When hiring nationally, some occupations have predictable wages regardless of location. Others vary dramatically by state. This tool measures wage volatility—how much wages differ across states—to help you understand which roles have stable costs and which require careful geographic planning.
Key Takeaways
- Low volatility = predictable costs. Some occupations pay similarly across all states, simplifying national hiring budgets.
- High volatility = location matters. Other occupations vary 50%+ between highest and lowest states—location choice dramatically affects costs.
- Coefficient of Variation (CV) quantifies volatility. CV below 10% is low volatility; above 15% is high.
- Use for multi-state planning. Know which roles need location-specific budgets vs. national standard offers.
- Volatility affects hiring strategy. High-volatility roles offer geographic arbitrage opportunities; low-volatility roles don’t.
Key Takeaways
- Low-volatility occupations (<10% CV) have similar wages nationwide
- High-volatility occupations (>15% CV) vary dramatically by location
- Geographic arbitrage works better for high-volatility roles
- Use volatility data to decide when location-specific pay bands matter
- Stable roles simplify budgeting; volatile roles require more planning
Table of Contents
Wage Volatility Index by Location
Measure how much wages vary across states for each occupation. High variation indicates volatile labor costs when hiring nationally; low variation means more predictable costs.
Wage Distribution by State
Full Volatility Analysis
| Rank | Occupation | Min Wage | Max Wage | Spread ($) | CV (%) | Volatility |
|---|
Methodology: Wage volatility is measured using the Coefficient of Variation (CV) - standard deviation divided by mean, expressed as a percentage. Higher CV indicates greater wage variation across states. Low volatility (<10%) suggests predictable costs; high volatility (>15%) indicates significant geographic wage differences. Data from BLS OEWS.
Overview
Not all labor costs are equally predictable. Understanding wage volatility helps you:
- Budget more accurately — Know when national averages apply vs. when location-specific figures matter
- Optimize hiring locations — High-volatility roles offer more savings from geographic strategy
- Set pay bands — Some roles need national consistency; others benefit from regional adjustments
- Plan expansions — Understand how labor costs will change as you enter new markets
This tool calculates the Coefficient of Variation (CV) for each occupation—a statistical measure of how spread out wages are across states.
Interpreting volatility results
Coefficient of Variation (CV)
CV is calculated as: Standard Deviation ÷ Mean × 100%
| CV Range | Volatility Level | What It Means |
|---|---|---|
| < 10% | Low | Wages are similar nationwide |
| 10-15% | Moderate | Some geographic variation |
| > 15% | High | Large differences by state |
Examples from the data
Low volatility occupations tend to have:
- Standardized skill requirements
- National labor markets
- Less geographic concentration
High volatility occupations often have:
- Industry concentration in specific regions
- Cost-of-living sensitivity
- Local market dynamics
Strategic uses for volatility data
For national hiring strategy
Low-volatility roles: Use national pay bands. A single compensation structure works because wages don’t vary much.
High-volatility roles: Use location-adjusted pay bands. Consider where you hire carefully—same role, same quality, dramatically different cost.
For cost optimization
High-volatility roles offer the most savings from geographic arbitrage:
- If a role has 20% CV and $150k average, the spread might be $120k-$180k
- Hiring in lower-cost states saves $30-60k per employee per year
- For a 20-person team, that’s $600k-$1.2M annual difference
Low-volatility roles don’t offer this—the savings from location optimization are minimal.
For remote work policy
High-volatility roles: Location-based pay makes economic sense. Remote workers in low-cost areas get lower pay; high-cost area workers get premiums.
Low-volatility roles: National pay may make more sense since geographic differences are small anyway.
For expansion planning
When opening offices in new states:
- High-volatility roles: Research local wages carefully—they may differ significantly from headquarters
- Low-volatility roles: National figures are reasonable planning estimates
Methodology
Data source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics (OEWS)
Volatility measure: Coefficient of Variation (CV) = Standard Deviation ÷ Mean × 100%
Spread calculation: Maximum state wage minus minimum state wage
Classifications:
- Low volatility: CV < 10%
- Moderate volatility: CV 10-15%
- High volatility: CV > 15%
Limitations:
- Measures geographic variation, not time-based volatility
- State averages may mask within-state metro variations
- Does not account for cost-of-living differences
- Limited to occupations tracked in OEWS
For time-based volatility: Use BLS Employment Cost Index for historical wage changes over time.
FAQs
What is the Wage Volatility Index?
It measures how much wages vary across states for each occupation using the Coefficient of Variation (CV).
Low CV means wages are similar nationwide; high CV means they vary dramatically by location.
Learn More...
The tool calculates the statistical spread of wages across all 50 states plus DC for each occupation.
This helps identify which roles have predictable labor costs nationally and which require careful geographic planning.
What is Coefficient of Variation (CV)?
CV is standard deviation divided by mean, expressed as a percentage. It measures relative variability.
Higher CV means more variation; lower CV means more consistency.
Learn More...
CV below 10% is considered low volatility—wages are fairly consistent across states.
CV between 10-15% is moderate—some geographic variation worth considering.
CV above 15% is high volatility—significant wage differences by location.
Why do some occupations have high wage volatility?
Industry concentration, cost-of-living sensitivity, and local market dynamics create geographic wage differences.
Tech roles in Silicon Valley pay more than the same roles in rural areas.
Learn More...
Occupations concentrated in high-cost metros (software developers in SF, financial managers in NYC) show high volatility.
Roles tied to local industries (oil & gas in Texas, entertainment in California) also vary by location.
Commoditized roles with national labor markets tend to have lower volatility.
How should I use this for compensation planning?
Use national pay bands for low-volatility roles; use location-adjusted bands for high-volatility roles.
High-volatility roles justify geographic pay differentials; low-volatility roles may not need them.
Learn More...
For roles with CV below 10%, a single national compensation structure is reasonable.
For roles with CV above 15%, consider metro-based or region-based pay bands.
This data can justify location-based pay policies to employees who question geographic differentials.
Can I save money by hiring in low-cost states?
For high-volatility occupations, yes—the savings can be substantial. For low-volatility occupations, the difference is minimal.
Check the spread between highest and lowest states to see potential savings.
Learn More...
A high-volatility role with $60k spread between states offers real arbitrage opportunity.
A low-volatility role with $10k spread doesn't justify the complexity of location-specific strategies.
Factor in talent availability, not just cost—some low-cost states have thin labor pools.
Does this measure wage changes over time?
No—this measures geographic variation at a point in time, not temporal volatility.
For wage changes over time, see the Wage Inflation Estimator or BLS Employment Cost Index.
Learn More...
Geographic volatility (this tool) tells you how wages vary by location.
Temporal volatility (not measured here) would tell you how wages change year over year.
Both types of volatility matter for planning but measure different things.
How often is the data updated?
The tool uses BLS OEWS data, released annually with a May reference period.
Geographic wage patterns tend to be stable, so annual data remains useful.
Learn More...
OEWS provides comprehensive state-by-state wage data for detailed volatility analysis.
Check the displayed survey year for the current data vintage.
Volatility patterns (which occupations are volatile vs. stable) change slowly over time.
In summary
Wage volatility varies dramatically by occupation. Some roles pay similarly regardless of location; others swing 50%+ between highest and lowest states. Understanding which category your key roles fall into helps you budget more accurately and make smarter hiring location decisions.
Use low-volatility data to simplify national compensation planning. Use high-volatility data to identify geographic arbitrage opportunities and justify location-based pay adjustments.
Ready to optimize your labor cost strategy?
- Labor Cost Tracker — Calculate team costs by location
- Wage Benchmarking Tool — Compare specific occupation wages
- Schedule a consultation — Get help with compensation strategy
