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.

The Occupational Employment and Wage Statistics (OEWS) program produces employment and wage estimates annually for approximately 830 occupations. These estimates are available for the nation as a whole, for individual states, and for metropolitan and nonmetropolitan areas; national occupational estimates for specific industries are also available.This resource contains OEWS estimates, including:National (XLSX): 1997-2024State (XLSX): 1997-2024Metropolitan and nonmetropolitan area (XLSX): 1997-2024National industry-specific and by ownership (XLSX): 1997-2024All data: 2011-2024Agricultural data supplement: 2011 onlyEstimates: 1988-1995 (HTML)Also see additional folders for:Research estimates: 2012-2023Featured tables (tables and charts): 2019-2024Additional tables: Various, 2011-2024Note that at present, this scrape does NOT include occupational profiles. This is due to issues scraping the most recent (2024) profiles from the web application. Will update with more clarification on whether we can indeed scrape these profiles, if we'll limit to 2023-and-earlier profiles, add to a separate project, etc.

Asian households measured the highest median household income among racial and ethnic groups in the United States. In 2024, Asian household incomes reached a median of 121,700 U.S. dollars. On the other hand, Black households had the lowest median income of 56,020 U.S. dollars. Overall, median household incomes in the United States stood at 83,730 U.S. dollars that year.Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, African American, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. nearing nine percent unemployed, according to the Bureau of Labor Statistics in 2024. Hispanic individuals (of any race) were most likely to go without health insurance as of 2024.

Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over (LES1252881600Q) from Q1 1979 to Q2 2025 about full-time, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

The Quarterly Census of Employment and Wages (QCEW) program (also known as ES-202) collects employment and wage data from employers covered by New York State's Unemployment Insurance (UI) Law. This program is a cooperative program with the U.S. Bureau of Labor Statistics. QCEW data encompass approximately 97 percent of New York's nonfarm employment, providing a virtual census of employees and their wages as well as the most complete universe of employment and wage data, by industry, at the State, regional and county levels. "Covered" employment refers broadly to both private-sector employees as well as state, county, and municipal government employees insured under the New York State Unemployment Insurance (UI) Act. Federal employees are insured under separate laws, but are considered covered for the purposes of the program. Employee categories not covered by UI include some agricultural workers, railroad workers, private household workers, student workers, the self-employed, and unpaid family workers. QCEW data are similar to monthly Current Employment Statistics (CES) data in that they reflect jobs by place of work; therefore, if a person holds two jobs, he or she is counted twice. However, since the QCEW program, by definition, only measures employment covered by unemployment insurance laws, its totals will not be the same as CES employment totals due to the employee categories excluded by UI.

Context

In May 2020, the United States suffered one of the largest single-month job losses in its history as state and local government imposed public policy measures to slow the spread of the COVID-19 virus which, in many cases, forced businesses to close or significantly curtail business activity. But not all counties experienced job losses compared to the prior year. Instead, some supported job gains. Can location quotients, which measure the importance of jobs in specific industries, be efficient predictors of job losses? Are there certain businesses, or groups of businesses, that had an effect on job gains/losses?

Content

The file data.csv contains Quarterly Census of Employment and Wage data published by the U.S. Bureau of Labor Statistics (https://www.bls.gov/cew/). The data is combined data from 2019 and May 2020, for each county, or county-equivalent, in the U.S.

area_fips: FIPS codes for U.S. county and county-equivalent entities area_title: Name of county may2020_empl_yy_pc: Year-over-year percent change in county total employment in May 2020 may2020_empl: Count of total employment in May 2020 naics_1111 to naics_9999: Employment concentration/location quotient for each 4-digit NAICS sectors. A location quotient less than 1.0 indicates that the count's share of sector employment to total employment is lower than the same ratio in the U.S overall, while a location quotient greater than 1.0 means that the county's share of sector employment to total employment is higher than the U.S. ratio. A description of the NAICS 4-digit numeric codes can be found at https://www.bls.gov/cew/classifications/industry/industry-titles.htm.

Graph and download economic data for Quits: Total Nonfarm (JTSQUR) from Dec 2000 to Aug 2025 about quits, nonfarm, and USA.

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August 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.

The Quarterly Census of Employment and Wages (QCEW) program (also known as ES-202) collects employment and wage data from employers covered by New York State's Unemployment Insurance (UI) Law. This program is a cooperative program with the U.S. Bureau of Labor Statistics. QCEW data encompass approximately 97 percent of New York's nonfarm employment, providing a virtual census of employees and their wages as well as the most complete universe of employment and wage data, by industry, at the State, regional and county levels. "Covered" employment refers broadly to both private-sector employees as well as state, county, and municipal government employees insured under the New York State Unemployment Insurance (UI) Act. Federal employees are insured under separate laws, but are considered covered for the purposes of the program. Employee categories not covered by UI include some agricultural workers, railroad workers, private household workers, student workers, the self-employed, and unpaid family workers. QCEW data are similar to monthly Current Employment Statistics (CES) data in that they reflect jobs by place of work; therefore, if a person holds two jobs, he or she is counted twice. However, since the QCEW program, by definition, only measures employment covered by unemployment insurance laws, its totals will not be the same as CES employment totals due to the employee categories excluded by UI.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Sep 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Job Quits Rate in the United States decreased to 1.90 percent in August from 2 percent in July of 2025. This dataset includes a chart with historical data for the United States Job Quits Rate.

BackgroundThe fast-changing labor market highlights the need for an in-depth understanding of occupational mobility impacted by technological change. However, we lack a multidimensional classification scheme that considers similarities of occupations comprehensively, which prevents us from predicting employment trends and mobility across occupations. This study fills the gap by examining employment trends based on similarities between occupations.MethodWe first demonstrated a new method that clusters 756 occupation titles based on knowledge, skills, abilities, education, experience, training, activities, values, and interests. We used the Principal Component Analysis to categorize occupations in the Standard Occupational Classification, which is grouped into a four-level hierarchy. Then, we paired the occupation clusters with the occupational employment projections provided by the U.S. Bureau of Labor Statistics. We analyzed how employment would change and what factors affect the employment changes within occupation groups. Particularly, we specified factors related to technological changes.ResultsThe results reveal that technological change accounts for significant job losses in some clusters. This poses occupational mobility challenges for workers in these jobs at present. Job losses for nearly 60% of current employment will occur in low-skill, low-wage occupational groups. Meanwhile, many mid-skilled and highly skilled jobs are projected to grow in the next ten years.ConclusionOur results demonstrate the utility of our occupational classification scheme. Furthermore, it suggests a critical need for skills upgrading and workforce development for workers in declining jobs. Special attention should be paid to vulnerable workers, such as older individuals and minorities.

Wages in Manufacturing in the United States increased to 29.03 USD/Hour in August from 29.01 USD/Hour in July of 2025. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Job Offers in the United States increased to 7227 Thousand in August from 7208 Thousand in July of 2025. This dataset provides the latest reported value for - United States Job Openings - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

View monthly updates and historical trends for US Unemployment Rate. from United States. Source: Bureau of Labor Statistics. Track economic data with YCha…

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOL) from Dec 2000 to Aug 2025 about job openings, vacancy, nonfarm, and USA.

This data collection is comprised of data from the 2009 Annual Social and Economic Supplement (ASEC), and is a part of the Current Population Survey (CPS) Series. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full time, total income and supplemental income components. Additional data are included that cover training and assistance received under welfare reform programs such as job readiness training, child care services, or job skill training. Data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance are also included.Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey.The original ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit.

OverviewThe NOAA Office for Coastal Management generates the Employment in Coastal Inundation Zones dataset. The dataset includes the number of establishments and jobs that fall within various coastal inundation zones:FEMA Special Flood Hazard AreasNOAA Sea, Lake, and Overland Surge from Hurricane (SLOSH) categories 1 to 4NOAA Tsunami Inundation ZonesNOAA Sea Level Rise (1 to 10 feet)This feature hosted layer (which has been visualized in an Experience Builder application) draws upon that dataset and includes additional insights. It provides the following:General economic insights specific to each county.Information on whether the county has mapping for the following inundation zones: FEMA Special Flood Hazard Areas, NOAA Tsunami Zones, NOAA SLOSH categories 1-4, and NOAA Sea Level Rise 1-10 feet.For each hazard, the layer details the number of business establishments and jobs located within the mapped inundation zones (i.e., the Employment in Coastal Inundation Zones dataset).Data SourcesGeneral Economic InsightsThis feature hosted layer includes additional economic insights:Business establishments and jobs are sourced from the Bureau of Labor Statistics’ Quarterly Census of Employment and Wages or QCEW (accessed on September 18, 2024).Labor force is sourced from the Bureau of Labor Statistics’ Local Area Unemployment Statistics (accessed on September 18, 2024).Mapped Inundation ZonesThis is based on the mapping that we utilized for the Employment in Coastal Inundation Zones analysis:FEMA Special Flood Hazard Area footprints are sourced from the Federal Emergency Management Agency.Tsunami footprints are sourced from several different states, including California’s Department of Conservation, Oregon’s Department of Geology and Mineral Industries, Washington’s State Department of Natural Resources, and Hawaii’s Emergency Management Agency.The hurricane storm surge footprints are based on the SLOSH model, and are sourced from NOAA’s National Hurricane Center.Sea level rise (SLR) footprints are sourced from NOAA’s Office for Coastal Management.Employment in Coastal Inundation Zones AnalysisThe NOAA Office for Coastal Management generates the underlying dataset by overlaying the coastal hazard footprints above with employment data from the Bureau of Labor Statistics’ Statistical Business Register. Per the Bureau of Labor Statistics, "The Business Register, which is made from the QCEW, contains employment and wage information from employers, as well as name, address, and location information."The most recent Employment in Coastal Inundation Zones analysis occurred in October 2023.Availability:Data are unavailable for Massachusetts, Michigan, New Hampshire, and New York due to state-specific regulations restricting access. Additionally, data are currently not available for Alaska or U.S. territories.Data Processing Notes:The geographic footprint contains over 900 records and is based on regional boundaries which were previously defined by NOAA’s Coastal Change Analysis Program (C-CAP). For more details, refer to the C-CAP Regional Land Cover Frequent Questions document (C-CAP Mapping Boundary accessed 2024).County boundaries are from the 2021 TIGER/Line® Shapefiles: Counties (and equivalent) national file, trimmed to the 2021 TIGER/Line® Shapefiles:Coastlinenational filefor cartographic purposes.Percentile rank of establishments has been calculated across the following hazards: FEMA Special Flood Hazard Areas, Tsunami Zones, SLOSH category 4, and SLR 10 feet. A percentile rank tells you how one specific value compares to the rest of the values in a group. It answers the question: "What percentage of the values are below this one?" We use an inclusive percentile rank to compare how the number of establishments in an inundation footprint (like a FEMA Special Flood Hazard Area) for one county compares to the number of establishments in other counties. We exclude counties which are not mapped to the hazard or which were not included in the Employment in Coastal Inundation Zones analysis (both of which are assigned a value of -2000).

The U.S. Bureau of Economic Analysis’ Total Full-Time and Part-Time Employment data provides one of the most comprehensive, publicly available accountings of average annual employment. Beyond full- and part-time employment types, it includes farm employment and other sectors that aren’t always included in other sources, such as Public Administration (with more detail of federal than state and local employment in this category). It also includes and distinguishes both Wage and Salary employees from Proprietors who own their own unincorporated businesses and handle taxation chiefly as personal income. Proprietors tend to be single-person or small businesses and can include construction or repair workers, babysitters, ride-share drivers, artists, local grocers, housekeepers, various freelancers and consultants, and some attorneys and doctors.

In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.