Use this page to benchmark mean annual wages from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS). Compare wages for all 50 states + DC, see which states pay the most for your occupation, and use the data to inform hiring, relocation, and compensation decisions.
Key Takeaways
- Location changes labor cost. The same role can pay 15–30%+ more in top states than the national mean (e.g., software developers in California vs. the U.S. average).
- Benchmark before you hire or relocate. A 10-person team at $150k mean vs. $120k is roughly $300k/year in payroll difference before benefits.
- Use mean wages for budgeting; use percentiles for offers. OEWS publishes means and percentiles; this tool focuses on mean annual wage for clear state comparisons.
- Pair wages with cost of living. High nominal pay does not always mean higher purchasing power.
- Data updates annually when BLS releases new OEWS survey results.
Key Takeaways
- Compare BLS mean annual wages by occupation across all 50 states + DC
- See national benchmark, top state, and full state ranking instantly
- Plan hiring, relocation, and compensation with real OEWS figures
- Understand limits: means, not total comp; annual survey snapshot
- Get help with multi-state entity setup and compliance from Business Initiative
Table of Contents
Interactive Wage Benchmarking Tool
Select an occupation to compare latest BLS OEWS mean annual wages across all 50 states + DC. See national benchmarks, the highest-paying state, and full state rankings with employment context.
Top 5 states by mean annual wage
| Rank | State | Mean annual wage | vs. national | Employment |
|---|
All states comparison
| Rank | State | Mean annual wage | vs. national | Employment |
|---|
Overview
Compensation is one of the largest controllable costs for growing businesses. Whether you are opening a second location, building a remote team with state-specific pay bands, or negotiating offers, you need a credible external benchmark—not guesswork.
This page combines:
- An interactive benchmark (above) powered by official BLS OEWS data for all 50 states + DC.
- Interpretation of what wage spreads mean for payroll, recruiting, and location strategy.
- Methodology and limitations so you can cite the numbers with confidence.
The tool currently includes eight high-demand occupations: all occupations, software developers, registered nurses, general and operations managers, accountants, management analysts, marketing managers, and financial managers.
State-by-state comparisons
Why state rankings differ by occupation
National “top paying state” lists are misleading if you only look at all occupations combined. High-cost states rank high on average because they mix expensive metros and high-paying industries—but your occupation may peak elsewhere.
Use the tool to see your occupation’s full state ranking and employment counts. The all-states table lets you sort by wage, employment, or premium vs. national.
Payroll illustration (software developers)
Suppose you staff 10 software developers at the national mean (~$148k) vs. the California mean (~$172k):
- National payroll (salaries only): ~$1.48M/year
- California-mean payroll: ~$1.72M/year
- Difference: ~$240k/year before benefits, taxes, or equity
If you instead hire in a lower-cost state, the same team could be ~$1.2–1.3M—materially below California. These are planning figures, not offer sheets.
Employment context matters
A state can show high wages but modest employment in your occupation (thin labor market), or large employment with moderate wages (deep market). The benchmark table includes OEWS employment so you can balance pay vs. talent pool size.
Key insights
Location arbitrage is real—but not free. Lower mean wages in some states can reflect labor supply, industry mix, or cost of living—not “cheaper talent” in every sense. Budget for recruiting time, remote pay equity policies, and registration/compliance if you hire across borders.
Top states cluster by sector. Tech wages peak on the West Coast and in the Northeast; health roles show different geographic peaks. Align geography with your industry’s labor market.
Means vs. offers. OEWS mean wages are pulled up by high earners. For entry-level hiring, also consult BLS percentiles (10th, 25th, 50th, 75th, 90th) on BLS OEWS tables.
Update cadence. OEWS is published annually with a May reference period. Check the survey year shown in the tool for the data vintage.
How to use this data (step by step)
Step 1 — Select your occupation in the tool and click Run benchmark. Start with the closest SOC title; use “All occupations” only for economy-wide context.
Step 2 — Note national mean and top state premium. If the premium is large (>15%), location is a strategic lever, not a rounding error.
Step 3 — Compare your target states. Use the full state table to filter and sort by state name, wage, or employment. Screenshot results for internal planning.
Step 4 — Adjust for cost of living and benefits. Use BEA regional price parities or local COL indexes for real purchasing power. Add 25–35%+ to salary for fully loaded employer cost.
Step 5 — Align offers to percentiles and role level. Use this page for market context; set offers using internal equity, experience, and BLS percentiles.
Step 6 — Operationalize. If you expand to a new state, plan for registration, withholding, and unemployment insurance—Business Initiative can help with entity structure and compliance.
Methodology and limitations
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics (OEWS).
Wage measure: Mean annual wage unless otherwise noted. Means are not median (“typical”) pay.
Geography: All 50 states + DC. Metro areas may differ sharply within a state (e.g., NYC vs. upstate New York).
What is included: Wages for employed workers in the occupation in that state.
What is not included: Signing bonuses, equity, benefits, self-employment income, or non-wage compensation.
Timeliness: OEWS is released annually with a May reference period. The survey year is displayed in the tool. For historical data or additional detail, visit BLS OEWS tables.
FAQs
What is the Wage Benchmarking Tool on this page?
It is an interactive calculator that compares BLS Occupational Employment and Wage Statistics (OEWS) mean annual wages by occupation across all 50 states + DC.
You select an occupation, run the benchmark, and see national averages, the top-paying state, and a full state ranking.
Learn More...
The tool is built for hiring managers, founders, and job seekers who need a quick, credible wage benchmark before setting offers or choosing a state for hiring.
All data comes directly from the Bureau of Labor Statistics OEWS survey, the federal government's standard source for occupational wages.
Which BLS data does the tool use?
Occupational Employment and Wage Statistics (OEWS), the official BLS survey for wages by occupation and location.
The primary wage measure shown is mean annual wage by state and nationally.
Learn More...
OEWS is the standard federal survey for occupational employment and wages across states and metros.
The tool displays the latest available survey year. For historical data or percentile wages (10th, 25th, 50th, etc.), visit BLS OEWS tables at bls.gov/oes.
How often is the data updated?
OEWS is released annually with a May reference period.
The tool is updated when new BLS survey data becomes available.
Learn More...
BLS typically publishes OEWS results in the spring following the May survey period.
Check the survey year displayed in the tool footnote for the data vintage.
Mean wage vs. median—which should I use for offers?
This tool shows mean annual wages, which are useful for budget modeling and state comparisons.
For typical or entry-level pay, also review OEWS median (50th percentile) and lower percentiles on BLS.gov.
Learn More...
Means are pulled upward by very high earners in an occupation; medians better represent a 'typical' worker.
Many employers set ranges using 25th–75th percentiles and adjust for experience, not the mean alone.
Does a high-paying state always mean higher hiring costs overall?
Not necessarily. Nominal wages are only one part of labor cost.
Cost of living, benefits, recruiting difficulty, and taxes also affect total cost and quality of hires.
Learn More...
A state with a higher mean wage may have better purchasing power after adjusting for regional price parities (see BEA RPP data).
Thin labor markets (low employment in your occupation) can increase time-to-fill and recruiting spend even if mean wages look attractive.
Can I use this for remote teams with employees in many states?
Yes, for market context—run the benchmark once per occupation and compare states where you hire.
You still need state-specific payroll compliance, withholding, and unemployment rules for each work location.
Learn More...
Remote pay policies often use a national band or geo-adjusted bands; this tool helps justify geographic differentials with external data.
Business Initiative can help with multi-state registration and employer compliance when you expand hiring.
What occupations are included in the tool?
The tool includes eight high-demand occupations: all occupations, software developers, registered nurses, general managers, accountants, management analysts, marketing managers, and financial managers.
Each occupation shows national and state-level mean wages plus employment counts.
Learn More...
These occupations were selected for broad business relevance across industries.
For other occupations, visit the BLS OEWS tables directly at bls.gov/oes for comprehensive data.
In summary
Benchmarking wages by state turns BLS OEWS data into a decision-ready view of where your occupation pays most, how far state means sit from the national average, and what that implies for payroll at your headcount.
Use the interactive tool for exploration, then validate critical hires with percentile data, local COL adjustments, and current-year OEWS releases.
Ready to act on a multi-state hiring or expansion plan?
- Explore state statistics
- State income power rankings (BEA)
- Schedule a consultation for entity setup, payroll, and compliance planning
