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 OES features several arts-related occupations, particularly in the Arts, Design, Entertainment, Sports, and Media Occupations group (Standard Occupational Classification (SOC) code 27-0000). Several featured occupation groups include the following: Art and Design Workers (SOC 27-1000) Art Directors Fine Artists, including Painters, Sculptors, and Illustrators Multimedia Artists and Animators Fashion Designers Graphic Designers Set and Exhibit Designers Entertainers and Performers, Sports and Related Workers (SOC 27-2000) Actors Producers and Directors Athletes Coaches and Scouts Dancers Choreographers Music Directors and Composers Musicians and Singers Media and Communication Workers (SOC 27-3000) Radio and Television Announcers Reports and Correspondents Public Relations Specialists Writers and Authors Data for years 1997 through the latest release and can be found on the OES Data page. Also, see OES News Releases sections for current estimates and news releases. Users can analyze the data for the nation as a whole, by state, by metropolitan or nonmetropolitan area, and by industry or ownership. As well, OES Charts are available. Users may also explore data using OES Maps. If preferred, data can also be accessed via the Multi-Screen Data Search or Text Files using the OES Databases page.

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:

• Total civilian labor force,
• Total number of people employed,
• Total number of people unemployed, and
• Unemployment rate

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.

Monthly statistics regarding the labor force, employment and unemployment in Mesa and nearby municipalities. Unemployment rate sourced at BLS.gov Data Viewer. Employment Data - Bureau of Labor Statistics - http://www.bls.gov/data/ Local Area Unemployment Statistics (LAUS) - https://www.bls.gov/lau/ (See for next data release dates). To see how these terms are defined and what they include, please visit the Terms Glossary from the United State Department of Labor’s Bureau of Labor Statistics (BLS), which can be found at the following web address: http://www.bls.gov/bls/glossary.htm

The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In June 2025, the national unemployment rate was at 4.1 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends.

Historical information on the Employment Dataset shows several current and historical annual statistics regarding population, the labor force, employment and unemployment in the City of Mesa. Monthly labor force, employment and unemployment information is at https://citydata.mesaaz.gov/External-Data/Employment-and-Labor-Force-Monthly/3vbg-xf63.

Sources: Population Data - United States Census Bureau -https://www.census.gov/topics/population/data.html Employment Data - Bureau of Labor Statistics - http://www.bls.gov/data/ Local Area Unemployment Statistics (LAUS) - https://www.bls.gov/lau/ To see how these terms are defined and what they include, please visit the Terms Glossary from the United State Department of Labor’s Bureau of Labor Statistics (BLS), which can be found at the following web address: http://www.bls.gov/bls/glossary.htm

The Quarterly Census of Employment and Wages (QCEW) program is a cooperative program involving the Bureau of Labor Statistics (BLS) of the United States Department of Labor and the State Employment Security Agencies (SESAs). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by State unemployment insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Publicly available data files include information on the number of establishments, monthly employment, and quarterly wages, by NAICS industry, by county, by ownership sector, for the entire United States. These data are aggregated to annual levels, to higher industry levels (NAICS industry groups, sectors, and supersectors), and to higher geographic levels (national, State, and Metropolitan Statistical Area (MSA)). To download and analyze QCEW data, users can begin on the QCEW Databases page. Downloadable data are available in formats such as text and CSV. Data for the QCEW program that are classified using the North American Industry Classification System (NAICS) are available from 1990 forward, and on a more limited basis from 1975 to 1989. These data provide employment and wage information for arts-related NAICS industries, such as: Arts, entertainment, and recreation (NAICS Code 71) Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation Professional, scientific, and technical services (NAICS Code 54) Architectural services Graphic design services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, book and music stores Book, periodical, and music stores Art dealers For years 1975-2000, data for the QCEW program provide employment and wage information for arts-related industries are based on the Standard Industrial Classification (SIC) system. These arts-related SIC industries include the following: Book stores (SIC 5942) Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums, Botanical, Zoological Gardens (SIC Code 84) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Services (SIC Code 78) The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit NAICS industry at the national, state, and county levels. At the national level, the QCEW program provides employment and wage data for almost every NAICS industry. At the State and area level, the QCEW program provides employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. Employment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers covered by the railroad unemployment insurance system. Wages represent total compensation paid during the calendar quarter, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). The QCEW program does provide partial information on agricultural industries and employees in private households. Data from the QCEW program serve as an important source for many BLS programs. The QCEW data are used as the benchmark source for employment by the Current Employment Statistics program and the Occupational Employment Statistics program. The UI administrative records collected under the QCEW program serve as a sampling frame for BLS establishment surveys. In addition, data from the QCEW program serve as a source to other Federal and State programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses QCEW data as the base for developing the wage and salary component of personal income. The Employment and Training Administration (ETA) of the Department of Labor and the SESAs use QCEW data to administer the employment security program. The QCEW data accurately reflect the ex

2004 to 2021 Virginia Employment Status of the Civilian Non-Institutional Population by Sex, by Race, Hispanic or Latino ethnicity, and detailed by Age, by Year. Annual averages, numbers in thousands.

U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, Expanded State Employment Status Demographic Data Data accessed from the Bureau of Labor Statistics website (https://www.bls.gov/lau/ex14tables.htm)

Statewide data on the demographic and economic characteristics of the labor force are published on an annual-average basis from the Current Population Survey (CPS), the sample survey of households used to calculate the U.S. unemployment rate (https://www.bls.gov/cps/home.htm). For each state and the District of Columbia, employment status data are tabulated for 67 sex, race, Hispanic or Latino ethnicity, marital status, and detailed age categories and evaluated against a minimum base, calculated to reflect an expected maximum coefficient of variation (CV) of 50 percent, to determine reliability for publication.

The CPS sample was redesigned in 2014–15 to reflect the distribution of the population as of the 2010 Census. At the same time, BLS developed improved techniques for calculating minimum bases. These changes resulted in generally higher minimum bases of unemployment, leading to the publication of fewer state-demographic groups beginning in 2015. The most notable impact was on the detailed age categories, particularly the teenage and age 65 and older groups. In an effort to extend coverage, BLS introduced a version of the expanded state employment status demographic table with intermediate age categories, collapsing the seven categories historically included down to three. Ages 16–19 and 20–24 were combined into a 16–24 year-old category, ages 25–34, 35–44, and 45–54 were combined into a 25–54 year-old category, and ages 55–64 and 65 and older were combined into a 55-years-and-older category. These intermediate age data are tabulated for the total population, as well as the four race and ethnicity groups, and then are evaluated against the unemployment minimum bases. The more detailed age categories continue to be available in the main version of the expanded table, where the minimum base was met.

Additional information on the uses and limitations of statewide data from the CPS can be found in the document Notes on Using Current Population Survey (https://www.bls.gov/lau/notescps.htm) Subnational Data and in Appendix B of the bulletin Geographic Profile of Employment and Unemployment (https://www.bls.gov/opub/geographic-profile/home.htm).

Unemployment Rate in the United States increased to 4.20 percent in July from 4.10 percent in June of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Context

U.S. Unemployment rate historical data, downloaded from U.S. Bureau of Labor Statistics website.

Content

Data starts from 01-Jan-1948 and is available at monthly level.

In June 2025, about 62.3 percent of the United States civilian labor force participated in the job market. Civilian labor force is a term used by the U.S. Bureau of Labor Statistics (BLS) to describe the subset of Americans who have jobs or are seeking a job, are at least 16 years old, are not serving in the military and are not institutionalized. In other words, all Americans who are eligible to work in the everyday U.S. economy.

Graph and download economic data for Labor Force Participation Rate - Women (LNS11300002) from Jan 1948 to Jul 2025 about participation, females, 16 years +, labor force, labor, household survey, rate, and USA.

The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE tables are an easy-to-use tool for obtaining arts-related spending estimates. They feature several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2023 and include: 1) Detailed tables with the most granular level of expenditure data available, along with variances and percent reporting for each expenditure item, for all consumer units (listed as "Other" in the Download menu); and 2) Tables with calendar year aggregate shares by demographic characteristics that provide annual aggregate expenditures and shares across demographic groups (listed as "Excel" in the Download menu). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 1980 through 2023 CE public-use microdata, including Interview Survey data, Diary Survey data, and paradata (information about the data collection process), are available on the CE website.

Code files used for Putting the Paycheck Protection Program into Perspective: An Analysis Using Administrative and Survey Data PPP data can be found on SBA website All other microdata requires access through bureau of labor statistics program https://www.bls.gov/rda/home.htm

This map shows the most current unemployment figures in the USA by states and counties. This is seen in two ways:The darkest red areas in the map have the highest unemployment rate (% of labor force)The LARGEST SYMBOLS have the highest count of unemployed peopleThe color pattern is reinforced behind the centroid layer in order to show the pattern by the boundaries. The figures shown are the most recent monthly figures provided by the Bureau of Labor Statistics (BLS), and the data updates behind the scenes automatically each month.The map uses the Bureau of Labor Statistics Monthly Unemployment layer from ArcGIS Living Atlas of the World. To find other web maps that show how unemployment looks in the US right now, check out the collection of maps created from this layer.

analyze the consumer expenditure survey (ce) with r the consumer expenditure survey (ce) is the primo data source to understand how americans spend money. participating households keep a running diary about every little purchase over the year. those diaries are then summed up into precise expenditure categories. how else are you gonna know that the average american household spent $34 (±2) on bacon, $826 (±17) on cellular phones, and $13 (±2) on digital e-readers in 2011? an integral component of the market basket calculation in the consumer price index, this survey recently became available as public-use microdata and they're slowly releasing historical files back to 1996. hooray! for a t aste of what's possible with ce data, look at the quick tables listed on their main page - these tables contain approximately a bazillion different expenditure categories broken down by demographic groups. guess what? i just learned that americans living in households with $5,000 to $9,999 of annual income spent an average of $283 (±90) on pets, toys, hobbies, and playground equipment (pdf page 3). you can often get close to your statistic of interest from these web tables. but say you wanted to look at domestic pet expenditure among only households with children between 12 and 17 years old. another one of the thirteen web tables - the consumer unit composition table - shows a few different breakouts of households with kids, but none matching that exact population of interest. the bureau of labor statistics (bls) (the survey's designers) and the census bureau (the survey's administrators) have provided plenty of the major statistics and breakouts for you, but they're not psychic. if you want to comb through this data for specific expenditure categories broken out by a you-defined segment of the united states' population, then let a little r into your life. fun starts now. fair warning: only analyze t he consumer expenditure survey if you are nerd to the core. the microdata ship with two different survey types (interview and diary), each containing five or six quarterly table formats that need to be stacked, merged, and manipulated prior to a methodologically-correct analysis. the scripts in this repository contain examples to prepare 'em all, just be advised that magnificent data like this will never be no-assembly-required. the folks at bls have posted an excellent summary of what's av ailable - read it before anything else. after that, read the getting started guide. don't skim. a few of the descriptions below refer to sas programs provided by the bureau of labor statistics. you'll find these in the C:\My Directory\CES\2011\docs directory after you run the download program. this new github repository contains three scripts: 2010-2011 - download all microdata.R lo op through every year and download every file hosted on the bls's ce ftp site import each of the comma-separated value files into r with read.csv depending on user-settings, save each table as an r data file (.rda) or stat a-readable file (.dta) 2011 fmly intrvw - analysis examples.R load the r data files (.rda) necessary to create the 'fmly' table shown in the ce macros program documentation.doc file construct that 'fmly' table, using five quarters of interviews (q1 2011 thru q1 2012) initiate a replicate-weighted survey design object perform some lovely li'l analysis examples replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using unimputed variables replicate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t -tests using unimputed variables create an rsqlite database (to minimize ram usage) containing the five imputed variable files, after identifying which variables were imputed based on pdf page 3 of the user's guide to income imputation initiate a replicate-weighted, database-backed, multiply-imputed survey design object perform a few additional analyses that highlight the modified syntax required for multiply-imputed survey designs replicate the %mean_variance() macro found in "ce macros.sas" and provide some examples of calculating descriptive statistics using imputed variables repl icate the %compare_groups() macro found in "ce macros.sas" and provide some examples of performing t-tests using imputed variables replicate the %proc_reg() and %proc_logistic() macros found in "ce macros.sas" and provide some examples of regressions and logistic regressions using both unimputed and imputed variables replicate integrated mean and se.R match each step in the bls-provided sas program "integr ated mean and se.sas" but with r instead of sas create an rsqlite database when the expenditure table gets too large for older computers to handle in ram export a table "2011 integrated mean and se.csv" that exactly matches the contents of the sas-produced "2011 integrated mean and se.lst" text file click here to view these three scripts for...

Description

From website:

The Statistical Abstract of the United States, published since 1878, is the authoritative and comprehensive summary of statistics on the social, political, and economic organization of the United States.

Use the Abstract as a convenient volume for statistical reference, and as a guide to sources of more information both in print and on the Web

Sources of data include the Census Bureau, Bureau of Labor Statistics, Bureau of Economic Analysis, and many other Federal agencies and private organizations

Sections include:

• Accommodation, Food, & Other Services
• Agriculture
• Arts, Recreation, & Travel
• Banking, Finance, & Insurance
• Births, Deaths, Marriages, & Divorces
• Business Enterprise
• Construction & Housing
• Education
• Elections
• Energy & Utilities
• Federal Gov’t Finances & Employment
• Foreign Commerce & Aid
• Geography & Environment
• Health & Nutrition
• Income, Expenditures, Poverty, & Wealth
• Information & Communications
• International Statistics
• Labor Force, Employment, & Earnings
• Law Enforcement, Courts, & Prisons
• Manufactures
• National Security & Veterans Affairs
• Natural Resources
• Population
• Prices
• Puerto Rico & the Island Areas
• Science & Technology
• Social Insurance & Human Services
• State & Local Gov’t Finances & Employment
• Transportation
• Wholesale & Retail Trade

Openness: OPEN

• License: US government so public domain.
• Access: ok. Most data provided as xls or pdf but no bulk.
  • www: yes. Browse and then get individual items as xls or pdf. Note one can get some of this information in more convenient form from http://www.usgovernmentspending.com/ (download series page).
  • bulk: no.

United States Employment: NF: sa: IF: WS: Web Search Portals & Others data was reported at 153.700 Person th in Mar 2025. This records a decrease from the previous number of 153.900 Person th for Feb 2025. United States Employment: NF: sa: IF: WS: Web Search Portals & Others data is updated monthly, averaging 57.800 Person th from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 162.700 Person th in Dec 2022 and a record low of 24.600 Person th in Jan 1990. United States Employment: NF: sa: IF: WS: Web Search Portals & Others data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G060: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

Employment: NF: sa: PW: PB: Waste Collection data was reported at 157.700 Person th in Sep 2018. This records an increase from the previous number of 157.500 Person th for Aug 2018. Employment: NF: sa: PW: PB: Waste Collection data is updated monthly, averaging 102.600 Person th from Jan 1990 (Median) to Sep 2018, with 345 observations. The data reached an all-time high of 157.700 Person th in Sep 2018 and a record low of 69.600 Person th in Jan 1992. Employment: NF: sa: PW: PB: Waste Collection data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G031: Current Employment Statistics Survey: Employment: Production Worker: Non FarmSeasonally Adjusted.

The historical Prevailing Wage public disclosure data available on the Office of Foreign Labor Certification (OFLC) web page in the Performance Data section. This dataset includes data collected from Prevailing Wage applications during previous fiscal years. It includes information on employers, geography, job details, etc. for participants in the Prevailing Wage program. Historical Prevailing Wage public disclosure data is available on the OFLC website in the Performance Data section. Data is available as Excel files in aggregate form for previous fiscal years at https://www.dol.gov/agencies/eta/foreign-labor/performance.

Employment: NF: sa: PW: PB: Landscape Architectural Services data was reported at 25.900 Person th in May 2018. This stayed constant from the previous number of 25.900 Person th for Apr 2018. Employment: NF: sa: PW: PB: Landscape Architectural Services data is updated monthly, averaging 25.600 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 40.200 Person th in Dec 2006 and a record low of 17.700 Person th in Feb 1992. Employment: NF: sa: PW: PB: Landscape Architectural Services data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G031: Current Employment Statistics Survey: Employment: Production Worker: Non FarmSeasonally Adjusted.