April 2010

Occupational Employment Statistics (OES) Highlights:
How Jobseekers and Employers Can Use Occupational Employment Statistics (OES) Data during Wage and Salary Discussions

(PDF version)

The economic downturn has many individuals reevaluating their career paths or struggling to find a market for their skills. As they explore career options, individuals may be wondering how their skills, experience, and education might translate into compensation. Employers even in turbulent economic times have an incentive to attract or retain quality workers by making sure the wages they offer are fair and competitive. A wide variety of literature is available on career exploration and the techniques that help in attaining employment, but prospective employees and employers both could benefit by having reliable information available on wages and wage distributions in the pay-setting process.

The average wage for a prospective occupation is useful starting information. It is important to note, however, that wage averages reflect the outcome of many factors, such as how an individual's experience compares with others in the occupation and how wages vary depending on the location and industry of the work. Information on average wages and wage distributions for occupations is available by industry and area on the OES Web site. Familiarity with the full distribution of wages for an occupation can provide a more complete perspective on wage expectations.

Average wages and wage distributions

A wage distribution, or wage range, can be useful in determining a base or target wage. Where an individual should expect to fall in a wage distribution is not always an easy judgment. Those who are just starting their careers may expect wages at the lower end of the distribution, near the 10th or 25th percentile, and those with more experience and education may expect wages near the 75th or 90th percentile. The wage distribution can also be used as an indicator of the variability in wages for an occupation and can be helpful in understanding potential wage growth as the worker gains more experience or education. Still, 10 percent of workers in the occupation earn more than the 90th percentile wage.

Percentile wages are helpful to know during wage negotiations because occupations with similar average wages may have different distributions. For example, film and video editors typically face highly variable wages, whereas signal and track switch repairers have a much flatter pay distribution, as shown by chart 1. Although these two occupations may have similar median wages, hourly earnings for workers at the lower and upper ends of the distribution are quite different. Average and percentile wage data are available for these and nearly 800 other occupations.

Occupations with similar medians, but differing wage variation

Click here to see these data in table format.


Many occupations can be found in a variety of different industries, or types of businesses. An employer's industry classification can have profound implications on pay. Some industries generally pay higher or lower wages for workers in the same occupations doing similar work. For example, accountants and auditors, who do similar work in a variety of industries, generally have higher average wages in accounting services firms and lower wages in clothing stores. However, as illustrated in chart 2, the spread of wages in clothing stores is relatively wide, compared with the wage distribution of other industries.

Distribution of wages for accountants and auditors in selected industries

Click here to see these data in table format.

The variability of wages by industry can depend on the occupation. As shown in chart 3, wages for accountants and auditors are expected to vary considerably across industries, whereas wages for customer service representatives are more consistent. This may be because the responsibilities of workers in an occupation vary by industry, or it simply may be because different industries have different pay practices.

Occupational wages in selected industries

Click here to see these data in table format.

It is also useful to know general pay practices in firms that are similar to the prospective employer. Industries with high profit margins are often able to provide higher wages and still remain competitive, whereas others find it necessary to keep wages low in order to remain competitive and charge lower prices. Nonprofit firms may pay lower wages for most occupations, but pay above average wages for the very lowest paid occupations1. Similarly, industries with higher levels of unionization tend to have flatter wage distributions across occupations2. If the firm's employees are unionized, individual workers may have little room for wage negotiation. The challenges or unique economic considerations facing industries can provide valuable insight when deciding on a target wage.

OES has wage and employment information for occupations in more than 300 specific industries.


The geographic location of the employer should also affect wages. Workers tend to have higher earnings in large metropolitan areas, where the high cost of living and other factors can drive wages higher. Chart 4 shows how wages vary by area for selected occupations and areas.

Occupational wages in selected metropolitan areas

Click here to see these data in table format.

For example, the average wage of electricians in San Francisco-Oakland-Fremont, CA is $36.11 compared with $19.66 in Miami-Fort Lauderdale-Miami Beach, FL, a difference of 84 percent. Area wage information can even be helpful when comparing specific areas within large metropolitan areas such as New York, Boston, and Los Angeles. These areas among others, are broken down into divisions that may also contain significant differences in wage and employment patterns. For example, although sales managers in the larger New York City metropolitan area earned an average $147,180 per year, those in the Nassau-Suffolk, NY Metropolitan Division earned $158,910, and those in the Newark-Union, NJ-PA Metropolitan Division earned $130,350.

Sales Managers in the New York City area

Click here to see these data in table format.

The OES program has wage data for all metropolitan and nonmetropolitan areas in the United States.

Employer benefits

The OES wage estimates include only wages and salaries, but not all compensation is in the form of wages and salaries. Benefits such as training opportunities, health insurance, and paid time off are not included in an individual's wages, but they add considerable value and are important to many prospective employees. Benefits are not always comparable between employers and should be considered along with wage compensation. Information on employee benefits is available from the BLS Employee Benefits Survey.

Success in wage negotiation depends in large part on the jobseeker's and employer's ability to objectively match the experience and skills of the worker with the needs of the employer. A number of factors play a role in the wage that an employer offers, including the employer's industry and geographic location. These indicators can suggest where an employee's wage should be on the distribution of incomes for the occupation.

Complete OES data, including data for more than 450 industries and industry aggregations, are available on the OES home page. Full wage distribution data, including the 10th, 25th, 50th, 75th, and 90th percentiles, can be downloaded in Excel format from the OES home page, or by using the OES query tool. Wage data for May 2009 will be released on May 14, 2010. This highlight was prepared by Clayton Lindsay. For more information, please contact the OES program by telephone at (202) 691–6569 or by e-mail at oesinfo@bls.gov

1Warren, Zachary, “Occupational employment in the not-for-profit sector,” Monthly Labor Review, November 2008, pp. 11–43 on the Internet at www.bls.gov/opub/mlr/2008/11/art2full.pdf

2Jones, John Ichiro, “An Investigation of Industry and Size Effects on Wage Dispersion,” Occupational Employment and Wages, May 2003, Bureau of Labor Statistics; September 2004; pp. 22-23 Bulletin 2567 www.bls.gov/oes/2003/may/dispersion.pdf


Last Modified Date: April 20, 2010