Federal Reserve Economic Data

In a previous FRED blog post, we discussed the Summary of Economic Projections (SEP) released by the FOMC this past March. In this blog post, we will again use ALFRED, the vintage data version of FRED, to compare the latest projections released in June 2025 with several of the recent projections through 2027 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, and 2027. Most recent values are shown by the gold bar. The median FOMC participant projects that the unemployment rate will average 4.5% in Q4 2025 and drop to 4.4% by 2027. This is just above the projection provided in March and only slightly higher than the longer-run unemployment rate projection of 4.2%.

The second graph shows the core inflation rate projections for the same years. The median FOMC participant now projects 3.1% inflation over 2025 and just-over-trend inflation of 2.1% by 2027.

The third graph, above, shows the median projections for real GDP growth. Growth projections for 2025 have been revised downward since December 2024, from 2.1% to 1.4%. However, the projections for growth over 2027 remain unchanged from the projections released in March, at 1.8%.

Our final graph shows the median participant’s projections of the federal funds rate. The most recent projections are unchanged from their March 2025 values for 2025, but are slightly higher than the March projections for 2026 and 2027. 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 3.6% to 4.4% (almost a full percentage point spread).

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 Joseph Martorana and Charles Gascon.

Credit spreads are the difference between the performance of corporate-issued debt and the spot Treasury curve. Analysts look at these spreads to gain insight into the return investors get for owning riskier securities, as opposed to risk-free Treasury bonds. However, different segments of the corporate credit sector have different means and variance, which makes it difficult to compare the evolution of credit spreads over time and understand if financial conditions are tight or loose.

The FRED graph above allows us to compare spreads across different investment grade categories: The blue, red, green, purple, and teal lines are credit spreads from the whole US corporate, BBB, single-A, AA, and AAA indices, respectively.

The graph displays the z-scores of credit spreads from the end of 1996 to the present. These z-scores are the position of a raw variable in terms of its distance from the mean, measured in standard deviation units. Values below zero indicate a negative distance from a mean credit spread, indicating relatively small spreads. On the other hand, values above zero indicate relatively large spreads. Not surprisingly, there are spikes across all investment categories during recession periods (shaded in gray). These spikes indicate the relatively high risk of purchasing corporate debt at these points in time compared with the entire period.

Since the pandemic, credit spreads have narrowed, with indices below zero indicating levels beneath the historical average. Further, credit spreads are currently about half a standard deviation below the historical mean across all investment-grade categories. This suggests that financial conditions are loose.

How this graph was created: Search FRED for and select the following series IDs. For each new credit spread, click the “Edit Graph” then the “Add Line” option.

• BAMLC0A4CBBB
• BAMLC0A0CM
• BAMLC0A3CA
• BAMLC0A2CAA
• BAMLC0A1CAAA

Download the data and calculate the mean and standard deviation of each credit spread using your favorite tool. Go back to the graph in FRED and edit the formula for each line. Change each formula from a to (a-u/s) where u and s are the mean and standard deviations for a given credit spread, respectively.

Suggested by Anna Cole and Julian Kozlowski.

The FRED Blog often uses data from the US Bureau of Labor Statistics (BLS): A few years ago, we used their Consumer Expenditures Survey to discuss the preferences for life insurance and other personal insurance services among different population groups. Today, we use data from the Producer Price Index program of the BLS to discuss the premiums charged for some of those services.

The two solid lines in the FRED graph above show the year-over-year percent growth rate in the premiums charged for insuring two types of assets: private automobiles (red line) and homes (green line). The dashed black line is the annual growth rate in the headline property and casualty producer price index, which includes, among others, commercial, medical, and worker’s compensation insurance.

Since 1999, when data are first available, cycles in the growth rate of insurance premiums are easily visible. For example, two distinct periods of fast growth in automobile insurance premiums in the early 2000s and mid-to-late 2010s were followed by periods of much slower growth and even decreases in premium values. So, what can help explain those cyclical fluctuations in value?

The 2023 annual report on the insurance industry by the Federal Insurance Office names several factors impacting the overall financial standing of insurers. Most recently, widespread natural disasters have resulted in large payouts and higher interest rates have decreased the value of fixed-income securities held in this sector’s investment portfolios. To compensate for those losses, insurers have raised their premiums at a pace not recorded in many years.

How this graph was created: Search FRED for and select “Producer Price Index by Industry: Premiums for Property and Casualty Insurance.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “Producer Price Index by Industry: Premiums for Property and Casualty Insurance: Premiums for Private Passenger Auto Insurance.” Click on “Add data series” and repeat the previous step to add “Producer Price Index by Industry: Premiums for Property and Casualty Insurance: Premiums for Homeowner’s Insurance” to the graph. Next, select the “Edit Lines” tab and use the “Units” dropdown menu to select “Percent Change from Year Ago.” Lastly, use the “Format” tab to customize the line styles.

Suggested by Diego Mendez-Carbajo.