The FRED^® Blog

The takeaway

Measures of household financial well-being don’t always align with consumer sentiment. You can feel relatively secure about your finances while still being pessimistic about the overall economy.

Are you doing OK?

In an earlier post, we described a measure of household financial well-being from the Federal Reserve Board’s Survey of Household Economics and Decisionmaking (SHED). In this post, we add a way to measure households’ view of the economy: the University of Michigan’s Index of Consumer Sentiment.

Our FRED graph above tracks, side by side, the share of adults who say they’re “doing okay financially” from the SHED and the index values of consumer sentiment from the University of Michigan.

Before the COVID-19 pandemic, these two measures moved in the same direction. The share of adults doing at least okay financially increased, while consumer sentiment was also relatively high. The story looks different after the pandemic. Consumer sentiment fell sharply and remains low: Its value averaged 95.9 in 2019 and was 71.7 in January 2025. The share of adults saying they’re doing at least okay, though, has remained relatively high: It was 75% in 2019 and it was 73% in 2025.

There seems to be a disconnect. Most respondents continue to report financial stability while overall consumer sentiment is much more pessimistic than it was before the pandemic.

Are you worse off today?

The SHED also asks a more specific question: Are you worse off financially than you were 12 months ago?

Our second FRED graph, above, compares this measure with the same Michigan Consumer Sentiment Index. (We plot 100 minus the percentage so that an increase in one series is consistent with a increase in the other.)

Here, the two measures tell a more similar story. Before the pandemic, the share of adults reporting they were not worse off than they were a year earlier was increasing. After the pandemic, that share dropped sharply and has remained low. Measured this way, households’ assessments of their own finances are more consistent with the decline in overall consumer sentiment.

The difference between the two SHED measures may partly reflect what each question is asking. Saying you’re doing okay financially describes your current financial position. Saying you’re worse off than a year ago describes how that position has changed. It’s not hard to imagine a household reporting both these things at the same time.

It’s also possible that financial experiences have become more uneven across households, with some households doing relatively well while others have seen their financial situations deteriorate, consistent with the divergence of the two SHED measures.

And there’s another possibility. People may feel relatively secure about their own finances while still being pessimistic about the economy overall. The SHED explicitly asks about respondents’ own financial situations. The Michigan index is broader, incorporating views about personal finances, business conditions, and buying conditions. That leaves room for a disconnect between how people assess their own circumstances and how they assess economic conditions more generally.

The graphs don’t tell us exactly what’s driving the difference, but they show people’s assessments of their own finances can look quite different from their assessments of the broader economy.

How the graphs were created:
For the first graph, search FRED for and select “Survey of Household Economics and Decisionmaking: At Least Doing Okay Financially: All Adults” (series ID ATLEASTDOINGOKAYFINANCIAL). Click “Edit Graph,” click “Add Line,”  and search for and select “University of Michigan: Consumer Sentiment” (series ID UMCSENT). Click “Add Data Series.” Next, select the University of Michigan series under “Edit Lines” and open the “Format” tab. Set its y-axis position to “Right.” Set this graph to begin on January 1, 2013. and end on January 1, 2025, corresponding to the first and last years, respectively, available for this SHED measure.
For the second graph, repeat the same steps, replacing the first SHED series with “Survey of Household Economics and Decisionmaking: Worse Off Financially Than 12 Months Ago: All Adults” (series ID WORSEOFFFINANCIALLYALLADU). For this series, enter 100-a in the formula field. Again, add UMCSENT as the second line and place it on the right y-axis. Set this graph to begin on January 1, 2014, and end on January 1, 2025, corresponding to the first and last years, respectively, available for this SHED measure.

Suggested by Victoria Gregory.

The takeaway

The most recent measure of the cost of owning a home (vs. renting a home) remains near historical peaks, suggesting renting today is a relatively better financial choice for housing.

To own or not to own?

Which is the better financial choice—owning or renting your home? The FRED Blog has discussed how the cost of owning a home and the cost of renting a home tend to move together. An indexed ratio of house prices to rents helps show their relative values more clearly and, by extension, can help examine the value of one choice over the other.

A high ratio means house prices are growing faster than rents, making homeownership a relatively more expensive proposition. A lower ratio means buying a home is a comparatively better deal.

The data

Researchers at the Dallas Fed used price index data for homeownership and renting to create an index that shows the rapid rise of homeownership costs in 2020 and the high values since then.

Our FRED graph above allows us to approximate their ratio and track the relative cost of owning a home from first quarter 1975 to first quarter 2026. Here we use two different price indexes to create our ratio of house prices to rents: the all-transactions house price index from the U.S. Federal Housing Finance Agency and the CPI for rents from the Bureau of Labor Statistics. Both indexes were “re-based” to a value of 100 in January 2015. Our index shows a rapid rise and continued high values of homeownership cost, similar to what the Dallas Fed research showed.

Deeper analysis

The report from the Dallas Fed uses both U.S. and international data to identify patterns and the likely future evolution of an elevated house price-to-rent ratio. It concludes that “Rents rise along with inflation, while nominal house-price growth trails inflation. On an inflation-adjusted basis, rents change very little, but house prices fall sharply.”

In this homeownership costs ratio, the numerator is house prices and the denominator is rent prices. The ratio will become smaller if the numerator falls or the denominator rises. Because inflation increases rent prices relatively more than house prices, higher inflation would drive the ratio down, closer to its historical average.

How this graph was created: Search FRED for and select the series “All-Transactions House Price Index for the United States.” Click “Edit Graph,” use “Customize data” to search for “Consumer Price Index for All Urban Consumers: Rent of primary residence,” and click “Add.” Input the formula a/b and click “Apply.”

Suggested by Houston Myer and Diego Mendez-Carbajo.

The takeaway

More workers are using generative AI tools, using them more often, and saving more time because of them, according to new survey data in FRED.

The survey

Economists Alexander Bick, Adam Blandin, and David Deming built the Generative Artificial Intelligence Adoption Tracker using data from the Real-Time Population Survey (RPS). The RPS is a nationally representative online survey of working-age adults aged 18 to 64. Each quarter, employed respondents report how fast and how intensely they’re adopting AI technology both at work and outside of work.

The data

Our FRED graph above shows three data series from the generative AI adoption tracker: “Use Last Week for Work” (solid blue line), “Work Hours Assisted” (dashed green line), and “Time Savings” (dashed orange line)—all measured as a percent of employed adults (left axis) or percent of work hours (right axis).

All three lines trend steadily upward. The share of employed adults who used generative AI for work in the past week grew from 28.2% in Q3 2024 to 39.2% by Q2 2026, indicating adoption is broadening. The share of work hours assisted by generative AI grew from 4.1% to 6.3% over roughly the same stretch. Perhaps most importantly, the share of work hours saved thanks to AI assistance grew from 1.6% to 2.2%.

The summary

The information is based on how respondents self-report their “time saved,” so the measurements are inherently approximate. But these three data series together do tell a coherent story of AI adoption: More workers are trying generative AI, and the ones already using it are leaning on it more heavily. Rising time savings suggest AI is not just a novelty; it’s starting to free up real work hours. If this trend holds, generative AI could show up in broader productivity statistics in the years ahead.

How this graph was created: Search FRED for “Generative Artificial Intelligence, Use Last Week for Work: Employed Adults.” Click “Edit Graph” and select the “Add Line” tab. Search for “Generative Artificial Intelligence, Work Hours Assisted: Employed Adults” and click “Add Data Series.” Repeat the last step to search for and add “Generative Artificial Intelligence, Time Savings: Employed Adults.” Select the “Format” tab to customize line 2 and line 3 by selecting “Y-Axis position: Right.”

Suggested by Diego Mendez-Carbajo.