Useful Stats: Where is US manufacturing? A county-level look at subsector-specific data

Despite a decades-long decline in its share of American jobs, manufacturing remains a foundational part of the U.S. economy as the third largest contributor to its gross domestic product (GDP). Despite the sector’s share of overall U.S. employment declining over time, manufacturing continues to anchor many local economies. In this edition of Useful Stats, SSTI unveils trends shaping the manufacturing landscape, from areas of sustained growth to places undergoing structural change, by examining employment and establishment data from the U.S. Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW) at the county level. 

Data at the two- and three-digit North American Industry Classification System (NAICS) level are used in this article. The two-digit level is more commonly referred to as the sector level, while the three-digit provides more nuance by describing subsectors. NAICS classifications can be as specific as the six-digit level, but privacy issues arise when trying to look at county-level data, perhaps making the three-digit level the most detailed available for national county-by-county examination. The manufacturing sector (NAICS 31-33) “comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products,” according to NAICS. These jobs tend to be innovative and encompass a key facet of the U.S.’ economy.  

The bulk of data used in this article comes from the QCEW, which has several limitations and should be interpreted with caution. Refer to the data limitations section at the end of this article for more detail. 

Manufacturing employment over time 

The manufacturing sector makes up around 12% of the nation's gross domestic product (GDP) each year, yet sector employment  is relatively stagnant,  decreasing manufacturing’s share of total U.S.  employment, as seen in Figure 1 (to view only manufacturing or only total nonfarm employment, click the “Enter series to show” box and select either “manufacturing” or “total nonfarm” to toggle the chart). In the early 1940s, manufacturing employment accounted for just under a third of the total nonfarm amount, peaking just short of 39% in late 1943 at the height of WWII, as per BLS data via The Federal Reserve Bank of St. Louis. Since then, manufacturing employment has dropped substantially as a share of total employment. Over the past decade, the rate has held consistently  around 8%, with a relatively slower downward trend compared to past decades. To view this trend, navigate to the second chart within Figure 1 via the arrows in its top right-hand side.   

Manufacturing employment peaked at approximately 19.5 million in the late 1970s. Employment ebbed and flowed through recessionary periods while trending down since its peak, before starting a slight upward trend following the 2008 Great Recession, albeit interrupted by the pandemic-induced recession in early 2020. Employment, however, quickly recovered from this abnormal recession, but remains comparable to many years in the early 1940s and levels seen during the mid-Great Recession and just prior to the pandemic.

Figure 1: U.S. manufacturing and total nonfarm employment 

A county-level look at the manufacturing sector      

County-level NAICS data reveal patterns, concentrations, and dependencies that broader state or national averages often miss, but regional innovation initiatives should try to incorporate in their strategies. The technological, workforce, and future industrial outlook will vary by subsector. Knowing about counties with a high concentration of a specific manufacturing subsector (explored more in the following section) or employment or establishments, within those subsectors with stronger-than-average anticipated growth trajectories can help target limited regional innovation tools more effectively.  Figure 2, below, maps the county-level annual average employment and establishment count for 2024, the most recent year of available data for the manufacturing sector (NAICS 31-33).

Figure 2: Private manufacturing sector (NAICS 31-33) employment and establishments, 2024 

Figure 2 highlights distinct geographic patterns, revealing a heavy concentration of private sector manufacturing employment in parts of Florida, Texas, and the Carolinas, as well as along the West Coast, Great Lakes, and New England Areas, among other regions. The rural counties along the Rocky Mountains tend to have much lower, if any, manufacturing employment, while some states, such as Nevada, New Mexico, and Utah, have distinct concentrations within a small number of counties. 

Los Angeles County in California topped the charts with over 300,000 private sector manufacturing employees in 2024. Harris County, Texas, home to Houston, and Cook County, Illinois, home to Chicago, are, respectively, the second and third largest counties by private manufacturing sector employment, with approximately 177,000 each. Employment in eight counties was in the six digits; in addition to the above, Orange County, California, Maricopa County, Arizona, Dallas County, Texas, and Santa Clara and San Diego Counties in California all had manufacturing sector employment above 100,000 in 2024. 

It is important to note that counties vary greatly in geographic size and number of cities and other subdivisions, making it important to consider adjacent counties when exploring the total employment of an area. 

The distribution of establishments (accessible via the toggle beneath Figure 2’s title) paints a slightly different picture, with more geographic concentration. This difference suggests that many counties host manufacturing operations, yet the spread of employment can vary dramatically. 

Many of the same counties, such as Los Angeles, California, and Cook, Illinois, are home to the largest number of establishments.  

A single year of data, while important, lacks the context of change; by comparing 2015 and 2024, a more comprehensive picture of the changes across employment and establishments within the manufacturing sector is revealed. 

Figure 3, below, shows the 10-year percentage change in private manufacturing jobs, with gains shaded in blue and declines in red. Note that to provide a clearer, less skewed view of the data, SSTI has limited the color scale to 200% growth despite some counties surpassing the threshold. Hovering over or clicking on any county will show its value.

Figure 3: 10-year percentage change in private manufacturing sector (NAICS 31-33) employment and establishments, 2015-2024 

While many counties experienced moderate shifts, some saw rapid expansion. In counties with lower initial values, this is often the result of new facility openings, production line additions, increased output in existing plants, or other reasons that may have substantially less impact on counties with well-established manufacturing operations. Others recorded sharp contractions, which may be due to automation or new technology removing the need for certain jobs, relocation of operations, or broader shifts in industry demand.     

For example, employment in Refugio County, Texas, increased by over 1,100% from 2015 to 2024, but experienced a more modest increase of 34 (employment increased from three in 2015 to 37 in 2024). On the other hand, Orange County, California, dropped approximately three-quarters of a percentage point, resulting in an employment loss of 1,175. Refer to Figure 3 for more details and trends. 

Breaking the data down: three-digit NAICS subsectors by county 

Sector-level data provides a broad view of manufacturing as a whole; subsector-level data at the three-digit NAICS level offers a more detailed understanding of the sector’s composition. Different manufacturing industries can follow very different growth patterns, respond to distinct market forces, and cluster in specific geographic areas. Analyzing at the subsector level helps identify which types of manufacturing are driving employment or establishment growth or decline. Figure 4 displays the 2024 annual average employment and establishment count by subsector for all counties for which data is available, with a dropdown menu beneath the title to toggle the subsector displayed. 

Note that at the three-digit NAICS level, there is a significant amount of missing data, as indicated by a grey checkerboard pattern within affected counties, relative to the higher-level maps. This missing data may be due to a variety of factors, such as data withheld by the QCEW to protect anonymity, or data not existing or otherwise not available. Data should be interpreted with caution.

Figure 4: Private manufacturing employment and establishments by three-digit NAICS subsector, 2024 

As previously mentioned, comparing multiple years provides important context regarding how these figures have changed over time. Figure 5, which comprises two maps, includes the ten-year percentage change from 2015 to 2024 for each private manufacturing subsector’s employment and establishments.     

The arrows in the top right corner of Figure 5 can be used to toggle between data on employment and establishments for all included three-digit NAICS level private manufacturing industries.

Figure 5: 10-year percentage change in private manufacturing employment and establishments by three-digit NAICS subsector, 2015-2024 

Data limitations     

Note that the QCEW employment data used are calculated as the annual average of the number of covered workers who either worked during or received pay for the pay period including the 12th day of the month. Some employment exclusions apply, such as proprietors and unpaid family members; refer to the QCEW overview for more detail. 

In addition to counties or county equivalents, the QCEW data set includes “Unknown or Undefined” geographies as catchalls for each state. These often account for sizable counts of employment and establishments, and may cause certain counties to be underrepresented in the dataset. 

Note that due to the small geographic scale of the data used, some data are excluded from the QCEW dataset to protect the confidentiality of firms. The impact of these exclusions is difficult to estimate, and likely impact many of the multi-year comparisons within this article. Data for many counties or county equivalents are also likely underrepresented due to these necessary exclusions. Impacted data are marked with a disclosure code in the data set. SSTI encourages those interested to refer to the data notes in the source for details on counties that may be affected.  

SSTI has included in this articles’ visuals counties with at least one establishment, but no employment but excluded counties with zero establishments and zero employees. 

This page was prepared by SSTI using Federal funds under award ED22HDQ3070129 from the Economic Development Administration, U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the views of the Economic Development Administration or the U.S. Department of Commerce.