Sydney Diavua

Good afternoon and welcome to Connecting Communities. Thank you for joining us for today’s webinar, Highlights from the 2024 Survey of Household Economics and Decisionmaking. I’m Sydney Diavua, assistant vice president, community development at the Federal Reserve Bank of St. Louis and I will serve as your moderator for today’s session.

Before we get started, let’s move to slide two where we can take care of a few housekeeping items. The 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 during the Q&A portion of this presentation.

Let’s keep the conversation going and engage with us on social media, using the hashtag #connectingcommunities and visit FedCommunities.org for a variety of community development articles, resources and data across the Federal Reserve system. And finally, this session will be recorded and the presentation, video, and podcast will be available on FedCommunities.org within two weeks of this event.

So, first off today is a presentation from the survey team and consumer and community research at the Federal Reserve Board of Governors. They will share highlights from this year’s SHED survey. Ellen Merry, principal economist will introduce the survey and provide an overview of the Family Finances section. Mike Zabek, senior economist, will follow with findings from the employment section. And Alicia Lloro, principal economist, will close with highlights from the financial risks section and takeaways. Then audience, it’s your term, our presenters will join us on screen so that you can ask questions about the survey findings. Remember to utilize the Q&A feature as we go along to enter your questions into the queue. Before we begin, we do have a question for our audience that will help shape the dialogue today.

You’ll see a polling question appear on the screen, which of the following best describes how you’ll use information from the SHED? A, analyze raw data for custom research. B, reference specific indicators or statistics. C, understand broad economic trends. D, general knowledge in my field or F, exploring potential uses or not using. So, we’ll just take a moment so you can fill out that poll. Thanks so much for sharing with us and helping us understand how today’s conversation can be useful to you. Now without further delay, I’ll turn it over to Ellen Merry. Ellen, the floor is yours.

Ellen Merry

Thank you, Sydney. We’re delighted to be able to share results with you all today. So, turning to slide six, I want to start by giving a brief overview of the approach that we take with SHED. The results we’re presenting today are from our 12th annual survey. We started the survey the first year was in 2013 and this past fall we surveyed a nationally representative sample of over 12,000 people. The survey was fielded in late October of 2024, so the results that were going to present reflect how US adults were doing financially last fall. The goals with SHED, I want to talk a little bit about that. The approach we take is to ask both subjective and objective questions to assess how people are faring financially. We also include some questions about motivations for financial decisions. For example, this year we added a new question about the reasons why some retirees are working.

We have the flexibility to cover new and emerging topics and this year we added new questions about whether people have experienced financial fraud or scams involving their money. Also, we added some questions this year on topics we covered for the first time last year on caregiving. This year we asked parents about their use of unpaid child care, and on homeowners insurance we added a question asking homeowners who didn’t have insurance, their reasons why. The reports on the survey with the results also with the underlying data for all years are available on the Board’s website at the link at the bottom of the slide. And I want to add a quick plug for the appendices that are also posted on the website. Those appendices include the survey question wording for all of our questions and tabulations of the questions as well. So, since we can’t discuss everything in the survey, in the report or in this presentation, looking at the appendices is another good way to check out what the survey covers.

So, turning to slide seven, first I’d like to talk about a few of our results on family finances and moving on to slide eight, we want to take first a look at people’s financial situation as of the fall of 2024 and we use these two series to take an overview shot. Looking first at the top line, we asked people how well they’re managing financially and in late 2024, 73% of adults reported doing okay or living comfortably. This year was essentially unchanged from the previous two years, but it was down from 2021. Just for a little context on this question, we gave people four options on how they were managing financially: living comfortably, doing okay, just getting by, or finding it difficult to get by. So, this dark blue line that we’re showing here is the share who answered with the highest two of those four categories.

Now the bottom line in medium blue shows the results from a different question asking people how they would handle an unexpected $400 expense. In 2024, 63% of adults said they would cover such an expense exclusively using cash savings or a credit card paid off at the next statement. We call this combination of methods of payment cash or its equivalent. And this share was similar to the prior two years, but it was down from a high in 2021. Now the 2024 survey also includes a question that we’re about how people handle changes in prices and you can see this on slide nine. The question asks how changes in the prices people paid compared to last year affected their financial situation, Respondents were offered five answer choices ranging from much worse to much better, and for simplicity in the figure we just show the share saying worse, which includes those who said their finances were much worse or somewhat worse as a result of changes in prices.

We asked this for the first time in 2023, so we show those two years at the top of the chart. Most adults said changes in prices they paid compared to last year made their finances worse, but the shares saying so decreased from 65% in 2023 to 60% in 2024. Now looking at the bottom part of this figure, adults with the highest income that is people with incomes of 100,000 or more were the least likely to say their finances were worse because of the changes in prices that they paid. Still the majority of people in all of the income categories appeared to be experiencing some negative effects from higher prices. Now turning to slide 10, SHED includes questions about different types of financial challenges that people may face, and this slide is focused on the challenge of not being able to keep up with regular bills.

If you look at the bars on the right of the graph, 17% of adults, that’s the light blue bar, said that they had not paid all their bills in a month prior to the survey. Also still focusing on those bars at the right, 25% of renters, that’s the medium blue bar, said that they had not paid a bill which is higher than the 11% of homeowners in dark blue who said so. Looking on the left side of the slide, we asked follow-up questions about different types of bills and whether people were able to pay them. The most common bills that people reported missing in the prior month were water, gas and electric bills and phone, internet and cable bills. Those are the two groups on the left side. Across all the bill types here though renters were still more likely than homeowners to have missed a bill. That concludes my portion of the presentation, so I’ll turn the floor over to Mike to talk about employment.

Mike Zabek

Thanks, Ellen and I am very happy to talk through a few of the results that we have In terms of employment. This is a broad set of results. I’ll talk about three broad areas. The first area is movements that people have made into potentially new jobs and how much that is reflected in terms of improved job quality for people, which is that we can uniquely measure in the SHED. Then I’ll talk a little bit about how families manage with child care, which as Ellen mentioned, we introduced a new question on this year, and then I’ll finish the employment section at least by talking about nontraditional or gig employment, which is something that we’ve followed for quite a while in the SHED and that we’ve reintroduced questions about with some new elements this year. Starting with slide 12 that is presenting on these movements into and out of jobs that we’re able to observe in the SHED.

Specifically, it mentions the share of all adults who applied for a job, started a job, left a job voluntarily or were laid off. Looking across these categories, we see similar shares between 2023 and 2024. One thing that is different is that if you look back to 2022, which was a period that many people referred to as the Great Resignation, we saw some differences. So, in particular we saw a lot of people leaving a job voluntarily, which kind of coincides with the naming of the Great Resignation since there were a lot of people who were leaving a job voluntarily and there were more people doing that in 2022 than there were in the last year 2024. We also saw fewer people starting a new job and a few more people being laid off. Interestingly, the share of people who applied for a new job is similar in 2024 to the share that we observed in 2022.

Looking at question 13, we probe a little bit deeper into, sorry, into slide 13, we probe a little bit deeper into how much those movements into new jobs translated into better working conditions for people. This is presenting a pretty unique question that we’ve asked in the SHED since 2021 where we ask people who have a new job this year that’s different from the job that they had last year to compare those two jobs. So, if you change job, we ask you basically, is your new job better than your old job? In 2024, 62% of people who were in a new job who changed jobs said that their new job was better. That’s down from a peak of 72% of people who changed jobs in 2022. Notably more people changed jobs in 2022 than did in 2024 and in 2022 if you changed jobs, you were more likely to say that your new job was better than you were in 2024.

We also are able to ask in the SHED about specific sub-characteristics of jobs. So, specifically we ask if the pay or benefits are better, if the interest in the work is better, if you have better opportunities for advancement and if your work-life balance is better. Looking across all these characteristics, we generally see these declines since 2022 that more or less match the pattern in terms of why the jobs are better overall. Another thing that I think is interesting and worth calling out is that if you just look at the share of people who say that their work-life balance is better in their new job, conditional unchanging jobs across all years, that number is lower than 50%. So, most people who changed jobs did not get better work-life balance in their new job. In a lot of cases, their work-life balance was pretty similar between their old and their new job and that applied also to 2022, which was a period when a lot of people were emphasizing the importance of work-life balance for people.

Slide 14 then goes and presents some of the results that we have in terms of paid and unpaid childcare with unpaid childcare in particular being a new question this year, and this is just showing the shares of parents of children under age 13 who use either unpaid or paid childcare. Looking at that, you see pretty high incidences of unpaid childcare in particular for people who are in families earning less than $100,000. You see across those categories about 48% of those parents have used unpaid childcare. Unpaid childcare is childcare that’s provided by someone besides the parents, but that’s not paid. A common source of unpaid childcare is a grandparent. It could also be an aunt or uncle, it could also be a neighbor in some cases is also something like a Head Start program. It can also be the child’s siblings. We see a slightly lower incidence of unpaid childcare among families that are in the highest income category earning $100,000 or more, but still a pretty meaningful share.

If you look at paid childcare, you see a really strong pattern by income with families that are in the topmost income bin that showed on this slide. So, making $100,000 or more being more likely to use paid childcare at 35% compared to numbers that are in that are 16 and 12% for the lower income bins. Slide 15 then goes in and presents a related breakdown of who uses unpaid and paid childcare, and that’s in terms of the number of parents and whether those parents are working. So, it shows the incidence of using unpaid childcare and paid childcare for single parents who are working, for two-parent households where both of the parents are working and for two-parent households where one of the parents is working and one of them is not. If you look across those different groups, you can see that single parents have the highest incidence of using unpaid childcare, which speaks to the importance of having support networks nearby for single parents in particular to help out with childcare.

If you look at two parents where both of the parents are working, we see the highest incidence of paid childcare among those couples or both of those parents are working. And this is obviously related to having two incomes and so it’s obviously related to the income pattern that we saw on the slide before, but it just shows that this is a particularly important source of childcare for those two-parent households where both are working. And we see lower incidences of both paid and unpaid childcare among two parent households where one parent is working and the other is not working. Slide 16 then goes into a related concept in terms of childcare and that’s just showing you the cost of childcare or showing you how much people pay for childcare. And so specifically those are median childcare costs for parents of children 13 years or under age 13 who use childcare at least 20 hours per week and it’s showing them relative to people’s housing payments.

So, it’s split out by homeowners who have a mortgage and renters who pay a positive rent. And across both of these groups, childcare costs are about 70% of people’s housing payments. So, for homeowners, that’s their mortgage, for renters, that’s their rent. Since this is the largest monthly expense for many households, this shows that childcare costs are pretty significant for many families if you’re using paid childcare at least 20 hours per week. Slide 17 then goes through and talks about these, this non-traditional or gig employment, which is something that we followed for a while in the SHED and that we’ve reintroduced this year. It presents three broad categories of gig work as we call it. So, that’s selling items. These are items that you could have owned for personal use. You could have made them, you could have bought them to resell them, and we saw that 13% of people sold items in the month before the survey, and that can be either online or offline in places like flea markets.

We also ask about offering short-term rentals or vehicles or properties. And then the third category are what we’re calling short-term tasks, which are small projects that people would do for money. This could be something like a home improvement project that you do for someone like mounting a TV for someone. You could design a logo for a small business. You could also drive someone somewhere or deliver food. We break out what we call platform tasks, which are these short-term tasks that you coordinate using an app or website in the case of for instance, driving someone somewhere that would be the Uber or the Lyft app or delivering some food, possibly Uber, possibly DoorDash, and then a few other apps that people would use to coordinate these other short-term tasks. We saw that about 4% of all adults did one of these short-term tasks using an app or website or a platform task in the prior month and 20% of people did one of the categories of gigs that we asked about in the prior month.

Slide 18 goes in and for those groups of people who did either platform tasks or did any gigs, basically it shows the share of people who agreed with a series of statements about what roles gigs serve and what they think about gigs in some sense. The first group of statements has to do with the unique characteristics of gigs relative to traditional or what we think of as traditional work, and that involves flexibility and agency. The first statement is, I’m my own boss doing it, which a majority of people across gig categories agreed with. So, they feel as if they have some agency and that they’re their own boss doing these kinds of gigs. The second statement is, it lets me work flexible hours, which in particular people who did platform tasks agreed with in large numbers, 78% of those folks agreed with that statement. The next statement is it gives me work-life balance, which a substantial but a smaller share of people agreed with, which just shows that work-life balance is not necessarily the same as flexibility for people.

And then the last statement is one of a series of statements that we ask people to evaluate that have to do with the financial role of gigs in people’s lives, and it’s a fairly strong statement. It’s, ”without it I would have trouble making ends meet.” So, this speaks to the importance of income from gigs in terms of bridging unexpected expenses or changes in people’s incomes or just managing their bills from month to month. And in particular, 41% of people who did platform gig work agreed that without this kind of gig work, they’d have trouble making ends meet. So, with that, I’ll move to the next slide and I’ll turn it over to my colleague Alicia Lloro who will talk through a few of the financial risks that we asked about with the SHED.

Alicia Lloro

Thanks, Mike. So, as Mike just mentioned, I’m next going to highlight three areas of financial risk for consumers involving Buy Now, Pay Later, Financial Fraud, and Scams, which were some new questions that we added to the survey this year. And then I’ll wrap things up with a discussion of homeowners insurance. So, moving to the next slide. So, on this slide, starting with the figure on the left, we show overall rates of buy now, pay later use, and here we can see that BNPL use has continued its upward trajectory taking up one percentage point to 15% in 2024. The figure on the right shows what I think is one of the more striking findings in the report this year, and that’s the spike in the share of buy now, pay later users who paid late and that’s shown by the top line in blue, darker blue. Nearly one quarter of buy now, pay later users paid late in 2024 up sharply from 18% in 2023.

The bottom line in the light blue shows the share of buy now, pay later users who are charged extra for paying late and here we see this has increased as the share of buy now, pay later users paying late has increased, and overall the share, yeah, who paid late has increased. Next slide. So, to dig into this result a little bit further about that spike we saw in the share of buy now, pay later users paying late, we look at how paying late varied across different income levels. And the main takeaway from this figure is that the increase in the share paying late occurred across all income levels, but if we look at just a percentage point increase, it was highest among those with an income of less than $25,000. Also, while not shown on this slide, we did look at other types of monthly payments, for example, credit cards and other monthly bill payments, and we didn’t see large changes in payment behavior with those other methods. So, this is something that we’re seeing was unique to BNPL at least in the SHED.

Next slide please. So, I’ll now turn to our results on financial fraud and scams. The figure on this slide is showing the share of adults who experienced financial fraud. This is both overall and by different age groups. So, we start with the set of three bars all the way to the right. It shows that overall 21% of adults said they experienced financial fraud. That’s the gold bar with 17% reporting credit card fraud in the light blue bar and 8% reporting another type of financial fraud, the dark blue bar. Then moving to the left, the group of bars shows how rates of financial fraud varied by age with the main takeaway here that adults age 45 and over were more likely to experience financial fraud, but this was mostly driven by their higher incidence of credit card fraud. So, that would be the light blue bar. You can see the increase there, other types of financial fraud while higher for the 45 and above. Then younger, it’s really not as drastic of a difference as the credit card fraud.

And one reason why we may be seeing the pattern with credit cards is that older adults are more likely to have credit cards in the first place. So, it follows that they’re more likely to have experienced credit card fraud. Moving on to the next slide. I would like to now turn to dollar losses that people experienced because of financial fraud, and this is one of the areas where we felt SHED could really be a value add in the financial fraud and scam space. We do know a lot about different types of frauds that are reported through official channels at the FTC or the FBI, but having a national random sample allows us to provide estimates for how much overall money was lost due to fraud. So, even though credit card fraud was the most common type of financial fraud and also as we know is quite costly for financial institutions, consumers are typically not required to cover these losses directly and it’s for this reason that we’re going to focus on losses for that 8% of adults who said they experienced financial fraud not related to their credit card.

So, among adults experiencing non-credit card related fraud, 63% reported losing money and 32% said that at least some of that money was not recovered. We also found that half of those who reported losing money lost at least $500 while a quarter lost 2,000 or more. We also saw that older adults tended to lose larger amounts of money, and this was particularly true at the higher end of the loss distribution, and we think this may be because older adults tend to have more wealth to begin with. So, that may be why we’re seeing they have higher dollar losses. Taken together the total dollar amount of non-credit card related fraud among consumers was estimated to be at least $84 billion. Consumers were compensated for 21 billion of that resulting in a net loss of $63 billion borne directly by consumers. Next slide.

So, this brings us to the final topic that we have today, which is homeowners insurance. We continue to hear reports in the news and elsewhere about insurers raising rates and even pulling out of certain markets or states entirely. And so to help inform how these developments may be impacting homeowners and their financial situation on the SHED, we again asked homeowners if they had homeowners insurance and this was for their primary residence. Overall, 7% of homeowners went without homeowners insurance and maybe at risk financially in the event of unexpected damage to their home. This share varied quite a bit across geography, which you can see here on the map on the slide. The lowest share we had was in New England and that was 2% going without homeowners insurance and then the region with the highest share was down there in dark pink including the states of Arkansas, Louisiana, Oklahoma, and Texas.

Also, while not shown on the slide, we find that people living in the southern region, so these states you see on the map shaded in pink, were also among the most likely to report being financially affected by a natural disaster or severe weather event. So, taken together with this figure, those areas where we’re seeing people having been financially affected by natural disasters are also among the most likely regions where people are going without homeowners insurance. Next slide. So, one new question that we added to the survey this year to help inform the results that we were seeing around homeowners insurance was to ask people who said they went without homeowners insurance the main reason why, and by far the most common reason was that they could not afford it and then a distant second was that it is not worth the cost.

But both of those were related to the cost of homeowners insurance. And despite the reports that we hear in the news about homeowners pulling out of states entirely, only 7% of those going without homeowners insurance said that it was because no insurance company will insure my home. So, I don’t want to overstate these results along those stories. It is possible that homeowners insurers pulling back has affected cost increase, which leads people to go without homeowners insurance, but at least from our results here, it’s not that they can’t find an insurance company, it’s that they can’t afford it is the most common main reason.

So, that wraps up the new results that we have for you. On the next slide, I would like to leave you with five key takeaways that we have from the presentation. So, in case you had to step away or you just want to, what do you all think are the five most important things from the talk today? That’s what we have here. So, number one is that financial well-being was similar to the previous two years, but below the high that we reached in 2021. Two, inflation and prices still were a major concern for people despite the official inflation rate having moderated. Several key measures of the labor market looked similar to 2023, although fewer people moved into jobs that they considered better.

Four, based on the new questions we added around financial fraud and scams, we found that the amount of money loss to non-credit card related fraud was substantial and much of that was borne directly by consumers. And finally, number five, most of those homeowners who were going without homeowners insurance said the main reason was that they couldn’t afford it. They did so because of cost. And then the last slide I have for you today here we show all the various sections that we have in the full report, so there’s so much more in the report that we have that we don’t have time to cover today. If you’re interested, I encourage you to go take a look at the report. Also, if you have some questions for us today about any of these topics, hopefully we can try to answer those questions if it’s something that we covered in the SHED. So, finally, I would like to pass things back to Sydney.

Sydney Diavua

Thanks, Alicia. And I’d like to invite Ellen and Mike back on the screen for all of our audience. Please continue to submit your questions via the Q&A function they are rolling in and we’re going to try to get to as many of them as possible today. And so Mike, I’m going to start with you because we got a lot of questions asking about the child care data you presented and looking for some clarification. And so here’s one question. One would think most means more than 50% of households, but your data shows between 42 and 48%. So, why does paid versus unpaid not total 100%? What were the other options? Were there other options?

Mike Zabek

Sure, Sydney, and my apologies if there are any misunderstandings. On slide 14 of the presentation, for example, we presented the shares of parents of children under age 13 who were using paid and unpaid child care in some form. And those were shares of parents under age 13 who just used unpaid care or paid care. So, for instance, if you see on that slide, we said that 48% of parents of children under age 13 who were in families earning less than $25,000 a year used unpaid care. So, that’s meaning that 48% of those parents used unpaid care in some form and then the remaining 52% didn’t use unpaid care. They might’ve used paid care, they just didn’t use unpaid care and similarly for paid care. So, we said like 12% for that same group, that’s 12% who use paid care. And then the remainder, math on top of my head, 88% did not use paid care.

So, a lot of people did not use paid care. We also broke out who is the person who’s providing that unpaid care, and that’s a specific table within the report. Specifically it’s table 11. Most commonly it was a child’s grandparents, child’s sibling was also pretty common. And then another relative was also pretty common. I think 30% of all parents of children under age 13 relied on children’s grandparents for unpaid care. And we also break out in figure 12 in the report specifically how many people didn’t use any form of child care paid or unpaid? How many used just paid, how many used unpaid and how many used both? So, hopefully that clears up any misunderstandings or allows people to go little into a little bit more depth about what those questions say.

Sydney Diavua

I think it does. I think I saw an applause reaction go up and so I think that helped it for our audience. Well, another question for you again, on child care, is there a sense of what type of unpaid child care is the most popular? What’s got the greatest market share?

Mike Zabek

So, I don’t know if I could say in terms of a market share, but I think that that table in the report, table 11 that I mentioned is kind of giving, who’s the person who’s the most likely to provide unpaid child care? And that’s most typically the child’s grandparents. Those people are about, as I said, 30% of parents of children under the age of 13 have relied on the child’s grandparents in some form to provide unpaid care. Another thing that’s notable that you can kind of see in the report and specifically in the appendices, we also ask a question about how many hours per week typically the person is providing unpaid care. One thing to note is that typically there’s fewer hours in a week where unpaid care is being provided than for instance, for paid care, which kind of makes sense. It kind of fits at least with my perception of unpaid care as being particularly useful in a pinch. But maybe not always something that everybody can rely on all the time, though it probably depends upon your individual circumstance.

Sydney Diavua

Thanks, Mike. I’m going to encourage our audience, please use the Q&A function. I know a lot of you all are getting a lot of great questions in via chat. We’re utilizing the Q&A function today to make sure we get to all the questions that folks have on the data. And so Alicia, I’m going to come to you. You talked about buy now, pay later. How did the survey define BNPL and was it limited to interest-free for payment loans as well as another part of this question is, did the survey ask about BNPL defaults, charge-offs collections or only late payment and associated fees?

Alicia Lloro

Yeah, thank you for the question. So, before I answer, I encourage you to heed Ellen’s advice and look at our appendices. So, we include the full instrument there. Happy to answer this question, but in case you’re wondering like, oh, what else might they have asked or how’d they ask this thing? It’s all there in the survey questionnaire so you can see, or if you forget what I say right now. So, the question that we asked was “in the past year have you used a buy now, pay later service to buy something?” Buy now, pay later lets you pay part of the price upfront and pay the rest over time?

It is sometimes called a pay-in-force service. And then we clarify that we are not asking about purchases made directly with credit cards, layaway or rent-to-own services. So, that’s our question. We’ve done a cognitive testing around that. One thing we wanted to make sure people weren’t including was like traditional installment payments, but as the buy now, pay later market continues to evolve, these definitions can get a little bit muddied. But anyhow, for the person who asked, that’s how we have asked it. And as far as the second part I think was about whether we’re asking about charge-offs or-

Sydney Diavua

Collections…

Alicia Lloro

For that one, yeah, for there we’re only asking people if they’ve paid late. So, it could be that they paid late and then they never cure or they never recover, but it could also be they paid late and then they make it up and then the loan becomes good again. So, we ask if they paid late and then among those who said that they paid late, we asked if they were charged a fee for paying late. So, these are really general questions and one of the reasons we do that is on the consumer side, they don’t think about things in the same way that we do as regulators.

So, we can’t obviously use words like charge-offs. So, we try to make it simple and also to provide information that we’re not getting elsewhere. So, we do see data on charge-offs from the big buy now, pay later firms, but just who’s initially paid late we may or may not see. So, that’s one of the reasons why we asked the question that way. Same thing for the fees, a lot of times, I think we don’t use the word fee. We say if you’ve paid extra for being late, because there can be different ways that consumers are charged. So, yeah, those are the answers there.

Sydney Diavua

That’s helpful. Alicia, I’m going to stick with you with one more question because I found this portion really interesting as well. In light of the new results, could you have asked more follow-up questions about financial fraud and scams? And if so, what would they have been and what are some questions that spring to your mind given these results?

Alicia Lloro

Yeah, thanks. So, again, this is an opportunity to look at our survey questionnaire. So, we did have more questions on financial fraud and scams than I was able to include in the presentation today. One of those that I think is useful that I would like to ask more of is about the non-financial costs of experiencing financial fraud and scams. So, obviously if you lose money, that’s not great, but also the time that you spend trying to recover funds or just dealing with the financial fraud or scams can also be very impactful for people. So, this time we had a question on that, so those results are in the report. There are other ways that you can be impacted non-financially. We chose to focus on hours. We’re always limited with how many questions we can ask, but I think exploring more of the non-financial impacts would be an interesting route.

Another area that I think would be nice to expand upon, excuse me, are the different payment instruments or the ways that people were affected by the fraud. These things can be really hard to ask about and kind of be clear on a survey. So, it is a challenge. We had some of that on the survey this year, but we restricted it to just bank-type products, excuse me, but I would be interested to open that up so we could see the impact of cryptocurrency and how people that interacts with fraud and scams. I will note it isn’t in the report, but we do see a strong correlation between people that say they used cryptocurrency to make a financial transaction and people who’ve said that they experienced financial fraud or scams. So, that’s another area that I think would be interesting to look at. There’s many, it’s sadly a very hot area of topic and lots of interesting things to pursue.

Sydney Diavua

But good to flag what you can pursue in the next survey. Ellen, I’m going to come to you and just ask a little bit about healthcare. And so would, do you consider including the impact of healthcare costs, both insurance premiums and out-of-pocket expense as part of tracking household fragility measures?

Ellen Merry

Yes, we do have some content on healthcare in the survey. For this I’d look in the income and expenses chapter. We don’t ask about the burden of premiums, but we do know about the types of insurance that people carry and we have several questions about whether or not people had a major unexpected medical expense in the past year and the size of that expense and whether or not they have medical debt. So, that is definitely a component of fragility. We also ask questions about people skipping medical care because of cost. So, that’s definitely a component of fragility.

Sydney Diavua

I’ve got a question on a pretty hot topic around homeowners insurance. So, did the homeowners without insurance own their home outright? Mortgage companies typically require homeowners insurance.

Alicia Lloro

Yeah, great question. So, last year when we asked this question, we only asked it of homeowners who own their homes free and clear without a mortgage for that reason, because typically if you have a mortgage, you’re required to have homeowners insurance and we found that 13% of those who own their homes free and clear went without homeowners insurance. For the latest survey, we decided to open it up to all homeowners. So, there is some evidence of frictions in the timing and of getting homeowners insurance. So, it is possible that some who do have mortgages are maybe in between policies. So, for that reason we did open it up to all homeowners. If we restrict 2024’s results to just those who own their homes free and clear, we get 13% of homeowners owning free and clear. So, the person who asked the question is right. Most of those going without homeowners insurance are the ones who own their homes free and clear. So, yeah, that’s driving the results.

Sydney Diavua

And we received another note on that home insurance question, which would be, it would be nice to know how many folks have homeowners insurance that they feel is inadequate coverage as many folks in California are forced into state plans that have very limited coverage because no one else will cover them. Is that something that you all have investigated or could?

Alicia Lloro

So, not on the current survey, we don’t have a question that gets at that. It’s something we could consider for future surveys. It is challenging in some ways because as this person notes, California has the sort of insurer of last resort plan, but maybe the coverage isn’t great. Other states have different regulatory environments where they can increase costs more, but then they don’t have a backup plan. So, taking into account all the differences in the state markets, it might make it a little bit challenging, but that is something we could pursue. And yeah, my guess is that people aren’t too happy with their coverage, especially given all the rate increases as well.

Sydney Diavua

Thanks. Mike, I’m going to come back to you. We still have some more questions around caregiving. Did you ask about other caregiving specifically providing unpaid care for an adult or caregiving for a spouse or older parent?

Mike Zabek

Yeah, we did, which is fortunate. So, we’ve included some questions that I’ve asked about if you care for an adult and in particular the most common adult that people would care for is a parent or an in-law where we saw that 61% of people who provided unpaid care for an adult because of aging, disability or illness, were providing care for either a parent or a spouse’s parent. It’s also common to provide care for another relative, sometimes a friend or neighbor, sometimes a spouse or partner. We have specific kind of breakouts in terms of who’s more likely to provide care for an adult. In particular, there’s sort of a mountain-like age profile.

So, where people who are 45 to 59 are the most likely aged group to provide care for an adult, which kind of matches with kind of demographic patterns. Women are more likely to provide care for an adult than men are. And we also see that Black, Hispanic, and Asian adults are more likely than White adults to provide care for another adult. All of that’s in the report. Also, when people provide care for an adult, they’re pretty likely to do it pretty frequently. It’s pretty common to do that on a daily basis, particularly if you’re providing care for your spouse or several days a week is also pretty common as well. So, there’s a good amount of material there both in the report and in the data about providing care for an adult.

Sydney Diavua

Thanks. So, to our audience, a link to the report is now in the chat. If you’re interested in going into the appendix and learning more, and this question may get answered by that, but to the group, is there any geographic breakdown in the data by states or by regions?

Alicia Lloro

I can answer for some of that. So, in the report, it depends on the section of the report whether or not we’ve shown breakouts by region. So, in the housing chapter we do a lot by region or something called census division, which is the map I showed you on homeowners insurance. So, we do the geographic breakdowns there. In the overall financial wellbeing section, we have some metro versus non-metro. We also do some splits by an LMI community versus or track non-LMI. So, it kind of depends on the report. We don’t do systematic breakouts.

And then as far as state goes, we typically don’t break things down by state because our sample isn’t large enough to provide a precise estimate for each state. Certain states we have more of a sample than others. So, usually if it’s broken out by geography in the report, it’s either the four census regions or the, I think it’s nine census divisions. So, that is what we have on the geography usually. But I do encourage for those of you who like playing with the data, you can go in, download the data and run things by geography if that’s something your skill set allows.

Sydney Diavua

So, we’ve got a question. Can you give us a quick summary of higher education and student loan findings?

Ellen Merry

Sure, I can give a few of the findings on that. As you might expect if you’re following that space, we have seen an uptick. And just as a brief recap, the student loan payments on federal student loans were paused for a good while during the pandemic, and we’ve seen an uptick in the share people saying they need to make payments on loans and also a little bit of an uptick in the share people who are behind from this last year to this year. A couple of the interesting cross-sectional findings that we flagged in our report this year, one is that people may not be aware of is that student loan debt is actually a little bit more common among those who are not quite our youngest group, like the 30 to 44 age group.

A little bit less common under age 30. And this is in line with outside data that there are a smaller share of people that are in the younger cohort that have taken out loans. And also we’re seeing more people behind who have less than a bachelor’s degree who say have completed some college but not gotten a degree or maybe have an associate’s or technical degree. So, those are a couple of things that we highlighted in this year’s report.

Sydney Diavua

Thanks. Great. Can you highlight the main findings about remote work? And on another note, does the data have a spatial component?

Mike Zabek

Sure. So, I will talk a little bit about what we’ve asked the question about remote work for a good amount of time. One thing that’s really striking about remote work, particularly when we feel that in the initial points during the pandemic and that’s continued to today, is just how different it is by education. So, in particular, people with a bachelor’s degree are much more likely than people with either some college or a high school degree or less to either do some or all of their work from home. That’s also something that we highlight in the report specifically in figure eight. Looking at that, 34% of people with a bachelor’s degree or more or 34% of workers with a bachelor’s degree or more I should say, are doing some of their work from home. 26% are doing all of their work from home. Adding those two up off the top of my head, I believe that that’s 60% who are doing at least some of their work from home.

If you compare that with people with a high school degree or less, that’s nine and nine, so that’s 18%. So, that’s a lot lower. Another thing that’s notable is we break it out in the report by whether someone’s self-employed or they work for someone else. Self-employed workers are more likely to work from home. And then over the past few years we’ve seen bigger declines in remote work for people who are employed by somebody else. Another thing that we highlight in the report. So, I think that that’s interesting. I don’t know that I can improve very much on Alicia’s response in terms of the geographic component of the data. We do have those breakouts by those different sections. I also would encourage you if you’re really interested in geographic breakouts and are willing to get your hands dirty to go through and look at all of our geographic identifiers in the public data. I believe we have state in there at least. So, you could look and see how it varies across different states. You could also do those kind of division breakouts that we showed.

Sydney Diavua

Thanks, Mike. So, we’re moving closer to the end of our time together, but I do want to come back to our polling question because about 33% of the group said that they were coming to this webinar to understand broad economic trends and about 28% said they were here for general knowledge. So, I want to come to you all as a survey team and just ask, what did you find most interesting about this year’s survey? What’s something that our audience should take away from your perspective on the survey? Mike, how about I start with you?

Mike Zabek

So, I’ll start. I obviously looked at the portions of the survey that I looked at and I’m interested in the things that I looked at. So, the thing that I thought that was really striking and I think is actually pretty unique in terms of the SHED is these questions that we had about people’s use of gig work and people’s motivations for doing gig work and some of those things that I presented in terms of the slide, notably just how many people said that without gig work, they would have trouble making ends meet. And also we had a pretty high share of people that said, particularly among platform workers, that they wish the pay was more consistent in terms of gig work.

And a lot of people said that the flexibility was really good. A decent portion said that it gives them work-life balance, but a lot of people really said they’d like the pay to be there more and that the pay was important for them in terms of making ends meet for, I guess a minority of people who were doing gig work, but a decent share nonetheless. So, I thought that that was particularly striking when I first saw it.

Sydney Diavua

Ellen, how about you?

Ellen Merry

Well, I think the things that stood out to me, again, I worked on the sections of the report related to income and expenses. And so some of the things that stood out in my mind were results related to prices and inflation. We continue to see that that’s an issue and a challenge for people. It comes out, and you can see it in the well-being chapter, a question about the top challenge that people face, inflation and prices is continuing, has been there for several years as the top challenge people mentioned. You also see it in the income and expenses results that the figure that I showed about people who said that changes in prices made their finances worse. There’s some interesting questions about people still taking actions in response to higher prices and even a time trend about people’s changes in expenses and changes in income. You can sort of see a pop-up a few years ago and it’s come down a little bit, but not dramatically. So, that stood out to me.

Sydney Diavua

And Alicia, final thoughts from you?

Alicia Lloro

Thank you. So, yeah, there’s so much that I find interesting. I’ll go with something that I didn’t talk about in the presentation and that is, it’s figure seven in the report and it goes over people’s assessment of their own financial wellbeing, their assessment of their local economy and their assessment of the national economy. And so a couple things from this figure I find interesting. So, first thing to note is that compared with 2019 before the pandemic, people’s assessment of their local and national economy has really plummeted. So, it dipped to maybe half for the national economy after the pandemic, and then as inflation took off it, things looked worse. But the part I found interesting, the most recent survey is that we saw increases from 2023 to 2024 in people’s views on the national economy and their local economy. And then these increases, if you look, there’s been a lot of questions about geography.

So, if you look at metro, non-metro or across regions, you’re seeing the increase by all those different geographies. So, it wasn’t a huge increase, but yeah, it was some, which again considered the context of when the survey was taken late October, early November. I was like, oh, interesting. But then I dovetail that with what Ellen mentioned, that people were still really concerned about inflation and they were still feeling the effects. So, they thought things were improving, but the inflation was still top of mind. So, I found that to be interesting knowledge that I wouldn’t have otherwise had if I didn’t work on SHED.

Sydney Diavua

Well, thank you so much for that, and thank you to the SHED team. Thank you to our speakers for providing all of this insightful and information. Thank you for engaging our audience. And audience, thank you for all of those great questions that you put into the queue and for all of your valuable time that you spent with us today. If you all would like more information on the survey on household decisionmaking, please visit federalreserve.gov/shed and that link is also in the chat.

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