Federal Reserve Economic Data

In a previous FRED blog post, we discussed the Summary of Economic Projections (SEP) released by the FOMC this past September. In this post, we  again use ALFRED to compare the latest projections released in December 2025 with several of the recent projections for the unemployment rate, core PCEPI inflation, real GDP growth, and the federal funds rate. Note that these projections represent neither a committee plan nor a decision on future policy.

Our 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 blue bar, the median FOMC participant projects that the unemployment rate will average 4.5% in Q4 2025 and drop to 4.4% by Q4 2026 and 4.2% by Q4 2027. This path is largely unchanged from the September projection.

Our second graph, above, shows the core inflation rate projections for the same years. The median FOMC participant projects 2.5% inflation over 2026, which is slightly lower than the 2.6% projection in September. Median projections for 2027 and 2028 were unchanged.

Our third graph, below, shows the median projections for real GDP growth. Growth projections for 2025 have been revised upward since September, from 1.6% to 1.7%. Growth projections for 2026 are notably higher than they were in September, revised upward from 1.8% to 2.3%. As Chair Powell noted during the press conference, the apparent boost to growth in 2026 is partially due to the effects of the government shutdown shifting about 0.2% of GDP growth from late 2025 into early 2026.

Our final graph, below, shows the median participant’s projections of the federal funds rate. The December median projections over the forecast horizon were from their September values. As a result, there is no December vintage in ALFRED. It is worth noting that, although the median projections were unchanged, the forecasts of individual participants were revised. For example, in the September projections, participants’ forecasts for the end of 2025 ranged from 2.9% to 4.4%, while the range narrowed to 3.4% to 3.9% in the December projections. The median projection for the policy rate at the end of 2026 was unchanged between September and December, at 3.4%. The range of projections widened from a range of 2.6% to 3.9% to a range of 2.1% to 3.9%. The range of projections for 2027 was unchanged, at 2.4% 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 John Fuller and Charles Gascon.

All Federal Reserve Banks operate within a specific geographic area—called a district. The Cleveland Fed is in the Fourth District of the Federal Reserve System, which covers Ohio and parts of Pennsylvania, Kentucky, and West Virginia.

The Cleveland Fed’s Survey of Regional Conditions and Expectations (SORCE) covers the Fourth District, and FRED now includes 27 of those data series.

The FRED graph above shows the broadest summary of business conditions captured by SORCE.

• Total (solid blue line)
• Manufacturing and transportation (dashed green line)
• Other (dashed orange line)

The latest value for total business conditions at the time of this writing is 8. And what does that mean?

Each index value shows the difference between the percentage of survey respondents reporting increases and the percentage reporting decreases in business conditions, including demand, employment, inflation, etc. Measures calculated this way are often called diffusion indexes.

These values vary from positive to negative: The index shows a negative value when survey respondents reporting decreases outweigh survey respondents reporting increases. It shows a positive value when survey respondents reporting increases outweigh survey respondents reporting decreases.

Between June 2014 and the time of this writing, the SORCE index values have ranged between a maximum of 67 (May 2018) and a minimum of -80 (May 2020). Most frequently, they oscillate between 30 and -20.

FRED has an array of regional Fed datasets, with a few of them listed below.

• Chicago Fed’s Midwest Economy Index
• Dallas Fed’s Texas Employment Data
• New York Fed’s Empire State Manufacturing Survey

How this graph was created: Search FRED for and select “Total Business Conditions, Diffusion Index for Survey of Regional Conditions and Expectations (SORCE).” Click on the “Edit Graph” button and select the “Add Line” tab to search for and select “Manufacturing & Transportation Business Conditions, Diffusion Index for Survey of Regional Conditions and Expectations (SORCE).” Don’t forget to click on “Add data series.” Repeat the last two steps to search for and add “Other Industries Business Conditions, Diffusion Index for Survey of Regional Conditions and Expectations (SORCE).”

Suggested by Diego Mendez-Carbajo.

What’s really happening in US manufacturing?

In our FRED graph above, we compare labor productivity for all workers in the manufacturing sector alongside the share of manufacturing employment in total US nonfarm employment since 1987. The graph tells a compelling story: We’re producing more per worker in manufacturing, but with far fewer workers relative to the overall workforce.

Manufacturing productivity rose strongly from the late 1980s until the Great Recession in 2008-09. During this period, workers were producing more value per hour due to advances in automation, more-efficient production processes, and improved capital equipment. At the same time, the share of manufacturing workers in the total nonfarm workforce has been shrinking. This shows that even as factories are producing more, they require a smaller share of the labor force. Notably, these trends—often referred to as structural transformation—were underway long before the China trade shock of the early 2000s.

Since 2010 or so, we see that labor productivity in manufacturing has largely flattened, showing little growth compared with the period before 2010. Meanwhile, the decline in the manufacturing employment share has also slowed considerably.

This divergence has large implications. First, it underscores how innovation is reshaping manufacturing. The trends displayed above are consistent with ideas surrounding automation and technology adoption. Second, it challenges notions about manufacturing being a major job engine. If productivity keeps rising while the share of manufacturing employment falls, employment gains in the economy will need to come from other sectors.

How this graph was created: Search FRED for “All Employees, Manufacturing.” Above the graph on the right, click on “Edit Graph,” add a series by searching for “All Employees, Total Nonfarm,” and apply formula a/b. Open the “Add Line” tab and search for and select “Manufacturing Sector: Labor Productivity (Output per Hour) for All Workers.” Open the “Format” tab and place the legend on the right for the second line. Start the graph on 1987-01-01.

Suggested by Alexander Bick and Kevin Bloodworth II.