WageDex guide
Understanding BLS Wage Data
What the numbers mean, how they are collected, and why employer-reported data beats self-reported surveys.
The short answer
BLS wage data comes from mandatory employer surveys covering 1.1 million businesses, not self-reported estimates, which makes it the most reliable occupation-level wage source in the US. Across the 825 occupations with a published national median (of 830+ occupations tracked), half pay under $61,390 a year.
- 1.1M+
- Establishments surveyed
- 825
- Occupations with published wages
- $61,390
- Median occupation wage
WageDex shows the full 10th-to-90th percentile distribution on every page, not just the median, so you can see what top and bottom earners make.
How BLS Collects Wage Data
The Bureau of Labor Statistics doesn't ask workers what they earn. Instead, it surveys employers directly through the OEWS program. Every six months, a sample of roughly 200,000 businesses receives a mandatory survey asking for employment counts and wage ranges by occupation. Over a three-year cycle, this covers approximately 1.1 million establishments.
This employer-based approach eliminates the self-selection and recall bias that plague salary websites. When Glassdoor shows a salary for "Software Developer," it's based on whoever voluntarily submitted their pay, which skews toward people who feel strongly about their compensation. When BLS reports the same occupation, it's based on a statistically designed sample of all employers who hire software developers.
Understanding Wage Percentiles
WageDex shows the full wage distribution for every occupation, not just a single number. The percentiles tell you:
- 10th percentile: Entry-level or lowest-paid workers. 90% of workers in this occupation earn more than this amount.
- 25th percentile: Below-average wages. Typical for early-career workers or lower-paying employers.
- Median (50th): The midpoint. Half earn more, half earn less. The most useful single number for "what does this job pay?"
- 75th percentile: Above-average wages. Typical for experienced workers or high-paying employers.
- 90th percentile: Top earners. Only 10% make more. Represents senior roles, high-cost-of-living areas, or premium employers.
The spread between the 10th and 90th percentile tells you how much wages vary within an occupation. A narrow spread (like bus drivers) means pay is relatively uniform. A wide spread (like software developers) means experience, location, and employer matter enormously.
Browse any occupation on WageDex to see the full percentile breakdown. Start with the careers directory.
US occupational wage distribution
Median annual wage across 825 detailed BLS occupations with a published median
$61,390 Top 50% higher than 50% of 825 US occupations
Each bar is a $20K-wide band; taller bars hold more US occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count, share, and where it sits relative to this entry.
Source U.S. Bureau of Labor Statistics, OEWS · May 2025
Geographic Wage Variation
The same occupation can pay very differently across locations. A registered nurse in San Francisco earns roughly 50% more than one in rural Alabama, but after adjusting for cost of living, the Alabama nurse may have more purchasing power. WageDex shows wages for every occupation across all 50 states and metro areas.
Location-based wage differences reflect several factors: local cost of living, supply and demand for workers, industry concentration (tech hubs pay more for engineers), state minimum wage laws, and unionization rates. Always compare wages within the same geographic area when evaluating offers.
What BLS Data Doesn't Cover
BLS wage data is powerful but has limitations:
- No benefits data: Health insurance, 401(k) matching, stock options, and bonuses are not included. Total compensation can be 30-40% higher than wages alone.
- No experience level: BLS doesn't break wages down by years of experience. The percentile distribution serves as a proxy, lower percentiles roughly correspond to less experience.
- No company-specific data: You can't look up what Google pays software engineers vs. what Oracle pays. BLS data is aggregated by occupation and geography.
- Annual lag: Data reflects conditions from the reference period (May 2025 for the current release), not today's market.
Frequently Asked Questions
What is the OEWS survey?
The Occupational Employment and Wage Statistics (OEWS) survey is the BLS's primary source for occupation-level wage data. It surveys approximately 1.1 million business establishments over a three-year cycle, collecting data on employment counts and wage percentiles for over 800 detailed occupations. The survey is based on what employers actually pay, not what workers self-report.
What is the difference between median and mean salary?
Median salary is the midpoint, half of workers earn more, half earn less. Mean (average) salary is the total wages divided by total workers. For most occupations, the mean is higher than the median because high earners pull the average up. The median is generally more useful for understanding what a "typical" worker earns.
Why does BLS data differ from Glassdoor or Salary.com?
BLS data comes from mandatory employer surveys, companies report what they actually pay. Sites like Glassdoor rely on voluntary self-reporting by workers, which introduces selection bias (people with strong opinions about pay are more likely to report). Self-reported data also tends to include bonuses and stock compensation inconsistently. BLS data is statistically sound but may not reflect total compensation.
How often is BLS wage data updated?
The BLS publishes new OEWS estimates annually, typically in the spring. The data reflects the previous May reference period. WageDex updates when new estimates are released. Current data on WageDex is from the May 2025 OEWS release.
What does "wages not available" mean?
Some occupations show suppressed wage data (N/A) where BLS disclosure standards are not met. This typically happens when an occupation has too few workers in a given area to ensure confidentiality, or when the data doesn't meet quality standards. It is more common at the state and metro level than nationally.
Does BLS wage data include benefits?
No. OEWS data covers wages and salaries only. It does not include employer-paid benefits like health insurance, retirement contributions, stock options, or bonuses. Total compensation is typically 30-40% higher than wages alone. The BLS publishes separate data on employer costs for benefits through the Employer Costs for Employee Compensation (ECEC) survey.
Sources
- U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics (OEWS), May 2025
- BLS Handbook of Methods, Chapter 3: OEWS Survey
This content is for informational purposes only and does not constitute financial advice. Salary data should be one factor among many in career and compensation decisions.
Understanding the Data
The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.
It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.
For readers who want to conduct their own research, we recommend going directly to the source whenever possible. the U.S. Bureau of Labor Statistics provides detailed documentation on the OEWS survey's collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.
How We Analyze Data Records
Our pipeline pulls the raw OEWS release, standardizes occupation and area names against a fixed taxonomy so the same job title matches across editions, and computes derived figures (percentile bands, metro-vs-national ratios, year-over-year change) that BLS publishes as separate files but most readers want to see side by side.
The metrics we track for every occupation include median and mean annual wage, employment counts, and percentile wage bands (10th through 90th percentile). These figures let you see not just what an occupation pays nationally, but how that compares across metro areas, states, and neighboring occupations, since a single national average can hide wide regional and role-level variation.