open-data

This dataset contains all job applications submitted through the Borough Offices, through eFiling, or through the HUB, which have a "Latest Action Date" since January 1, 2000. This dataset does not include jobs submitted through DOB NOW. See the DOB NOW: Build – Job Application Filings dataset for DOB NOW jobs.

Missouri Career Centers offer personal assistance for your job search or hiring needs. Our staff is trained to assist you with products and services designed for both Job Seekers and Employers!

This dataset contains current job postings available on the City of New York’s official jobs site (http://www.nyc.gov/html/careers/html/search/search.shtml). Internal postings available to city employees and external postings available to the general public are included.

This data shows jobs by industry, beginning in 2012, created from a dataset of economic profiles of the 10 Empire State Development (ESD) economic development regions. Refer to the About section for the data dictionary and other information.

Position & Salary information for San Mateo County Job Classifications

Listing of job openings in Missouri state government

The job title, job class code, hours per pay period, number of steps, hourly step rates, and yearly step rates per job classification.

Current salary steps (A Step - I Step) and unit designations for all job classifications.

List of most job filings filed in DOB NOW. This dataset does not include certain types of job. For Electrical jobs, use https://data.cityofnewyork.us/browse?Data-Collection_Data-Collection=DOB+NOW+Electrical+Permits+Data. Elevator and LAA jobs will also be published separately.

Listing of job openings registered through Workforce1 Center. This data is up to date as of the date reflected in the "About" tab of this dataset.

This data will be updated when further major updates occur, either as a result of collective bargaining or updates to the City’s overall salary structure resulting from the Job Architecture System Project.This dataset is a listing of all active City of Edmonton job code titles and salary ranges. The working title may be different.

Data Owner: Compensation and Classification, Employee Services

City of LA job applicants by the job they applied for and demographic information.

We are currently undergoing a data inventory to improve usability on the site. We're aware that this dataset is out of date but wanted to err on the side of making incomplete data available. Thank you for your patience, please contact the dataset owner or mayor.opendata@lacity.org with questions or ideas.

Top career graded jobs from 2018-2028 occupational projections for Missouri and ten workforce regions.

Data from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

The list tracks the number of businesses that NYC Business Acceleration has assisted in opening and how many jobs were created by those businesses. This data is up to date as of the date reflected in the "About" tab of this dataset.

Job preparation or training programs

This dataset contains records of work completed and in-progress work from June 2018 to present for the purpose of tracking the installation and maintenance of roadway markings across the City of Austin. The Jobs dataset is separated into four categories: Long Line, Short Line, Specialty Markings, and Raised Pavement Markings.

Long Line: Work group responsible for installing and maintaining lane lines, double yellow centerlines, bike lane lines, and turn bay.

Short Line: Work group responsible for installing and maintaining crosswalks, school zone lines, and stop lines.

Specialty Markings: Work group responsible for installing and maintaining arrows, words, bike symbols, pedestrian symbols, railroad crossings, yield triangles, parking stalls/Ls/Ts, green pads, and speed hump markings.

Raised Pavement Markings: Work group responsible for installing and maintaining delineators, raised pavement markings (RPMs), and concrete domes.

This work is managed by the Signs & Markings Division of the City of Austin Transportation Department.

You may also be interested in these related datasets, which can be joined together using the work order ID columns:

• Road Markings Work Orders: https://data.austintexas.gov/Transportation-and-Mobility/Roadway-Markings-Work-Orders/nyhn-669r
• Signs and Markings Time Logs: https://data.austintexas.gov/dataset/Work-Order-Signs-Markings-Time-Logs/qvth-gwdv
• Signs and Markings Reimbursements: https://data.austintexas.gov/dataset/Signs-and-Markings-Reimbursement-Tracking/pma8-yy5k

Division website: http://www.austintexas.gov/department/signs-markings

Job growth is often used as a measure of economic expansion and health. The city's job growth consistently exceeds local competitors. Future job growth in Henderson is predicted to be 42.1%, higher than the US average of 33.5%. Note: Most current US Census data is 2018.

This dataset represents the CHANGE in the number of jobs per industry category and sub-category from the previous month, not the raw counts of actual jobs. The data behind these monthly change values is from the Bureau of Labor Statistics (BLS) Current Employment Statistics (CES) program. CES data represents businesses and government agencies, providing detailed industry data on employment on nonfarm payrolls.

Ratio of the number of jobs in Santa Monica to the amount of housing.

Dataset showing job creation and job destruction. A negative number indicates jobs destroyed (positions eliminated due to businesses closing or contracting). Job creation is employment resulting from new businesses starting up or existing businesses expanding their payrolls with new positions. The source data for the data is the Longitudinal Employer-Household Dynamics (LEHD) linked employer employee microdata. A wide variety of record sources contribute to the construction of the Quarterly Workforce Indicators (QWI), including the administrative records on employment collected by the states, Social Security data, Federal tax records, and other census and survey data.

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.

This Dataset indicates average salary by position title and grade for full-time regular employees. Data excludes elected, appointed, non-merit and temporary employees. Underfilled positions are also excluded from the dataset. Update Frequency : Annually

Demographic data for job applicants at the City of Gainesville for both General Government and GRU since October 2010.

This dataset reflects hire actions submitted to the Civil Service Department for classified positions. Hire actions include new employees hired since January of 2019. This data includes the position and requisition number hired for by date and department. Data is updated on a monthly basis.

This is a multi-year state agency salary report. To learn more about state salaries visit the Oregon Transparency Program website. https://www.oregon.gov/transparency/Pages/index.aspx. To learn more about state jobs and salaries visit https://www.oregon.gov/das/hr/pages/index.aspx.

This dataset contains a list of all Montgomery County job classifications, grades and specifications. The Classification Plan table can be viewed at https://www2.montgomerycountymd.gov/OHRClassification/jobclass.aspx Update Frequency : Annually

US Census Business Dynamics Statistics tracking annual Job Creation and Firm Establishments within the Seattle-Tacoma-Bellevue Metropolitan Statistical Area.

VITAL SIGNS INDICATOR Jobs (LU2)

FULL MEASURE NAME Employment estimates by place of work

LAST UPDATED March 2020

DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/

U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/

U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/

Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017.

The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

Statistics on monthly job placement trends.

Empire State Development produces a quarterly report with a cumulative list of businesses admitted to the Excelsior Jobs Program. The dataset displays the name and type of business, the location, job and investment commitments, and the dollar amount of tax credits allocated to each business.

The Iowa Industrial New Jobs Training (260E) program provides employers expanding Iowa’s workforce with new employee training. The 260E program is designed to increase worker productivity and company profitability, and is administered by Iowa's 15 community colleges and financed through bonds sold by the colleges. Depending on wages paid, the participating businesses divert 1.5% or 3% of the Iowa state withholding taxes generated by the new positions to the community college to retire the bonds. Businesses may also be eligible to receive reimbursement for their on-the-job training expenses, and/or corporate tax credits.

This dataset lists 260E contracts open in or after 2012, Qtr 2, and includes information on: the administering community college, participating employer, location of employment, training expenses, and employment information.

More on Iowa's 260E program.

Learn More

This dataset reflects applications submitted to the Civil Service Department for classified positions. Application data included here is for promotions and new hires submitted since January of 2018. Contains official City position name and date of each single application by a candidate. This dataset includes data for positions for which the screening of applications has been delegated to the Sewerage and Water Board. Cannot be connected to requisitions by any unique ID. Data is updated on a monthly basis.

VITAL SIGNS INDICATOR Jobs (LU2)

FULL MEASURE NAME Employment estimates by place of work

LAST UPDATED October 2019

DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/

U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/

U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/

Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017.

The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

VITAL SIGNS INDICATOR Jobs (LU2)

FULL MEASURE NAME Employment estimates by place of work

LAST UPDATED October 2019

DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/

U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/

U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/

Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017.

The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

Total number of jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

Information about each regular hire* employee at specific points in time, at the end of each calendar year. Employee-related information includes ethnicity, gender and age range. Age range can change from year to year. Job-related information includes date of regular hire, type of regular hire, date of any termination, department, title, SOC job code, SOC job code description, EEO4 job code and management level.

Data is at the end of each calendar year for each of 2013 through 2018. Data is updated annually.

Hire dates for regular hire employees hired before 2013 are all set to December 31, 2012, so accurate employee longevity counts cannot be determined. Employee numbers in the data set are masked, and are not actual employee numbers.

• Regular hire employees have full salaries and benefits and do not have fixed terms on their employment.

The Database of Economic Incentives (DOEI) is a public, searchable database for various economic development projects that Empire State Development (ESD) administers.

Recharge New York Power is available to businesses and not-for-profit corporations for job retention and business expansion and attraction purposes. This dataset contains Recharge New York Customers, including their location, amount of allocation, and amount of jobs committed.

Workers compensation claims by department.

Total number and percent of jobs in Pierce County with an annual average wage at or above 80% of the median household income for the corresponding year for Pierce County.

VITAL SIGNS INDICATOR Jobs (LU2)

FULL MEASURE NAME Employment estimates by place of work

LAST UPDATED October 2019

DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/

U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/

U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/

Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017.

The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

This dataset reflects requisitions submitted to the Civil Service Department for both unclassified and classified positions. Classified positions are hired within the civil service system; unclassified positions are appointed. A requisition is the electronic document authorizing a new hire, promotion or other personnel transaction. Requisition data included here is for promotions and new hires submitted since January of 2018. Data is updated on a monthly basis.

The number of existing full time and/or part time employment positions created and/or retained as reported by a MBE client served.

The Occupational Employment Statistics (OES) program produces employment and wage estimates annually for over 800 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.

MBDA tracks job creation and job retention through its national network of Minority Business Centers, Advanced Manufacturing Centers, the Federal Procurement Center, and the American Indian, Alaska Native, Native Hawaiian Broad Agency Announcements.

A listing of open bid opportunities provided by the City of Los Angeles and available on the Regional Alliance Marketplace for Procurement, RAMP at https://www.rampla.org

The number of existing full time and/or part time employment positions created and/or retained as reported by a MBE client served.

Total number of manufacturing jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

Annual number of on-the-job injury claims

Information about each regular hire* employee at specific points in time, at the end of every year. Employee-related information includes ethnicity, gender and age range. Age range can change from year to year. Job-related information includes date of regular hire, date of any termination, department, title, and management level.

Data is at the end of each calendar year from 2021 forward. Data is updated annually.

Employee numbers in the data set are masked, and are not actual employee numbers.

• Regular hire employees have full salaries and benefits and do not have fixed terms on their employment.

This data set contains information on the yearly average of the number of jobs in Somerville since 2001. The data comes from the Massachusetts Department of Economic Research's Employment and Wage (ES-202) Reports. For more information, see https://lmi.dua.eol.mass.gov/lmi/EmploymentAndWages.

Number of jobs created through minority business manufacturing and export activity. MBDA tracks job creation and job retention through its national network of Minority Business Centers, Advanced Manufacturing Centers, the Federal Procurement Center, and the American Indian, Alaska Native, Native Hawaiian Broad Agency Announcements.

Dataset provides monthly information about the accuracy and timeliness of print jobs generated by the city’s print services. These measures are verified from data collected on customer service satisfaction surveys, percent of jobs delivered by the due date and percent of jobs free of defect. The fields in this dataset pertain to percent of print jobs completed by the due date.

Gross metro product per job (2013 inflation-adjusted dollars)

Total number of private only jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

Total number of retail/trade jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

Total Full and Part-Time Jobs in Maryland by Type and Industry from 2010 to 2020. Sourced from the U.S. BEA Table CAEMP25N.

2014 Inflow/Outflow Job Counts (All Jobs). Source US Census

Temporary dataset of the number of jobs and businesses within the Falcon Field business area by month.

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 c

File for Bay Area jurisdictions containing: Households (DOF E5 2019) Jobs (LEHD WAC total jobs, averaged 2015-2017)

Raw data which powers the Mapped In NY site at http://www.mappedinny.com/

Total number of education/health jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

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Description: LAHD financed projects since 2003 to present. These projects are financed with programs including Affordable Housing Managed Pipeline, Supportive Housing Program, Affordable Housing Bond Program, and the Proposition HHH Supportive Housing Loan Program. This project list contains participants, property, units, construction and milestone information. Each line contains both site and project level information. Site level information are presented with "SITE_" in the column headers. Column headers without "SITE_" are project level information.

Tax Law section 31(e) requires the Tax Department to produce an Excelsior Jobs Program Credit Report by June 30th of each year. The program is administered by Empire State Development and offers a tax credit comprised of five credit components focused on certain strategic industries such as biotechnology, pharmaceutical, high-tech, clean-technology, green technology, financial services, child care services, agriculture, manufacturing and life sciences. The components of the credit are the jobs tax credit, the investment tax credit, the research and development tax credit, the real property tax credit, and the child care services tax credit. Firms in the strategic industries that create and maintain new jobs or make significant investments are eligible to apply for the credit.

This data set represents employers in Utah who could not fill job openings & had to import foreign labor from the H1B Visa program to fill those jobs. This data is from the US Dept of Labor.

List of Benefits Access Centers that offer temporary financial assistance, food stamps and Medicaid to eligible individuals

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.

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.

The Family Business Loan Program is a public-private partnership between the City of Austin, HUD, and participating private lenders to offer low-interest loans to qualified small businesses that are expanding and creating jobs.

Listing of open and closed CDBG contracts between NYS Homes & Community Renewal’s Office of Community Renewal and grant recipients. Details include contract number, project name, project type, activity, contract amount, grant recipient, county, municipality and contract status, for the Community Development Block Grant (CDBG) Program.

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 c

This represents a first attempt to illustrate race/ethnicity and gender representation in the top Pathway and Career jobs in King County, as defined by the 2016 Washington Roundtable Pathways report.

These are jobs supported through Economic Development Department program, services and activities.

Total number of professional/science/tech jobs that reside in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

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 California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.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.

List of SNAP Centers that offer temporary financial assistance, food stamps and Medicaid to eligible individuals.

VITAL SIGNS INDICATOR
Jobs (LU2)

FULL MEASURE NAME
Employment estimates by place of work

LAST UPDATED
October 2022

DESCRIPTION
Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

U.S. Census Bureau: LODES Data - http://lehd.ces.census.gov/
Longitudinal Employer-Household Dynamics Program
2002-2018

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) monthly employment data 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.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of cities included in a sub-county is one for San Francisco and San Jose and more than one for all other sub-counties. Estimates for sub-county areas are the sums of Census block-level estimates from the U.S. Census Bureau: LEHD data.

The following incorporated cities and towns are included in each sub-county area:

• North Alameda County: Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont
• East Alameda County: Dublin, Livermore, Pleasanton
• South Alameda County: Fremont, Hayward, Newark, San Leandro, Union City
• Central Contra Costa County: Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek
• East Contra Costa County: Antioch, Brentwood, Oakley, Pittsburg
• West Contra Costa County: El Cerrito, Hercules, Pinole, Richmond, San Pablo
• Marin County: Belvedere, Corte Madera, Fairfax, Larkspur, Mill Valley, Novato, Ross, San Anselmo, San Rafael, Sausalito, Tiburon
• Napa County: American Canyon, Calistoga, Napa, St. Helena, Yountville
• San Francisco County: San Francisco
• North San Mateo County: Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco
• Central San Mateo County: Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo
• South San Mateo County: East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside, Atherton
• North Santa Clara County: Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale
• San Jose: San Jose
• Southwest Santa Clara County: Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga
• South Santa Clara County: Gilroy, Morgan Hill
• East Solano County: Dixon, Fairfield, Rio Vista, Suisun City, Vacaville
• South Solano County: Benicia, Vallejo
• North Sonoma County: Cloverdale, Healdsburg, Windsor
• South Sonoma County: Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

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 California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.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.

Sum of earnings for calendar year 2019 for each job class by employee.

This dataset contains the New York Power Authority’s hydropower customers having an allocation of Expansion Power, Replacement Power, and/or Preservation Power, including their location, amount of allocation, and amount of jobs committed.

Data on the number of trainees for green business job training programs by year

The number of existing full time and/or part time employment positions created and/or retained as reported by a MBE client served.

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:
(aggregatio

Job vacancies, payroll employees, and job vacancy rate, NB / Postes vacants, employés salariés et taux de postes vacants, NB

VITAL SIGNS INDICATOR Change in Jobs by Industry (EC2)

FULL MEASURE NAME Employment by place of work by industry sector

LAST UPDATED May 2019

DESCRIPTION Change in jobs by industry is the percent change and absolute difference in the number of people who have jobs within a certain industry type in a given geographical area

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.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.

Dataset showing employment change resulting from new business establishments and from existing firm expansion. Includes both the total for the 7 County Metro and the average of six counties, excluding Ramsey County for comparison.

The formula-driven calculation projects investment data at 3, 6, and 9 year intervals from the investment award. The formula is based on a study done by Rutgers University, which compiled and analyzed the performance of EDA construction investments after 9 years. This approach was reviewed and validated by third-party analysis conducted by Grant Thornton in 2008. Based on this formula and a review of EDA's historical results, EDA estimates that 40% of the 9-year projection would be realized after 3 years, 75% after 6 years, and 100% after 9 years.

This dataset contains a list of open positions and classifications available in the County. Update Frequency : Weekly

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 c

This dataset contains summary information on numbers for all jobs pledged to be created and retained through the Department of Community and Economic Development.

The data collection started January 20th, 2015.

VITAL SIGNS INDICATOR
Jobs (LU2)

FULL MEASURE NAME
Employment estimates by place of work

LAST UPDATED
October 2022

DESCRIPTION
Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

U.S. Census Bureau: LODES Data - http://lehd.ces.census.gov/
Longitudinal Employer-Household Dynamics Program
2002-2018

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) monthly employment data 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.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of cities included in a sub-county is one for San Francisco and San Jose and more than one for all other sub-counties. Estimates for sub-county areas are the sums of Census block-level estimates from the U.S. Census Bureau: LEHD data.

The following incorporated cities and towns are included in each sub-county area:

• North Alameda County: Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont
• East Alameda County: Dublin, Livermore, Pleasanton
• South Alameda County: Fremont, Hayward, Newark, San Leandro, Union City
• Central Contra Costa County: Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek
• East Contra Costa County: Antioch, Brentwood, Oakley, Pittsburg
• West Contra Costa County: El Cerrito, Hercules, Pinole, Richmond, San Pablo
• Marin County: Belvedere, Corte Madera, Fairfax, Larkspur, Mill Valley, Novato, Ross, San Anselmo, San Rafael, Sausalito, Tiburon
• Napa County: American Canyon, Calistoga, Napa, St. Helena, Yountville
• San Francisco County: San Francisco
• North San Mateo County: Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco
• Central San Mateo County: Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo
• South San Mateo County: East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside, Atherton
• North Santa Clara County: Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale
• San Jose: San Jose
• Southwest Santa Clara County: Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga
• South Santa Clara County: Gilroy, Morgan Hill
• East Solano County: Dixon, Fairfield, Rio Vista, Suisun City, Vacaville
• South Solano County: Benicia, Vallejo
• North Sonoma County: Cloverdale, Healdsburg, Windsor
• South Sonoma County: Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

Find information on population, income, jobs, wages, graduation rates, highways, water and healthcare for the Comptroller's 12 Economic Regions.

See https://comptroller.texas.gov/about/policies/privacy.php for more information on our agency’s privacy and security policies.

This dataset contains the job opportunities with The City of Calgary. City of Calgary employees operate the facilities, deliver the services and run the programs that support our city. We are committed to building and maintaining a respectful, inclusive and equitable workplace that is representative of the community we serve. We value individuals who bring diverse experience, skills and opinions to our services. We seek individuals who are committed to public service, enjoy collaborating with others and who share our values, including The City’s commitment to anti-racism and reconciliation. Accommodations are available during the hiring process upon request.

This data set shows a comparison of the number of jobs companies in the Executive Priority program estimated their projects would create to the number actually realized in the first and second years after project completion.

The number of projected jobs created versus the actual jobs created for new redevelopment agreements in the Reporting Year. The increment projected versus the actual increment created for new redevelopment agreements in the Reporting Year.

For the detailed reports for each TIF district for each year, please see https://www.chicago.gov/city/en/depts/dcd/supp_info/tif-district-annual-reports-2004-present.html.

A list of all contractors providing service(s) to New York City youth and the amount of their contract

The formula-driven calculation projects investment data at 3, 6, and 9 year intervals from the investment award. The formula is based on a study done by Rutgers University, which compiled and analyzed the performance of EDA construction investments after 9 years. This approach was reviewed and validated by third-party analysis conducted by Grant Thornton in 2008. Based on this formula and a review of EDA's historical results, EDA estimates that 40% of the 9-year projection would be realized after 3 years, 75% after 6 years, and 100% after 9 years.

The Career Centers data set houses the Division’s information for customers on all of the Career Centers across the state.

Average Wage Per Job in Maryland and its Jurisdictions (Constant 2017 Dollars) from 2012 to 2022. Data source from U.S. Bureau of Economic Analysis (Table CA30), November 2023.

Full And Part Time Jobs in Maryland and its Jurisdictions: 1970 to 2020 Historical and 2025 to 2050 Projected.

The dataset is collected and owned by the Department of Social Services (DSS). The Human Resources Administration or Department of Social Services (HRA/DSS) is the department of the government of New York City in charge of the majority of the city's social services programs. HRA helps New Yorkers in need through a variety of services that promote employment and personal responsibility while providing temporary assistance and work supports. Its regulations are compiled in title 68 of the New York City Rules. If you have a question related to the dataset, please submit your query via the Contact Us Page on NYC Open Data (https://opendata.cityofnewyork.us/engage/), and someone from the Open Data Team will reach out. This datasets contains information about Jobs-Plus service (http://opportunitynycha.org/workforce-development/jobs-plus/), a place-based employment program designed to increase the earnings and employment of working-age residents in designated public housing developments or a cluster of developments.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

Port of Los Angeles - Historical TEU Statistics: A "TEU" is a "twenty-foot equivalent unit," which is a standard measurement of shipping cargo based on a twenty-foot long shipping container.

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 California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.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.

VITAL SIGNS INDICATOR
Jobs (LU2)

FULL MEASURE NAME
Employment estimates by place of work

LAST UPDATED
October 2022

DESCRIPTION
Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

U.S. Census Bureau: LODES Data - http://lehd.ces.census.gov/
Longitudinal Employer-Household Dynamics Program
2002-2018

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) monthly employment data 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.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of cities included in a sub-county is one for San Francisco and San Jose and more than one for all other sub-counties. Estimates for sub-county areas are the sums of Census block-level estimates from the U.S. Census Bureau: LEHD data.

The following incorporated cities and towns are included in each sub-county area:

• North Alameda County: Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont
• East Alameda County: Dublin, Livermore, Pleasanton
• South Alameda County: Fremont, Hayward, Newark, San Leandro, Union City
• Central Contra Costa County: Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek
• East Contra Costa County: Antioch, Brentwood, Oakley, Pittsburg
• West Contra Costa County: El Cerrito, Hercules, Pinole, Richmond, San Pablo
• Marin County: Belvedere, Corte Madera, Fairfax, Larkspur, Mill Valley, Novato, Ross, San Anselmo, San Rafael, Sausalito, Tiburon
• Napa County: American Canyon, Calistoga, Napa, St. Helena, Yountville
• San Francisco County: San Francisco
• North San Mateo County: Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco
• Central San Mateo County: Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo
• South San Mateo County: East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside, Atherton
• North Santa Clara County: Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale
• San Jose: San Jose
• Southwest Santa Clara County: Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga
• South Santa Clara County: Gilroy, Morgan Hill
• East Solano County: Dixon, Fairfield, Rio Vista, Suisun City, Vacaville
• South Solano County: Benicia, Vallejo
• North Sonoma County: Cloverdale, Healdsburg, Windsor
• South Sonoma County: Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

Port of Los Angeles - Historic Tonage Data MMRT

Job Creation Rates DOL, Bureau of Labor Statistics Nov 2013- Nov 2014

Wage and classification information of City of Seattle Employees. Exclusions may apply for vulnerable populations.

The percentage of School to Work (STW) students who exit the program with a job.

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:
(aggregatio

VITAL SIGNS INDICATOR
Jobs (LU2)

FULL MEASURE NAME
Employment estimates by place of work

LAST UPDATED
October 2022

DESCRIPTION
Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

U.S. Census Bureau: LODES Data - http://lehd.ces.census.gov/
Longitudinal Employer-Household Dynamics Program
2002-2018

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) monthly employment data 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.

For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of cities included in a sub-county is one for San Francisco and San Jose and more than one for all other sub-counties. Estimates for sub-county areas are the sums of Census block-level estimates from the U.S. Census Bureau: LEHD data.

The following incorporated cities and towns are included in each sub-county area:

• North Alameda County: Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont
• East Alameda County: Dublin, Livermore, Pleasanton
• South Alameda County: Fremont, Hayward, Newark, San Leandro, Union City
• Central Contra Costa County: Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek
• East Contra Costa County: Antioch, Brentwood, Oakley, Pittsburg
• West Contra Costa County: El Cerrito, Hercules, Pinole, Richmond, San Pablo
• Marin County: Belvedere, Corte Madera, Fairfax, Larkspur, Mill Valley, Novato, Ross, San Anselmo, San Rafael, Sausalito, Tiburon
• Napa County: American Canyon, Calistoga, Napa, St. Helena, Yountville
• San Francisco County: San Francisco
• North San Mateo County: Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco
• Central San Mateo County: Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo
• South San Mateo County: East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside, Atherton
• North Santa Clara County: Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale
• San Jose: San Jose
• Southwest Santa Clara County: Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga
• South Santa Clara County: Gilroy, Morgan Hill
• East Solano County: Dixon, Fairfield, Rio Vista, Suisun City, Vacaville
• South Solano County: Benicia, Vallejo
• North Sonoma County: Cloverdale, Healdsburg, Windsor
• South Sonoma County: Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma

The Department of Buildings (DOB) issues permits for construction and demolition activities in the City of New York. The construction industry must submit an application to DOB with details of the construction job they would like to complete. The primary types of application, aka job type, are: New Building, Demolition, and Alterations Type 1, 2, and 3. Each job type can have multiple work types, such as general construction, boiler, elevator, and plumbing. Each work type will receive a separate permit. (See the DOB Job Application Filings dataset for information about each job application.) Each row/record in this dataset represents the life cycle of one permit for one work type. The dataset is updated daily with new records, and each existing record will be updated as the permit application moves through the approval process to reflect the latest status of the application.

This dataset contains a forecast of the total population and jobs in each transportation zone from 2014 to 2076. This forecast series is a backcast scenario to achieve growth targets identified in the Municipal Development Plan. (www.calgary.ca/mdp)

Jobs in the different career paths

The ACT Migration Program attracts overseas skilled workers, with occupations in demand, to work in Canberra by nominating their skilled migration visa application.

The number of Development Disabilities - Adult Services clients who received job coaching supports

Total Jobs by Industry (NAICS), Historic 2010 to 2020 and Projected 2025 to 2050 in Maryland.

VITAL SIGNS INDICATOR Change in Jobs by Industry (EC2)

FULL MEASURE NAME Employment by place of work by industry sector

LAST UPDATED May 2019

DESCRIPTION Change in jobs by industry is the percent change and absolute difference in the number of people who have jobs within a certain industry type in a given geographical area

DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2017 http://www.labormarketinfo.edd.ca.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 performance indicator measures the estimated number of jobs created and retained, by communities and regions, attributable to the EDA grant to support entrepreneurship

Average Wage Per Job in Maryland and its Jurisdictions in Current Dollars from 2012 to 2022. Source data from U.S. Bureau of Economic Analysis, December 2023.

The formula-driven calculation projects investment data at 3, 6, and 9 year intervals from the investment award. The formula is based on a study done by Rutgers University, which compiled and analyzed the performance of EDA construction investments after 9 years. This approach was reviewed and validated by third-party analysis conducted by Grant Thornton in 2008. Based on this formula and a review of EDA's historical results, EDA estimates that 40% of the 9-year projection would be realized after 3 years, 75% after 6 years, and 100% after 9 years.

Count of employees by job title, by agency, with their pay ranges.

Not seasonally Adjusted Unemployment Rate. Values also include Preliminary and Confirmed rates.

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

This data set contains the veterans unemployment rate in Maryland. Figures come from the Bureau of Labor Statistics, and are subject to revision.

Percent of managers that provided a rating of 8 or higher on a scale of 1 - 10 to the question "Applicants referred had the skills to perform the job"

Salt Lake City MSA Occupational Projections 2012-2022

Port of Los Angeles - Cruise Passenger (1990 - 2014) Historical published data. The Port no longer collected cruise passenger data.

Historical information about the total Employees and Businesses Dataset is a snapshot of the total number of businesses that are currently in Mesa, as well as the total number of employees that work in Mesa. Source: ESRI Community Analyst. It is important to note that in this dataset, a “Full-Time Employee (FTE)” in Mesa is someone who may not necessarily live in Mesa, however, they are employed at a business that is located in Mesa. This is a distinct difference between the “Employment” number in Mesa, which is stated in the “Employment Dataset.” Employment refers to the total number of Mesa residents that are employed, within or outside of the City of Mesa.

The number of Developmental Disabilities - Adult Services clients who received job development services.

The Department of Commerce reports these aggregate performance metrics for its Central Business Licensing System (CBL) to the Governor's Office of Performance Improvement (GOPI) each month. The Department of Information Technology (DoIT) formats and uploads the data to data.maryland.gov, and generates the descriptive analytics included here.

Legend for asterisks in column names: *This represents business registrations from CBL and does not include tax accounts Comptroller tax account filings added ***Prior to June, 2014 this number included both SDAT and Comptroller numbers of businesses incorporated. As of June, the number only includes SDAT numbers. **Adoption rate-percentage calculation = CBL registrations divided by SDAT registrations

This measure highlights change in jobs that communities or businesses generate or save due to Sea Grant assistance (i.e., providing information to help communities, industries or businesses expand, make better decisions or avoid mistakes). Sea Grant provides the information and training that informs business decisions, and in some Hurricane forecast track error cases firms create or sustain jobs as a result. A job created is a new position created and filled as a result of Sea Grant activities. An existing position that is filled with a Sea Grant-trained applicant should not be reported in this measure. A job sustained is an existing, filled position that is sustained as a direct result of Sea Grant activities. A job cannot be reported as both created and sustained in the same year.

The number of existing full time and/or part time employment positions created and/or retained as reported by a MBE client served.

Commerce Dashboard Measures - Fiscal Year Part 2

The information in the dataset provides information on the MCG Recruitment and Selection Activities which includes the volume of applications received for each job vacancy, number of applicants hired, applicant statuses and the type of hires (Permanent, Temporary, Rehire) for the respective fiscal year. Update Frequency : Annually

The percentage of School of Work students who exited the program with a job

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:
(aggregatio

Current Employment by Industry (CES) data reflect jobs by "place of work." It does not include the self-employed, unpaid family workers, and private household employees. Jobs located in the county or the metropolitan area that pay wages and salaries are counted although workers may live outside the area. Jobs are counted regardless of the number of hours worked. Individuals who hold more than one job (i.e. multiple job holders) may be counted more than once. The employment figure is an estimate of the number of jobs in the area (regardless of the place of residence of the workers) rather than a count of jobs held by the residents of the area.

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:
(aggregatio

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:
(aggregatio

The new compensation and classification structure began in January 2025. A Compensation and Classification Modernization webpage is available for employees on RamseyNet with more information including additional benefit updates such as increased parental leave and increased floating holiday time.

The dataset contains geographic and contact information for the New York City Family Justice Centers, including: borough, facility name (always Family Justice Center), street address, city, state, zip code, telephone number, hours, service type, latitude, longitude, community board, council district, 2010 census tract, building identification number (BIN), borough/block/lot number (BBL) and neighborhood tabulation area (NTA).

The Business Breakdown Dataset shows the number of businesses and employees from a wide variety of unique industries throughout Mesa. This data is pulled annually (usually in the summer) from the ESRI Community Analyst database.

Employment figures and unemployment rate, 2009 - present. (Non-seasonally adjusted.) As of June 2017 this dataset was marked for no additional updates because this data is available for all counties in the state in other datasets so there was no need to continue updating it for Anne Arundel County only.

An exempt position is one that involves policy making to an extent or is confidential in such a way that political affiliation is an appropriate consideration for the effective performance of the job. Please refer to the exempt list and associated job descriptions for more information.

Data set is results of commissioned questions the Atlantic Quarterly omnibus public opinion survey conducted in August 2017. These commissioned questions relate to public opinion regarding perceptions of career opportunities and role of young Nova Scotians in the provincial economy. Overall results are provided for each question and results are also broken down by various demographic markers (age, gender, geographic region, education level and household income).

Monthly estimates of labor force, employment and unemployment by county for the seven county metro area.

Jobs Created by Energy Cost Savings Program Savings for Businesses

Port of Los Angeles - Historic Tonage Data Short Ton(1920-1970)

The Montgomery County Government has a diverse workforce of employees that cross five generations and multiple age, race, gender and ethnic groups. The dataset is a summary of the County's turnover percentage by generational category, age, race, ethnicity, gender and job class. (Turnover percentage is calculated using only full time-regular and part time-regular employees. Full time-temporary and part time-temporary employees are excluded for turnover calculation). Data covers 1/1 to 12/31 of the previous calendar year. (Other = Employees who identify as American Indian/Alaskan Native or Native Hawaiian/Pacific Islander) Update Frequency : Annually

Fort Collins 4th quarter employment and wages from 2013-2017 by 3-digit NAICS code as reported to the Unemployment Administration. Certain categories have been suppressed to preserve business anonymity.

Salary information for State of Vermont active employees from all branches. Generally, employees who are expected to work year-round have salaries stated as salary type "Annual." Temporary employees have salaries stated as salary type "Hourly." Legislators, who usually do not work year-round, have salaries stated as salary type "Weekly." The weekly rate reported here is the rate paid during the legislative session. Data as of the last Friday of each month. NOTE: Individuals covered by the Safe at Home Act (Title 15 Sections 1150-1160) have been excluded from this list.

List of all approved permits in DOB NOW

Percent of clients receiving job development services that secure employment. Human Services Agency performance measure 7330P ID 540.

The dataset represents information on the performance of the portfolio of loans issued through the GJGNY Residential Loan Fund. The loan performance results of the GJGNY portfolio have shown strong performance to date, with lower levels of delinquencies and defaults/losses than other consumer loan asset classes. This performance data is useful to lender/capital providers, rating agencies, researchers, and interested stakeholders to assist in anticipating performance results for their-party financing products aimed at consumer clean energy financing. Users can access an Interactive Dashboard with charts, graphs, and tables at https://nyserda.ny.gov/Researchers-and-Policymakers/Green-Jobs-Green-New-York/Data-and-Trends

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

Total number of jobs by industry sector (NAICS) as reported by the California Economic Development Department.

Information about employers and employees in the City of Mesa by industry and census tract. Data is collected annually by Maricopa Association of Governments (MAG) from a variety of sources. NOTE: Location of employees are generalized based on the center point of census tract and are NOT an exact location.

Monthly historical data for the unemployment rate (not seasonally adjusted) in San Mateo County from 1990-2013.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

UrbCtrHighDensOffice

The number of existing full time and/or part time employment positions created and/or retained as reported by a MBE client served.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

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:
(aggregatio

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:
(aggregatio

Total number of businesses by industry sector (NAICS) as reported by the California Economic Development Department.

Data from the Workforce Solutions Annual Report.

Number of workers commuting from Pierce County to other counties in Washington. Data is sourced from LEHD Origin-Destination Employment Statistics (LODES). Sample Universe: Workers 16 years (members of the Armed Forces and civilians) who were at work during the reference year.

Payroll information for all Los Angeles City Employees including the City's three proprietary departments: Water and Power, Airports and Harbor. Data is updated bi-weekly by the Los Angeles City Controller's Office. Payroll information for employees of the Department of Water and Power is updated every three months.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

San Mateo County and Other Bay Area Counties Annual Unemployment Rate (not seasonally adjusted) for years 2000-2019 Compared to Marin County, San Francisco County, Santa Clara County, and the State of California. Data is non-preliminary.

Employment, establishments and wage data from the Bureau of Labor Statistics' Quarterly Census of Employment and Wages.

Dataset showing the number of residents employed full-time in the past 12 months with income below federal poverty guidelines.

Tracks total covered employment in Pierce County by year

This performance indicator measures the estimated number of jobs created and retained, by communities and regions, attributable to EDA investments made to support the travel and tourism sectors.

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.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

Top 10 employers residing in Corona, CA. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures

This Indicator is measured by the percent of employed individuals who are not employed in industries with a mean annual wage of at least $80,000. In 2016, these industries included management occupations; legal occupations; healthcare practitioners and technical occupations; computer and mathematical occupations; architecture and engineering occupations; life, physical, and social science occupations; and business and financial operations occupations. (Source: Occupational Employment Statistics, CA Employment Development Department https://data.edd.ca.gov/Wages/Occupational-Employment- Statistics-OES-/pwxn-y2g5)

Proposed new indicator for FY 2022. Measure is under development.

Office of Central Services Performance Metrics Objective 1.2- Percentage of contract dollars awarded to diverse suppliers as outlined in the Jobs First Act at or above 30%, FY 2019 Proposed Budget

Outdoor advertising regulations and zoning laws reduce visual clutter and protect people from dangerous and illegally installed signs. Signs must comply with regulations outlined in the NYC Construction Codes and the NYC Zoning Resolution. This dataset lists all sign applications filed in New York City.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

This Indicator measures the hourly wage for all workers ages 16 and older and compares it to the 2016 Oakland living wage ($14.86 per hour). Hourly wages are calculated by dividing the total person’s earnings by the product of the weeks worked and the usual hours worked per week during the past 12 months. The weeks worked variable was set to the midpoint of the interval included in the ACS data. Only workers with non-zero earnings, who were not self- employed or unpaid family workers, and who were at work or had a job but were not at work last week were included in the analysis. (Source for methodology: http://laborcenter.berkeley.edu/pdf/2014/chartbook-data-and-methods.pdf)

This Indicator measures the percent of the unemployed population (ages 16 and up) in Oakland by race/ethnicity who did not participate in the City of Oakland’s Workforce Development program between 7/1/2016 and 6/30/2017. The percent that did participate for each race/ethnicity is calculated by dividing number of participants of that race/ethnicity by the number of unemployed people in the labor force in Oakland of that race/ethnicity. Percent that did not participate is 100% minus the percent that did participate. NOTE: Participation is not the most meaningful metric, but was the data available. In the future, we hope to replace this with a measurement of exit outcomes for participants by race/ethnicity (i.e., did participants successfully find jobs?).

All incident segments for each of the first responding agencies (PD, FD and EMS) that contribute to the end-to-end response times. This data set provides call volumes broken down by incident type for each Week Start time period as well as the timestamps and average response times (in seconds) for each segment of the call.

For the Incident Type Definitions please refer to this link.

Number of workers commuting to Pierce County from other counties in Washington. Data is sourced from LEHD Origin-Destination Employment Statistics (LODES). Sample Universe: Workers 16 years (members of the Armed Forces and civilians) who were at work during the reference week.

Data is from the Local Area Unemployment Statistics (LAUS), a Federal-State cooperative effort in which monthly estimates of total employment are provided. Update Frequency: Monthly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

Percent of residents employed and working outside the home where commuting times to their place of work less is than 30 minutes.

The Business Source Center (BSC) Program, funded through the Community Development Block Grant (CDBG), provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small business the support they need to start and/or expand their business. Goals are established through United States Department of Housing and Urban Development (HUD) guidelines and local measures.

The information included in this dataset is for the Governor’s Executive Budget and provides key Program Measures by Agency or Office.

This data set shows the number of businesses and total for establishments that operate without employees

BOSL4 Measure K Performance

Texas Code, Texas Enterprise Zone Agreements

This dataset is part of the DOB NOW Electrical Permit Data Collection: https://data.cityofnewyork.us/browse?Data-Collection_Data-Collection=DOB+NOW+Electrical+Permits+Data This dataset contains general information about the job filing, including location, applicant, type of work and fee information. Each instance of electrical work might have one row/record for the Initial application, as well as one or more Post Approval Amendment or Subsequent Filing. (See Filing_Type field.)

Jobs_Housing_Fit_Ratio

Unemployment rate data for census tracts in Hamilton County from 2013 to 2018

Healthy Housings data for Get Healthy San Mateo County's Healthy Cities SMC: http://www.gethealthysmc.org/healthy-cities-smc

DECD's listing of direct financial assistance to businesses from July 1, 2009 through June 30, 2024. New projects are usually added quarterly, but updates may be made on an ongoing basis.

Small Business Boost loan recipients can be found here: https://data.ct.gov/d/yk65-8y82

An application to work on an Antenna, a device, usually placed at the highest possible height, that transfers electrical signals across air or wires and can receive, transmit, or broadcast signals to singular or multiple locations.

Increase the number of EDI awards.

This data set contains employment projections, educational levels, average wages for projected jobs in Washington County.

Total Jobs by Industry, Historic 2001 to 2018 and Projected 2020 to 2040 in Prince George's County by Industry and by Place of Work

Not all households in San Mateo County enjoy the opportunities that its high-performing economy has to offer. DOH's goal is to increase the rate at which the County’s disenfranchised residents are able to access the opportunities the county has to offer by encouraging affordable housing development in the HOJR areas.

A list of permits issued by the Department of Buildings from 1989 to 2013. This dataset was originally released to provide data from before the DOB Permit Issuance dataset began. DOB Permit Issuance has since been updated to incorporate this date range, and this historical dataset is now redundant.

State employee salary, benefits and expense reimbursement information starting with fiscal year 2015. For the purpose of this report, all employees of the Department of States Attorneys and Sheriffs are included. Employees in the respective county offices , such as States Attorneys, Sheriffs and Deputy States Attorneys are County employees not State employees. To access the pay and expense data for Fiscal years 2009-2014, please see data set: Total Pay and Expenses FY2009-2014. NOTE: Individuals covered by the Safe At Home Act (Title 15 Sections 1150-1160) have been excluded from this list. 2017 Change - Temporary employees now earn sick leave per 21 V.S.A. § 487. Capping this data set at five years. Please see new data set Total Compensation and Expenses FY2020 - 2021 for the next five year set

City of Janesville TIF Development Agreements dating back to 2013

Employment and training services under the WIOA adult program serves eligible adults 18 years and over who are unemployed, underemployed, low-income adults who are willing to improve their careers, or change their living style from poor wage to a livable wage. This data shows program service outcomes by demographic markers : Race and ethnicity, gender and age group.

Number of jobs attracted and retained through EDC efforts.

Total Jobs by Industry, Historic 2010 to 2020 and Projected 2025 to 2050 in Maryland by Industry and by Place of Work.

This performance indicator measures the estimated number of jobs created and retained attributable to EDA investments made in/to underserved communities and populations.

Government Employment in Utah, data from the US Bureau of Labor Statistics, downloaded on 2/10/2016. Employment numbers in 1000s.

The Title and Salary Listing is a compilation of job titles under the jurisdiction of the Department of Civil Service.

This collection contains applications submitted online via "DOB NOW: BUILD" portal by Design Professionals to get an authorization to begin work on an elevator project.

Data in this collection is limited to applications (job filings) related to elevator applications only (also known as ELV1) submitted on DOB NOW, and includes Initial (New), subsequent, and Post Approval Amendment (PAA) filing types.

DOB NOW: BUILD is an online portal that allows users to file for permit applications, check the status of an application, make payments, schedule appointments, and print permits.

This dataset contains general information about the job filing, including location, applicant, type of work and fee information. Each instance of elevator work might have one row/record for the Initial application, as well as one or more Post Approval Amendment. (See Filing_Type field.)

Cache County Seasonally Adjusted Unemployment Rate 1990-2015

Annual salaries paid to employees by the Cook County Comptroller as of August 28, 2014. For 2015 data see https://datacatalog.cookcountyil.gov/d/9tzu-m4zi.

Annual salaries paid to employees by the Cook County Comptroller as of November 24, 2015. This dataset does not include salaries for Cook County Forest Preserves.

This dataset is no longer updated. Newer data is available at https://datacatalog.cookcountyil.gov/d/xu6t-uvny.

For 2014, see https://datacatalog.cookcountyil.gov/d/hdna-35se.

State employee salary and expense reimbursement information for the fiscal years 2009 through 2014. Starting with fiscal year 2015, this data is in a new data set with additional benefits data, please see data set: Total Compensation and Expenses FY2015-19 and Total Compensation and Expenses FY2020- *Notes: From time to time, pay categories for reporting purposes are reviewed and adjusted. Paid leave has been re-categorized from "other pay" to "pay." Total pay is not affected.
Base pay for certain law enforcement positions includes premium pay at overtime rates for a specified number of regularly scheduled hours each pay period. Within FY13/14, categorization of this premium base pay has been reviewed and adjusted. It has been re-categorized to "pay" from "overtime." Total pay is not affected. It was adjusted back to "overtime" in Jan.2014

The Connect Community program is offered as an alternative to the Main Street program through the Wisconsin Economic Development Corporation. As a Connect Community, the City of Janesville is required to attend three training events and file an annual report on the business and real estate activity occurring in the downtown over the previous year.

Dataset captures the number of jobs supported by calendar year (CY)

Employment, investment and tax credit information reported by businesses certified in the Empire Zones Program.

This performance indicator measures the number of jobs created and retained by communities and regions attributable to the EDA grant to support workforce development through training.

This measure provides an indication of whether the Comprehensive Economic Development Strategy process is market based and whether EDA is helping to create an environment conducive to the creation and retention of higher skill, higher wage jobs. Research conducted on 2002 data established a baseline measure for subsequent years.

Percent of the resident population between ages 24 and 34.

This data set provides information on each payment and completed compliance report associated with all executed Chapter 380 agreements. This information is updated regularly to include new payments and adjustments.

Do not use this dataset. It does not actually provide Property Data in its current form. We are working on improvements to the dataset to more accurately reflect its title and original intent.

This dataset reveals the employees of the City of Austin that are currently paid under the per hour living wage.

This dataset supports measure(s) EOA.B.5 of SD23 . Data Source: Banner

This is a data report that did not require a calculation.

Measure Time Period: Annually (Fiscal Year)

Automated: No

Date of last description update: 9/26/22

More information related to measure can be viewed on its story page : https://data.austintexas.gov/stories/s/hynm-5nw6

Industrial Development Agencies (IDA) are required by section 859 of General Municipal Law to submit annual financial statements and are required by Section 2800 of Public Authorities Law to submit annual reports to the Authorities Budget Office. The reported information includes financial assistance provided by the IDA and job creation/retention for each project receiving assistance. The dataset includes project data as reported by each IDA that covers 8 fiscal years, which includes fiscal years ending in the most recently completed calendar year.

Public authorities are required by Section 2800 of Public Authorities Law to submit annual reports to the Authorities Budget Office that includes grants data. Local Development Corporations are required to report information on the projects they support and how those approved projects are financed (either through grants, loans, or bonds). The dataset consists of grants data reported by Local Development Corporations that covers 8 fiscal years, which includes fiscal years ending in the most recently completed calendar year.

Note this dataset is no longer being updated. Please use the updated payroll dataset with current pay year information: https://controllerdata.lacity.org/Payroll/City-Employee-Payroll-Current-/g9h8-fvhu.

Payroll information for all Los Angeles City Employees including the City's three proprietary departments: Water and Power, Airports and Harbor. Data is updated on a quarterly basis by the Los Angeles City Controller's Office. Payroll information for employees of the Department of Water and Power is provided by the Department.

Percentages of Corona employment by industry. Data provided by a report from the City of Corona Economic Development team. Update Frequency: Yearly Data Disclaimer: The City Of Corona (“Corona”) provides data available on this website as a service to the public. The data provided by Corona is based on historical data, information directly provided by Corona, information directly provided by Corona contractors and in some cases, information acquired during physical inspections. Corona does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing the public with information regarding this program and not for any commercial, legal or other use. Corona assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. Corona reserves the right to alter, amend or terminate at any time the display of this data.

This dataset contains information on estimated proposed salaries by position for all Cook County employees excluding the Forest Preserves of Cook County. Salaries are budgeted based on the fiscal year which is the 12 month period that begins on December 1 and ends on November 30 of the succeeding year. The Budgeted Salary does not include fringe benefits such as Medical Insurance, Dental Insurance, etc. The Budgeted Salary and position title may change throughout the fiscal year; any such changes will not be updated in this dataset.

It may be helpful to know the Job Code contained in the dataset is a unique 4-digit number assigned to each specific Job Title while the Position ID is a unique 8-digit number that identifies a position. This helps create consistency and accuracy in the dataset over time, in case of a name change or other change.

Cook County voluntarily provides this dataset as a service to the public. Cook County makes no warranty, representation, or guaranty as to the content, accuracy, timeliness, or completeness of any of the data provided at this website. Cook County shall assume no liability for: 1. any errors, omissions, or inaccuracies in the data provided at this website regardless how caused; or, 2. any decision made or action taken or not taken by anyone using or relying upon data provided at this website. Cook County assumes no liability for any virus or other damage to any computer that might occur during or as a result of accessing this website or the data provided herein.

State employee salary, benefits and expense reimbursement information starting with fiscal year 2020. For the purpose of this report, all employees of the Department of States Attorneys and Sheriffs are included. Employees in the respective county offices , such as States Attorneys, Sheriffs and Deputy States Attorneys are County employees not State employees. To access the pay and expense data for Fiscal years 2009-2014, please see data set: Total Pay and Expenses FY2009-2014. To access the previous 5 years of this data set, please see: Total Compensation and Expenses FY2015-2019. NOTE: Individuals covered by the Safe At Home Act (Title 15 Sections 1150-1160) have been excluded from this list. 2017 Change - Temporary employees now earn sick leave per 21 V.S.A. § 487. NOTE: Family and Medical Leave Insurance (FMLI) in Fiscal Year 2024 was not paid for by departments. In Fiscal Year 2025 it will be paid for by departments and included in the Total Compensation and Expenses report. This data set will be capped when it reaches five fiscal years of data.

Job Referrals Made to Employers on Behalf of Students with Disabilities while Still in High School

The Montgomery County Government has a diverse workforce of employees that cross five generations and multiple age, race, gender and ethnic groups. The dataset is a summary of the County's size and composition by generational category, age, race, ethnicity, gender, years of service and job class. Update Frequency : Annually

Source: U.S. Census Bureau, OnTheMap Application and LEHD Origin-Destination Employment Statistics (Beginning of Quarter Employment, 2nd Quarter of 2002-2014). Selection area is TID 36 - Downtown boundary. Note: Educational Attainment is only produced for workers aged 30 and over.

Small Business Improvement Fund data includes all projects that have received a final grant payment since January, 2001. SBIF uses TIF revenues to provide reimbursement grants to small commercial and industrial businesses and property owners to help fund permanent improvements to their buildings and improve the appearance of their neighborhoods.

Annual report totals.

County workforce job data, demographics, and job categories as defined by the Equal Employment Opportunity Commission. More information about the job categories can be found in Appendix 2 at the following link: https://eeocdata.org/EEO4/howto/instructionbooklet

A listing of DECD administered tax credits that have been allocated and/or earned for projects with agreements executed from FY 2014- February 2025.

Please note- Film, Television & Digital Media tax credit activity has been removed from this dataset and can be found here: https://data.ct.gov/Business/DECD-Film-TV-and-Digital-Media-Tax-Credit-Activity/kjsu-mdny

emp_chg_2010_2040_em_poly

Montgomery County public employees are required to obtain approval from the Ethics Commission for any employment other than County service. This dataset contains all currently active approvals of outside employment requests. For approvals that have expired, refer to the Ethics Commission website at https://montgomerycountymd.gov/ethics/oe/OEapproved.html. Update Frequency : Monthly

This dataset includes information on economic development projects that have been awarded incentives through Iowa Economic Development Authority programs as early as FY 2003, have signed contracts with the state and are in either the “performance” period, the “maintenance” period or are "in default" as of the end of the fiscal year noted. In most cases, projects are required to have met job, wage and capital investment obligations by their “Project Completion Date”. Beyond the completion date, projects are required to maintain the obligated jobs and investment through the “Maintenance Date." All projects provide information on total project costs, capital investment, as well as the amount of direct assistance and tax credits awarded to the project. Projected and contracted job data is available for all projects. However, project completion jobs and reported jobs is only available for those projects in the "maintenance" period. Projects in the "performance" period are still in the process of being implemented and are not yet complete. Projects in Default were considered “in default” as of the end of the annual report cut-off date (typically end of fiscal year). The status “in default” is a temporary one since businesses are allowed a contractually designated cure period to correct the default. Reasons for being considered “in default” range from not filing required reports to not creating the obligated jobs or investment required by the contract.

Affidavit Details - Journey Level Trades And Wage Rates

Cost per client receiving Vocational Rehabilitation services. Human Services Agency performance measure 7330P ID 552.

A Certificate of Occupancy (CO) states a building’s legal use and/or type of permitted occupancy. New buildings must have a CO, and existing buildings must have a current or amended CO when there is a change in use, egress or type of occupancy. No one may legally occupy a building until the Department has issued a Certificate of Occupancy or Temporary Certificate of Occupancy. The Department issues a final Certificate of Occupancy when the completed work matches the submitted plans for new buildings or major alterations. It issues a Letter of Completion for minor alterations to properties. These documents confirm the work complies with all applicable laws, all paperwork has been completed, all fees owed to the Department have been paid, all relevant violations have been resolved and all necessary approvals have been received from other City Agencies.

This dataset contains all Certificates of Occupancy issued since 7/12/12.

This dataset is for historical reference only. For current information see https://datacatalog.cookcountyil.gov/d/6ybd-qcyy. Data last updated March 26, 2012. Exhibit B of the Cook County Employment Plan, shows all Shakman Exempt positions for each department in the Offices Under the President. Department, Job Title, Job Code, Position ID and link to Job Description are included.

This dataset includes information on economic development projects were awarded incentives through Iowa Economic Development Authority programs as early as FY 2003, and are considered “completed” by IEDA’s compliance team at the end of the fiscal year (annual report cut-off date). Each project has been evaluated to determine if the it met all the terms of the contract. If all contractual terms are met, projects are categorized as "successful" and are under no additional obligation to report information to IEDA regarding the project. If a project was unable to meet all terms required in the contract, the IEDA compliance team determined the award “recapture” – consisting of paying back all or a portion of the direct assistance provided by the state or returning (or not claiming) some or all tax credits that had been awarded. These projects would be categorized as either “full recapture” or “partial recapture” of the award.

THIS DATASET IS NO LONGER UPDATED In November 2018, the City-Parish switched to a new payroll system. We are in the final stages of adding employee data from the new system into Open Data BR. This data can be used to see employees as of the last day in the former payroll system.

City-Parish employees, both active and inactive, that exist in the City-Parish Payroll System.

Public authorities are required by Section 2800 of Public Authorities Law to submit annual reports to the Authorities Budget Office that includes loans data. Local Development Corporations are required to report information on the projects they support and how those approved projects are financed (either through grants, loans, or bonds). The dataset consists of loans data reported by Local Development Corporations that covers 8 fiscal years, which includes fiscal years ending in the most recently completed calendar year.

Percent of eligible foster youth enrolled in college and vocational training. Human Services Agency performance measure 7440P ID 547.

The Bipartisan Infrastructure Law (BIL) is the largest long-term investment in our infrastructure in nearly a century. Signed into law by President Joe Biden on Nov. 15, 2021, this historic act will make life better for millions of Connecticut residents and create economic growth. To date, Connecticut has received $6.4 billion in Bipartisan Infrastructure Law (BIL) funding with over 167 specific projects identified for funding. Many more projects will be added in the coming months, as funding opportunities become grant awards and as formula funds become specific projects. By reaching communities across Connecticut – including rural communities and historically underserved populations – the law makes critical investments that will improve the lives of Connecticut residents and position the state for success.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC NTAs since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

Dataset includes information about the job that creates and sends payroll direct deposit file to the bank and the job the imports timecards into the payroll system. Note this dataset received updates on the Wednesday following the bi-weekly pay period.

Data Description: This dataset lists all current City of Cincinnati employees, including full names, department, position title, full-time employee status, employee age range, employee race, and annual salary rate.

Data Creation: This data is pulled directly from the City's HR software; which centralizes all department HR actions city wide.

Data Created By: City Human Resource Information System (CHRIS)

Refresh Frequency: Daily

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/Employee-Profile/wjqv-hgc9/

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Property Tax Abatement data includes all projects that have received a supporting City Council Ordinance since January, 2011. Cook County offers several property tax incentive programs that promote economic development and employment opportunities by reducing property taxes on qualifying properties for a fixed period. The Department of Planning and Development reviews applications for compliance with program eligibility requirements.

All permits issued through the Planning & Development permit center. Includes building, mechanical plumbing, garage sales and others. Data is updated monthly and may not reflect recent activity.

Economic impacts of the 15 Division of Science, Technology and Innovation (NYSTAR) Centers for Advanced Technology (CATs).

The City’s certification programs, including the Minority and Women-owned Business Enterprise (M/WBE) Program, the Emerging Business Enterprise (EBE) Program and the Locally-based Business Enterprise (LBE) Program certify, promote, and foster the growth of the City’s minority and women-owned businesses and eligible small construction and construction-related businesses. Companies that become certified obtain greater access to and information about contracting opportunities, receive technical assistance to better compete for those opportunities, and benefit from inclusion in the City’s Online Directory of Certified Firms. This list contains detailed information on certified companies, including a brief description of their work history, contact information, and detailed information about what the companies sell. This data is up to date as of the date reflected in the "About" tab of this dataset.

This dataset includes information on economic development projects that were awarded incentives through Iowa Economic Development Authority programs as early as FY 2003, but selected not to move forward in receiving funding. This doesn’t necessarily mean that the project didn’t or won't take place. Projects include those whose awards were declined, rescinded or terminated.

Data on County employee demographics and job categories and functions as defined by the Equal Employment Opportunity Commission. More information about the job categories and functions can be found in Appendix 2 and Section 5C at the following link: https://eeocdata.org/EEO4/howto/instructionbooklet

Texas Code, Chapter 380 Payments & Compliance Dataset

Budgeted Salaries by Position

City-Parish employees' annual salaries and other payroll related information. Information is calculated after the last payroll is run for the year specified. Some fields, such as job title and department, are accurate as of the time the data was captured for Open Data BR. For example, if an employee worked for three departments throughout the year, only the department they worked for at the time we collected the data will be shown.

***In November of 2018, the City-Parish switched to a new payroll system. This data contains employee information from 2018 onward. For prior year data, please see the Legacy City-Parish Employee Annual Salaries https://data.brla.gov/Government/Legacy-City-Parish-Employee-Annual-Salaries/g5c2-myyj

First & last name, work email address, work phone, job title and job location for all active Texas Lottery Commission employees.

OPT does not operate any buses nor does it directly employ any bus drivers or attendants. Drivers and attendants (sometimes referred to as ‘matrons’ or ‘escorts’) and employed by bus vendors themselves. OPT manages systems and processes to ensure that drivers and attendants have all requisite background checks and certifications. The Driver and Attendant summary data is available for each bus vendor and describes the number of active employees by job type.

Annual salaries paid to employees by the Cook County Comptroller as of September 22, 2011. Does not include deduction for furlough or closure days for employees subject to furloughs and closures. Does not include amounts paid by other governmental entities. For 2014 salaries see https://datacatalog.cookcountyil.gov/resource/hdna-35se

This dataset relates work completed for the purpose of installing and maintaining roadway markings and street signs across the City of Austin. Each row records time spent by one or more technicians who completed the work order. This work is managed by the Signs & Markings Division of the City of Austin Transportation Department.

You may also be interested in these related datasets, which can be joined together using the work order ID columns:

• Road Markings Work Orders: https://data.austintexas.gov/Transportation-and-Mobility/Roadway-Markings-Work-Orders/nyhn-669r
• Road Markings Jobs: https://data.austintexas.gov/dataset/Work-Order-Markings-Jobs/vey3-7n3x
• Signs Work Orders: https://data.austintexas.gov/dataset/Work-Order-Signs/ivss-na93
• Signs and Markings Reimbursements: https://data.austintexas.gov/dataset/Signs-and-Markings-Reimbursement-Tracking/pma8-yy5k

To ensure the timely preparation of financial statements, for both internal and external users, the financial period close should occur 5 business days after the period end. This dataset contains information from the Advantage FIN system related to when statements are posted relative to the period end.

City-Parish employees, both active and inactive, that exist in the City-Parish Payroll System. The information includes employee current pay information, including any special pay. Special pay is earned per pay period.

***In November of 2018, the City-Parish switched to a new payroll system. This dataset contains employee information from this new system. For data prior to 2018, please see the Legacy City-Parish Employees at https://data.brla.gov/Government/Legacy-City-Parish-Employees/gyhq-w3h3

The Agency Report Table aggregates pay and employment characteristics in accordance with the requirements of Local Law 18 of 2019. The Table is a point-in-time snapshot of employees who were either active or on temporary leave (parental leave, military leave, illness, etc.) as of December 31st of each year the data is available (see Column "Data Year"). In addition, the Table contains snapshot data of active employees in seasonal titles as of June 30th. To protect the privacy of employees, the sign “<5” is used instead of the actual number for groups of less than five (5) employees, in accordance with the Citywide Privacy Protection Policies and Protocols. The Pay and Demographics Report, and the list of agencies included is available on the MODA Open Source Analytics Library: https://modaprojects.cityofnewyork.us/local-law-18/

Each row represents a group of employees with a common agency, EEO-4 Job Category, pay band, employee status and demographic attributes, which include race, ethnicity and gender.

Instances when department called the police department for assistance at a job center or SNAP center, disaggregated by: (a) Whether a department employee witnessed an arrest being made; (b) Whether a department employee witnessed a police officer displaying a firearm, oleoresin capsicum spray, conducted electrical weapon, baton, or any other weapon.

Summary by Department of State of Vermont Executive Branch employees, separated by job type, providing a count and FTE's represented in the count. Data is refreshed on the last Friday of every month

THIS DATASET IS NO LONGER UPDATED In November 2018, the City-Parish switched to a new payroll system. This dataset contains annual salaries through 2017. For data from 2018 onward, visit https://data.brla.gov/Government/City-Parish-Employee-Annual-Salaries/g9vh-zeiw

City-Parish employees' annual salaries and other payroll related information. Information is calculated after the last payroll is run for the year specified.

This program has ended. Please see notes below and datasets for past clients.

Reporting covers July 1 to June 30, annually. For more information on Oregon's program visit https://www.oregon.gov/biz/programs/NMTC/Pages/default.aspx

Please see notes regarding specific columns in the table below.

Eligibility Determination made by Community Development Entity - *Wells Fargo Community Development took over the credits for Albina Community Bank when they ceased operations.

Total Costs of Professionals Fees - *CDE does not charge fees.

Maximum Amount of Tax Credit Made Available to Quality Equity Investor in Current Tax Year - * Advantage Capital has one QEI

Scored report tracking Cash Assistance Job Center performance.

Compliance Reports

Number of individuals enrolled in Medical Assistance Benefits for Workers with Disabilities (MAWD) by Ethnicity with Workers with Job Success (WJS). Total for all Ethnicities for each month is included in the dataset with the Total label.

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks. Data files are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2013. To browse the LODES data files in their directory structure or to access them with a FTP program (must be able to access HTTP), go to http://lehd.ces.census.gov/data/lodes/.

Check out the data dictionary at http://celebratingcities.github.io/docs.html

Annual City employee earnings for calendar-year 2017. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This measure highlights change in jobs that communities or businesses generate or save due to Sea Grant assistance (i.e., providing information to help communities, industries or businesses expand, make better decisions or avoid mistakes). Sea Grant provides the information and training that informs business decisions, and in some cases firms create or sustain jobs as a result. A job created is a new position created and filled as a result of Sea Grant activities. An existing position that is filled with a Sea Grant-trained applicant should not be reported in this measure. A job sustained is an existing, filled position that is sustained as a direct result of Sea Grant activities. A job cannot be reported as both created and sustained in the same year.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC Census Blocks since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

This dataset displays the current salaries for City of Little Rock employees. Some employees are hourly. Their pay is reflected as an hourly rate.

At universities throughout the state, Centers of Excellence (COEs) encourage industry-university collaboration in developing and applying new technologies from nanoelectronics and materials to automation and biotechnology.

Economic Impacts of the 10 Division of Science, Technology and Innovation (NYSTAR) National Institute of Standards and Technology (NIST) Manufacturing Extension Partnership (MEP) Regional Technology Development Centers (RTDC).

This metric tracks workforce employment services including basic services, skills training and job placement per month. DFSS provides workforce development services to low income adults, dislocated workers and ex-offenders. These services include job readiness training, vocational training, job placement, supportive services and post-placement retention services. The Chicago-Cook Workforce Partnership, a newly created agency designed to reform and revitalize workforce development in the greater Chicagoland area, took over operation of DFSS’s Workforce Investment Act funding and delegate agency contracts on July 1, 2012. http://www.workforceboard.org

This dataset contains counts of full-time staff, aggregated at the state, district, and school level. Additionally, the data are aggregated by job classification, education level, gender, race, and experience.

Pursuant to Section 2-573 of the Cook County Code of Ethics, officials that hold employment outside their elected office shall disclose such employment, or any change in employment to the Ethics Director and the Board of Ethics within 30 days of engaging in such employment or change in employment. Such disclosures by officials should be posted and made publicly available on the Ethics Departments web-page.

The number of reportable job-related incidents that result in the inability of an employee to perform full job duties for at least one working day beyond the day of the incident, as well as a breakdown of the number of Employees and Lost Time Accident Rates.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC City Council Districts since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

Infill enforcement data for Community Standards Peace Officers

Neighborhood Opportunity Fund, Large Project data includes all projects that have received a final grant payment. Large Projects have grants over $250,000 and are required to obtain City Council approval, as well as have a full Redevelopment Agreement governing the terms of the grant. The Neighborhood Opportunity Fund (“NOF”) receives funds from downtown development in order to support the growth and creation of inclusively vibrant commercial corridors in Chicago’s underserved neighborhoods. Business and property owners may apply for grant funding that will pay for the development or rehabilitation of real estate and projects that support new or expanding businesses or cultural assets.

Public authorities are required by Section 2800 of Public Authorities Law to submit annual reports to the Authorities Budget Office that includes bonds data. Local Development Corporations are required to report information on the projects they support and how those approved projects are financed (either through grants, loans, or bonds). The dataset consists of bonds data reported by Local Development Corporations that covers 8 fiscal years, which includes fiscal years ending in the most recently completed calendar year.

Number of individuals enrolled in Medical Assistance Benefits for Workers with Disabilities (MAWD) with Job Success ( WJS) by Language. Total for all Languages for each month is included in the dataset with the Total label.

Data is suppressed to ensure personally identifiable information is not indirectly revealed in instances where the data is less than 11 records.

Infill enforcement data for Lot Grading Inspectors

This data set contains job projections for Salt Lake County through 2022. It contains educational levels, average wages, work experience, annual openings, etc.

This dataset is part of the DOB NOW Electrical Permit Data Collection: https://data.cityofnewyork.us/browse?Data-Collection_Data-Collection=DOB+NOW+Electrical+Permits+Data This dataset contains details of the electrical scope of work. For each Job Filing Number, there can be multiple rows/records in this dataset. For example, there might be electrical work being performed in the basement as well as on the 4th floor. One row/record for Basement and one for the floor. The job might have some 101 to 200 amps Service Switches as well as some Up to 100 amps Service Switches, and there would be one row/record for each.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC Community Districts since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

Aggregate monthly wait times for clients at Job Center services.

This dataset provides base salary information about City of Norfolk employees. This data is provided by Norfolk's Department of Human Resources and is updated daily.

This dataset includes detailed information regarding the use of TIF for all economic development projects with a City Council approved TIF redevelopment agreements (RDAs) since January, 2011. This does not include approved RDAs for affordable housing, approved intergovernmental agreements (IGAs), or TIF-funded public infrastructure. For more information on the Tax Increment Financing program including a full list of all TIF-funded projects, please see http://cityofchicago.org/tif.

Employee payroll data for all Cook County employees excluding Forest Preserves, indicating amount of base salary paid to an employee during the County fiscal quarter. Salaries are paid to employees on a bi-weekly basis. Any pay period that extended between quarters will be reported to the quarter of the Pay Period End Date. (e.g. If a Pay Period runs 02/21-03/05, that pay period would be reported in the Q2 period, as the end of the pay period falls in March - Q2)

The county fiscal quarters are: Q1: December - February Q2: March - May Q3: June - August Q4: September - November

The Employee Unique Identifier field is a unique number assigned to each employee for the purpose of this data set, that is not their internal employee ID number, and allows an employee to be identified in the data set over time, in case of a name change or other change. This number will be consistent within the data set, but we reserve the right to regenerate this number over time across the data set.

ISSUE RESOLVED: As of 4/19/2018 there was an issue regarding employee FY2016 and FY2017 payroll in which records were duplicated in the quarterly aggregation, resulting in inflated base pay amounts. Please disregard any data extracted from this dataset prior to the correction date and use this version moving forward.

KNOWN ISSUE: Several records are missing Bureau and Office information. We are working on correcting this and will update the dataset when this issue has been resolved.

For data prior to Fiscal Year 2016, see datasets at https://datacatalog.cookcountyil.gov/browse?tags=payroll

Schedule of recruitment events offered by Workforce1 Center. This data is up to date as of the date reflected in the "About" tab of this dataset.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC Census Tracts since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

The data represents the percent change in wages for an individual who has wages recorded in the Unemployment Compensation (UC) wage record file in the quarter in which they completed Industry Partnership training and wages found in the UC wage record file for that individual four quarters later. The change could be an increase or a decrease in wages. For example, if an individual completed training in the third quarter of 2013 and earned $5,000 in that quarter and earned $7,500 in the third quarter of 2014 the percent change for that individual would be 50%. The file incudes a count of all individuals who benefited from industry partnership training, the workforce development area of the industry partnership, the training program completed and the percentage change in wages per individual training. The top line of the file includes the overall percentage change for all trainings.

*The goal for Labor & Industry is based on receiving $10 million to fund Industry Partnerships.

This dataset is for Program Year 2013-2017 and will be updated annually due to federal release schedule. There are many reasons why an individual’s wage may have changed dramatically. Some of the reasons for negative wage changes or large increases in wages are listed below (not an exhaustive list). • An individual may have left the job, was laid off, or retired within the year after they were trained. • An individual may have become ill and left work. • An individual may have accepted a job in or moved to another state. • An individual may have been working two jobs and switched to one, or vice versa. • An individual’s hours may have been reduced/increased during a quarter. • Overtime hours may have been reduced/increased during a quarter. • An individual may have taken family leave. • A bonus could have been paid right after training was completed. • Wage records may not have been reported. • An employer may have closed and laid off all of their employees.

Commercial and Residential building permit applications from January 2011 to Jun 30, 2020

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

Annual certifications of facility to receive Oregon Investment Advantage tax benefit under ORS 316.778 or 317.391 for Fiscal Years 2016-2024, for which much of this information is not otherwise maintained in any database. Additional (recent) documentation of certification applications required by ORS is attached as well.

For more information visit https://www.oregon.gov/biz/programs/OIA/Pages/default.aspx

This is a multi-year salary report for the Oregon Lottery. Visit the Oregon Transparency Program website for more information. https://www.oregon.gov/transparency/Pages/index.aspx. Or, visit the Oregon Lottery at https://www.oregonlottery.org/about/.

This dataset contains information about the New York City Housing Authority’s (NYCHA) Office of Resident Economic Empowerment and Sustainability (REES). REES supports NYCHA public housing and Section 8 residents’ increased income and assets through programs, policies and formal partnerships in the areas of employment and advancement, adult education and training, financial literacy and asset building and resident business development. Each row in the dataset represents the number of public housing residents on a NYCHA Development-level who receive or utilize this service. Data on interagency collaborations such as Jobs-Plus and Business Pathways are not part of this data but are accounted for in NYC Business Solutions and Human Resources data respectively. As per HUD regulations REES serves NYCHA public housing, NYCHA Section 8 and Section 3 residents.

The dataset is part of the annual report compiled by the Mayor’s Office of Operations as mandated by the Local Law 163 of 2016 on different services provided to NYCHA residents. See other datasets in this report by searching the keyword “Services available to NYCHA Residents - Local Law 163 (2016)” on the Open Data Portal.

This data set includes certificates of occupancy issued through the New York City Department of Buildings' DOB NOW: Certificate of Occupancy module. This module was released in March of 2021, anbd from that point onward this data set should be utilized instead of the "DOB Certificate of Occupancy" data set. The data is collected because the Department of Buildings tracks Certificates of Occupancies issued. This data include items such as job filing name, job filing label, BIN, Address, and Certificate of Occupancy status, sequence, label, and issuance date.

"A Certificate of Occupancy (CO) states a legal use and/or type of permitted occupancy of a building. New buildings must have a CO, and existing buildings must have a current or amended CO when there is a change in use, egress or type of occupancy. No one may legally occupy a building until the Department has issued a CO or Temporary Certificate of Occupancy (TCO).

A CO confirms that the completed work complies with all applicable laws, all paperwork has been completed, all fees owed to the Department have been paid, all relevant violations have been resolved, and all necessary approvals have been received from other City Agencies. The Department issues a final CO when the completed work matches the submitted plans for new buildings or major alterations."

Credits claimed against the CT Personal Income Tax. For more recent tax data, see Connecticut Personal Income Tax Summary.

Annual City employee earnings for calendar-year 2019. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

The Los Angeles BusinessSource Centers provide startup ventures and current small business owners various cost effective tools to make their business a success. Through these tools, small businesses can grow and remain competitive within the City of Los Angeles.

Microenterprise: Prestartups focuses on providing critical support to entrepreneurs and to prospective new business owners, focusing on low and moderate-income clientele living in the City.

Contact information for the Seattle Department of Construction and Inspections' staff, including name, title, phone, email, supervisor name, and workgroup.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/FY2014-Business-Development-Program/FY2014-Business-Development-Program-Report/r5hg-r2wf

Neighborhood Opportunity Fund, Small Project data includes all projects that have received a final grant payment. Small Projects may have grants up to $250,000 and must be located in an Eligible Commercial Corridor. The Neighborhood Opportunity Fund (“NOF”) receives funds from downtown development in order to support the growth and creation of inclusively vibrant commercial corridors in Chicago’s underserved neighborhoods. Business and property owners may apply for grant funding that will pay for the development or rehabilitation of real estate and projects that support new or expanding businesses or cultural assets.

Certified models meet all ENERGY STAR requirements as listed in the Version 3.0 and Version 3.1 ENERGY STAR Program Requirements for Imaging Equipment that are effective as of October 11, 2019 and the V3.2 Program Requirements that are effective as of November 18, 2021. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/office_equipment/imaging_equipment/key_product_criteria

This dataset highlights the General Salary Schedule (GSS), Police Leadership Service (PLS) and Management Leadership Services (MLS) salary adjustments from Fiscal Year 2015 to current. The additional Salary Schedule information can be viewed at https://www.montgomerycountymd.gov/HR/compensation/Compensation.html

Permits issued by the Department of Buildings. This data is replaced on a daily basis. Historical data is not retained here and should be downloaded by the user on a daily basis for recording purposes.

The City funds a number of full-service WorkSource Centers in the City of Los Angeles that provide a full range of assistance to job seekers and employers under one roof. Job seekers can receive career counseling, job listings, labor market information, training referrals, and other employment-related services. Employers can avail themselves of business services such as recruiting, posting job vacancies, human resources services, and customized training.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

This is the number of individuals enrolled in Medical Assistance Benefits for Workers with Disabilities (MAWD) by Race with Workers with Job Success (WJS). Total for all Genders for each month is included in the dataset with the Total label.

Data showing the changes in assessed valuation and jobs from projects that received Executive Priority.

Net change in housing units arising from new buildings, demolitions, or alterations for NYC Community District Tabulation Areas (CDTAs) since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

The Paycheck Protection Program (PPP) loans provide small businesses with the resources they need to maintain their payroll, hire back employees who may have been laid off, and cover applicable overhead. This data set includes businesses in New Jersey who received PPP funding, how much funding the employer received & how many jobs the employer claims they saved. The NAICS (National Industry Classification) was provided by the loan recipient.

Note: As per SBA, The Paycheck Protection Program (PPP) ended on May 31, 2021 so no updates has been made on this dataset.

Please see attached document on landing page for more details.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

Listing of GED Plus locations. GED plus helps students earn their GED and prepares them for college and career options.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part A of a four (4) part report. A data dictionary and additional notes document are attached as resources; column header numbers (1-8) can be located in the notes document for additional information.

For more information, visit Business Oregon https://www.oregon.gov/biz/programs/enterprisezones

This dataset supports measure CLL.B.2 of SD23 and reports the total number of jobs per North American Industry Classification System [NAICS] codes in the Austin metro area. Data sourced from Creative Vitality Suite.

View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/nhps-8c54

Recreational facilities in New York City Department of Parks & Recreation properties that are accessible to the disabled.

This datasets contains information about NYC Resident Economic Empowerment and Sustainability (REES) service, a service offered by the New York City Housing Authority (NYCHA) that connects residents to services and opportunity through a formal place-based network. Each row in the dataset represents the number of public housing residents on a Borough-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

Workforce Innovation and Opportunities Act Measures This dataset contains Workforce Innovation and Opportunities Act (WIOA) measures covering Title I Adult, Title I Dislocated Workers and Title I Youth programs. This program replaces the Workforce Investment Act, (WIA), program. The Workforce Investment Act (WIA) performance goals and outcomes reported through Program Year 2015 before transitioning to WIOA performance outcomes commencing Program Year 2016.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

Searchable listing of Ethics Liaison Officer Contact Information which includes mailing address, phone number, and email address

Position details for the Adopted Fiscal Year 2017 Budget Summary of Positions by Business Unit. For more information on the budget see http://www.cookcountyil.gov/budget/

Number of individuals enrolled in Medical Assistance Benefits for Workers with Disabilities (MAWD) by County with Workers with Job Success (WJS). Total for all Counties for each month is included in the dataset with the Total label.

Data is suppressed to ensure personally identifiable information is not indirectly revealed in instances where the data is less than 11 records.

The Los Angeles BusinessSource Centers provide startup ventures and current small business owners various cost effective tools to make their business a success. Through these tools, small businesses can grow and remain competitive within the City of Los Angeles.

The Operating Businesses component, defined as employing 6 or more employees, focuses on providing business assistance and training to emerging companies that will give them the highest opportunities for success. The business services provided to the clients shall include, but not be limited to, customized technical business assistance (industry specific) particular to their business needs in order to stabilize the business, increase revenues and increase operational performance which will lead to the greatest impact on their economic viability and increase profitability.

This data set contains job projections for Utah County for years 2012-2022. The data contains annual growth, average wages, educational requirements and job training levels.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

Executive Recommendation for the Fiscal Year 2016 Budget Summary of Positions by Business Unit. For more information on the budget and schedule of public hearings see http://www.cookcountyil.gov/budget/

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

Workforce travel habits - commute times and destinations.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with distance to larger employment centers weighted more heavily. Values are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood.

Dataset contains information on rat inspections.

Rat Information Portal Data Release Notes April 20, 2015

The Rat Information Portal (RIP) is a web-based mapping application where users can view rat inspection data.

Data sources: NYC Department of Health and Mental Hygiene (DOHMH), Division of Environmental Health Pest Control Database

Notes on data limitations: Please note that if a property/taxlot does not appear in the file, that does not indicate an absence of rats - rather just that it has not been inspected. Similarly, neighborhoods with higher numbers properties with active rat signs may not actually have higher rat populations but simply have more inspections.

See our Data Disclaimer: http://www.nyc.gov/rats

Individualize Education Program (IEP) that Include New or Significantly Modified Goals and Specific Steps Toward the Attainment of Competitive Integrated Employment. Successful transition of high school students with disabilities into competitive integrated employment. No Values means the numbers were suppressed less than 10.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/dataset/FY-2014-Renaissance-Zone-Annual-Report/5ihe-rmwc

List of NYPD members of service

Total estimated annual dollar value of utility discounts for businesses approved for ECSP benefits during the fiscal year.

An itemized list of all the expenditures in a fund balance for each TIF district during the Reporting Year.

For the detailed reports for each TIF district for each year, please see https://www.chicago.gov/city/en/depts/dcd/supp_info/tif-district-annual-reports-2004-present.html.

Contractor filing intent details about their wages and trades

TIFWorks data includes all projects that have been completed and received a grant payment since January, 2011. TIFWorks stimulates business success by funding workforce-training costs for companies located in tax increment financing (TIF) districts. With TIFWorks support, businesses can become better equipped to improve performance and productivity, expand product lines and gain new customers.

This report includes data from Enterprise Zone Businesses to begin exemption on qualified property in 2021. This is Part B of a four(4) part report. A data dictionary and additional notes document are attached as resources. For more information, visit https://www.oregon.gov/biz/programs/enterprisezones

This dataset contains information about the New York City Housing Authority’s (NYCHA) Office of Resident Economic Empowerment and Sustainability (REES). REES supports NYCHA public housing and Section 8 residents’ increased income and assets through programs, policies and formal partnerships in the areas of employment and advancement, adult education and training, financial literacy and asset building and resident business development. Each row in the dataset represents the number of public housing residents on a City Council District level who receive or utilize this service. Data on interagency collaborations such as Jobs-Plus and Business Pathways are not part of this data but are accounted for in NYC Business Solutions and Human Resources data respectively. As per HUD regulations REES serves NYCHA public housing, NYCHA Section 8 and Section 3 residents.

The dataset is part of the annual report compiled by the Mayor’s Office of Operations as mandated by the Local Law 163 of 2016 on different services provided to NYCHA residents. See other datasets in this report by searching the keyword “Services available to NYCHA Residents - Local Law 163 (2016)” on the Open Data Portal.

Annual City employee earnings for calendar-year 2018. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This dataset displays state and district level educator data by race and ethnicity for each district, with rows for different years, different educator job groups, and a wide range of indicators. It was created as part of a dashboard supporting the Massachusetts Department of Elementary and Secondary Education's commitment to provide all students with a racially diverse and culturally responsive educator workforce. Total Educators: This displays the annual number and percent of distinct educators who self-reported/identified as the selected Race/Ethnicity as of the first weekday in October of each school year. Data are further disaggregated by job classification group. Educator Retention: This displays the number and percent of educators who were working in the same position from one school year to the next (via consecutive October EPIMS collections). New Hires: This displays the annual number and percent of new hires in the selected Race/Ethnicities. It counts teachers who were reported as "working" in the annual October EPIMS collection who were hired on or after June 1 of the prior school year. This dataset contains the same data that is also published in the Total Educators, Educator Retention, and New Hires tables on our Educator Dashboard.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

Forecasts for Year 2010 through 2040 containing values for Households by Inc. Quartile; Households; Jobs; Population by Gender, Age; Units; Employed Residents; Population by Age; Population for jurisdictions in the nine county San Francisco Bay Area region.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

City of Miami Active Positions

The Employment data from the 2021 Federal Census covers labour force status, employment status, labour force participation rate, industry, and occupation. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Labour force status refers to whether a person was employed, unemployed or not in the labour force during the reference period. Not in the labour force refers to persons who were neither employed nor unemployed during the reference period. This includes persons who, during the reference period were either unable to work or unavailable for work. It also includes persons who were without work and who had neither actively looked for work in the past four weeks nor had a job to start within four weeks of the reference period.

Employment status refers to the employment status of a person during the period of Sunday, May 2 to Saturday, May 8, 2021. An employed person is one who did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment. This category excludes persons not at work because they were on layoff or between casual jobs, and those who did not then have a job (even if they had a job to start at a future date). While an unemployed person is one who was without paid work or without self-employment work and was available for work. An unemployed person either: had actively looked for paid work in the past four weeks; was on temporary lay-off and expected to return to his or her job; or had definite arrangements to start a new job in four weeks or less.

Labour force participation rate refers to the total labour force in that group, expressed as a percentage of the total population in that group.

Industry refers to the general nature of the business carried out in the establishment where the person worked. The industry data are produced according to the North American Industry Classification System (NAICS).

Occupation refers to the kind of work performed in a job, a job being all the tasks carried out by a particular worker to complete their duties. An occupation is a set of jobs that are sufficiently similar in work performed. The occupation data are produced according to the National Occupational Classification (NOC) 2021.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

The City funds a number of full-service WorkSource Centers in the City of Los Angeles that provide a full range of assistance to job seekers and employers under one roof. Job seekers can receive career counseling, job listings, labor market information, training referrals, and other employment-related services. Employers can avail themselves of business services such as recruiting, posting job vacancies, human resources services, and customized training.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

Baseline: 2019 households

Data from the Current Population Survey (CPS) provide detailed labor market information and demographics. The CPS data are provided for NYS. Topics include Veterans (employment status and selected demographics only available for New York State), employment status and other labor force demographics.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

The NYC Department of City Planning's (DCP) Housing Database contains all NYC Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. It includes the three primary construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. Records in the Housing Database Project-Level Files are geocoded to the greatest level of precision possible, subject to numerous quality assurance and control checks, recoded for usability, and joined to other housing data sources relevant to city planners and analysts. Data are updated semiannually, at the end of the second and fourth quarters of each year. Please see DCP's annual Housing Production Snapshot summarizing findings from the 21Q4 data release here. Additional Housing and Economic analyses are also available. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.

Listing of referral Centers For High School Alternatives

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/2015-Mega-Annual-Report/LEG-2015-MEGA-Annual-Report/pq7k-uvsy

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

Number of individuals enrolled in Medical Assistance Benefits for Workers with Disabilities (MAWD) by Race with Workers with Job Success (WJS). Total for all Races for each month is included in the dataset with the Total label.

Data is suppressed to ensure personally identifiable information is not indirectly revealed in instances where the data is less than 11 records.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

The labor-market engagement index provides a summary description of the relative intensity of labor market engagement and human capital in a neighborhood. This is based upon the level of employment, labor force participation, and educational attainment in a census tract. Values are percentile ranked nationally and range from 0 to 100. The higher the score, the higher the labor force participation and human capital in a neighborhood.

The Employment data from the 2021 Federal Census covers labour force status, employment status, labour force participation rate, industry, and occupation. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Labour force status refers to whether a person was employed, unemployed or not in the labour force during the reference period. Not in the labour force refers to persons who were neither employed nor unemployed during the reference period. This includes persons who, during the reference period were either unable to work or unavailable for work. It also includes persons who were without work and who had neither actively looked for work in the past four weeks nor had a job to start within four weeks of the reference period.

Employment status refers to the employment status of a person during the period of Sunday, May 2 to Saturday, May 8, 2021. An employed person is one who did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment. This category excludes persons not at work because they were on layoff or between casual jobs, and those who did not then have a job (even if they had a job to start at a future date). While an unemployed person is one who was without paid work or without self-employment work and was available for work. An unemployed person either: had actively looked for paid work in the past four weeks; was on temporary lay-off and expected to return to his or her job; or had definite arrangements to start a new job in four weeks or less.

Labour force participation rate refers to the total labour force in that group, expressed as a percentage of the total population in that group.

Industry refers to the general nature of the business carried out in the establishment where the person worked. The industry data are produced according to the North American Industry Classification System (NAICS).

Occupation refers to the kind of work performed in a job, a job being all the tasks carried out by a particular worker to complete their duties. An occupation is a set of jobs that are sufficiently similar in work performed. The occupation data are produced according to the National Occupational Classification (NOC) 2021.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

This dataset contains information about the Workforce 1 service, a service offered by the Department of Small Business Services (SBS) that connects New Yorkers to job opportunities. Each row in the dataset represents the number of public housing residents on a Borough-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

The Los Angeles BusinessSource Centers provide startup ventures and current small business owners various cost effective tools to make their business a success. Through these tools, small businesses can grow and remain competitive within the City of Los Angeles.

Startups focuses on owners of businesses with five (5) or fewer employees, one of whom owns the enterprise, and have net operating income of less than Two Hundred Thousand Dollars ($200,000). This focus is particularly important as the majority of the businesses within the City may be categorized as “survivors,” and historically, many such businesses fail in their first two years of operation. The survival and growth of such businesses is still very important to the ongoing economic vitality of the City.

Apprentice Level Worker Details

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part A of a four (4) part report. A data dictionary and additional notes document are attached as resources. For more information, visit Business Oregon https://www.oregon.gov/biz/programs/enterprisezones

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

The Unemployment Insurance Recipiency Rate is the ratio of Insured Unemployed to Total Unemployed. It provides an estimate of the percentage of unemployed persons who are receiving unemployment insurance benefits. Data based on a moving twelve-month period.

Baseline: Jobs 2015-2017 (LEHD)

Payroll expenditures for Colorado Department of Transportation for the current and previous state fiscal year.

The 2014 Austin Digital Assessment Project was supported by the Telecommunications & Regulatory Affairs Office of the City of Austin, the Telecommunications and Information Policy Institute at the University of Texas, and faculty and graduate students from the Department of Radio, Television, and Film and the University of Texas.

This dataset includes the individual survey responses. To see aggregated dataset weighted to reflect Austin demographics, refer to the attached document.

Job Openings and Labor Turnover Survey data from the U.S. Bureau of Labor Statistics

This dataset contains information about the Workforce 1 service, a service offered by the Department of Small Business Services (SBS) that connects New Yorkers to job opportunities. Each row in the dataset represents the number of public housing residents on a NYCHA Development-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part B of a four (4) part report. A data dictionary and additional notes document are attached as resources; column header numbers (1-6) can be located in the notes document for additional information.

For more information, visit https://www.oregon.gov/biz/programs/enterprisezones

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Michigan-Strategic-Fund-Act-Annual-Report/wrfw-fizh

The NYC Women's Resource Network is a free, user-friendly database of over 1,000 nonprofit organizations and governmental agencies that work to advance and benefit women and families in New York City. A user can tailor their search by keyword, category, and/or borough to receive a customized listing of organizations that address their needs.

This datasets contains information about NYCHA residents who were employed by the Work Progress Program (WPP). WPP is a subsidized wage program designed to complement existing youth services by providing participating low-income young adults with work experience. Through WPP, HRA reimburses providers for wages paid to low-income young adults (aged 16-24) who have been placed in short-term jobs that typically last 12 weeks, with a special emphasis on serving opportunity or at-risk youth. WPP is not a stand-alone program. WPP provides wage reimbursements for nonprofits to provide subsidized jobs to their existing program participants. WPP supports providers that prioritize recruitment of NYCHA youth. NYCHA residency is self-reported in each providers intake and enrollment processes. Providers then report to Human Resources Administration (HRA) if someone is a NYC MAP resident or non-NYCHA MAP resident. The NYCHA MAP initiative includes 15 developments that were identified under the Mayoral Action Plan for Neighborhood Safety.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

Executive Recommendation for the Fiscal Year 2017 Budget Summary of Positions by Business Unit. For more information on the budget and schedule of public hearings see http://www.cookcountyil.gov/budget/

Annual City employee earnings for calendar-year 2016. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This collection contains elevator applications, aka job filings, submitted online through the "DOB NOW: BUILD" portal. An approved application allows the applicant to pull a permit and begin work on an elevator project.

DOB NOW: BUILD is an online portal that allows users to file for permit applications, check the status of an application, make payments, schedule appointments, and print permits.

Data in this collection is limited to elevator applications (also known as ELV1) submitted through DOB NOW, and includes Initial (New), Subsequent, and Post Approval Amendment (PAA) filing types. The collection includes all electrical applications submitted to the Department of Buildings since December 11, 2017, when the applications were launched in DOB NOW and were no longer accepted through other submission processes.

This dataset contains details for each device on the application. There should be one row per device/Job Filing Number in this dataset. For example, an Initial Permit Application for Device 1234 and Device 5678 would have 2 rows (one for 1234 and one for 5678). If a Post Approval Amendment (PAA) was submitted for this application, then the Device rows would be repeated but the Job Filing Number would have a P1 suffix to indicate the PAA.

This dataset presents the 2012-2017 list of funding approved by the ESD Directors. Data categories are project name, region, program, funding amount and fiscal year.

ESD will no longer update this data set. Updated data can now be found in the Database of Economic Incentives at https://data.ny.gov/Economic-Development/Database-of-Economic-Incentives/26ei-n4eb.

Baseline: 2050 households

NOTE TO USERS – There may be disruption to this data set between April 9 to April 19 related to an upgrade. Please contact dsdopendata@austintexas.gov with questions.

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq

Building, Electrical, Mechanical, and Plumbing Permits and Driveway/Sidewalk Permits issued by the City of Austin. Includes relevant details such as issue date, location, council district, expiration date, description of work, square footage, valuation, and units.

This dataset is compliant with the Building & Land Development Specification (BLDS) data standard.

Development Services DEPARTMENT DATA DISCLAIMER:

1. The data provided are for informational use only and may differ from official DSD data.
2. DSD’s database is continuously updated, so reports run at different times may produce different results. Care should be taken when comparing against other reports as different data collection methods and different data sources may have been used.
3. The Development Services Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided.

This data was used to create the Economic Development Department's 2016 Creative Economy Snapshot Report available at http://www.austintexas.gov/page/creative-development.

Data was compiled by the CreativeVitality Suite from a variety of sources including Occupations & Demographic: Economic Modeling Specialists International, Industry Sales: Economic Modeling Specialists International, State Arts Agency Grants: National Assembly of State Arts Agencies (Final Descriptive Reports), Nonprofit Revenues: National Center for Charitable Statistics, NCCS.

This product has been produced by the Economic development Department of the City of Austin for the sole purpose of informational reference. No warranty is made by the City of Austin regarding specific accuracy or completeness.

Listing of domestic violence non-residential services. Phone numbers and the borough where service is provided is included.

Data about applications submitted by employers requesting visas to employ foreign citizens in Cambridge, MA and received by the U.S. Department of Labor through the Labor Condition Application (LCA) and the Permanent Labor Certification (PERM) programs. The LCA program covers H-1B, H-1B1 and E-3 visas.

Each row in the data set represents a single employer application. In the LCA program this application can request one or more positions. Employers can make multiple applications during a single year.

Standard, overtime, and other pay totals for Ramsey County employees by year. This data includes deferred compensation and pandemic pay as part of an employee's overall compensation. It does not include vaccination incentives or COVID-19 testing payments.

Employees with start dates of "Jan 1, 1901" are missing an official start date in their record and we are working to update this data.

Annual City employee earnings for calendar-year 2010. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

Increase job retention rate of workers with barriers to successful employment.

Employment, Unemployment and Labor Data from the Bureau of Labor Statistics

The Employment data from the 2021 Federal Census covers labour force status, employment status, labour force participation rate, industry, and occupation. For questions, please contact socialresearch@calgary.ca. Please visit Data about Calgary's population for more information.

Labour force status refers to whether a person was employed, unemployed or not in the labour force during the reference period. Not in the labour force refers to persons who were neither employed nor unemployed during the reference period. This includes persons who, during the reference period were either unable to work or unavailable for work. It also includes persons who were without work and who had neither actively looked for work in the past four weeks nor had a job to start within four weeks of the reference period.

Employment status refers to the employment status of a person during the period of Sunday, May 2 to Saturday, May 8, 2021. An employed person is one who did any work at all at a job or business, that is, paid work in the context of an employer-employee relationship, or self-employment. This category excludes persons not at work because they were on layoff or between casual jobs, and those who did not then have a job (even if they had a job to start at a future date). While an unemployed person is one who was without paid work or without self-employment work and was available for work. An unemployed person either: had actively looked for paid work in the past four weeks; was on temporary lay-off and expected to return to his or her job; or had definite arrangements to start a new job in four weeks or less.

Labour force participation rate refers to the total labour force in that group, expressed as a percentage of the total population in that group.

Industry refers to the general nature of the business carried out in the establishment where the person worked. The industry data are produced according to the North American Industry Classification System (NAICS).

Occupation refers to the kind of work performed in a job, a job being all the tasks carried out by a particular worker to complete their duties. An occupation is a set of jobs that are sufficiently similar in work performed. The occupation data are produced according to the National Occupational Classification (NOC) 2021.

This is a one-time load of Statistics Canada federal census data from 2021 applied to the Communities, Wards, and City geographical boundaries current as of 2022 (so they will likely not match the current year's boundaries). Update frequency is every 5 years. Data Steward: Business Unit Community Strategies (Demographics and Evaluation). This dataset is for general public and internal City business groups.

Department of Education borough enrollment offices

Quarterly Measure A dashboard data for StarVista Daybreak Youth Residential Services initiative. Data sourced from Daybreak quarterly narratives and statistics.

Employees may be reimbursed for expenses through two mechanisms. This dataset shows reimbursements through the payroll system. See https://data.cityofchicago.org/d/g5h3-jkgt for reimbursements through direct vouchers.

The data submitted reflects the number of trainings of Pennsylvania workers offered by DCED and its affiliate programs in Fiscal Year 2015-2018

Annual City employee earnings for calendar-year 2012. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This dataset shows the population, civilian labor force, unemployed, and unemployment rate for people aged 16 to 24 years in New York State and its Labor Market Regions.

Dataset lists each project that was eligible for Impact Fees, the amounts assessed for each type of Impact Fees, the reason why Impact Fees were assessed or not assessed.

Baseline: Future Year 2050 Households (Final Blueprint)

Jurisdiction share of total Bay Area housing by 2050 per Plan Bay Area 2050 Final Blueprint

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

Annual City employee earnings for calendar-year 2014. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

This dataset provides demographic information about City of Norfolk employees. The data is provided by Norfolk's Department of Human Resources and is updated daily.

Local area labor force information. Information by calendar year including labor force, employed, unemployed, and unemployment rate. Statewide and county statistics.

Eligible Training Providers (ETPs) are entities with job training programs approved by the Texas Workforce Commission (TWC) to provide Workforce Innovation and Opportunity Act (WIOA)–funded training services. Local Workforce Development Boards (Boards) fund training for Adult and Dislocated Worker program participants primarily through Individual Training Accounts (ITAs). The publicly accessible Statewide Eligible Training Providers List (ETPL) includes all programs that are currently approved by TWC for ITA funding. Note: This data is refreshed monthly.

This data set contains employment projections, educational levels, average wages for projected jobs in Beaver, Garfield, Iron and Kane counties.

Annual City employee earnings for calendar-year 2011. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part A of a four (4) part report. A data dictionary and additional notes document are attached as resources. For more information, visit Business Oregon https://www.oregon.gov/biz/programs/enterprisezones

Baseline: Jurisdictions, clipped to urbanized areas, protected OS removed

Provo- Orem, Utah MSA- Occupational Projections 2012-2022

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.

This report includes data from Enterprise Zone Business Projects -with exemptions on qualified property.This is Part A of a four (4) part report. A data dictionary and additional notes document are attached as resources. Visit the Oregon Transparency website https://www.oregon.gov/transparency/Pages/index.aspx or Business Oregon https://www.oregon4biz.com/Oregon-Business/ for more information.

The Maryland Department of Commerce collects and publishes its Commerce Consolidated Finance Tracker data to provide information on how the agency's grants, tax credits, equity investments and loan enhancements were distributed between FY 2016 and the most recent past fiscal year. Users can search and sort by company, amount, location and program.

The employee engagement survey is distributed to all classified and exempt employees in the Executive Branch annually. Survey participation is voluntary, and the scores only reflect those who participated in the process. An “Employee Engagement Score” is calculated as an index of overall employee engagement. The index is the average of seven components of employee engagement, each based on a subset of questions in the employee engagement survey: Growth – personal growth and development, Balance – work-life, Supervisor – support, recognition and feedback, Communication – value employee voices, ideas, opinions, Peers – positive relationships in the workplace, Alignment – understanding the link between one’s job and the organization’s mission, Satisfaction – work and employer. The score is the average of the seven components of engagement listed above. For 2022 the average employee engagement score was 3.84 out of a possible 5.0. Scores increased 3.6% from 2014 to 2017. There was a slight drop from 2017 to 2021. The 2022 survey shows overall engagement score going up slightly to be just shy of the highest score (2017; 3.85) we've seen since the survey began. Please see the online resource for more detailed information on the employee engagement survey and how the engagement score was calculated. https://humanresources.vermont.gov/document/employee-engagement-survey-results-2022

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

Budgeted salaries by position in Cambridge Public Schools for fiscal year 2023.

NOTE: This dataset will be incorporated into Cambridge's existing budget dataset when that dataset is updated in early summer 2022. That dataset is available at https://data.cambridgema.gov/Budget-Finance/Budget-Salaries/ixg8-tyau.

The Connect Community program is offered as an alternative to the Main Street program through the Wisconsin Economic Development Corporation. As a Connect Community, the City of Janesville is required to attend three training events and file an annual report on the business and real estate activity occurring in the downtown over the previous year.

This dataset contains information about Park Opportunity Program (POP), a service offered by the Department of Parks and Recreation (DPR) aimed at getting New Yorkers in the workforce for six months to clean and green DPR’s parks, playgrounds and other facilities citywide. Each row in the dataset represents the number of public housing residents on a Borough-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.”

This report includes data from Enterprise Zone Businesses to begin exemption on qualified property in 2022. This is Part B of a four(4) part report. A data dictionary and additional notes document are attached as resources. For more information, visit https://www.oregon.gov/biz/programs/enterprisezones

Dataset describes jurisdictions according to 8 measures which will be used to gauge RHNA performance. Each measure has been categorized into two groups, for most the top 25 cities in a category versus the remainder.

The core metrics mapping directly to CA HCD objective metrics include: Percent of RHNA as lower income units for jurisdictions with the highest housing costs. Measure: Housing costs Share of homeowners living in units valued above $750,000. Threshold grouping: upper third vs rest Percent of RHNA as lower income units for jurisdictions with highest percent of single-family homes. Measure: Percent single family Threshold grouping: upper third vs rest Total unit allocations for jurisdictions with the most jobs. Measure: Total Jobs Threshold grouping: upper third vs rest Allocations of lower income units for jurisdictions with the most low-wage jobs. Measure: Low wage jobs Threshold grouping: upper third vs rest Percent of RHNA as lower income units for jurisdictions with the highest ratio of low-wage jobs to housing units affordable to low-wage workers. Measure: jobs-housing fit Threshold grouping: upper third vs rest Percent of RHNA as lower income units for low-income jurisdictions. Measure: median household income. Low income threshold: bottom third Percent of RHNA as lower income units for high-income jurisdiction. Measure: median household income. High income threshold: upper third Percent of RHNA as lower income units for jurisdictions with the most households in High Resource/Highest Resource tracts. Measure: Share households in HRAs Threshold grouping: upper third vs rest

List of all after-hours variances issued in DOB NOW

This data set contains employment projections, educational levels, average wages for projected jobs in Beaver, Garfield, Iron and Kane counties.

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/2016-Renaissance-Zone-Annual-Report-Final/gdux-qms2/data?firstRun=true

The Paycheck Protection Program (PPP) loans provide small businesses with the resources they need to maintain their payroll, hire back employees who may have been laid off, and cover applicable overhead. This data set includes businesses in Utah who received PPP funding, how much funding the employer received & how many jobs the employer claims they saved. The NAICS (National Industry Classification) was provided by the loan recipient.

A labor market area that is usually a group of contiguous counties where employment, training, and educational services are provided as established under the Workforce Innovation and Opportunity Act to provide services for dislocated workers and other eligible individuals.

The Workforce Innovation and Opportunity Act (WIOA) is a federal act passed in 2014 designed to help job seekers access employment, education, training, and support services to succeed in the labor market and to match employers with the skilled workers they need to compete in the global economy. WIOA ensures that employment and training services provided by the core programs of employment services, workforce development, adult education, and vocational rehabilitation activities are coordinated and complementary so that job seekers acquire skills and credentials that meet employers' needs.

Annual City employee earnings for calendar-year 2015. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

Salaries and compensation for all employees of the County of San Mateo [Note: 2020 salaries are based on 27 pay periods due to leap year]

The Citywide Mobility Survey (CMS) is a mixed-methodology survey of New York City residents' travel choices, behaviors, and perceptions. The Trip dataset provides trip-level data.

Annual City employee earnings for calendar-year 2013. Earnings figures are those taxed by Medicare.

This dataset cannot be directly combined with previous- or future- year earnings because it doesn't account for title changes or other job status changes. Further, the data represents paid amounts rather than stated salaries – i.e. if an employee worked March-December of a given year, the data reflects 10 months of compensation for the year.

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part A of a four (4) part report. A data dictionary and additional notes document are attached as resources; column header numbers (1-8) can be located in the notes document for additional information.

For miscellaneous local Enterprise Zone information, please visit https://data.oregon.gov/Revenue-Expense/Local-Enterprise-Zone-Reports-Miscellaneous-/bx8i-r869/about_data

For more information on Enterprise Zones, visit Business Oregon https://www.oregon.gov/biz/programs/enterprisezones

Tax Law section 35(d) requires the Tax Department to produce an Economic Transformation and Facility Redevelopment (ETFR) Program Credit Report by July 31 of each year. The program is designed to mitigate the economic consequences in certain communities where the following types of facilities closed: • Correctional facilities operated by the Department of Corrections and Community Supervision (DCCS) • Facilities operated by the Office of Children and Family Services (OCFS), and • Psychiatric facility previously owned by New York State and operated under the Mental Hygiene Law located in the Metropolitan Commuter Transportation District (but outside of New York City)

The program is administered by Empire State Development (ESD) and offers a refundable tax credit with four components to redevelop closed facilities and attract new businesses to the surrounding areas. Taxpayers may claim credit for five consecutive years. The components of the credit are: • ETFR Jobs Tax Credit Component • ETFR Investment Tax Credit Component • ETFR Job Training Tax Credit Component • ETFR Real Property Tax Credit Component

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

This data set contains employment projections, educational levels, average wages for projected jobs in Beaver, Garfield, Iron and Kane counties.

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

All salaries as reported on Transparent California, http://transparentcalifornia.com/, for 2014

On May 16, 2011, Mayor Emanuel enacted Executive Order 2011-1. It requires Shakman-exempt employees of Executive Departments, department heads, non-clerical employees of the Mayor's Office, and persons appointed by the Mayor to City boards, commissions, authorities or agencies on or after May 16, 2011, to sign an Ethics Pledge http://bit.ly/mSkLU1. On July 28, 2011, this requirement was enacted into law by the City Council, as Section 2-156-015 of the Governmental Ethics Ordinance (effective September 8, 2011) http://bit.ly/qYti7P. The law requires new hires or appointees to sign the pledge within 14 days of starting their employment or appointments. The pledge obligates signers to abide by a ban on lobbying activity for two years after their City service ends. The Board of Ethics maintains these signed pledges. As a convenience, we are pleased to attach a list of persons who have signed this pledge. This list is sortable by name and department.

This data set contains employment and occupational projections for Wayne, Millard, Piute, Sanpete and Sevier Counties for 2012-2022.

This dataset contains average total, federal, state, and local salaries for full-time staff. In addition, this file provides the number of full-time equivalent positions in each organization, average years of experience, as well as average years of age. Data is aggregated at the state, district, and school level.

Tracks highway sign installations and repairs.

Dubuque County Average Monthly Earnings By Quarter from US Census Bureau

PACE provides loans to residential and commercial development projects specifically for energy-efficiency improvements. The cost of the loan is paid back over time through a voluntary assessments that is attached to the property.

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

(This item will be removed from public view after May 8, 2025. For current employment statistics visit https://esd.wa.gov/jobs-and-training/labor-market-information/employment-and-wages/washington-employment-estimates-wa-qb-ces. Contact LMIR@esd.wa.gov with questions) Historical estimates of nonfarm employment, by industry, in Washington State. Index of Washington State and labor market areas, 1990-2022 Each month, economists estimate monthly job gains and losses based on the survey of employers (CES). Then, at the end of each quarter, economists revise the estimates based on actual numbers from employer tax records (QCEW).

Baseline: Draft Blueprint HH Growth 2015-2050

Jurisdiction share of total Bay Area housing growth, based upon 2015 to 2050 housing growth in Plan Bay Area 2050

Long​-Term Rural Enterprise Zone Facilities Program: Extends property tax abatement for 7–15 years, compared to the standard three to five years, in most rural enterprise zones. See ORS 285C.409(1)(c).

Any type of business activity is eligible, but these incentives depend on local approval and minimum levels for investment size, job creation and employee compensation.

The Long-Term Rural Enterprise Zone Facilities Program Reports are usually received by the Oregon Department of Revenue (DOR) the first quarter of the year.

Historical reports are provided here as PDF files. Starting in 2025, company specific data is also appended as a dataset to this page.

For more information on Long-Term Rural Enterprise Zones, visit Business Oregon https://www.oregon.gov/biz/programs/enterprisezones/Long-TermRuralEnterpriseZone/Pages/default.aspx

State Of Utah Employment Projections By County And Multi- County District 1980-2030

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY-2017-MEGA-Annual-Report/ecmr-ss2d/data?firstRun=true

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

Total private-sector employment for jobs covered by Unemployment Insurance as reported by employers through the Quarterly Census of Employment and Wages (QCEW).

This data set contains occupational and employment projections for the Ogden Clearfield MSA (metropolitan statistical area) - Weber and Davis counties.

Baseline: Growth 2015-2050

This data set contains employment projections, educational levels, average wages for projected jobs in Beaver, Garfield, Iron and Kane counties.

This data set contains employment projections for the Bear River Dept of Workforce Services region- Cache, Rich and Box Elder Counties.

This dataset contains retention, transfer, and turnover rates for full-time staff. In addition, this file provides one through five year rates for each mobility category. Data is aggregated at the state, district, and school level.

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

NOTE: For annually updated, granular ad spend data, please visit Local Law 83 - City Agency Advertising Spend dataset.

Fiscal Year 2022 spans over two administrations. The first half of the fiscal year (FY22, Q1 and Q2) was per Executive Order 47. The second half of the fiscal year (FY22, Q3 and Q4) was per Local Law 83.

To learn more about the differentiation and review the FY2022 annual report click here

To see the agency spend for FY22 broken down by administration click here

Dataset describes jurisdictions according to 8 measures which will be used to gauge RHNA performance. Each measure has been categorized into discrete buckets, for use in summarizing the jurisdiction-specific RHNA allocation.

The core metrics mapping directly to CA HCD objective metrics include:

Measure 1a: Lower Income RHNA in High Cost Areas Measure 1b: Lower Income RHNA in Single-Family Home Areas Measure 2a: Household Growth in Job Centers Measure 3a: Lower Income RHNA in Jobs-Housing Fit Imbalanced Areas Measure 4a: Lower Income RHNA in Areas with High Share of Low-Income Households Measure 4b: Lower Income RHNA in Areas with High Share of High-Income Households Measure 5a: Lower Income RHNA in High Opportunity Areas Measure 5b: Household Growth in High Divergence Score Areas with High-Income Households Measure 6b: Household Growth in High Hazard Risk Areas

Colorado Springs Open Budget Revenue Monthly export from the City's Enterprise Resource Planning system.

Count and rate of population with income in the last 12 months below poverty level in an area. ( B17001). County and State values are from ACS 1-year survey.

This dataset contains counts of full-time staff across 12 salary ranges. Data is aggregated at the state, district, and school level. Additionally, the data are aggregated by job classification, education level, gender, race, and experience.

Listing of vocational training courses eligible for Individual Training Grants

This report includes data from Enterprise Zone Business Projects - with exemptions on qualified property. This is Part B of a four (4) part report. A data dictionary and additional notes document are attached as resources; column header numbers (1-6) can be located in the notes document for additional information.

For miscellaneous local Enterprise Zone information, please visit https://data.oregon.gov/Revenue-Expense/Local-Enterprise-Zone-Reports-Miscellaneous-/bx8i-r869/about_data

For more information on the Enterprise Zone program, visit https://www.oregon.gov/biz/programs/enterprisezones

The BSC Program, funded through the CDBG, provides entrepreneurial training, technical assistance and access to capital for micro-enterprise and start-up businesses. The program promotes job creation for Angelenos by providing entrepreneurs and small businesses the support they need to start and/or expand their businesses. Goals are established through HUD guidelines and local measures.

Data from the Current Population Survey (CPS) provide employment status for Veterans and Nonveterans.

This dataset contains interest earned since 2013.

This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form55a-Source-Table/kuvg-3uwp.

Approved in 2005, EDTIF is a state incentive program that allows local governments to create “economic development zones” in order to encourage job creation and capital investment. New or existing businesses creating new jobs or significant capital investment within these zones may apply for a partial rebate (30%) for up to 20 years of taxes paid to the state. The rebate may apply to “new state income” generated by the job growth or capital investment, including the payroll tax of the new employees, corporate income tax, and sales tax. Qualifying companies must create new jobs paying at least the median state wage.

This table is generated off of a report for the Michigan legislature. To see the full report and footnotes, go to https://transparency.michigan.gov/Michigan-Economic-Development-Corporation/FY2015-Renaissance-Zone-Annual-Report/7yau-8nzf

Construction_ProjectsEvents

The City partnered with Burke, Inc. and The Voice of Your Costumer research and marketing firms to conduct a statistically significant survey of over 1,000 residents, including 500 Black/ African American residents to understand barriers around reaching financial freedom. The survey insights uncovered racial disparities around job mobility, housing (rental and homeownership), debt and consumer protection, banking and financial access, and financial planning and coaching.

This data set contains employment and occupational projections for Sevier, Millard, Piute, Sanpete and Wayne Counties for 2012-2022.

This data set contains employment projections for the Weber and Davis County MSA (Metropolitan Statistics Area) for 2012-2022.