This summary examines what would happen to local unemployment rates throughout the US if the US Department of Government Efficiency (DOGE) were to cut 75 percent of the federal workforce. The analysis uses geographic-specific counts of federal civilian employees from the US Office of Personnel Management and Bureau of Labor Statistics to simulate a 75 percent reduction in the federal workforce.

Why This Matters

The federal civilian workforce is spread across the country. While the Washington, DC, metropolitan area has the largest number of federal workers—nearly 315,000 people, who constitute about 9 percent of the local area workforce—DC-area federal workers make up only about 15 percent of the total federal civilian workforce. In other areas around the country, federal workers make up higher proportions of local labor markets, particularly in areas with military bases or federal correctional facilities. In those areas, cutting 75 percent of the federal workforce could have large impacts on local unemployment rates.

What We Found

• With a focus on federal civilian employment (i.e., not including uniformed military personnel), it would be impossible for DOGE to achieve their goal of cutting 75 percent of the federal workforce without cuts to national and homeland security.
• In areas with small labor forces, such workforce cuts would likely affect local unemployment rates. In the 10 areas in the country with the smallest labor forces, adjusted unemployment rates would rise by upwards of 0.6 percentage points. In Zapata, TX, for example, located on the Texas–Mexico border and home to the US Customs and Border Protection Zapata Station, the estimated unemployment rate would increase from 6.9 percent to 9.4 percent.
• Among the 10 metropolitan areas with the largest labor forces in the country, simulated unemployment rates would rise by about a percentage point for these 10 areas as a whole. The Atlanta metropolitan area would see an increase of about 1 percentage point and the Philadelphia metropolitan area would see an increase of about 0.9 percentage points.

How We Did It

The analysis draws on March 2024 data from the US Office of Personnel Management at the Core Based Statistical Area level, which are matched to March 2024 county-level Local Area Unemployment Statistics program data from the US Bureau of Labor Statistics. The final dataset and underlying code to merge the various files together is available on the Urban Institute Github repository.