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The Economic Divide Among America's Veteran Counties

Written by Adelle Wood | May 5, 2026 5:34:22 PM

In Cumberland County, Kentucky, 6.1% of residents are veterans and 33.9% live in poverty. Less than 200 miles away in concept but worlds apart economically, counties like Fairfax County, Virginia pair a similarly high veteran share with a median household income of $150,113. Service itself does not determine economic outcomes. Where veterans land after service does.

Two Very Different Veteran Communities

Nationally, 5.7% of county residents are veterans. But among the 725 counties where veteran share runs above that median, economic conditions split sharply. Roughly half of those counties also sit above the national median poverty rate of 13.4%. The other half report household incomes well above the national median of $63,162. The difference comes down to base proximity, local industry, housing costs, and the depth of VA and community support infrastructure available to veterans after they separate.

Counties Where High Veteran Share Meets High Poverty

These counties all have above-average veteran populations and poverty rates that exceed the national median. Many are rural, far from major VA facilities, and anchored to industries with limited upward mobility.

  1. Cumberland County, Kentucky: 6.1% veterans, 33.9% poverty rate
  2. Calhoun County, West Virginia: 8.2% veterans, 33.4% poverty rate
  3. Buffalo County, South Dakota: 7.3% veterans, 32.5% poverty rate
  4. Socorro County, New Mexico: 6.8% veterans, 29.0% poverty rate
  5. Kleberg County, Texas: 7.2% veterans, 28.8% poverty rate
  6. Nevada County, Arkansas: 7.3% veterans, 28.5% poverty rate
  7. Menifee County, Kentucky: 6.6% veterans, 28.2% poverty rate
  8. Stewart County, Georgia: 7.5% veterans, 27.8% poverty rate
  9. Lanier County, Georgia: 9.3% veterans, 27.7% poverty rate
  10. Cibola County, New Mexico: 6.3% veterans, 27.6% poverty rate

Counties Where Veterans and Prosperity Align

At the other end, these counties combine strong veteran representation with high household incomes. Most cluster near large active-duty installations, technology corridors, or high-cost metros where veteran hiring pipelines and GI Bill education benefits translate into above-average wages.

  1. Fairfax County, Virginia: 5.9% veterans, $150,113 median household income
  2. Douglas County, Colorado: 5.8% veterans, $145,737 median household income
  3. Los Alamos County, New Mexico: 6.0% veterans, $143,188 median household income
  4. Stafford County, Virginia: 12.5% veterans, $133,792 median household income
  5. Fairfax city, Virginia: 5.7% veterans, $132,774 median household income
  6. Calvert County, Maryland: 8.3% veterans, $132,059 median household income
  7. Fauquier County, Virginia: 7.7% veterans, $129,495 median household income
  8. Elbert County, Colorado: 8.5% veterans, $129,477 median household income
  9. Prince William County, Virginia: 8.5% veterans, $128,873 median household income
  10. Poquoson city, Virginia: 12.0% veterans, $120,919 median household income

What Separates the Two Groups

The gap between the highest-income veteran-dense county and the lowest-income veteran-dense county in this analysis exceeds $98,348 in median household income. Disability rates, access to broadband, and distance to the nearest VA medical center all correlate with where counties fall on this spectrum. Counties near large bases tend to benefit from federal contracting, defense employment, and a steady influx of younger, skilled veterans. Isolated rural counties often see aging veteran populations, higher disability rates, and fewer job options within commuting distance.

The Policy Implication

Mapping veteran share alone does not reveal economic need. Layering poverty rates and income data on top of veteran concentration reveals which communities are most underserved relative to their veteran population. Counties like Cumberland County, Kentucky represent places where targeted support, expanded telehealth VA access, and workforce transition programs could have an outsized effect. The data makes the geography of need visible.

Data source: U.S. Census Bureau, American Community Survey (ACS) 5-Year Estimates