The Job Openings and Labor Turnover Survey (JOLTS) program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations. Unadjusted counts and rates of all data elements are published by supersector and select sector based on the North American Industry Classification System (NAICS). The number of unfilled jobs—used to calculate the job openings rate—is an important measure of the unmet demand for labor. With that statistic, it is possible to paint a more complete picture of the U.S. labor market than by looking solely at the unemployment rate, a measure of the excess supply of labor. Information on labor turnover is valuable in the proper analysis and interpretation of labor market developments and as a complement to the unemployment rate. For more information and data visit: https://www.bls.gov/jlt/
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The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible.
The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series.
The OEWS estimates are published annually.
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The Occupational Employment Statistics (OES) program conducts a semiannual survey designed to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates for the nation as a whole, by state, by metropolitan or nonmetropolitan area, and by industry or ownership. The Bureau of Labor Statistics produces occupational employment and wage estimates for approximately 415 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and selected 5- and 6-digit North American Industry Classification System (NAICS) industrial groups. The OES program surveys approximately 200,000 establishments per panel (every six months), taking three years to fully collect the sample of 1.2 million establishments. To reduce respondent burden, the collection is on a three-year survey cycle that ensures that establishments are surveyed at most once every three years. The estimates for occupations in nonfarm establishments are based on OES data collected for the reference months of May and November. The OES survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OES survey make these estimates possible.
The American Time Use Survey (ATUS) is an annual survey which provides nationally representative estimates of how, where, and with whom Americans aged 15 years old and up spend their time. The data includes information collected from nearly 245,000 interviews conducted from 2003 to 2023. It is the only federal survey providing data on the full range of nonmarket activities, from childcare to volunteering. ATUS data can be used in economic research, health and safety indicators, measures of family and work-life balance, and international comparisons. ATUS data files can be linked to the Current Population Survey.
The Occupational Employment and Wage Statistics (OES) program conducts a semi-annual survey to produce estimates of employment and wages for specific occupations. The OES program collects data on wage and salary workers in nonfarm establishments in order to produce employment and wage estimates for about 800 occupations. Data from self-employed persons are not collected and are not included in the estimates. The OES program produces these occupational estimates by geographic area and by industry. Estimates based on geographic areas are available at the National, State, Metropolitan, and Nonmetropolitan Area levels. The Bureau of Labor Statistics produces occupational employment and wage estimates for over 450 industry classifications at the national level. The industry classifications correspond to the sector, 3-, 4-, and 5-digit North American Industry Classification System (NAICS) industrial groups. More information and details about the data provided can be found at http://www.bls.gov/oes
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The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States.
CES data reflect the number of nonfarm, payroll jobs. It includes 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 or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services.
The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.
1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.
Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.
U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)
Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)
Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.
These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.
To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.
Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.
For each area, the following measures are presented by place of residence:
Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.
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The Occupational Employment Statistics (OES) and National Compensation Survey (NCS) programs have produced estimates by borrowing from the strength and breadth of each survey to provide more details on occupational wages than either program provides individually. Modeled wage estimates provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation.
Direct estimates are based on survey responses only from the particular geographic area to which the estimate refers. In contrast, modeled wage estimates use survey responses from larger areas to fill in information for smaller areas where the sample size is not sufficient to produce direct estimates. Modeled wage estimates require the assumption that the patterns to responses in the larger area hold in the smaller area.
The sample size for the NCS is not large enough to produce direct estimates by area, occupation, and job characteristic for all of the areas for which the OES publishes estimates by area and occupation. The NCS sample consists of 6 private industry panels with approximately 3,300 establishments sampled per panel, and 1,600 sampled state and local government units. The OES full six-panel sample consists of nearly 1.2 million establishments.
The sample establishments are classified in industry categories based on the North American Industry Classification System (NAICS). Within an establishment, specific job categories are selected to represent broader occupational definitions. Jobs are classified according to the Standard Occupational Classification (SOC) system.
Summary: Average hourly wage estimates for civilian workers in occupations by job characteristic and work levels. These data are available at the national, state, metropolitan, and nonmetropolitan area levels.
Frequency of Observations: Data are available on an annual basis, typically in May.
Data Characteristics: All hourly wages are published to the nearest cent.
This dataset was taken directly from the Bureau of Labor Statistics and converted to CSV format.
This dataset contains the estimated wages of civilian workers in the United States. Wage changes in certain industries may be indicators for growth or decline. Which industries have had the greatest increases in wages? Combine this dataset with the Bureau of Labor Statistics Consumer Price Index dataset and find out what kinds of jobs you would need to afford your snacks and instant coffee!
This file provides data for October 1981 drawn from the 1977 Census of Governments on full- and part-time employment, full-time equivalent employment, and payroll statistics by type of government (State, county, township, special district, and school district) and by function (local schools, police protection, higher education, fire protection, financial administration, general, control, highways, public welfare, sanitation other than sewerage, parks and recreation, health, hospitals, water supply, electric power, gas supply, transit systems, natural resources, corrections, libraries, airports, water transportation, other education, State liquor stores, Employment Security Administration, and housing and urban renewal). Also shown are data on policies for labor-management relations, number of organized employees by function, number of bargaining units, number of employees in bargaining units, number of contractual agreements, and number of employees covered by contractual agreements. State and local data are provided, including for the 75 largest Standard Metropolitan Statistical Areas (SMSAs) and their constituent county areas, plus 69 other large county areas outside of the 75 SMSAs.
Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08134.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.
VITAL SIGNS INDICATOR Jobs by Industry (EC1)
FULL MEASURE NAME Employment by place of work by industry sector
LAST UPDATED July 2019
DESCRIPTION Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.
DATA SOURCE Bureau of Labor Statistics: Current Employment Statistics 1990-2017 http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment by place of work and by industry. Industries are classified by their North American Industry Classification System (NAICS) code. Vital Signs aggregates employment into 11 industry sectors: Farm, Mining, Logging and Construction, Manufacturing, Trade, Transportation and Utilities, Information, Financial Activities, Professional and Business Services, Educational and Health Services, Leisure and Hospitality, Government, and Other. EDD counts all public-sector jobs under Government, including public transportation, public schools, and public hospitals. The Other category includes service jobs such as auto repair and hair salons and organizations such as churches and social advocacy groups. Employment in the technology sector are classified under three categories: Professional and Business Services, Information, and Manufacturing. The latter category includes electronic and computer manufacturing. For further details of typical firms found in each sector, refer to the 2012 NAICS Manual (http://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2012).
The Bureau of Labor Statistics (BLS) provides industry estimates for non-Bay Area metro areas. Their main industry employment estimates, the Current Employment Survey and Quarterly Census of Employment and Wages, do not provide annual estimates of farm employment. To be consistent, the metro comparison evaluates nonfarm employment for all metro areas, including the Bay Area. Industry shares are thus slightly different for the Bay Area between the historical trend and metro comparison sections.
The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of the nation’s employment in that same sector. Because BLS does not provide national farm estimates, note that there is no LQ for regional farm employment. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.
This dataset contains annual average CES data for California statewide and areas from 1990 to 2023. The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States. CES data reflect the number of nonfarm, payroll jobs. It includes 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 or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.
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This dataset from the Bureau of Labor Statistics provides monthly estimates regarding total employment and unemployment, which together comprise the labor force. Our data extract lists all data published for North Carolina’s counties from January 2019 to the present. This dataset is a comprehensive nationwide representation using estimates derived from the national Current Population Survey (CPS) and American Community Survey 5-year estimates. No disaggregations by demographic or worker characteristics are included in the labor force estimate. Time series reports for each variable (employment, unemployment, and labor force) are available for each geography (county) using the BLS multi-screen data tool. Preliminary estimates are released within 30 days of each month and finalized within another 30 days, resulting in a 2-month data lag. The data is available from BLS for a variety of geographic areas, including states, MSAs, counties, cities and towns, and other census regions.
The marital and family labor force statistics (FM) database from the Current Population Survey reflects data published each year in the news release, Employment Characteristics of Families. At the present time, only data for persons are available in the FM database. Person data include employment status by marital status and presence and age of own children. For example, the FM database includes the labor force participation rate of mothers with children under age 6 (series FMUP1378865).
Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.
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The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week. The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files. The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. "Processing Files" of the Diary Survey Users' Guide. A second documentation guide, the "Users' Guide to Income Imputation," includes information on how to appropriately use the imputed income data. Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over. The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.
Standard labor force activity data for the week prior to the survey are provided in this data collection. Comprehensive data are supplied on the employment status, occupation, and industry of persons 15 years old and over. Also presented are personal characteristics such as age, sex, race, marital status, veteran status, household relationship, educational background, and Spanish origin. Supplemental data pertaining to work schedules include items on the usual number of hours worked daily and weekly, usual number of days and specific days worked weekly, starting and ending times of an individual's work day, and whether these starting and ending times could be varied. For deviations from regular work schedules, the main reason and length of time a particular schedule or shift was worked is elicited. Questions dealing with overtime include number of extra hours worked and rate of pay. For dual jobholders, data are provided on starting and ending times of the work day, number of weekly hours worked, earnings, occupation, industry, and main reason for working more than one job. Questions are included about primary job-related activities completed at home and about temporary work. Data on volunteer work are also provided. (Source: downloaded from ICPSR 7/13/10)
Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09809.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.
The American Time Use Survey (ATUS) is the Nation’s first federally administered, continuous survey on time use in the United States. The goal of the survey is to measure how people divide their time among life’s activities.
In ATUS, individuals are randomly selected from a subset of households that have completed their eighth and final month of interviews for the Current Population Survey (CPS). ATUS respondents are interviewed only one time about how they spent their time on the previous day, where they were, and whom they were with. The survey is sponsored by the Bureau of Labor Statistics and is conducted by the U.S. Census Bureau.
The major purpose of ATUS is to develop nationally representative estimates of how people spend their time. Many ATUS users are interested in the amount of time Americans spend doing unpaid, nonmarket work, which could include unpaid childcare, eldercare, housework, and volunteering. The survey also provides information on the amount of time people spend in many other activities, such as religious activities, socializing, exercising, and relaxing. In addition to collecting data about what people did on the day before the interview, ATUS collects information about where and with whom each activity occurred, and whether the activities were done for one’s job or business. Demographic information—including sex, race, age, educational attainment, occupation, income, marital status, and the presence of children in the household—also is available for each respondent. Although some of these variables are updated during the ATUS interview, most of this information comes from earlier CPS interviews, as the ATUS sample is drawn from a subset of households that have completed month 8 of the CPS.
The user guide can be found here.
There are 8 datasets containing microdata from 2003-2015:
Respondent file: The Respondent file contains information about ATUS respondents, including their labor force status and earnings.
Roster file: The Roster file contains information about household members and nonhousehold children (under 18) of ATUS respondents. It includes information such as age and sex.
Activity file: The Activity file contains information about how ATUS respondents spent their diary day. It includes information such as activity codes, activity start and stop times, and locations. Because Activity codes have changed somewhat between 2003 and 2015, this file uses activity codes that appear in the 2003-2015 ATUS Coding Lexicon (PDF).
Activity summary file: The Activity summary file contains information about the total time each ATUS respondent spent doing each activity on the diary day. Because Activity codes have changed somewhat between 2003 and 2015, this file uses activity codes that appear in the 2003-2015 ATUS Coding Lexicon (PDF).
Who file: The Who file includes codes that indicate who was present during each activity.
CPS 2003-2015 file: The ATUS-CPS file contains information about each household member of all individuals selected to participate in ATUS. The information on the ATUS-CPS file was collected 2 to 5 months before the ATUS interview.
Eldercare Roster file: The ATUS Eldercare Roster file contains information about people for whom the respondent provided care. Eldercare data have been collected since 2011.
Replicate weights file: The Replicate weights file contains miscellaneous ATUS weights.
The ATUS interview data dictionary can be found here.
The ATUS Current Population Survey (CPS) data dictionary can be found here.
The ATUS occupation and industry codes can be found here.
The ATUS activity lexicon can be found here.
The original datasets can be found here.
How do daily activities differ by:
labor force status
income
household composition
geographical region
disability status
To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, and migration from the March Annual Demographic Supplement and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.
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The Current Population Survey (CPS) is a monthly survey of households conducted by the Bureau of Census for the Bureau of Labor Statistics. It provides a comprehensive body of data on the labor force, employment, unemployment, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics.
More information and details about the data provided can be found at http://www.bls.gov/cps
The Job Openings and Labor Turnover Survey (JOLTS) program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations. Unadjusted counts and rates of all data elements are published by supersector and select sector based on the North American Industry Classification System (NAICS). The number of unfilled jobs—used to calculate the job openings rate—is an important measure of the unmet demand for labor. With that statistic, it is possible to paint a more complete picture of the U.S. labor market than by looking solely at the unemployment rate, a measure of the excess supply of labor. Information on labor turnover is valuable in the proper analysis and interpretation of labor market developments and as a complement to the unemployment rate. For more information and data visit: https://www.bls.gov/jlt/