the survey that sort of touch on this, but recognizing that the different ways in which people help other family members are very varied and may not necessarily involved with somebody who’s lived in their household. So I think that’s an interesting and I think growing in importance area.
Thank you, Ellen. Alicia, this is another one for you, which is, you talked about buy now, pay later products, and it seems like buy now, pay later products would be particularly appealing to people who are using payday loans, using some of these alternative financial services. Do you see that? What’s the relationship look like between buy now, pay later and alternative inter services like payday loans?
Yeah, that’s a really good question. Yeah, we actually do see that in the SHED. So those who use, we call alternative financial services credit. So we group that together. It’s like payday pawn, auto title, refund anticipation type loans. They’re much more likely to use buy now, pay later than those who haven’t used those products. I forget the exact numbers, but it’s something around four times as likely. And I think the question’s intuition is right. It makes a lot of sense. As I mentioned earlier, typically buy now, pay later, you’re not paying interest on those. You may be charged late fees, but compared to the interest rates and the fees that are on those other types of credit, it seems like the rational decision, if I will, to use buy now, pay later as well.
And we’re pretty much at time, but one last question, which I think is a great one to end on because it’ll help to point people to be able to answer additional questions. You mentioned a couple of times that the data are available. Where are people able to download that data?
It’s on the board’s website. If you, under Consumers and Communities, look for survey of household economics and decision making if you’re navigating from www.federalreserve.gov. We also included a link on the second slide of our deck. Well, I don’t know how it’s numbered, but very early in the deck right after the big title slide where we show where to get the report and data. So you can look over to the left for the data tab. It’s all there.
Ellen, Alicia, thank you so much for the great information today and for answering so many questions that have come in. I know there are even more questions that we haven’t been able to get to. So thank you to everyone that has been asking questions, those we were able to answer as well as those that we weren’t able to get to. I hope you all appreciated the information today. And, Jennie, I will pass the floor back to you.
Hey, great. Thank you, Jeff. Thanks to our speakers for providing such insightful information. The questions were just rolling in and we appreciate the audience for just being so engaged and thank you for spending your time with us today. But before we end the session, we do have a few requests. If you could please complete a survey. We’re going to send it to you immediately after today’s event so we can improve and continue to bring you timely and relevant topics.
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