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. Forms are mailed to approximately 200,000 establishments in May and November of each year for a 3-year period. The nationwide response rate for the May 2005 survey was 78.4 percent based on establishments and 73.2 percent based on employment. The survey included establishments sampled in the May 2005, November 2004, May 2004, November 2003, May 2003, and November 2002 semiannual panels.
The OES survey uses the Office of Management and Budget's (OMB) occupational classification system, the Standard Occupational Classification (SOC) system. The SOC system is the first OMB-required occupational classification system for federal agencies. The OES survey categorizes workers in 1 of 801 detailed occupations. Together, these detailed occupations comprise 23 major occupational groups, one of which-military specific occupations-is not included in the OES survey. The major groups are as follows:
For more information about the SOC, please see the BLS Web site at http://www.bls.gov/soc/.
The OES survey uses the North American Industry Classification System (NAICS). For more information about NAICS, see the BLS Web site at http://www.bls.gov/bls/naics.htm.
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 executive branch of the federal government and the U.S. Postal Service also are included. An establishment is defined as an economic unit that processes 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.
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, and metropolitan statistical areas (MSAs). 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; the 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. Samples selected in panels prior to May 2005 were stratified using MSA definitions based on the 1990 Metropolitan Statistical Area Standards. Beginning with the May 2005 panel, the sample was stratified using new MSA definitions based on the 2000 Metropolitan Statistical Area Standards.
A census of federal government and the U.S. Postal Service is taken every panel. A census of state government and Hawaii's local government is taken every November panel. 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 make up approximately 65 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 form sent to establishments with more than 10 workers contains 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. Employers with 10 or fewer 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, non-production bonuses, employer cost for supplementary benefits, and tuition reimbursements.
The OES survey collects wage data in 12 intervals. Employers report the number of employees in an occupation per each wage range. The wage intervals used for the November 2004 survey are as follows:
|Interval||Hourly Wages||Annual Wages|
|Range A||Under $6.75||Under $14,040|
|Range B||$6.75 to $8.49||$14,040 to $17,679|
|Range C||$8.50 to $10.74||$17,680 to $22,359|
|Range D||$10.75 to $13.49||$22,360 to $28,079|
|Range E||$13.50 to $16.99||$28,080 to $35,359|
|Range F||$17.00 to $21.49||$35,360 to $44,719|
|Range G||$21.50 to $27.24||$44,720 to $56,679|
|Range H||$27.25 to $34.49||$56,680 to $71,759|
|Range I||$34.50 to $43.74||$71,760 to $90,999|
|Range J||$43.75 to $55.49||$91,000 to $115,439|
|Range K||$55.50 to $69.99||$115,440 to $145,599|
|Range L||$70.00 and over||$145,600 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. To calculate the mean hourly wage of each occupation, total weighted hourly wages are summed across all intervals and divided by the occupation's weighted survey employment. 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).
The mean hourly wage value for the highest wage interval, $70.00 and over, was computed separately for NCS data from 2004, 2003, 2002, and 2001. The average of these mean wage rates was used for all of the $70.00 and over data in the November 2004 survey. The wage rates for this interval do not go through any wage updating procedures.
Because there is wide variation in the number of hours worked by those employed as actors, dancers, musicians, and singers, only hourly wages are available for those occupations. Many jobs are for a duration of 1 day or 1 week and it is extremely rare for a performer to have guaranteed employment for a period that exceeds 3 to 6 months.
Percentile wage. The p-th percentile wage rage 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 uniformly distributing the workers inside each wage interval, ranking the workers from lowest paid to highest paid, and calculating the product of the total employment for the occupation and the desired percentile 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 full time, 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 full time, 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.
Each OES panel includes approximately 200,000 establishments. The OES survey is designed to produce estimates using six panels (3 years) of data. The full six-panel sample of 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.
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 sample 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 2004 and May 2005 employment) from the BLS Quarterly Census of Employment and Wages to employment totals from the OES survey.
May 2005 OES survey estimates. The May 2005 OES survey estimates are based on all data collected from establishments in the May 2005, November 2004, May 2004, November 2003, May 2003, and November 2002 semiannual samples.
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 (i.e., 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, mistakes made in entering collected data into the database, and mistakes made in editing and processing the collected data.
May 2005 National Occupational Employment and Wage Estimates
May 2005 State Occupational Employment and Wage Estimates
May 2005 Metropolitan Area Occupational Employment and Wage Estimates
May 2005 National Industry-Specific Occupational Employment and Wage Estimates
List of Occupations in SOC Code Number Order
List of Occupations in Alphabetical Order
Download May 2005 Occupational Employment and Wage Estimates in Zipped Excel files
Last Modified Date: May 24, 2006