Prior to 2002, the Occupational Employment Statistics (OES) survey was an annual mail survey measuring occupational employment and occupational wage rates for wage & salary workers in nonfarm establishments by industry. The survey sampled and contacted approximately 400,000 establishments in the fourth quarter of each year. Over the course of a 3-year cycle approximately 1.2 million establishments were sampled. Beginning in November 2002, the OES survey converted to a semi-annual survey sampling approximately 200,000 establishments per panel. The reference periods are the second and the fourth quarter of each year. For the November 2003 survey, data collected in November 2003 were combined with data collected in May 2003, November 2002, 2001, and a subset of units sampled in 2000 to yield a sample of approximately 1.2 million establishments. Data collected in 2001 and 2000 were collected through an annual sample. The 2001 sample is the equivalent of two panels, and the subset of the 2000 sample is the equivalent of one panel. The national response rate for the survey was 79 percent based on establishment units and 73 percent based on employment. While estimates can be produced from a single panel or a single year of data, the data set is too small to produce reliable estimates at fine levels of geographical, industrial, and occupational detail. Pooling data from six semiannual panels, however, will create a sufficiently large data set. Estimates from the November 2003 survey are based on data collected from establishments using the Standard Occupational Classification system. A brief description of this system is provided below.
The Occupational Classification Standard for November 2003In 1999, the OES survey began using the Office of Management and Budget's occupational classification system—the Standard Occupational Classification system (SOC). The SOC system is the first OMB-required occupational classification system for federal agencies. The OES survey categorizes workers in one of about 770 detailed occupations. Together, these detailed occupations comprise 22 major occupational groups. The major groups of the SOC system are as follows:
For more information about the SOC, please see the BLS Web site at https://www.bls.gov/soc
BLS funds the survey and provides the procedures and technical support, while the State Employment Security Agencies (SESAs) collect the data. BLS funds the survey and provides procedural and technical support. The State Employment Security Agencies (SESAs) collect the data. BLS produces cross industry and North American Industry Classification System (NAICS) estimates for the nation, states, and metropolitan statistical areas (MSAs). NAICS estimates are produced primarily at the sector, 3 and 4-digit level with some 5-digit exceptions. BLS releases all cross industry and national estimates while the SESAs release estimates at the state and MSA levels.
The OES survey defines employment as the number of workers who can be classified as full-time or part-time employees, including workers on paid vacations or other types of 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 survey excludes the self employed, owners/partners of unincorporated firms, and unpaid family workers. Employees are reported in the occupation in which they are working, not necessarily for which they were trained.
The OES survey currently uses the North American Industry Classification System to classify all establishments by major economic activity. 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 scope of the survey includes establishments in NAICS sectors 11 (logging and support activities for agriculture 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. This scope covers workers in logging; support activities for agriculture; mining; utilities; construction; manufacturing; wholesale trade; retail trade; transportation and warehousing; information; finance and insurance; real estate and rental and leasing; professional, scientific, and technical services; management of companies and enterprises; administrative and support and waste management and remediation services; educational services; health care and social assistance; arts, entertainment, and recreation; accommodation and food services; other services (except public administration and private households); and state & local government. Data for the U.S. Postal Service (most of NAICS code 4911) and the federal government are universe counts obtained from the Postal Service and the Office of Personnel Management, respectively.
States' 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 geographic area, industry, and size class. Size classes are defined as follows:
|Size class||Number of employees|
|1||1 to 4|
|2||5 to 9|
|3||10 to 19|
|4||20 to 49|
|5||50 to 99|
|6||100 to 249|
|7||250 and above|
UI reporting units with 250 or more employees are sampled with virtual certainty across a six panel cycle. Generally, one-sixth of the certainty units are sampled in each panel and state. Some states, however, sampled more than one-sixth of their certainty units during the May 2003 panel to make up for a shortfall in a previous panel.
Employmentis the estimate of total wage and salary employment in an occupation across the industries in which it was reported. The OES survey form sent to an establishment contains between 50 and 225 SOC occupations selected on the basis of the industry classification and size class of the sampled establishments. To reduce paperwork and respondent burden, no survey form contains every SOC occupation. Thus, data for specific occupations are collected primarily from establishments within industries that are the predominant employers of labor in these occupations. Each survey form is structured, however, to allow a respondent to provide information for each detailed occupation employed at the establishment; that is, unlisted occupations can be added to the survey form.
Wagesfor 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 of 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 2003 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 rate. 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. Total hourly wages are calculated as follows:
Mean annual wage rate. Many employees are paid at an hourly rate by their employers. Some, however, may work more than or less than 40 hours per week. Mean annual wage rates in this release are estimated by taking the product of mean hourly wage rate and 2,080 (the approximate number of hours that a full-time worker works in a year, 52 weeks by 40 hours). This statistic, in some cases, may not represent the actual annual pay of a worker if the worker works more than or less than 2,080 hours per year. Furthermore, some occupations have workers who are paid on an annual basis but who do not work the usual 2,080 hours per year. Because the OES survey does not collect the actual hours worked by an employee, mean hourly wage rates can not be derived with any reasonable degree of confidence from mean annual wage rates. Consequently only mean annual wage rate estimates are calculated for these occupations. Occupations whose workers typically work less than 2,080 hours per year include teachers, pilots, flight attendants, musicians, and entertainers.
P-th percentile hourly wage rate. The p-th percentile hourly wage rate for an occupation is the wage rate where p percent of all workers in the estimates cell earn that amount or less and where (100-p) percent of all workers earn that amount or more. This statistic is calculated as follows:
P-th percentile annual wage rate. Many employees are paid at an hourly rate by their employers. Some, however, may work more than or less than 40 hours per week. P-th percentile annual wage rates in this release are estimated by taking the product of the p-th percentile hourly wage rate and 2,080 (the approximate number of hours that a full-time worker works in a year, 52 weeks by 40 hours). This statistic, in some cases, may not represent the actual annual pay of a worker if the worker works more than or less than 2,080 hours per year. Furthermore, some occupations have workers who are paid on an annual basis but who do not work the usual 2,080 hours per year. Occupations whose workers typically work less than 2,080 hours per year include teachers, pilots, flight attendants, musicians, and entertainers
Hourly versus annual wage reporting. For each occupation, respondents are asked to report the number of employees paid within specific wage rate intervals. These intervals are defined by hourly wage rates and by corresponding annual wage rates. Annual wage rates are calculated by taking the product of hourly wage rates and 2,080 hours. When reporting wage rate data for its workers, the respondent can report the data on an hourly or an annual basis with the exception of part-time workers. For this type of worker, the respondent is asked to report wage rate data on an hourly basis only
Prior to 2002, the OES survey sampled approximately 400,000 establishments in the fourth quarter of each year. Over a 3-year period approximately 1,2 million establishments were sampled. Beginning with the fourth quarter of 2002, the survey now samples approximately 200,000 establishments semiannually in two panels. One panel is sampled in the second quarter, the other in the fourth quarter. Approximately 1.2 million establishments are sampled over a 6 panel cycle. While estimates can be made from a single panel or a single year of data, the OES survey is designed to produce estimates at a desired level of precision using six panels. A six panel sample allows the production of estimates at fine levels of geographical, industrial, and occupational detail. For the November 2003 survey, data collected in November 2003 were combined with data collected in May 2003, November 2002, 2001, and a subset of units sampled in 2000. Producing estimates using six panels of data (or, in this case, its equivalent) provides significant sampling error reductions particularly for small geographic areas. Combining panel data, however, has a quality limitation in that it requires wage data from prior panels be adjusted to the current reference period to account for the passage of time. This procedure is referred to as "wage updating".
Wage Updating. As noted above, combining multiple years of data has statistical advantages and a limitation. Advantages include (1) reduced sampling error, (2) improved reliability of wage rate and employment estimates for detailed occupations in small geographic areas, and (3) more complete coverage of the certainty strata (these strata cover establishments employing 250 or more employees). The limitation is that wage rate data from previous panels must be updated to the current reference period.
Beginning with the 1997 estimates, the OES program has been using the Bureau of Labor Statistic's Employment Cost Index (ECI) to update wage rate data from previous panels before combining them with the current panel. The wage updating process assumes that (1) each occupation's wage rate, as measured in earlier panels, shifts across time at the same pace as the broader occupation division that encompasses it and (2) geography and industry are not major factors in the wage updating process. The Bureau has conducted research over the past several years on the accuracy of updating wage rates using the ECI. In this research, the ECI wage-updating approach was compared to alternative modeling approaches. Current research results support the continued use of ECI wage-updating.
November 2003 OES survey estimates. The November 2003 estimates for the OES survey are based on data collected from establishments in November 2003, May 2003, November 2002, 2001, and a subset of units sampled in 2000. Wage rate data collected in previous panels were updated using the ECI before being combined with data from the current panel. In addition, a "nearest neighbor" hot deck imputation procedure was used to impute occupational employment totals for establishments that reported no employment data. For establishments that reported or imputed occupational employment totals but did not report an employment distribution across the wage intervals, a variation of mean imputation is used to impute that distribution. During estimates processing, OES employment estimates are benchmarked to the mean of employment totals extracted from the Bureau's November 2003 and May 2003 Quarterly Micro Files.
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 of the population (i.e., a sample) instead of the full population. When a subset of the population is sampled, it is very likely that the sample estimate of the characteristic of interest will 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 many times using the same survey design, approximately 95 percent of the intervals created by adding and subtracting 2 SEs from the sample estimate would include the population value. This interval is called a 95-percent confidence interval. 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 replication technique known as the Jackknife. Mean wage rate RSEs are calculated using a variance components model that accounts for both the observed and unobserved components of wage data. The variances of the unobserved components are estimated using wage data from the Bureau's 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 interval may not reflect the prescribed level of confidence.
Nonsampling error occurs for a variety of reasons, none of which are directly connected to sampling like sampling error. Examples of nonsampling error include: nonresponse, data incorrectly reported by the respondent, mistakes made in entering collected data into the database, mistakes made in editing and processing the collected data.
For additional information, contact the Office of Employment and Unemployment Statistics, Occupational Employment Statistics, Room 2135, 2 Massachusetts Avenue, NE, Washington, DC, 20212; telephone: 202-691-6569; e-mail: OES staff.
Information in this release will be made available to sensory impaired individuals upon request. Voice phone: 202-691-5200; TDD message referral phone number: 1-800-877-8339.
Last Modified Date: April 9, 2018