LOCAL ECONOMIES & UNDERWRITING · SEPTEMBER 22, 2026
County Wage Growth Outpaces Employment Growth in the Latest QCEW
BLS's latest county report showed national employment up 0.1% over the year to March while average weekly wages rose 3.9% to $1,654 in the first quarter, with wide differences among large counties.
What the latest county report shows
Source publication date: August 28, 2026. In its latest County Employment and Wages release, BLS reported that national employment rose 0.1% over the year to 154.8 million in March 2026. Employment increased in 151 of the 376 largest counties. National average weekly wages rose 3.9% over the year to $1,654 in the first quarter, and 358 of the largest counties recorded wage increases.
- 01Employment: +0.1%
- 02Wages: +3.9%
- 03151 large counties added jobs
Local outcomes varied materially
Licking County, Ohio, had the largest reported employment gain among the largest counties at 3.6%, while Washington, D.C., and Arlington County, Virginia, each declined 4.5%. BLS reported the largest weekly-wage gain in St. Tammany Parish, Louisiana, and the largest decline in San Francisco County, California. Individual county changes can be influenced by industry mix and unusually large compensation events, so headline rankings require local and sector context.
Why county-level detail can improve underwriting
Local employment and pay can affect customer demand, apartment and commercial occupancy, tenant sales, labor availability, wage budgets, capex plans, and property values. Yet quarterly county data arrive with a lag and do not replace current rent rolls, payroll, bookings, deposits, customer pipelines, leasing activity, or market studies. A national wage gain does not prove that a specific business can raise prices or that a property's tenants can absorb higher rents.
Practical borrower and investor takeaway
Identify the counties and industries that actually drive the business or property, then compare BLS context with recent company and submarket evidence. Build payroll by position, reconcile wage assumptions to current compensation, and model slower hiring or higher labor cost. For real estate, connect local employment and wages to tenant exposure, collections, rollover, concessions, new supply, and achievable rents. Document the gap between lagged public data and the transaction's current facts.
Borrowers and property investors should use county and industry evidence to support payroll, rent, demand, and exit assumptions, then reconcile the national backdrop to their own operating data.
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