From AEAStat staff:
The Bureau of Labor Statistics has asked OMB for approval to conduct the Occupational Employment Statistics (OES) survey through 2023 and invites the public to provide comments to OMB by April 13 regarding any aspect of the OES, including scope, methodology, sample design, analysis, and data dissemination.
Federal Register notice inviting input:
https://www.federalregister.gov/documents/2020/03/10/2020-04802/agency-information-collection-activities-submission-for-omb-review-comment-request-report-on
Submission to OMB:
https://www.reginfo.gov/public/do/PRAViewICR?ref_nbr=202001-1220-002
See IC List for survey forms, Supporting Statement for plans, methods, sample design, schedule
While BLS is not proposing any significant changes in the OES, economists are welcome to suggest desirable improvements.
Excerpts from Supporting Statement:
Uses:
The OES employment data are used as inputs to the Employment Cost Index, the Occupational Requirements Survey, and estimates of Occupational Injury and Illness rates. Data are used by the Centers for Medicare and Medicaid Services in the calculation of reimbursement rates for Medicaid and Medicare providers. Special tabulations of workers in Science, Technology, Engineering, and Math (STEM) are provided annually to the National Science Foundation. Additionally, special tabulations of employment by State, industry, and wage range are supplied to the Bureau of Economic Analysis for estimating Social Security payments from employers.
National OES wage data collection can provide a significant source of information to support a number of different federal, state, and local efforts. For instance, occupational wage data can be extremely useful in the administration of the Unemployment Insurance (UI) system. Generally, UI clients must meet work-search requirements and take jobs that pay equivalent to their previous employment. Wage data by occupation can help employment services identify occupations that meet the requirements of these individuals. Similarly, the dislocated workers program uses previous wages as a guide in preparing dislocated workers for employment. The OES survey can provide a standard source of occupational wage data to assist these workers.
Wage data at the occupational level can assist States and local authorities in carrying out vocational rehabilitation programs. The data can support U.S. military interests by providing State and local career information for Department of Defense workers. Minimum wage deliberations can use OES employment and wage data as a source of information.
OES wage data provides vocational trainers and enrollees with information on what occupations are present in the economy as well as their corresponding wage rates. These data will assist the national, State, and local coordinating committees to develop occupational information systems designed to aid job searchers and career counselors. As an example of use of the OES program, Career One Stop provides to individuals and career counselors the OES employment and wage data at its Web site at
http://www.careerinfonet.org/
Reliable wage data has many practical uses. OES wage data can be an important analytical tool with enormous explanatory power. Wage data can be used to understand the direction and quality of the jobs being created in our economy and can play a part in important legal and administrative decisions. More importantly, wage information is a valuable commodity to the general public, whether the data are assembled in the BLS Occupational Outlook Handbook, or released across the country in occupational information systems. The detail, reliability, and applicability of the OES wage survey argues strongly for its expanded support.
Respondent Universe:
The universe for this survey consists of the Quarterly Contribution Reports (QCR) filed by employers subject to State Unemployment Insurance (UI) laws. The U.S. Bureau of Labor Statistics (BLS) receives these QCR for the Quarterly Census of Employment and Wages (QCEW) Program from the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. The QCEW data, which are compiled for each calendar quarter, provide a comprehensive business name and address file with employment, wage, detailed geography (i.e., county), and industry information at the six-digit North American Industry Classification System (NAICS) level. This information is provided for nearly ten million business establishments of which about 7.7 million are in the scope of this survey. The final data is stored in a Longitudinal Data Base (LDB), which is then used as a sampling frame for sample selection.
Sample Size--The sample size is approximately 1.1 million establishments over a 3-year period. The sample is divided into six panels over three years with two semi-annual samples of about 180,000 establishments selected each year.
Sample Design
Allocation method--A variation of Neyman allocation procedure called a Power Allocation (Bankier, 1988) is used to allocate the non-certainty sample to each State-/area/3-4-5-6-digit NAICS stratum. The allocation methodology balances employment size of areas and industries with the variability of the occupational employment in each industry. The use of the power allocation shifts sample away from very large areas and industries to medium and smaller ones allowing more comparable estimates for smaller domains.
Sample Selection--Within each stratum, the sample is selected using probability proportional to estimated employment size with large units being selected with certainty. Each semi-annual panel sample is designed to represent the frame. Every attempt is made to ensure that private and local government establishments are only selected once every three years. Consequently, each sampled establishment is assigned a sampling weight equal to the reciprocal of its probability of selection in the sample. Note: Censuses of federal and state government are collected annually.
Occupational employment data from prior survey rounds are used by BLS-Washington to produce sample allocations that result in relative standard errors (RSE) on mean wages of 10 to 20 percent for the typical occupations in each MSA/ three-, four-, five-, or six-digit industry cell. Mean wage estimates for typical occupations at higher aggregate levels of area and industry will have substantially smaller relative standard errors.
Frequency of Sampling--Each year, semiannual panels of about 180,000 to 190,000 establishments each are selected for the May and November reference periods.
Sample Selection--Within each stratum, the sample is selected using probability proportional to estimated employment size with large units being selected with certainty. Each semi-annual panel sample is designed to represent the frame. Every attempt is made to ensure that private and local government establishments are only selected once every three years. Consequently, each sampled establishment is assigned a sampling weight equal to the reciprocal of its probability of selection in the sample. Note: Censuses of federal and state government are collected annually.
Occupational employment data from prior survey rounds are used by BLS-Washington to produce sample allocations that result in relative standard errors (RSE) on mean wages of 10 to 20 percent for the typical occupations in each MSA/ three-, four-, five-, or six-digit industry cell. Mean wage estimates for typical occupations at higher aggregate levels of area and industry will have substantially smaller relative standard errors.
Frequency of Sampling--Each year, semiannual panels of about 180,000 to 190,000 establishments each are selected for the May and November reference periods.
For AEA members wishing to provide comments, "A Primer on How to Respond to Calls for Comment on Federal Data Collections" is available at
https://www.aeaweb.org/content/file?id=5806 AEA staff support is available at areamer@gwu.edu and 202-994-7866.
