Federal Reserve Economic Data

The FRED® Blog

State and metro employment: First quarter 2025

On April 18, 2025, the Bureau of Labor Statistics released the first quarter data for total nonfarm employees at the state and metro levels. At the state level, Texas led all states, adding 74,100 jobs in the first quarter. California had the largest decline, losing 54,800 jobs.

The FRED map above shows the change in employment in each state during the first quarter. If you sum up the individual states, you’ll see a net gain of 301,600 jobs. This is different from the reported number for the nation, which was 456,000 as of April 29. This difference is because the state level has different sampling and tends to have a larger margin of error than the national number.

At the metro level, the Philadelphia-Camden-Wilmington MSA led the nation with 18,700 jobs added in the first quarter. The Los Angeles-Long Beach-Anaheim MSA had the largest decline, losing 25,200 jobs in the first quarter. These numbers tend to vary greatly from quarter to quarter, with even greater sampling errors than the errors at the state and national levels. So, take these numbers with a grain of salt.

How these maps were created: Search FRED for “total nonfarm employees in Missouri” (or any other state). Click “View Map” and then “Edit Map.” Change the units to “Change, Thousands of Persons” and the frequency to quarterly with aggregation method “End of Period.” Under “Format,” select “User Defined Method” for how to group the data: Switch the number of color groups to 3 and change the colors to red for states that shed jobs (or a value less than or equal to 0), light green for states with modest job growth (or less than 10), and dark green for states with strong growth (or a value large enough to incorporate the rest of the states). For the second map, repeat the process with an MSA—St. Louis, for example.

Suggested by Jack Fuller and Charles Gascon.

Unemployment rates by nativity and timing of immigration

Recent insights from the Research Division

FRED has data for various segments of the US labor force, including employment of native-born and foreign-born workers. Today’s post taps into unemployment data for these groups.

The FRED graph above shows US Bureau of Labor Statistics data on the fraction of the native-born labor force (solid blue line) and foreign-born labor force (dashed green line) who are out of a job and actively seeking one.

These data don’t show major differences between the groups, but recent research from Alexander Bick at the St. Louis Fed uncovered nuances in the data. He used the BLS survey that collects household labor market information to examine unemployment rates of immigrants according to how long they had resided in the US.

Between 2014 and 2024, immigrants in the US for more than 3 years often had slightly lower unemployment than native-born workers. More-recent immigrants often had higher unemployment than both those groups.

Average unemployment rates since 2022

  • Non-recent immigrants 3.3%
  • U.S. natives 3.8%
  • Recent immigrants 7.6%

Bick’s analysis also considers the potential effects of undercounting immigrants. If unemployed immigrants are undercounted to a large-enough degree, actual demand for labor may be weaker than what official data show. But he finds the impact to be small: In October 2024, an estimate of unreported recent immigrants would have increased the overall unemployment rate by 0.1 percentage points.

For more about this and other research, visit the publications page of the St. Louis Fed’s website, which offers an array of economic analysis and expertise provided by our staff.

How this graph was created: Search FRED for and select “Unemployment Rate – Native Born.” Click on the “Edit Graph” button, select the “Add Line” tab, and search for “Unemployment Rate – Foreign Born.” Don’t forget to click “Add data series.”

Suggested by Diego Mendez-Carbajo.

Sizing up US manufacturing

Manufacturing is the creation or production of goods with the help of equipment, labor, and chemical or biological processing or formulation. It’s different from mining and construction.

Our first FRED graph, above, tracks the number of employees in these three industries since 1939. After a strong buildup during WWII, manufacturing employment has stayed within a band of 11 to 20 million, with about 13 million currently. There are obvious cyclical fluctuations, but no longer-term trends after its big decline in the first decade of the 21st century. Employment has steadily increased for construction and decreased for mining.

Our second graph divides the same data by the total number of US employees. When we look at each industry’s share of employment in the economy, we get a different perspective: Manufacturing has  steadily declined, construction is stable, and mining has become very small.

Now let’s look at the output of the manufacturing sector. These data don’t go far back, but we can see a marked rise from 1987 to about 2000 and then a flat trend with some cyclical fluctuations. This graph uses an index, which doesn’t say anything about the share of manufacturing output in the economy.

Our last graph tracks the share of manufacturing output in the economy: The data start in 2005 and show the tail end of the decline in the 2000s before it flattens out. Clearly, manufacturing output has done better than manufacturing employment due to an increase in productivity, in part thanks to a move to higher value manufacturing. There may also be very different evolutions for subsectors within the manufacturing industry, as well as long-run trends that any modern economy might experience.

How these graphs were created: Search FRED for the Current Employment Statistics release table and choose Table B-1 (seasonally adjusted); select the series you want and click “Add to Graph.” This the first graph. From the “Edit Graph” panel, for each line add series “All employees, non-farm” and apply formula a/b*100. You have the second graph. For the last two, simply search FRED for “manufacturing output” and “manufacturing value added.”

Suggested by Christian Zimmermann.



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