Technical Notes for May 2009 OES Estimates

Scope of the Survey

The Occupational Employment Statistics (OES) survey is a semiannual mail survey measuring occupational employment and wage rates for wage and salary workers in nonfarm establishments in the United States. Guam, Puerto Rico, and the Virgin Islands also are surveyed, but their data are not included in this release. OES estimates are constructed from a sample of about 1.2 million establishments. Each year forms are mailed to two semiannual panels of approximately 200,000 sampled establishments, one panel in May and the other in November. May 2009 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2009, November 2008, May 2008, November 2007, May 2007, and November 2006. The overall national response rate for the six panels is 78.2 percent based on establishments and 74.5 percent based on employment.

The Occupational Coding System

The May 2009 OES estimates are based on the Office of Management and Budget’s 2000 Standard Occupational Classification (SOC) system. The OES survey categorizes workers into 801 detailed occupations. Together, these detailed occupations make up 22 of the 23 major occupational groups. Military specific occupations are not included in the OES survey. The major groups are as follows:

  • Management occupations
  • Business and financial operations occupations
  • Computer and mathematical science occupations
  • Architecture and engineering occupations
  • Life, physical, and social science occupations
  • Community and social services occupations
  • Legal occupations
  • Education, training, and library occupations
  • Arts, design, entertainment, sports, and media occupations
  • Healthcare practitioner and technical occupations
  • Healthcare support occupations
  • Protective service occupations
  • Food preparation and serving related occupations
  • Building and grounds cleaning and maintenance occupations
  • Personal care and service occupations
  • Sales and related occupations
  • Office and administrative support occupations
  • Farming, fishing, and forestry occupations
  • Construction and extraction occupations
  • Installation, maintenance, and repair occupations
  • Production occupations
  • Transportation and material moving occupations
  • Military specific occupations (not surveyed in OES).

For more information about the SOC system, please see the BLS Web site at

The Industry Coding System

The OES survey uses the North American Industry Classification System (NAICS). Since May 2008, OES estimates and survey data have been based on the 2007 NAICS. Earlier panel data and estimates were based on the 2002 NAICS. For more information about NAICS, see the BLS Web site at

The OES survey includes establishments in NAICS sectors 11 (logging and agricultural support activities only), 21, 22, 23, 31-33, 42, 44-45, 48-49, 51, 52, 53, 54, 55, 56, 61, 62, 71, 72, 81 (except private households), state government, and local government. The U.S. Postal Service and the executive branch of the federal government also are included. An establishment is defined as an economic unit that produces goods or provides services, such as a factory, mine, or store. The establishment is generally at a single physical location and is engaged primarily in one type of economic activity.

The OES survey covers all full- and part-time wage and salary workers in nonfarm industries. The survey does not include the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers.

Survey Sample

BLS funds the survey and provides the procedures and technical support, while the State Workforce Agencies (SWAs) collect most of the data. BLS produces cross-industry and industry-specific estimates for the nation, states, metropolitan statistical areas (MSAs), metropolitan divisions, and nonmetropolitan areas. Industry-specific estimates are produced at the NAICS sector, 3-digit, 4-digit, and selected 5-digit industry levels. BLS releases all cross-industry and national estimates; many SWAs release industry-specific estimates at the state and MSA levels.

State unemployment insurance (UI) files provide the universe from which the OES survey draws its sample. Employment benchmarks are obtained from reports submitted by employers to the UI program. Supplemental sources are used for rail transportation (NAICS 4821) and Guam because they do not report to the UI program. The OES survey sample is stratified by metropolitan and nonmetropolitan areas and industry. The 2000 Metropolitan Statistical Area standards were used to define the metropolitan areas.

An annual census is taken of the executive branch of the federal government, the U.S. Postal Service, state government, and Hawaii's local government. In order to provide the most occupational coverage, larger employers are more likely to be selected than smaller employers. The unweighted employment of sampled establishments across all six semiannual panels represents approximately 60.5 percent of total national employment.


Occupational employment is the estimate of total wage and salary employment in an occupation across the industries surveyed. The OES survey defines employment as the number of workers who can be classified as full- or part-time employees, including workers on paid vacations or other types of paid leave; workers on unpaid short-term absences; salaried officers, executives, and staff members of incorporated firms; employees temporarily assigned to other units; and employees for whom the reporting unit is their permanent duty station regardless of whether that unit prepares their paycheck.

The OES survey forms sent to larger establishments, generally those with 20 or more workers, contain between 50 and 225 SOC occupations selected on the basis of the sampled establishment's industry classification. To reduce paperwork and respondent burden, no survey form contains every SOC occupation. Thus, data for specific occupations are collected primarily from establishments in industries that are the predominant employers of workers in those occupations. Each survey form is structured, however, to allow a respondent to provide detailed occupational information for each worker at the establishment; that is, unlisted occupations can be added to the survey form. Smaller establishments, generally those with fewer than 20 workers, are sent a form with no occupations listed, and are instructed to fill in the occupations for their workers.

Wages for the OES survey are straight-time, gross pay, exclusive of premium pay. Base rate, cost-of-living allowances, guaranteed pay, hazardous-duty pay, incentive pay including commissions and production bonuses, tips, and on-call pay are included. Excluded are back pay, jury duty pay, overtime pay, severance pay, shift differentials, nonproduction bonuses, employer cost for supplementary benefits, and tuition reimbursements.

OES receives an annual census of Federal Government and U.S. Postal Service data including wage rates. For non-federal establishments, the OES survey collects wage data in 12 intervals. Employers report the number of employees in an occupation for each wage range. The wage intervals used for the May 2009 survey are as follows:

May 2009 wage intervals

Interval Hourly Wages Annual Wages
Range A Under $9.25 Under $19,240
Range B $9.25 to $11.49 $19,240 to $23,919
Range C $11.50 to $14.49 $23,920 to $30,159
Range D $14.50 to $18.24 $30,160 to $37,959
Range E $18.25 to $22.74 $37,960 to $47,319
Range F $22.75 to $28.74 $47,320 to $59,799
Range G $28.75 to $35.99 $59,800 to $74,879
Range H $36.00 to $45.24 $74,880 to $94,119
Range I $45.25 to $56.99 $94,120 to $118,559
Range J $57.00 to $71.49 $118,560 to $148,719
Range K $71.50 to $89.99 $148,720 to $187,199
Range L $90.00 and over $187,200 and over

Mean hourly wage. The mean hourly wage rate for an occupation is the total wages that all workers in the occupation earn in an hour divided by the total employment of the occupation.

For data from non-federal establishments: Total weighted non-federal hourly wages are summed across all intervals. The occupation's weighted survey non-federal employment is also summed. The mean wage for each interval is based on occupational wage data collected by the BLS Office of Compensation and Working Conditions for the National Compensation Survey (NCS). With the exception of the highest wage interval, mean wage rates for each panel are calculated using NCS data for the panel's reference year. The lower boundary of the highest wage interval in May 2009 was $90.00. The mean hourly wage for this interval was calculated using the average of the 2006, 2007, and 2008 NCS data.

For federal workers: The hourly wages for an occupation within an establishment are summed to get total federal wages. Federal employment for that occupation within that establishment is also summed to get total federal employment. The total wages and total employment across all establishments in the occupation for the estimation level of interest are summed.

Mean Wage = (Total Non-Federal Wages + Total Federal Wages) / (Total Non-Federal Employment + Total Federal Employment)

Percentile wage. The p-th percentile wage rate for an occupation is the wage where p percent of all workers earn that amount or less and where (100-p) percent of all workers earn that amount or more. This statistic is calculated by first distributing federal and non-federal workers inside each wage interval: Federal workers are distributed throughout the wage intervals according to their wage rates, while non-federal workers are distributed uniformly within each wage interval. Next, workers are ranked from lowest paid to highest paid. Finally, the product of the total employment for the occupation and the desired percentile is calculated to determine the worker that earns the p-th percentile wage rate.

Annual wage. Many employees are paid at an hourly rate by their employers and may work more than or less than 40 hours per week. Annual wage estimates for most occupations in this release are calculated by multiplying the mean hourly wage by a "year-round, full-time" figure of 2,080 hours (52 weeks by 40 hours). Thus, annual wage estimates may not represent the actual annual pay received by the employee if they work more or less than 2,080 hours per year. Some workers typically work less than 40 hours per week, year round. For these occupations, the OES survey collects and reports either the annual salary or the hourly wage rate, depending on how the occupation is typically paid, but not both. For example, teachers, flight attendants, and pilots may be paid an annual salary, but do not work the usual 2,080 hours per year. In this case, an annual salary is reported. Other workers, such as entertainment workers, are paid hourly rates, but generally do not work 40 hours per week, year round. For these workers, only an hourly wage is reported.

Hourly versus annual wage reporting. For each occupation, respondents are asked to report the number of employees paid within specific wage intervals. The intervals are defined both as hourly rates and the corresponding annual rates, where the annual rate for an occupation is calculated by multiplying the hourly wage rate by a typical work year of 2,080 hours. The responding establishment can reference either the hourly or the annual rate for full-time workers, but they are instructed to report the hourly rate for part-time workers.

Estimation methodology

With the exception of the May 2008 panel, each OES panel includes approximately 200,000 establishments. Due to budget constraints, the May 2008 sample was reduced to approximately 174,000 establishments. The OES survey is designed to produce estimates using six panels (3 years) of data. The full six-panel sample of nearly 1.2 million establishments allows the production of estimates at detailed levels of geography, industry, and occupation.

Wage updating. Significant reductions in sampling errors are obtained by combining six panels of data, particularly for small geographic areas and occupations. Wages for the current panel need no adjustment. However, wages in the five previous panels need to be updated to the current panel's reference period.

The OES program uses the BLS Employment Cost Index (ECI) to adjust survey data from prior panels before combining them with the current panel's data. The wage updating procedure adjusts each detailed occupation's wage rate, as measured in the earlier panel, according to the average movement of its broader occupational division. The procedure assumes that there are no major differences by geography, industry, or detailed occupation within the occupational division. The wage rates for the highest wage interval are not updated.

Imputation. About 20 percent of establishments do not respond for a given panel. A "nearest neighbor" hot deck imputation procedure is used to impute missing occupational employment totals. A variant of mean imputation is used to impute missing wage distributions. The variant of mean imputation for wage distributions also is applied to establishments that provide reports with occupational totals but partial or missing wage data.

Weighting and benchmarking. The sampled establishments in each panel are weighted to represent all establishments that were part of the in-scope frame from which the panel was selected. Based on the sampled establishments, sampling weights are adjusted when six panels are combined. Sampling weights are further adjusted by the ratio of employment totals (the average of November 2008 and May 2009 employment) from the BLS Quarterly Census of Employment and Wages to employment totals from the OES survey.

May 2009 OES survey estimates. The May 2009 OES survey estimates are based on all data collected from establishments in the May 2009, November 2008, May 2008, November 2007, May 2007, and November 2006 semiannual sample panels.

Reliability of the estimates. Estimates calculated from a sample survey are subject to two types of error: sampling and nonsampling. Sampling error occurs when estimates are calculated from a subset (that is, a sample) of the population instead of the full population. When a sample of the population is surveyed, there is a chance that the sample estimate of the characteristic of interest may differ from the population value of that characteristic. Differences between the sample estimate and the population value will vary depending on the sample selected. This variability can be estimated by calculating the standard error (SE) of the sample estimate. If we were to repeat the sampling and estimation process countless times using the same survey design, approximately 90 percent of the intervals created by adding and subtracting 1.645 SEs from the sample estimate would include the population value. These intervals are called 90-percent confidence intervals. The OES survey, however, usually uses the relative standard error (RSE) of a sample estimate instead of its SE to measure sampling error. RSE is defined as the SE of a sample estimate divided by the sample estimate itself. This statistic provides the user with a measure of the relative precision of the sample estimate. RSEs are calculated for both occupational employment and mean wage rate estimates. Occupational employment RSEs are calculated using a subsample, random group replication technique called the jackknife. Mean wage rate RSEs are calculated using a variance components model that accounts for both the observed and unobserved components of the wage data. The variances of the unobserved components are estimated using wage data from the BLS National Compensation Survey. In general, estimates based on many establishments have lower RSEs than estimates based on few establishments. If the distributional assumptions of the models are violated, the resulting confidence intervals may not reflect the prescribed level of confidence.

Nonsampling error occurs for a variety of reasons, none of which are directly connected to sampling. Examples of nonsampling error include: nonresponse, data incorrectly reported by the respondent, errors in the administrative data used to create the sampling frame, mistakes made in entering collected data into the database, and mistakes made in editing and processing the collected data. Every attempt is made to minimize nonsampling error through survey methods such as data editing, imputation methods, and benchmarking of data to current employment totals.

May 2009 National Occupational Employment and Wage Estimates

May 2009 State Occupational Employment and Wage Estimates

May 2009 Metropolitan and Nonmetropolitan Area Occupational Employment and Wage Estimates

May 2009 National Industry-Specific Occupational Employment and Wage Estimates

List of Occupations in SOC Code Number Order

List of Occupations in Alphabetical Order

Download May 2009 Occupational Employment and Wage Estimates in Zipped Excel files

Technical notes


Last Modified Date: May 14, 2010