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Occupational Employment and Wage Statistics Technical Notes


The Occupational Employment and Wage Statistics (OEWS) survey is a semiannual mail survey of employers that measures occupational employment and occupational wage rates for wage and salary workers in nonfarm establishments, by industry. OEWS estimates are constructed from a sample of about 44,400 establishments. Each year, forms are mailed to two semiannual panels of approximately 7,400 sampled establishments, one panel in May and the other in November. Estimates are based on responses from six semiannual panels collected over a 3-year period.

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor funds the survey and provides the procedures and technical support. The New York State Department of Labor (NYSDOL) collects and processes the data.

Survey Definitions and Concepts

Many of the concepts and definitions used in the OEWS survey are similar to those in the Current Employment Statistics survey, a monthly BLS payroll survey of nonagricultural establishments. Many others, however, are unique to the OEWS survey. Key definitions for the OEWS survey follow.

An establishment is an economic unit that produces goods or services, such as a factory, a mine, or a store. It is generally at a single location and predominantly engaged in one economic activity.

The OEWS 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 their present occupation which might be different from the occupation for which they were trained.

Benchmark weights are used to compute estimates of occupational employment. Estimates are produced for cells defined by geographic area, industry group, and size of establishment (i.e., size class). Total employment for an occupation in a cell is estimated by taking the product of reported occupational employment and benchmark weight for each establishment in the cell and summing the product across all establishments in the cell.

Wages for the OEWS 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. Back pay, jury duty pay, overtime pay, severance pay, shift differentials, non-production bonuses, and tuition reimbursements are excluded.

The OEWS survey collects wage data for 12 wage intervals. That is, for each occupation, employers report the number of employees that fall within each wage range. The wage intervals used for the survey are as follows:

For The May 2020 Panel:
IntervalHourly wagesAnnual wages
Range A Under $9.25 Under $19,240
Range B $9.25 to $11.74 $19,240 to $24,439
Range C $11.75 to $14.74 $24,440 to $30,679
Range D $14.75 to $18.74 $30,680 to $38,999
Range E $18.75 to $23.99 $39,000 to $49,919
Range F $24.00 to $30.24 $49,920 to $62,919
Range G $30.25 to $38.49 $62,920 to $80,079
Range H $38.50 to $48.99 $80,080 to $101,919
Range I $49.00 to $61.99 $101,920 to $128,959
Range J $62.00 to $78.74 $128,960 to $163,799
Range K $78.75 to $99.99 $163,800 to $207,999
Range L $100.00 and over $208,000 and over

Hourly versus annual wage reporting: For each occupation, respondents are asked to report the number of employees whose wages fall within specific wage intervals. The intervals are defined both as hourly rates and as the corresponding annual rates. Annual rates are constructed by multiplying the hourly wage rate for the interval by the typical work year of 2,080 hours. In reporting, the respondent can reference either the hourly or the annual rate for full-time workers, but the respondent is instructed to report the hourly rate for part-time workers.

There are workers in some occupations whose pay is based on an annual amount and who generally work less than the usual 2,080 hours per year. Since the survey dOEWS not collect data on the actual number of hours worked, hourly rates cannot be calculated with a reasonable degree of confidence from the annual wages paid to these workers. For this reason, the annual salary is reported for these occupations. Occupations that typically have a work-year of less than 2,080 hours include certain musicians and entertainers, pilots, flight attendants, and teachers. In cases where an annual wage is not available, the entry will read N/A.

A mean wage and a median wage are calculated using wage data from establishments in the industries that reported employment for an occupation.

The mean wage is the estimated total wages for an occupation, divided by its weighted survey employment. A mean wage value is calculated for each wage interval based on occupational wage data collected by the Office of Compensation and Working Conditions of the U.S. Department of Labor. These interval mean wage values are then attributed to all workers reported in the interval. For each occupation, total weighted wages in each interval (i.e., mean wages times weighted employment) are summed across all intervals and divided by the occupation's weighted survey employment to obtain a mean wage.

The median wage is the estimated 50th percentile of the distribution of wages: 50 percent of workers in an occupation earn wages below the median wage, and 50 percent earn wages above. The wage interval containing the median wage is located using a cumulative frequency count of employment across wage intervals. After the targeted wage interval is identified, the median wage rate is estimated by a linear interpolation procedure.

The entry wage is the mean (average) of the bottom third of wages in an occupation.

The experienced wage is the mean (average) of the top two-thirds of wages in an occupation.

Sampling Procedures

New York State's Unemployment Insurance (UI) files provide the universe from which the OEWS survey draws its sample. The employment benchmarks are obtained from reports submitted by employers to the UI program. In some non-manufacturing industries, supplemental sources are used for establishments that do not report to the UI program. Samples selected in panels prior to May 2017 were stratified using MSA definitions based on the 2000 Metropolitan Statistical Area Standards. Beginning with the May 2017 panel, the sample was stratified using new MSA definitions based on the 2015 Metropolitan Statistical Area Standards.

The OEWS survey sample is stratified by 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

Method of Collection

Survey schedules initially were mailed to virtually all sampled establishments. Additional mailings were sent to non-responding establishments. Telephone follow-ups were made to non-responding establishments throughout the course of the survey.

The Occupational Coding System

The May 2020 OEWS estimates contain nearly 800 occupational categories based on the Office of Management and Budget’s Standard Occupational Classification (SOC) system. Together, these occupations make up 22 of the 23 SOC major occupational groups. Major group 55, Military Specific Occupations, is not included.

For more information about the SOC system, please see the BLS SOC page.

The May 2020 OEWS estimates use a hybrid of the 2010 and 2018 SOC systems. For more information on the hybrid classification system, please see the “Changes and special procedures in the May 2020 estimates” section of this technical note.

The Industry Coding System

The May 2020 OEWS estimates use the 2017 North American Industry Classification System (NAICS). For more information about NAICS, see the BLS NAICS page.

The OEWS survey excludes the majority of the agricultural sector, with the exception of logging (NAICS 113310), support activities for crop production (NAICS 1151), and support activities for animal production (NAICS 1152). Private households (NAICS 814) also are excluded. OEWS federal government data include the U.S. Postal Service and the federal executive branch only. All other industries, including state and local government, are covered by the survey.

Estimation methodology

The OEWS survey is designed to produce estimates by combining six panels of data collected over a 3-year period.  The 3-year period has approximately 44,400 sample members, and approximately 7,400 establishments per panel. Each semiannual panel represents a one-sixth sample of the full three-year sample plan. While estimates can be made from a single year of data, the OEWS survey has been designed to produce estimates using the full three years of data. The full three-year sample allows the production of estimates at fine levels of geography, industry, and occupational detail, while estimates using any one year of data would be subject to a higher sampling error (due to the smaller sample size) and the limitations associated with having only one-third of the units from the certainty strata.

Producing estimates with three years of sample data reduces sampling error significantly, particularly for small geographic areas and occupations. However, this process also has some quality limitations in that it requires the adjustment of earlier years' data to the current reference period, a procedure called "wage updating."

Starting with the 1997 estimates, the OEWS program has used the over-the-year fourth-quarter wage changes from the Bureau's Employment Cost Index (ECI) to adjust prior-year survey data before combining it with the data for the current year. The wage updating procedure assumes that each occupation's wage, as measured in the earlier years, moves according to the average movement of its occupational division, and that there are no major geographic or detailed occupational differences. This may not be the case. BLS has conducted research over the past several years on the accuracy of the ECI wage-updating method versus other modeling approaches. Current research results support the continued use of the ECI wage-updating methodology.

The 2002 and later estimates also use the estimation methodology introduced in 1997, which uses a "nearest neighbor" imputation approach for non-respondents and applies employment benchmarks at a detailed MSA by three-digit industry and broad size-class level.

The New York State Department of Labor used wage-updating factors for later time periods to further update the data to a more current time period, the first quarter of 2021. As a result, wage-updating factors have been applied to all of the data included in these estimates. The updated data contained in this report are not official BLS data series and BLS has not validated them. As a result of using 3 years of sampled data, some occupations have wage estimates that fall below the appropriate New York State minimum wage. In these cases, the estimates are increased to equal the current local base minimum wage that was in effect at the time the estimates were prepared ($15.00 per hour in New York City, $14.00 per hour in Long Island, and $12.50 per hour in the remainder of the state). Wages may be subject to a higher minimum wage depending on a company's size, location, and/or industry. The New York State Department of Labor may adjust estimates to reflect changing economic conditions, updates, or changes in State or Federal law.

Reliability of the Estimates

The occupational employment and wage rates in this report are estimates derived from a sample survey. Two types of errors are possible in an estimate based on a sample survey -- sampling error and nonsampling error. Sampling error occurs because the observations are based on a sample, rather than on the entire population. Nonsampling error is due to response, nonresponse, and operational errors.

Nonsampling errors: Estimates are subject to various response, nonresponse, and operational errors during the survey process. Sources of possible errors are data collection, response, coding, transcription, data editing, nonresponse adjustment, and estimation. These errors would also occur if a complete census were to be conducted under the same conditions as the sample survey. Explicit measures of the effects of these errors are not available. However, it is believed that the important response and operational errors were detected and corrected during the review and validation process.

The limitations placed on the size of the benchmark factors are another source of potential bias. A benchmark factor is the ratio of a known employment value to a sample-derived employment estimate. This factor is used to make a post-stratification adjustment, forcing the calculated total weighted employment estimate [at the state-Metropolitan Statistical Area (MSA) / 4-digit NAICS (with 5-digit exceptions) employment-size class level] to match the population employment (at that same level). The source of the population employment data is New York's Quarterly Unemployment Insurance files for the reference period of the survey.

In cases where a small sample was taken, the ratio factor can become large or small. In order to prevent an establishment from contributing either too much or not enough to an MSA's occupational employment and wage rate estimates, the benchmark factor was not allowed to exceed a predetermined value. The total employment count for the MSAs where the benchmark factor was limited by this ceiling will be biased to a small degree in those strata. The employment not assigned to those strata because of this ceiling was then distributed across the other MSAs in the state/4-digit industry, so that the estimated employment of the state/4-digit industry would match the known employment totals at that level.

Sampling errors: The particular sample used in this survey is one of a large number of possible samples of the same size that could have been selected using the same sample design. For example, occupational employment and wage rate estimates derived from the different samples will differ from one another. The deviation of a sample estimate from the average of all possible sample estimates is called the sampling error. The standard error of an estimate is a measure of the variation of estimates across all possible samples and thus is a measure of the precision with which an estimate from a particular sample approximates the average result of all possible samples.

Quality Control Measures

Quality control measures implemented in the OEWS survey include the following:

  • follow-up solicitations of non-respondents (especially critical non-respondents)
  • review of survey schedules to verify the accuracy and reasonableness of the reported data
  • adjustments of atypical reporting units on the data file
  • validation of the non-response adjustment factors
  • validation of the population employment and ratio factors
  • standardized data processing programs and activities

Changes and special procedures in the May 2020 estimates

Due to features of the OEWS methodology, the May 2020 estimates do not fully reflect the impact of the COVID-19 pandemic. Because five of the six survey panels used to produce the estimates date from before the COVID-19 pandemic, only the most recent (May 2020) survey panel will reflect changes in occupational proportions related to the pandemic.

In addition, because the OEWS employment estimates are benchmarked to the average of QCEW employment for November 2019 and May 2020, the estimates will reflect only part of the pandemic’s impact on employment as of May 2020. Although the May 2020 QCEW data reflect the early employment effects of the COVID-19 pandemic, the November 2019 QCEW employment data precede the COVID-19 pandemic, and therefore do not reflect its impact.

As a result of the pandemic, response rates for the November 2019 and May 2020 panels were lower in some areas. Lower response rates may negatively affect data availability and data quality.

For more information about the impact of the COVID-19 pandemic on OEWS, see the OEWS COVID-19 impact statement.

With the May 2019 estimates, the OEWS program began implementing the 2018 Standard Occupational Classification (SOC) system. Because the May 2020 estimates are based on a combination of survey data collected using the 2010 SOC and survey data collected using the 2018 SOC, these estimates use a hybrid of the two classification systems that contains some combinations of occupations that are not found in either the 2010 or 2018 SOC. These combinations may include occupations from more than one 2018 SOC minor group or broad occupation. Therefore, OEWS will not publish data for some 2018 SOC minor groups and broad occupations in the May 2020 estimates. The May 2021 estimates, to be published in summer 2022, will be the first OEWS estimates based entirely on survey data collected using the 2018 SOC.

In addition, the OEWS program has replaced some 2018 SOC detailed occupations with SOC broad occupations or OEWS-specific aggregations. These include home health aides and personal care aides, for which OEWS will publish only the 2018 SOC broad occupation 31-1120 Home Health and Personal Care Aides.

More information on the occupational classification system used in the May 2020 OEWS estimates is available on the OEWS 2018 SOC implementation page and in the OEWS frequently asked questions.

The May 2020 OEWS estimates use the metropolitan area definitions delineated in Office of Management and Budget (OMB) Bulletin 17-01. For more information, please see the OEWS area definitions.

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