Salary & Compensation Data Across America (2026)

Salary differences between cities are shaped by four fundamental forces: cost of living adjustments (employers in expensive metros must pay more to attract talent, though purchasing power often lags behind), local labor demand (tech hubs pay software developers more because demand outstrips supply), industry concentration (cities with major hospital systems or universities create competitive hiring markets for nurses and teachers), and remote work dynamics (geographic arbitrage has compressed but not eliminated pay gaps since 2020).

Raw salary numbers tell only part of the story. A software developer earning $180,000 in San Francisco may have less disposable income than one earning $120,000 in Austin after accounting for housing, taxes, and daily expenses. Our city-level data helps you evaluate compensation in context — comparing not just what you'd earn, but what that salary actually buys in each market. This is especially critical for professionals considering relocation or negotiating remote work arrangements.

Data Sources: Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS), American Community Survey (ACS) income data, and Glassdoor/Indeed salary aggregates for validation.

Methodology: Base salary figures use BLS OEWS metropolitan area estimates, supplemented with cost-of-living adjustments for cities within the same MSA. Ranges represent 25th to 75th percentile annual compensation for each occupation.

Limitations: Salary data reflects base compensation and may not include bonuses, stock options, overtime, or benefits packages. Experience level, employer size, and specialization within occupations significantly affect individual compensation.

Last Updated: March 2026 · Confidence: High — salary data is derived primarily from BLS OEWS surveys with large sample sizes and annual updates.