The establishment payroll survey, known as the Current Employment Statistics (CES) survey, is based on a survey of approximately 145,000 businesses and government agencies representing approximately 697,000 worksites throughout the United States. Two CES programs - CES National (CES-N) and CES State and Area (CES-SA) - use the data derived from the survey to produce monthly estimates of employment, hours, and earnings for the Nation, States, and major metropolitan areas. For more information about the CES National program, see the CES National page at https://www.bls.gov/ces/.
For more information about the CES survey, see the CES Technical Notes at https://www.bls.gov/sae/overview.htm#employ.
The CES and Quarterly Census of Employment and Wages (QCEW) programs are related but do not report the exact same information at the same frequency. The CES-SA program releases data monthly, typically five weeks after the survey reference week. The QCEW program releases data quarterly, between five and six months after the end of the reference quarter. The QCEW program publishes a quarterly count of employment and wages covering 98 percent of U.S. jobs, available at the county, Metropolitan Statistical Area (MSA), State, and National levels by industry. The CES program surveys about 145,000 businesses and government agencies, representing approximately 697,000 worksites, in order to provide detailed industry data on employment, hours, and earnings of workers on nonfarm payrolls on a monthly basis. The QCEW is also used as the universe for CES benchmarks.
For more information about the QCEW program, see the QCEW homepage at https://www.bls.gov/cew.
The Local Area Unemployment Statistics (LAUS) program shares two monthly press releases with CES State and Area. The LAUS program produces monthly and annual employment, unemployment, and labor force data by place of residence for Census regions and divisions, States, counties, metropolitan areas, and many cities. The concepts and definitions underlying LAUS data come from the Current Population Survey (CPS), a monthly household survey that is a measure of the labor force.
For more information about the LAUS program, see the LAUS homepage at https://www.bls.gov/lau.
CES data are a coincident economic indicator and are often cited in national and local newspapers, magazines, and reports. This press generates enthusiasm, curiosity and a wealth of outside material for supplementary reading. The College of Business Administration at the University of South Carolina uses seasonally adjusted employment as an indicator of current employment trends in South Carolina. The regional Federal Reserve Banks use CES data in easy-to-understand economic applications. For example, the edition of the Southwest Economy from the Federal Reserve Bank of Dallas used employment and unemployment data in two different articles: one explaining the Phillips curve and another describing the changing job market. Students and faculty can write the regional FRBs to be placed on their mailing lists. The Philadelphia, Dallas, Boston, Cleveland, and San Francisco FRBs provide excellent articles for undergraduate students.
CES data are tangible and versatile. Employment, hours, and earnings data can be used to study abstract economic concepts which students can more easily comprehend with the use of data. Students often need help in seeing how formal models can be used to explain the real world economy. Business cycles, the effects of shocks in the economy, and the impact of policy changes are examples of concepts that are more readily understood when using CES data. Also, combined with data from other sources, such as output data from the national accounts, they can be used to compute productivity and other measures. Primarily, the concept of employment is easy to comprehend, which permits a wide range of study and understanding by graduate and undergraduate students, policy makers, and business people. Data can be used for projects in labor economics, time series analysis, business cycle theory, statistics, geography, urban planning, and public policies.
CES data invite comparisons and analysis. CES data provides complete coverage and consistently derived methodology at the state and area levels for employment in major industries allowing for interstate and inter-area comparisons using CES data alone or in conjunction with other economic data. They allow one to compare growth patterns across states and regions. One can relate cyclical changes to geographic employment changes. For example the 1990-91 recession did not affect states and regions equally or at the same time. Employment declines started in the Northeast and spread along the Atlantic and Pacific coasts. The Midwest was largely unaffected. These diverse movements among states show how the mixture of industry, migration, and public policies affect employment. For this type of study, CES data can be combined with and compared to census migration data, immigration data, and public policy data that affect economic activity.
CES data are affordable. They are collected, tabulated, and distributed as part of the BLS and States' mission to provide economic data to policy makers, business, labor, and the public. Subscriptions are inexpensive and data on Internet are free. Since CES data are time series data, forecasters are able to depend on a consistent series to use in their modeling applications without incurring excessive costs.
Users should be aware of the intricate revision process which the CES estimates undergo. Preliminary monthly, final monthly, post benchmark projection, and final benchmark data are constructed for each monthly estimate. Analysis using estimates before they are final benchmarked estimates is affected by subsequent revisions.
Users of time series CES data should also review the entire time-series file to note any NAICS or MSA administrative breaks where reconstruction of series was not possible. Breaks will only be noted on the month where the time series break occurs. For example, a comparison of total nonfarm employment for the Washington D.C. metropolitan area between 1980 and 2003 actually involves multiple definitions of the official metropolitan area.
CES National (CES-N) estimates are independently produced and are not an aggregation of statewide data. Therefore users cannot disaggregate or compare CES National economic movements to state, regional, or metropolitan area CES-SA estimates.
CES data are not to be confused with data from the Current Population Survey (CPS) which is a household survey. The CES survey counts jobs; the CPS counts people. A worker with two jobs is counted twice in the CES but only once in the CPS.
Geographic hours and earnings data from the CES are limited in industry coverage and scope. The only extensive industry coverage is in manufacturing. CES hours and earnings data are also limited to money wages of production workers in manufacturing. Researchers looking at total labor costs and total compensation should be aware of these limitations.
The Current Employment Statistics State and Area Employment (CES-SA) program administers the establishment survey and uses the data collected to produce monthly nonfarm payroll estimates for states, metropolitan areas, and metropolitan divisions. The types of data produced include the following:
All data, with the exception of the three-month average change, are available not seasonally adjusted, and some data are available seasonally adjusted.
The State Employment and Unemployment and the Metropolitan Area Employment and Unemployment news releases are published monthly in conjunction with data derived from the Local Area Employment and Unemployment Statistics (LAUS) program. The State Employment and Unemployment news release is typically published on the fifth week after the conclusion of the reference week, which is the week that includes the 12th of the month. The Metropolitan Area Employment and Unemployment news release is typically published the week following the State Release. A schedule of upcoming news release dates is available at https://www.bls.gov/schedule/news_release/laus.htm.
The BLS LABSTAT database, available at https://www.bls.gov/sae/data/home.htm, has only the latest published statistics. CES-SA does not keep a separate database of first-published numbers. However, preliminary estimates for some data types for a limited level of detail can be obtained from archived news releases available here: https://www.bls.gov/bls/news-release/laus.htm, for the State Employment and Unemployment press release, and here: https://www.bls.gov/bls/news-release/metro.htm, for the Metropolitan Area Employment and Unemployment press release. Archived Employment and Earnings data are available here: https://www.bls.gov/opub/ee/archive.htm, and the monthly revision tables are available here: https://www.bls.gov/sae/tables/nonfarm-payroll-employment-revisions-between-over-the-month-estimates-by-state-not-seasonally-adjusted-january-2003-to-present.htm.
CES State and Area Employment (CES-SA) data date back to 1939 at the highest levels of aggregation. Most detailed industries only date back to 1990, and most all employee hours and earnings series start in 2006.
Additionally, discontinued SIC-based employment estimates are available from 2003 going back to 1964 and in some cases as far back as 1939 or 1919. At a detailed industry level, these series are not comparable with current CES NAICS-based series. To access these discontinued CES data, go to https://www.bls.gov/sae/data/home.htm and view Discontinued Data Series. For more information about SIC coding of industries, visit https://www.census.gov/eos/www/naics/faqs/faqs.html#q8.
Manufacturing and other goods-producing industries were the primary focus of early industry data produced by the BLS. Therefore, hours and earnings time series for these industries have a relatively long history. Data for manufacturing and its broadest industry categories begin in 1939, and for mining and construction, in 1947. Prior to 1964, however, the collection of hours and earnings data for the service-providing sector was limited to a few select industries. Given this incomplete industry coverage along with the size of the services portion of the economy, it was not possible to compute hours and earnings estimates for all of the private industries. Beginning in 1964, the collection of hours and earnings data for services was expanded to an extent sufficient to compute total private hours and earnings estimates. These estimates were first published in 1967.
Discontinued SIC-based hours and earnings estimates are available from 2003 going back to 1964 and in some cases as far back as 1947 or 1939. At a detailed industry level, these series are not comparable with current CES-SA NAICS-based series. To access these discontinued CES-SA data, go to https://www.bls.gov/sae/data/home.htm. For more information about SIC coding of industries, visit https://www.census.gov/eos/www/naics/faqs/faqs.html#q8.
CES draws its sample and sets its benchmark employment level from the business establishment list maintained by the Quarterly Census of Employment and Wages (QCEW) program. This universe for business establishments is based on Unemployment Insurance (UI) administrative records, so workers who are not covered by UI will not be captured. In agriculture there are numerous exemptions to requirements for UI coverage, making the sample frame for agriculture insufficient for calculating statistically sound estimates. In addition, a substantial number of agricultural enterprises are sole proprietorships, which are out of scope for the CES survey.
Historically, the U.S. Department of Agriculture's Census of Agriculture has been the primary survey used to measure farm labor. Census of Agriculture data are available at https://www.agcensus.usda.gov/.
Some BLS data about agricultural employment can be obtained from the QCEW (https://www.bls.gov/cew/), Current Population Survey (https://www.bls.gov/cps/), and Occupational Employment Statistics (https://www.bls.gov/oes/) programs.
CES estimates are categorized by ownership and industry. The Quarterly Census of Employment and Wages (QCEW) assigns respondents an ownership code — private or public with public ownership further divided into federal, state, or local. Respondents are then assigned a North American Industry Classification System (NAICS) code. NAICS codes group establishments into industries based on the activity in which they are primarily engaged. Establishments using similar raw material inputs, similar capital equipment, and similar labor are classified in the same industry. More information about NAICS codes in general is available at https://www.bls.gov/bls/naics.htm. More information about NAICS codes in the CES State and Area program is available at https://www.bls.gov/sae/additional-resources/details-and-documentation-on-the-conversion-to-the-2007-north-american-industry-classification-system-naics-from-2002-naics.htm.
CES survey respondents are categorized by Unemployment Insurance (UI) accounting code, location, ownership, size, and reporting unit. Each business has also been categorized into a certain industry by North American Industry Classification System (NAICS) code. Establishments are stratified by UI account number for the purpose of sample allocation and selection. The sample strata, or subpopulations, are defined by State, metropolitan statistical area, industry, and employment size, yielding a state-based design. Thirteen industries (treating manufacturing as one industry and not including government) and 8 size classes result in 104 total allocation cells per state.
In 2003, CES retired the SIC system and replaced it with the NAICS. NAICS is the product of a collaborative effort between the United States, Canada, and Mexico. A classification system shared across the three countries allows direct comparison of economic data across borders in North America.
NAICS codes are not directly comparable to SIC codes; rather NAICS is a completely redesigned way of coding industries. NAICS recognizes hundreds more types of businesses than SIC did, largely in the fast-growing service sector.
The U.S. Census Bureau issued a notice, available at https://www.census.gov/eos/www/naics/federal_register_notices/notices/fr09ap97.pdf, making NAICS effective in the U.S. in April 1997 and published the first NAICS U.S. manual in mid-1998. NAICS 2002 was the first version implemented by BLS, and the CES program converted from SIC to NAICS in June 2003. Reviews of NAICS are scheduled every five years; NAICS 2017 is the most current version.
More information about the CES conversion from SIC to NAICS 2002 is available at https://www.bls.gov/ces/naics/naics-2002.htm.
The U.S. Census Bureau reviews and updates NAICS codes every 5 years. Once these updates are available to BLS, CES converts all estimates to these revised NAICS codes. The most current version is NAICS 2017. More information about NAICS 2002, NAICS 2007, and NAICS 2012 is described and linked below.
With the release of January 2018 data on March 12, 2018, CES updated the State and Area nonfarm payroll series to the NAICS 2017 from the NAICS 2012 basis. This conversion resulted in minor revisions reflecting content and coding changes within retail trade and information sectors for CES State and Area. All CES series affected by the revisions remain in-scope; thus, total nonfarm employment is not impacted in any state or metropolitan area.
The full concordance between NAICS 2012 and NAICS 2017 codes is available through the U.S. Census Bureau at https://www.census.gov/eos/www/naics/concordances/2017_to_2012_NAICS.xlsx.
With the release of January 2012 data on March 13, 2012, CES updated the State and Area nonfarm payroll series to the NAICS 2012 from the NAICS 2007 basis. The conversion to NAICS 2012 resulted in minor content changes within the manufacturing and the retail trade sectors, as well as minor coding changes within the Utilities and the leisure and hospitality sectors. Several industry titles and descriptions also were updated. All employee (AE) series are published at a more detailed level than all employee hours and earnings, production employee, or production employee hours and earnings series, collectively called non-AE series. The non-AE series were sometimes unaffected or affected at a less-detailed level than the AE series.
The full concordance between NAICS 2007 and NAICS 2012 codes is available through the U.S. Census Bureau at https://www.census.gov/eos/www/naics/concordances/2012_to_2007_NAICS.xls.
With the release of January 2008 data on March 11, 2008, the CES State and Area nonfarm payroll series updated to the NAICS 2007 from the NAICS 2002 basis. The conversion to NAICS 2007 resulted in minor definitional changes within manufacturing, telecommunications, financial activities, and professional and technical services. Several industry titles and descriptions also were updated.
The full concordance between NAICS 2002 and NAICS 2007 codes is available through the U.S. Census Bureau at https://www.census.gov/eos/www/naics/concordances/2007_to_2002_NAICS.xls.
With the release of January 2003 data on March 20, 2003, the basis for industry classification changed from the SIC 1987 to the NAICS 2002. SIC-based data are available in the BLS discontinued database located here https://www.bls.gov/data/archived.htm.
The full concordance between SIC and NAICS 2002 codes is available through the U.S. Census Bureau at https://www.census.gov/eos/www/naics/concordances/2002_NAICS_to_1987_SIC.xls.
CES-SA data are published monthly, but are also available as historical time series. The data are available as part of a monthly news release, as a searchable database, and in text format. The table below lists the ways to download CES data from https://www.bls.gov/sae. CES-SA Employment and Earnings tables have been discontinued as of August 16, 2019, with the release of July 2019 tables. Archived editions of Employment and Earnings Online are available from April 2007 forward here: https://www.bls.gov/opub/ee/archive.htm. Earlier back issues are kept at federal depository libraries.
To join the BLS e-mail subscription service that provides excerpts from and links to the State Employment and Unemployment, Metropolitan Area Employment and Unemployment, and other BLS news releases of interest, visit the BLS News Service Subscription E-mail page, available at https://subscriptions.bls.gov/accounts/USDOLBLS/subscriber/new.
One Screen Data Search
|https://data.bls.gov/pdq/querytool.jsp?survey=sm||JAVA must be installed on your computer and pop-up blockers must be turned off. Choose each option in order of the red numbers. Time periods can be adjusted to include more than 10 years, both seasonally and not seasonally adjusted data are included, graphs can be automatically generated, and the table format can be changed.||HTML table or Excel (.xls) download|
Multi-screen Data Search
|https://data.bls.gov/cgi-bin/dsrv?sm||If you do not have JAVA, this tool will search the same database as the One Screen Data Search. Time periods can be adjusted to include more than 10 years, both seasonally and not seasonally adjusted data are included, graphs can be automatically generated, and the table format can be changed.||HTML table or Excel (.xls) download|
|https://download.bls.gov/pub/time.series/sm/||Only seasonally adjusted data are included.||Text files|
|https://beta.bls.gov/dataQuery/find?fq=survey:[sm]&q=sm||Data Finder is still in beta stages of development.||HTML table or Excel (.xlsx or .csv) download|
CES-SA maintains a list of published series by state and area available here: https://www.bls.gov/sae/additional-resources/list-of-published-state-and-metropolitan-area-series/home.htm.
The mission of the BLS is to collect, process, analyze, and disseminate essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor. In order to maintain credibility and trust with our survey respondents, confidentiality protections for our data are essential. Protecting the confidentiality of data is central to accomplishing the BLS mission.
When collecting data, the BLS makes a pledge of confidentiality to its respondents. This pledge varies depending on the context of each survey, but the standard BLS confidentiality pledge promises that data collected are used for statistical purposes only. Information about the BLS confidentiality policy and the laws that protect reporters to BLS surveys can be found here: https://www.bls.gov/bls/confidentiality.htm.
Researchers can get access to BLS microdata under certain circumstances. Information about qualifying for the program and the application process through which access may be granted can be found here: https://www.bls.gov/bls/blsresda.htm.
CES does not collect or publish government hours or earnings data. Government earnings data are available from the Quarterly Census of Employment and Wages (QCEW) program. QCEW provides annual, quarterly, and weekly wage data for various private and government industries based on Unemployment Insurance tax reports. QCEW wage information can be found at https://www.bls.gov/cew/.
The Current Employment Statistics (CES) sample is a stratified, simple random sample of worksites, clustered by Unemployment Insurance (UI) account number. The UI account number is a major identifier on the Bureau of Labor Statistics (BLS) Longitudinal Database (LDB) of employer records, which serves as both the sampling frame and the benchmark source for the CES employment estimates. The sample strata, or subpopulations, are defined by state, industry, and employment size, yielding a state-based design. The sampling rates for each stratum are determined through a method known as optimum allocation, which distributes a fixed number of sample units across a set of strata to minimize the overall variance, or sampling error, on the primary estimate of interest. The total nonfarm employment level is the primary estimate of interest, and the CES sample design gives top priority to measuring it as precisely as possible, or minimizing the statistical error around the statewide total nonfarm employment estimates.
Information about the current CES sample can be found in the CES Technical Notes available at https://www.bls.gov/web/empsit/cestn.htm.
The establishment survey, like other sample surveys, is subject to two types of error, sampling and nonsampling error. The magnitude of sampling error, or variance, is directly related to the size of the sample and the percentage of universe coverage achieved by the sample. The establishment survey sample covers over one-third of total universe employment; this yields a very small variance on the total nonfarm estimates. More information about error in the CES survey and measurements of the error associated with sample estimates are available in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm. More information about the variance and standard error in State and Area estimates is available at https://www.bls.gov/sae/additional-resources/reliability-of-state-and-area-estimates.htm.
Yes, about 40 percent of the establishment survey sample is comprised of business establishments with fewer than 20 employees. The establishment survey sample is designed to maximize the reliability of the total nonfarm employment estimates for each state; firms from all size classes and industries are appropriately sampled to achieve this goal. Sample data are weighted to represent other establishments in the same state, industry, and size class. More information about the sampling methods used for the CES survey is available at https://www.bls.gov/web/empsit/cestn.htm.
The CES government sample is not part of the probability-based survey design. CES is able to achieve a very high percent of universe employment coverage (70 percent) by obtaining full payroll employment counts for many government agencies, thus a probability-based sample design is not necessary for government. The high coverage rate virtually assures a high degree of reliability for the government employment estimates. The large government sample does not bias the total nonfarm employment estimates because it is used to estimate only the government portion of total nonfarm employment. The probability sample is used to estimate employment for all industries in the private sector. Total private and government estimates are summed to derive total nonfarm employment estimates.
More information about coverage levels of both private and government employment in the CES sample is available at https://www.bls.gov/web/empsit/cestn.htm.
Each month, BLS collects data on employment, payroll, and paid hours from a sample of establishments. To encourage participation in this voluntary survey, BLS uses a variety of collection techniques, tailored to individual firm preferences. Data collection centers perform initial enrollment of each firm via telephone, collect the data for several months via Computer Assisted Telephone Interviewing (CATI), and where possible transfer respondents to a self-reporting mode such as touch-tone data entry, fax, or web collection. Very large, multi-establishment firms' ongoing reporting is established via Electronic Data Interchange (EDI). Firms using EDI provide electronic files to BLS that include data from all their worksites.
More information about CES data collection is available at https://www.bls.gov/web/empsit/cestn.htm.
CES tracks collection rates for the CES sample on a monthly basis for each release of estimates. Collection rates are the percent of reports received for a monthly estimate compared to the total number of actively-reporting sample units on the sample registry, and are available at https://www.bls.gov/web/empsit/cesregrec.htm.
More information about registry receipts is available at https://www.bls.gov/web/empsit/cestn.htm#section6.
The Current Employment Statistics State and Area (CES-SA) program uses a matched sample concept and weighted link relative estimator to produce employment estimates. Hours and earnings estimates are produced using a weighted difference link and taper method. A matched sample is defined to be all sample members that have reported data for the reference month and the month prior. Excluded from the matched sample is any sample unit that reports that it has zero employees in the current or previous month. These reports are instead factored into a model of business births and deaths which is used to adjust monthly estimates. Further explanation of the birth/death adjustment is available below in question 14.
More information about CES-SA monthly estimation is available at https://www.bls.gov/sae/overview.htm.
Links to the equations for the calculation of CES monthly estimation of employment, hours, and earnings are listed in the table below.
|Equation Title||Equation Location|
Equation 4. All employees
Equation 5. Production and nonsupervisory employees
Equation 6. Average weekly hours
Equation 7. Average hourly earnings
CES employment is an estimate of the number of nonfarm, payroll jobs in the U.S. economy. Employment is the total number of persons on establishment payrolls employed full- or part-time who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave, on paid holiday, or who work during only part of the specified pay period. A striking employee who only works a small portion of the survey period, and is paid, would be included as employed under the CES definitions. Persons on the payroll of more than one establishment are counted in each establishment. Data exclude proprietors, self-employed, unpaid family or volunteer workers, farm workers, and domestic workers. Persons on layoff the entire pay period, on leave without pay, on strike for the entire period, or who have a pending job but have not yet reported for work are not counted as employed. Government employment covers only civilian employees; it excludes uniformed members of the armed services.
For more information about CES employment, see the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm.
The definition of employment in the Current Population Survey (the household survey) is available at https://www.bls.gov/cps/faq.htm.
CES draws the survey sample from roughly 9 million U.S. business establishments covered by the Unemployment Insurance (UI) tax system representing 97 percent of all employment within the scope of CES in the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Excluded from the CES scope, although they are included in the list of establishments covered by UI taxes, are private households and agricultural businesses.
The remaining 3 percent of establishments included in the CES scope that are not covered by UI laws include students paid by their school as part of a work study program, interns of hospitals paid by the hospital for which they work, elected officials, independent or contract insurance agents, employees of non-profits and religious organizations (this is the largest group of employees not covered), and railroad employees covered under a different system of UI administered by the Railroad Retirement Board (RRB). More information about noncovered employment and the methodology used to include this employment in the CES benchmark can be found in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm.
The CES data also exclude proprietors, the unincorporated self-employed, unpaid volunteer or family employees, farm employees, and domestic employees. Government employment covers only civilian employees; military personnel are excluded. Employees of the Central Intelligence Agency, the National Security Agency, the National Imagery and Mapping Agency, and the Defense Intelligence Agency also are excluded.
The production and nonsupervisory employee groups vary by industry. In service-providing industries, these data are collected for nonsupervisory employees — those who are not owners or who are not primarily employed to direct, supervise, or plan the work of others.
In goods-producing industries, the data are collected for production employees in mining and logging and in manufacturing, and for construction employees in construction. Production and construction employees include working supervisors or group leaders who may be "in charge" of some employees, but whose supervisory functions are only incidental to their regular work. The production employee/construction employee categories in goods-producing industries exclude employees not directly involved in production, such as managers, sales, or accounting personnel.
More information about which employees are included or not included in the definitions of all employees and production and nonsupervisory employees is available on the CES report forms at https://www.bls.gov/ces/report-forms/home.htm, or in the CES Technical Notes, available at https://www.bls.gov/web/empsit/cestn.htm#section3a.
Yes, the CES survey captures counts of all employees on the payroll, including part-time employees. However, part-time employees are not counted separately from full-time employees, so CES does not produce separate estimates of part- and full-time employment.
The Current Population Survey (CPS) does have a separate estimate of part-time employees. More information about CPS collection of full- and part-time employment is available at https://www.bls.gov/cps/lfcharacteristics.htm.
It is likely that the CES survey includes at least some undocumented immigrants. However, the establishment survey is not designed to identify the legal status of workers. Therefore, it is not possible to determine how many are counted in the survey.
The Current Population Survey (CPS), also known as the household survey, does include questions which identify the foreign and native born employees, but it does not include questions about the legal status of the foreign born employees. More information about foreign born employees in the CPS survey is available at https://www.bls.gov/cps/demographics.htm#foreignborn.
BLS is unable to quantify the impact of reservists being called to active duty in CES employment figures. In concept, persons on active military duty for the entire survey reference period are not included on employer payrolls. Some reservists hold jobs not covered by the payroll survey — such as the self-employed or those in agriculture — and others may not hold jobs at all. Any reservist who worked for or received pay from their regular employer during the survey reference period is counted on the employer's payroll. If reservists are replaced by new employees on an employer's payroll during the pay period including the 12th of the month, there is no net change in the number of jobs counted. If reservists are not replaced, a net decline in the employer's job count results. If a reservist and a replacement employee for the reservist each worked at any time during the same reference pay period, they are counted as two employees.
Government employment includes only civilian employees. Military personnel on active duty are excluded. Employees of the Central Intelligence Agency, the National Security Agency, the National Imagery and Mapping Agency, and the Defense Intelligence Agency also are excluded.
Establishments report the number of persons on payroll during the pay period that includes the 12th of the month. A person working multiple jobs at different establishments is counted once at each establishment. A person working different jobs at the same business establishment is counted once.
In order for unusually severe weather, natural disasters, government shutdowns, and other catastrophic events to reduce estimates of payroll employment, employees have to be out of work without pay for the entire reference period, which in the establishment survey is the pay period that includes the 12th of the month. About two-thirds of all employees in the payroll survey have a 2-week, semi-monthly, or monthly pay period. Employees who receive pay for any part of the pay period, even 1 hour, are counted in the payroll employment figures. The hours that employees work can be impacted by these special circumstances, but those employees might still be counted as employed by an establishment if they were paid for work done during a portion of the pay period, it is not possible to quantify the effect of a catastrophic event on estimates of employment from the establishment survey.
Catastrophic events may have an impact on CES estimates of average weekly hours even without an impact on employment. Average weekly hours are estimated for paid time during the reference pay period, including pay for holidays, sick leave, or other time off. Any event in which employees are prevented from working a normal schedule typically results in a reduction in average weekly hours. For example, some employees may be off work for part of the pay period and not receive pay for the time missed, while some workers, such as those dealing with cleanup or repair, may work extra hours.
Severe weather, natural disasters, and catastrophic events can impact the underlying assumptions that are part of the estimation process. In these instances, these assumptions are tracked to identify issues such as response rates in the affected areas that might impact their representation in the estimates, and business closures that might impact the assumptions relating to the birth/death model. If the assumptions appears to be violated, adjustments are sometimes made to the methodology to adjust sample weights in under-represented areas and/or include business closures. Model-based series may also be adjusted to rely more heavily on the sample in the areas affected by the event.
The national and sum-of-state series do not equal for several reasons, primarily due to differences in timing and in estimation procedures. The state series are produced independently from the national series a few weeks after the national estimates are produced. Therefore, the state series are produced with additional business reports that were obtained following the production of the national estimates. Additionally, many state series are produced using estimators that have been developed specifically for smaller domains; these estimators are rarely used for national series. As a result of these differences in timing and in estimation procedures, differences between the national and sum-of-state estimates do occur. Due to these limitations, BLS does not compile a "sum-of-states" employment series, and cautions users that such a series may be different from the national series.
More information about the differences in State and Area and National CES estimates is available at https://www.bls.gov/web/empsit/cestn.htm.
The Current Employment Statistics (CES) program produces earnings, but not wage data. CES average earnings are a measure of gross payrolls divided by total hours paid during the pay period that includes the 12th day of the month. Averages of hourly earnings differ from wage rates. Earnings are the return to an employee for a stated period on average in an industry; rates are the amount stipulated for a given unit of work or time in a specific job. Average hourly earnings do not represent employers total compensation costs because they exclude items such as employee benefits, irregular bonuses and commissions, retroactive payments, and the employer's share of payroll taxes. A more comprehensive explanation is available at https://www.bls.gov/opub/hom/pdf/homch2.pdf.
The Quarterly Census of Employment and Wages (QCEW) program produces wages by industry, available at https://www.bls.gov/cew/. The Occupational Employment Survey produces wages by occupation (instead of industry), available at https://www.bls.gov/oes/.
Yes, employers report total gross pay earned during the entire pay period, including overtime pay but excluding irregular payments, and the total number of hours for which employees received pay during the entire pay period including overtime. Overtime hours are published for manufacturing industries only. Respondents in manufacturing report the total number of hours for which employees received overtime premiums because they worked more than their regularly scheduled hours.
BLS recommends that CES earnings series not be used in contract escalation clauses. Instead, BLS recommends that you use the Employment Cost Index (ECI), which measures changes in labor costs free from the influence of employment shifts among industries and occupations. For help on how to use the ECI for contract adjustments, visit https://www.bls.gov/ncs/ect/escalator.htm.
The CES sample alone is not sufficient for estimating the total employment level because each month new firms generate employment that cannot be captured through the sample. There is an unavoidable lag between a firm opening for business and its appearance on the CES sample frame. The sample frame is built from Unemployment Insurance (UI) quarterly tax records. These records cover virtually all U.S. employers and include business births, but they only become available for updating the CES sampling frame 7-9 months after the reference month. After the births appear on the frame, there is also time required for sampling, contacting, and soliciting cooperation from the firm, and verifying the initial data provided. In practice, CES cannot sample and begin to collect data from new firms until they are at least a year old.
There is a parallel though somewhat different issue in capturing employment loss from business deaths through monthly sample collection. Businesses that have closed are unlikely to respond to the survey, and data collectors may not be able to ascertain until after the monthly collection period that firms have in fact gone out of business. As with business births, hard information about business deaths eventually becomes available from the lagged UI tax records.
Difficulty in capturing information from business birth and death units is not unique to the CES; virtually all current business surveys face these limitations. Unlike many surveys, CES adjusts for these limitations explicitly, using a statistical modeling technique. Because the goal of the CES program is to estimate an employment total each month and business births and deaths are important components contributing to these totals, CES uses a model-based adjustment in conjunction with the sample. Without the net birth/death model-based adjustment, the CES nonfarm payroll employment estimates would be considerably less accurate.
More information about the CES net birth/death model is available in the CES Birth/Death Frequently Asked Questions at https://www.bls.gov/web/empsit/cesbdqa.htm, or in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm#section5c. Current net birth/death contributions to the CES National employment estimates are available at https://www.bls.gov/web/empsit/cesbd.htm.
Most series published by the Current Employment Statistics (CES) program show a regularly recurring seasonal movement that can be measured from past experience. By eliminating that part of the change attributable to the normal seasonal variation, it is possible to observe the cyclical and other non-seasonal movements in these series. Seasonal adjustment is the process by which these normal seasonal patterns are removed from the estimates leaving behind only non-seasonal trends and irregular movements. Seasonally adjusted estimates of employment and other series are generated using the X-13 ARIMA SEATS program developed by the United States Census Bureau. This program adjusts estimates for fluctuations that occur on a regular basis within a year. For example, employment in retail trade rises prior to the Christmas holiday season and then falls following the holiday. This holiday change in retail trade is seasonal and is removed by seasonally adjusting the series. Seasonally adjusted series are published monthly for selected state and area employment estimates.
More information about seasonal adjustment in the CES program is available at https://www.bls.gov/web/empsit/cesseasadj.htm.
CES-SA employs a two-step process that uses the seasonal trends found in census-derived employment counts to adjust historical benchmark employment data while also incorporating sample-based seasonal trends to adjust sample-based employment estimates. By accounting for the differing seasonal patterns found in historical benchmark employment data and the sample-based employment estimates, this technique yields improved seasonally adjusted series with respect to analysis of month-to-month employment change. Seasonally adjusted employment data for the most recent 13 months can be found here: https://www.bls.gov/sae/tables/home.htm.
More information about the two-step seasonal adjustment process is available at https://www.bls.gov/osmr/research-papers/1994/pdf/st940350.pdf.
BLS published employment on a seasonally adjusted basis beginning in April 1955. Before this period, the Federal Reserve seasonally adjusted CES employment; those series are available on the St. Louis FRED website at https://fred.stlouisfed.org/categories/11.
The 4/5 week adjustment used in the Current Employment Statistics (CES) program's seasonal adjustment procedures adjusts for inconsistencies in the CES series that arise because of variations of 4 or 5 weeks between reference periods in any given pair of months. In highly seasonal months and industries, this variation can be an important determinant of the magnitude of seasonal hires or layoffs that have occurred at the time the survey is taken, thereby complicating seasonal adjustment.
The CES program first incorporated a 4/5 week adjustment with the release of May 1996 data. At that time, historical estimates were revised for the 4/5 week differences back to January 1986. Furthermore, historical data was again re-seasonally adjusted using the 4/5 week adjustment back to January 1986 when CES switched from SIC-based industry definitions to NAICS-based industry definitions in 2003.
A research paper discussing these 4 to 5 week inconsistencies in the CES estimates called Adjusting for a Calendar Effect in Employment Time Series (1996) is available at https://www.bls.gov/osmr/research-papers/1996/pdf/st960190.pdf . More information about the CES seasonal adjustment process and special model adjustments such as the 4 to 5 week calendar effect are available at https://www.bls.gov/web/empsit/cestn.htm#section6e.
With the release of January 2018 data, CES State and Area converted to concurrent seasonal adjustment which uses all available estimates, including those for the current month, in developing sample-based seasonal factors. Previously, CES State and Area forecasted the sample-based seasonal factors once annually and applied these factors to the sample estimates for the remainder of the year. Concurrent sample-based seasonal factors are created every month for the current month’s preliminary estimates as well as the previous month’s final estimates in order to incorporate the real-time estimates. CES State and Area research shows that concurrent seasonal adjustment will reduce the revisions of the seasonally adjusted estimates compared to seasonally adjusted benchmark data as well as reduce the month-to-month variability of the seasonally adjusted time series.
Concurrent sample-based seasonal factors are created every month for the current month’s preliminary estimates as well as the previous month’s final estimates in order to incorporate the real-time estimates.
Relatively small sample sizes in some estimating cells limit the reliability of employment estimates produced using the robust weighted link relative estimator. For these cases, BLS uses the CES small domain model. The small domain model (SDM) estimate can be described as a weighted average of three inputs: (1) an estimate based on available CES sample for that series, (2) an estimate based on a large CES sample from the same industry for the entire State, and (3) an Autoregressive Integrated Moving Average (ARIMA) projection based on trend from 10 years of historical data from the Quarterly Census of Employment and Wages (QCEW) program for the estimating cell.
More information about the CES SDM is available at https://www.bls.gov/web/empsit/cestn.htm#section6b. More information about the QCEW program is available at https://www.bls.gov/cew/.
To estimate employment for state super-sector cells with smaller sample size, the CES program utilizes an estimator based on the Fay-Herriot (FH) model. In the smaller cells, a direct sample-based estimate of the over-the-month change in employment often is unreliable due to the large variance, although the direct estimator is assumed to be approximately unbiased. In order to make more stable estimates, additional information is used. The model is formulated for a set of states in a given super-sector at a given month. The resulting Fay-Herriot model estimate can be presented as a weighted average of the sample-based estimate and an adjusted ARIMA forecast. A version of the Fay-Herriot model is also used to estimate many series in smaller MSAs.
CES revises published estimates to improve its data series by incorporating additional information that was not available at the time of the initial publication of the estimates. CES-SA revises its initial monthly estimates once, in the immediately succeeding month, to incorporate additional sample receipts from respondents in the survey. More information about the monthly revisions is available at https://www.bls.gov/sae/tables/nonfarm-payroll-employment-revisions-between-over-the-month-estimates-by-state-not-seasonally-adjusted-january-2003-to-present.htm.
On an annual basis, CES incorporates a benchmark revision that re-anchors estimates to nearly complete employment counts available from Quarterly Census of Employment and Wages (QCEW) data, County Business Pattern data, and other state-collected data. The benchmark helps to control for sampling error in the estimates.
It can be nearly 2 years before not seasonally adjusted CES estimates are considered final. Current Employment Statistics State and Area (CES-SA) first preliminary estimates of employment, hours, and earnings are published each month approximately 5 weeks after the reference period. Estimates are then revised once before being held constant until the annual benchmark release. Final sample-based estimates for a given month are published the month following their initial release. The annual benchmark revisions affect nearly 2 years of data, so most months are subject to revisions during 2 separate benchmark periods.
Seasonally adjusted CES estimates are generally subject to revisions for 5 years after their initial publication. Current Employment Statistics (CES) first preliminary seasonally adjusted estimates of employment, hours, and earnings are published each month approximately 5 weeks after the reference period. Estimates are then revised once before being held constant until the annual benchmark release. Final sample-based estimates are published the month after their initial release. Once a year with the benchmark release, 5 years of seasonally adjusted CES estimates are re-seasonally adjusted.
Further revisions may occur after the final estimates have been produced due to changes in scope, NAICS revisions, data errors, or other circumstances that require the reconstruction of historical CES estimates.
More information about the monthly revisions is available at https://www.bls.gov/web/empsit/cestn.htm#section7a. More information about the benchmark revisions is available at https://www.bls.gov/web/empsit/cestn.htm#section7b.
The benchmark adjustment, a standard part of the CES survey estimation process, is a once-a-year re-anchoring of the sample-based employment estimates to full population counts available principally through Unemployment Insurance (UI) tax records filed by employers with state labor market information agencies. The difference between the population counts and the sample-based employment estimates for any given month is referred to as the benchmark revision. The benchmark revision, affecting 21 months of previously published not seasonally adjusted data, is published with the January preliminary estimates in March.
More information about the CES-SA benchmarking process is available at https://www.bls.gov/web/laus/bmrk_article.htm.
The Quarterly Census of Employment and Wages (QCEW) program maintains a quarterly tabulation from administrative records of the number of employees covered by Unemployment Insurance (UI) laws, including Unemployment Compensation for Federal Employees (UCFE). UI universe counts, available on a lagged basis, contain individual employer records for approximately 9 million establishments and cover nearly 97 percent of Total nonfarm employment; these records provide most of the benchmark levels for the sample-based estimates. For the small segment of the population not covered by UI, BLS develops employment benchmarks from several alternative sources, primarily records from the Railroad Retirement Board and County Business Patterns.
More information about CES-SA benchmark revisions are available in the Benchmark Article at https://www.bls.gov/sae/publications/benchmark-article/annual-benchmark-article.htm, or in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm#section7b.
Following standard BLS methodology for State and Area estimates, the UI-based benchmark employment level replaces the sample-based employment estimate for every month beginning in April of the year prior to the benchmark year through September of the benchmark year. This 18-month span is referred to as the replacement period. For example, the benchmark revision that was released in March 2020 replaced the estimates with the benchmark level for April 2018 through September 2019. Employment benchmarks are applied to not seasonally adjusted estimates. On a seasonally-adjusted basis, 5 years of historical data may be revised, because new models for seasonal adjustment are selected and seasonal factors based on the new models are updated with each year's benchmark release.
More information about CES-SA benchmarking is available in the Benchmark Article at https://www.bls.gov/sae/publications/benchmark-article/annual-benchmark-article.htm or in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm#section7b.
Estimates for October through December of the benchmark year, called the re-estimation period, are calculated for each month by applying the standard estimation methodology to the revised benchmark levels (i.e. the over-the-month sample change ratio plus birth death model values for October is applied to the September benchmark level to calculate the new level for October, which is then used in the calculation for November, and so on until December). For example, the benchmark revision that was released in March 2020 replaced the estimates with the re-estimated level for October through December 2019 and set the anchor employment level for January 2020.
With re-estimation, new sample that has been collected is introduced starting with October re-estimates. Other re-estimation updates include new net birth/death model estimates, changes in estimation methods and publication structures.
More information about CES-SA benchmarking is available in the Benchmark Article at https://www.bls.gov/sae/publications/benchmark-article/annual-benchmark-article.htm or in the CES Technical Notes at https://www.bls.gov/web/empsit/cestn.htm#section7b.
To begin reporting your CES data or if you have any questions while reporting, please contact the CES Help Desk or call 1-800-827-2005. If available, please include your CES report number(s) in your request or have them available when you call.
More information for CES respondents is available at https://www.bls.gov/respondents/ces/home.htm.
Each month the CES program surveys about 145,000 businesses and government agencies, representing approximately 697,000 worksites, in order to provide detailed industry data on employment, hours, and earnings of employees on nonfarm payrolls. Input to this survey is greatly appreciated.
In most States the CES survey is voluntary. However, it is required by state law in North Carolina, South Carolina, and Oregon. Information about these requirements, including documentation of the applicable legal code, is available on the first page of the report forms. Electronic copies of the report forms for each industry are available at https://www.bls.gov/ces/report-forms/home.htm.
More information for CES respondents is available at https://www.bls.gov/respondents/ces/home.htm.
Last Modified Date: May 8, 2020