On September 30, the Federal Housing Finance Agency (FHFA) released estimates of house price growth for the second quarter of 2025. Their index is estimated using actual sales prices as well as appraisal data, but the data are _not_ seasonally adjusted. Because home prices can fluctuate over the year, with a cooler market in winter months and a pick-up in the spring, it’s best to measure home prices relative to the same period a year ago. And that’s what our FRED graph above does. * Since 1976, housing prices have increased an average of 5.1% per year, while the consumer price index (CPI) inflation rate has increased an average of 3.7% per year. * In the second quarter of 2022, coming out of the COVID-19 pandemic, house price growth and CPI inflation peaked at 20.5% and 8.6%, respectively. * In the second quarter of 2025, the most recent data available indicate house price growth and CPI inflation increased 3.8% and 2.5%, respectively. While broader CPI inflation trends are relatively consistent across the nation, there’s considerable variation in house prices. (FRED also has CPI data for US metro areas.) The FRED map below shows second-quarter house price growth for all 50 states and Washington, DC. Prices increased in all states, but declined in DC. Outside of the nation’s capital, house price growth was the slowest in Colorado (0.9%) and Florida (1.0%). The fastest house price growth was in the Northeastern portion of the US, with Connecticut and New York home prices both increasing 7.5% from one year ago. For more geographic detail, check out FRED’s FHFA house price data for 337 US metro areas, 24 of which had price declines relative to one year ago. The steepest drop in prices occurred in Punta Gorda, Florida, at –7.4%, followed by Cape Coral-Fort Myers, Florida, at –6.6%. Sumter, South Carolina, had the fastest growth at 18.0%, followed by Auburn-Opelika, Alabama, at 11.8%. **How this graph and map were created** : **Graph:** Search FRED for and select “All-Transactions House Price Index for the United States.” The series you want should be at the top of the results. Change the time frame to 1976-01-01 to the Most Recent data release. From the “Edit Graph” section, change the units to “Percent Change from a Year Ago.” Click “Add Line” and search for “Consumer Price Index for All Urban Consumers: All Items in U.S City Average” and click “Add data series.” Make sure the units are also “Percent Change from Year Ago.” **Map:** Search FRED for and select “All-Transactions House Price Index for Missouri.” Click the “View Map” button and then “Edit Map”; change units to “Percent Change from Year Ago” and the “Data grouped by” to “User Defined Method” with intervals of 0, 2, 4, 6, and 8. Change the <0 to the color red to identify negative values. Suggested by John Fuller and Charles Gascon.

On September 26, 2025, the Bureau of Economic Analysis released real GDP data for all US states for the second quarter of 2025. The FRED map above shows the percent change growth rates from the previous quarter: Red denotes contraction, light green denotes slight growth, and dark green denotes rapid growth. **Highlights** * 48 of 50 state economies grew in the second quarter, with a national average of 3.3% growth annualized. * The median state grew at 3.5%, and 23 other states had slower growth than the US average. * North Dakota had the fastest growth, at 7.3% annualized. * Arkansas had the steepest contraction, at –1.1% annualized. The St. Louis Fed’s Eighth District states all grew except for Arkansas and Mississippi, which contracted 1.1% and 0.9%, respectively. Illinois and Kentucky were the only District states that grew above the national average: Illinois had the largest growth, at about 4.8%, and Kentucky grew 4.6%. Missouri, Tennessee, and Indiana were all close to the national average, each growing 3.1%. **NOTE:** These data are subject to future revision by the source. Our ALFRED database records vintages of the data, so users can view the data as they appeared at various points in history. The link takes you to real GDP for Missouri, as of September 26, 2025. **How this map was created** : Search FRED for “Real Total Gross Domestic Product for Missouri” and click the first available series. Click the “View Map” button and then the blue “Edit Map” button. Modify the units to “Compounded Annual Rate of Change.” Use “Format” to switch the number of color groups to 3, with the data grouped by “User Defined Method”; then define the scales to be 0, 4, and 10. For values less than 0, choose red to show contraction; for values less than 4, choose light green to show slight growth; for values less than 10, choose dark green to show faster growth. Suggested by John Fuller and Violeta Gutkowski.

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Net worth is the difference between total assets and liabilities. Tracking changes in the distribution of net worth can provide insight into how individual economic groups are faring, at least compared with each other. Our FRED graph above uses Board of Governors financial accounts data from third quarter 1989 to first quarter 2025 to track five percentile groups of US households: * Top 0.1% * Top 1% * 90th to 99th percentiles * 50th to 90th percentiles * 1st to 50th percentiles For most of the time, the 90th to 99th percentile group (pink line) has had the largest share of overall net worth. Much of the time it’s closely followed by the 50th to 90th percentile group (green line). In 2003, the shares of these two groups began to diverge and the gap between them began to widen. Right before and throughout the pandemic, however, that gap markedly shrank: The share of the 90th to 99th percentile group decreased as the share of the 50th to 90th percentile group increased, shown by the convergence of the green line and the pink line. The difference in aggregate wealth between these groups was 11.4 percentage points in 2019:Q2. In 2022:Q3, that difference fell to nearly 5 percentage points, the lowest it’s been since 2006. **Some background** It’s possible that changes in spending behaviors and income set off by COVID-19 contributed to a smaller gap between the 90th to 99th percentile group and the next 40 percentiles. In their FEDS Notes article, Michael Batty, Ella Deeken, and Alice Henriques Volz report that a rebound in the stock market combined with increases in pension entitlements drove up assets for the 50th to 90th percentile group. Our FRED graph below shows the difference in the share of wealth between the 90th to 99th percentile group and the 50th to 90th percentile group. Although the gap fell somewhat drastically from 2019 to 2022, it has risen in recent years, indicating that lower inequality between these groups might be short-lived. **How these graphs were created** : Search FRED for “share of net worth” and select the first series labeled by percentile. Use the “Add line” tab to search for and select the other four percentile groups. For the second graph, select the 90th to 99th net worth percentile series. Use the “Customize Data” tab to search for and add the 50th to 90th group. Type _a-b_ in the formula field. Suggested by Anna Cole and Michael McCracken.

Consumer price indices are supposed to cover everything that households buy. That includes “administratively set prices” for various fees and taxes. Postal services is one example. Our FRED graph above shows postal services price indexes for a few European countries. These prices typically change infrequently; thus, their evolution often looks like a step function. (This step pattern can also occur for some product categories that aren’t sampled every month, such as housing rents.) There’s also some indication these price have changed more frequently recently. This may have to do with the “technological” innovation in some countries of labeling stamps as a service instead of a value, which makes it easier to change the price. (Read more about this menu-cost theory of price stickiness.) Our second FRED graph, above, provides some local color: In the Netherlands and Latvia, letter postage is lower in December to encourage people to write to family and friends for the holidays. There are even special December stamps that are valid only from mid-November to early January. Our third FRED graph, above, explores the interesting case of Denmark. The Danes have highly advanced digital communications and send few physical letters anymore. Their postage prices (solid blue line) have increased much more than their general level of prices (dashed green line). It now costs 29 Danish kroner ($4.56) to mail a domestic letter, and the Danish postal service will stop delivering letters at the end of 2025. Then there’s the case of Turkey, shown in our final FRED graph below. They’ve had an even speedier increase in postal prices, but it’s largely due to overall inflation. **How these graphs were created** : Search FRED for and select the “postal Spain” price index. From the “Edit Graph” panel, use the “Add Line” tab to search for and select the “postal Greece” and “postal France” series. From the “Format” tab, change the line patterns to make the separate steps more apparent. Use a similar process for the other graphs. Suggested by Christian Zimmermann.

In a previous FRED blog post, we discussed the Summary of Economic Projections (SEP) released by the FOMC this past June. In this blog post, we will again use ALFRED to compare the latest projections released in September 2025 with several of the recent projections for the following variables: * the unemployment rate * core PCEPI inflation * real GDP growth * the federal funds rate It’s important to note that these projections represent neither a committee plan nor a decision on future policy. The first ALFRED graph, above, shows the unemployment rate projections for the fourth quarters of 2025, 2026, 2027, and 2028 according to the four most recent SEPs. Every September the FOMC adds another year to the projections. Most recently, as shown by the gold bar, the median FOMC participant projects that the unemployment rate will average 4.5% in Q4 2025 with a drop to 4.3% by 2027. This is slightly below the projection provided in June. The median projection for the unemployment rate in 2028 is 4.2%. The second graph shows the core inflation rate projections for the same years. The median FOMC participant projects 3.1% inflation over 2025, with a return to the FOMC target of 2.0% by 2028. The third graph, below, shows the median projections for real GDP growth. Growth projections for 2025 have been revised downward since December 2024, from 2.1% to 1.6%, but are above June’s projection of 1.4%. The projections for real GDP growth in 2026 and 2027 are slightly higher than they were in June, revised upward from 1.6% to 1.8% and 1.8% to 1.9%, respectively. The longer-run projection for 2028 is 1.8%. Our final graph below shows the median participant’s projections of the federal funds rate. The most recent projections for the fourth quarter of 2025 are lower than their June 2025 values: from 3.9% down to 3.6%. But they are similar to the March and December projections for 2026 and 2027, at 3.4% and 3.1%. June’s projections were slightly raised for 2026 and 2027, at 3.6% and 3.4%. The federal funds rate is projected to remain at 3.1% in 2028. It is worth noting, though, that focusing on the median federal funds rate projection does obscure some of the dispersion of the individual participant projections. For example, projections for the year-end policy rate range from 2.6% to 3.9%. **How these graphs were created** : Search ALFRED for “FOMC unemployment” and take the median projection. Click on “Edit Graph,” choose a bar graph, and add three bars with the same series again. Finally, select the proper vintage for each bar. For the other three graphs, proceed similarly with “FOMC Consumption,” “FOMC Growth,” and “FOMC Fed Funds Rate.” Suggested by by John Fuller and Charles Gascon.

During the onset of the COVID-19 pandemic, many credit card holders improved their repayment histories and enjoyed a noticeable boost in credit scores. However, research by Juan M. Sánchez and Masataka Mori at the St. Louis Fed has underscored the temporary nature of the factors driving that improvement in creditworthiness. Our FRED graph above uses large bank credit card data, reported by the Federal Reserve Bank of Philadelphia, to offer a complementary perspective on this topic: * The solid blue line shows the percentage of credit card accounts that recorded an increase in their borrowing limits. Between 2013 and 2019, that percentage rose steadily, declined precipitously during 2020, and quickly bounced back to its pre-pandemic trend. * The dashed green line shows the percentage of credit card accounts that recorded a decrease in their borrowing limits. The uptick in 2020 doesn’t stand out all that much compared with the entire period between 2013 and 2024. Thus, the short-lived boost to credit scores referenced earlier did not seem to translate into broad changes to borrowing limits. Our interpretation of the data matches the findings from recent research by Joanna Stavins at the Boston Fed. She notes that, as of late 2024, “any erosion of lending standards that took place during the early stages of the pandemic has been reversed.” In other words, the credit card industry has seemingly returned to its long-term, relatively stable practices. **How this graph was created** : Search FRED for and select “Large Bank Consumer Credit Card Balances: Accounts with Credit Line Increase.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Large Bank Consumer Credit Card Balances: Accounts with Credit Line Decrease.” Suggested by Noelle Pak and Diego Mendez-Carbajo.

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Visit any data series page in FRED and you’ll see a “Notes” section below the graph. The metadata there provide details that help tell the story behind the numbers. Arguably, the single most important metadata are the data _units_. Our FRED graph above shows potato farming acreage in four different countries—the US, France, Germany, and Great Britain—between 1829 and 1951. Just as languages can differ across countries, so can the units of measure. So when using data to measure the land area used to plant potatoes, potatos, Kartoffeln, or pommes de terre, it’s important to confirm all data series are using the same units. In this case, data from continental Europe were reported using the decimal system (in hectares) and data from Great Britain and the US were reported using the imperial system (in acres). Fortunately, FRED makes data customization very easy: Use the “Edit Line” tab to select the relevant series that use hectares and input the formula _a*2.47105_ to effectively convert those units to acres. After customizing the potato acreage data, we can properly compare the disparate size of potato farming across these four countries. Note the very large land area that Germany devoted to potatoes. If we hadn’t accounted for the difference in units, we could have easily drawn a completely different conclusion. What a dis-tater that could have been. A note about the metadata in FRED’s notes section: * _Source_. Name of the organization reporting the data. * _Release_. Name of the publication in which the data are reported. * _Units_. Standardized quantities used to measure a concept. * _Notes_. Additional information about the methods used to report the data or guidelines for sharing those data. * _Suggested citation_. Bibliographical citation of the data series shown in the graph, ready to copy and paste . **How this graph was created** : Search FRED for and select “Potato Crop Acreage for United States.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Potato Crop Acreage for France.” Click on “Add data series.” Next, use the “Edit Lines” tab to select “Line 2” and customize the data by typing the formula “a*2.47105” and clicking “Apply.” Repeat the “Add data series” steps to search for and add “Potato Crop Acreage for England, Wales, Scotland, Great Britain” and “Potato Crop Acreage for Germany.” Lastly, customize the data for Germany applying the formula spelled out above. Suggested by Diego Mendez-Carbajo.

The labor force participation rate (LFPR)—the percentage of civilians employed or actively seeking work—has declined since the turn of the century as shown in our first FRED graph above. Previously, total LFPR had risen after an increase in women entering the workforce and a corresponding but smaller drop in men’s LFPR. Since 1990, women’s LFPR has stabilized but men’s LFPR has continued to decline at an average rate of 2.7 percentage points per decade. Our second FRED graph above splits male workers into three age groups—15 to 24 (high school and college age); 25 to 54 (prime working age); and 55 to 64 (near-retirement). The rate for older men (orange line) has been relatively constant, but the rate for prime-age men (green line) has steadily decreased. The decline for younger men (blue line) is even more pronounced, which may be explained by more young men opting for more education. The drop in the LFPR for prime-age men was studied by Leila Bengali, Evgeniya Duzhak, and Cindy Zhao at the San Francisco Fed. They state that the gap in participation between prime-age male Millennials today and male Baby Boomers (when they were of prime working age) can be explained by higher incidence of postsecondary education attainment, self-reported disabilities or illnesses, and caretaking responsibilities. They also summarize other economic research that attributes this decline to changing industry structure, falling demand for jobs that prime-age men have traditionally held, and the opioid crisis. **How these graphs were created** : Search FRED for and select “Labor Force Participation Rate.” Below the graph, click on the release table link, select the series, and click “Add to Graph.” Use the “Format” tab to customize line style and color. Take a similar approach for the second graph after searching for “Infra-Annual Labor Statistics: Labor Force Participation Rate Male: From 15 to 24 Years for United States.” Note: Labor force participation rates by age group in FRED are sourced from the Organisation for Economic Co-operation and Development. The labor force participation rate data in the first graph is from the Bureau of Labor Statistics. There may be slight differences in LFPR values between the two agencies. Suggested by Brooke Hathhorn and Michael Owyang.

IDEAS is a central index of economics research

CitEc is an autonomous citation index for documents distributed on the RePEc Research Papers in Economics, data base. It provides indicators like impact factor and h-index for journals and working paper series