Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

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. SOURCE: https://www.bls.gov/oes/oes_emp.htm

The most recent statewide occupational estimates available. Produced in cooperation with the United States Bureau of Labor Statistics (BLS).

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

Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Jun 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.

Wages in the United States increased 4.72 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Annual Average Employment and Wages reports several labor statistics related to employment and wage. Domain

The most recent occupational estimates for Kentucky’s ten Local Workforce Areas.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

LAST UPDATED January 2019

DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

American Community Survey (2001-2017) http://api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

The wages on the Job Bank website are specific to an occupation and provide information on the earnings of workers at the regional level. Wages for most occupations are also provided at the national and provincial level. In Canada, all jobs are associated with one specific occupational grouping which is determined by the National Occupational Classification. For most occupations, a minimum, median and maximum wage estimates are displayed. They are update annually. If you have comments or questions regarding the wage information, please contact the Labour Market Information Division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

Graph and download economic data for Employed full time: Wage and salary workers: Human resources workers occupations: 16 years and over (LEU0257855600A) from 2011 to 2024 about human resources, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

The Quarterly Census of Employment and Wages (QCEW) program serves as a near census of employment and wage information. The program produces a comprehensive tabulation of employment and wage information for workers covered by Connecticut Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. Data on the number of establishments, employment, and wages are reported by industry for Connecticut and for the counties, towns and Labor Market Areas (LMAs) and Workforce Investment Areas (WIAs).

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program.

The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers.

Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys.

In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income.

The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends.

The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

description: The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering 98 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. More information and details about the data provided can be found at http://www.bls.gov/cew; abstract: The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering 98 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. More information and details about the data provided can be found at http://www.bls.gov/cew

The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering 98 percent of U.S. jobs, available at the county, MSA, state and national levels by industry.

More information and details about the data provided can be found at http://www.bls.gov/cew

Graph and download economic data for Employment Cost Index: Wages and Salaries: Private Industry Workers (ECIWAG) from Q1 2001 to Q1 2025 about cost, ECI, salaries, workers, private industries, wages, private, employment, industry, inflation, indexes, and USA.

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

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, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

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 California's employment in that same sector. 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.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering more than 95 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. The dataset, hosted as part of the Cloud Public Datasets Program , gives county-level information on jobs and wages each quarter starting in 1990. The counties are identified by geoid which can easily be joined with both all FIPS codes or US county boundaries to unlock new insights within the data. Both of these datasets are available in BigQuery through the Cloud Public Datasets Cleaning and onboarding support for this dataset is provided by CARTO . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: 16 years and over (LEU0252881500Q) from Q1 1979 to Q2 2025 about second quartile, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.