The Current Employment Statistics (CES) program provides estimates of employment, hours, and earnings information on a national basis and in considerable industry detail. The Bureau of Labor Statistics collects payroll data each month from a sample of business and government establishments in all nonfarm activities. This product contains the complete dataset originally published at https://download.bls.gov/pub/time.series/ce. Sections 2-7 of the file ce.txt explain dataset features.
Survey Description: The Current Employment Statistics (CES) program provides estimates of employment, hours, and earnings information on a national basis and in considerable industry detail. The Bureau of Labor Statistics collects payroll data each month from a sample of business and government establishments in all nonfarm activities. Employment data include series for total employment, number of women employees, and number of production or nonsupervisory employees. Estimates of average hourly earnings, average weekly hours, average weekly earnings, and average weekly overtime hours are produced for both all employees and for production or nonsupervisory employees. Overtime hours are produced for manufacturing industries only. A sample of approximately 149,000 businesses and government agencies representing approximately 651,000 worksites throughout the United States is utilized for this monthly survey. The sample contains about 300,000 employer units. All employment, hours and earnings series are classified according to the 2012 North American Industry Classification System (NAICS). The industry code used in the survey corresponds to the NAICS code, except in those cases where multiple industries have been combined.
Summary of Data Available: For all employees, women employees, and production or nonsupervisory employees, CES publishes about 4,300 monthly series. The series for all employees cover more than 900 industries on both a seasonally adjusted and not seasonally adjusted basis. Approximately 2,500 series for AHE, AWH, and, in manufacturing, AWOH for both all employee and production and nonsupervisory employees are published monthly on a not seasonally adjusted basis and cover about 600 industries. About 5,800 seasonally adjusted employment, hours, and earnings series for AE, PE, and WE are published. Over 8,600 derivative series such as average weekly earnings (AWE), indexes, and constantdollar series for AE and PE are also published for approximately 600 industries. Most employment series begin in 1990, although some series, including industry supersectors, are available from 1939. Supersectors include: mining and logging; construction; manufacturing; trade, transportation, and utilities; information; financial activities; professional and business services, education and health services; leisure and hospitality, other services, and government.
Frequency of Observations: Data series are monthly in most cases; quarterly averages are available for total employment, average weekly hours, and average overtime hours, seasonally adjusted (datatypes 19, 20, 25, 36, and 37). Annual averages are available for all series that are not adjusted for seasonality (except for the 12-month diffusion index series).
Data Characteristics: Earnings are measured in dollars and are published to the nearest cent (two decimal places). Average weekly and overtime hours are measured in hours and are published to the nearest tenth of an hour (one decimal place). Employment is measured in thousands of workers and is stored with no decimal place for all supersectors and for both durable goods and nondurable goods in manufacturing. Employment for all other industries are stored to one decimal place. Special characteristics of the data are footnoted where necessary. For example; I indicates that the seasonally adjusted series is independently seasonally adjusted and not used in aggregating to higher summary industries. For all employees, higher summary series, such as total nonfarm, are aggregated up from the 3-digit NAICS level.
If you have any questions about the CloudFormation stack, Lambda code or any of the AWS services being used, please contact info@rearc.io.
About Rearc
Rearc is a cloud, software and services company. We believe that empowering engineers drives innovation. Cloud-native architectures, modern software and data practices, and the ability to safely experiment can enable engineers to realize their full potential. We have partnered with several enterprises and startups to help them achieve agility. Our approach is simple — empower engineers with the best tools possible to make an impact within their industry.
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This listing is free. You subscribe through a single dimension, Product Access (Units), which grants you access to the dataset. There are no tiers, usage add-ons, or instance-size options to choose from. The vendor publishes this publicly available employment statistics dataset so you can consume it directly through AWS Data Exchange in a consistent format. Because access carries no charge and only one dimension exists, your cost does not scale with usage, data volume, or number of users.
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What does the single Product Access (Units) dimension actually grant me?
It grants your subscription access to the employment statistics dataset. You consume it through AWS Data Exchange in a consistent format. There is one unit that unlocks access, so you do not count seats, hosts, or instances. Access does not vary by number of users or data volume.
Does my cost change if I query the dataset more often or add more users?
No. This listing is free and has only one access dimension. Nothing meters your usage, so pulling the data more often, storing more of it, or adding users does not create software charges. AWS may still apply standard fees for any AWS services you use to consume or store the data.
How is the data delivered once I subscribe?
The vendor publishes this publicly available dataset on AWS Data Exchange. After you subscribe through the single access dimension, you consume it directly in a consistent format. The vendor handles sourcing and transforming the data, so you do not manage that acquisition work yourself.
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