Government Payrolls in the United States increased by 22 thousand in September of 2025. This dataset provides the latest reported value for - United States Government Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Employment by Industry reports several labor statistics related to employment and wage. Domain Frequency Annual Full Description Employment by Industry reports the total Number of Employers, the Annual Average Employment, and the Annual Average Wage by industry at the town, county, and state level. Industries included in this dataset vary from location to location. In as many locations as possible, five specific industry segments are consistently present (Construction, Manufacturing, Retail Trade, All Industries, Total Government) as well as the largest 3 out of the remaining segments for that location, ranked by Annual Average Employment. Not every location has data for every segment, and some may not have data for the five consistently reported segments. This data is from the Connecticut Department of Labor Quarterly Census of Employment and Wages (QCEW). The program produces a comprehensive tabulation of employment and wage information for workers covered by Connecticut Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program.

‘This dataset provides information regarding the total approved actual expenses incurred by Montgomery County government employees traveling non-locally (over 75 miles from the County’s Executive Office Building at 101 Monroe St. Rockville, MD) for official business, beginning on or after August 12, 2015. The dataset includes the name of traveling employee; the employee’s home department; travel start and end dates; destination; purpose of travel; and actual total expenses funded by the County. Update Frequency: Monthly

The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States.

CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services.

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

The 2020 Public Service Employee Survey (PSES) was administered by Advanis, on behalf of the Office of the Chief Human Resources Officer, Treasury Board of Canada. This comprehensive survey measured federal government employees’ opinions about their engagement, leadership, workforce, workplace, workplace well-being, compensation, diversity and inclusion, and the impacts of COVID-19. The 2020 Public Service Employee Survey was conducted from November 30, 2020 to January 29, 2021. A total of 188,786 employees in 87 federal departments and agencies responded to the 2020 Public Service Employee Survey, for a response rate of 61%. The 2020 Public Service Employee Survey datasets contain the results of the survey by year (2020, 2019 and 2018) for the Public Service and departments/agencies, and the results broken down by demographic characteristics (e.g., age, gender) and organizational units. Results for 2019 and 2018 are only provided for questions repeated in the 2020 Public Service Employee Survey.

Explore the number of employees in government sectors dataset for insights on labor and employment trends in Saudi Arabia. Analyze data collected by SAMA Annual.

Labor, Government, employment, SAMA Annual

Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..Note:The Statistics include men and women working under the following ladders: (Public Ladder of Employee Salaries, Ladder of Health Jobs, Ladder of Educational Jobs, Ladder of the Teaching staff, lecturers and teaching assistants, Judge Ladder, Ladder of Investigation staff and public prosecutors, and Ladder of Wage - earners).

Government spending in the United States was last recorded at 39.7 percent of GDP in 2024 . This dataset provides - United States Government Spending To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

US Federal Funding Gaps History

Historical US Federal Funding Gaps & Political Party Control

By Throwback Thursday [source]

About this dataset

This dataset is a comprehensive historical record of federal funding gaps in the United States, spanning from 1976 to 2018. It provides detailed information on each funding gap, including the start and end dates, total duration in days, and whether or not employees were furloughed.

The dataset also includes data on the political party control during each funding gap, specifically for both the Senate and the House of Representatives. For each chamber, it indicates which party had control - either Democrats or Republicans - as well as any representation by Independent members.

Additionally, this dataset contains valuable insights into the impact of federal funding gaps on government employees. It records the number of employees who were furloughed during each gap, allowing for analysis of workforce disruption and potential economic consequences.

By leveraging this dataset's wealth of information on federal funding gaps in the United States over more than four decades, researchers can gain a deeper understanding of these significant events in governmental operations and their broader implications for various stakeholders

How to use the dataset

Introduction:

• Understanding the Columns: a) Start Date: The date when a federal funding gap began. b) End Date: The date when a federal funding gap ended. c) Total days: The duration of the federal funding gap in days. d) Employees furloughed: A boolean value indicating whether or not employees were furloughed during that specific funding gap. (True = Employees were furloughed, False = No employee was furloughed.) e) Number of Employees Furloughed: The actual count of employees who were furloughed during that specific funding gap. f) Senate Control: The political party that had control over the Senate during each particular period specified. (Categorical - Democratic, Republican) g) Senate Democrats: The number of Democratic senators serving during that specific funding gap. h) Senate Republicans: The number of Republican senators serving during that particular period specified. i) Senate Independents: The number of Independent senators serving at that time frame. j ) House Control :He political party that had control over House Representatives throughoted specific dataried by each perticularnce k ) House Democrats -

• Analyzing Duration and Furloughs: You can compute various statistics about federal funding gaps using relevant columns such as 'Start Date,' 'End Date,' 'Total days,' 'Employees furloughed,' 'Number of Employees Furloughed. For example:

  • Calculate the average duration of funding gaps during a specific time period.
  • Determine the total number of funding gaps that resulted in employee furloughs.
  • Analyze the average number of employees furloughed during various periods.

• Understanding Party Control: The dataset includes information about political party control over Senate and House Representatives during funding gaps. • Analyzing Senate Control:

  • Determine which party controlled the Senate during each funding gap period.
  • Compare the prevalence of Democratic, Republican, or Independent control over time.
  1. Exploring

Research Ideas

• Analyzing the impact of federal funding gaps on government employees: This dataset can be used to study the number of employees who were furloughed during each funding gap and analyze the duration of their furlough. It can provide insights into the economic effects and hardships faced by government workers during such periods.
• Examining the political dynamics during funding gaps: By analyzing the control of both the House of Representatives and Senate during each funding gap, this dataset can shed light on how political party control affected negotiations and resolutions. It can help identify patterns or trends in bipartisan cooperation or conflict during these periods.
• Comparing different funding gaps over time: With information on start dates, end dates, and total days for each gap, this dataset allows for comparisons across different periods in history. Researchers can assess whether funding gaps have become more frequent or longer-lasting over time and identify any patterns that may exist in relation to economic factors or political developments

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset d...

Data is collected because of public interest in how the City’s budget is being spent on salary and overtime pay for all municipal employees. Data is input into the City's Personnel Management System (“PMS”) by the respective user Agencies. Each record represents the following statistics for every city employee: Agency, Last Name, First Name, Middle Initial, Agency Start Date, Work Location Borough, Job Title Description, Leave Status as of the close of the FY (June 30th), Base Salary, Pay Basis, Regular Hours Paid, Regular Gross Paid, Overtime Hours worked, Total Overtime Paid, and Total Other Compensation (i.e. lump sum and/or retro payments). This data can be used to analyze how the City's financial resources are allocated and how much of the City's budget is being devoted to overtime. The reader of this data should be aware that increments of salary increases received over the course of any one fiscal year will not be reflected. All that is captured, is the employee's final base and gross salary at the end of the fiscal year. In very limited cases, a check replacement and subsequent refund may reflect both the original check as well as the re-issued check in employee pay totals.

NOTE 1: To further improve the visibility into the number of employee OT hours worked, beginning with the FY 2023 report, an updated methodology will be used which will eliminate redundant reporting of OT hours in some specific instances. In the previous calculation, hours associated with both overtime pay as well as an accompanying overtime “companion code” pay were included in the employee total even though they represented pay for the same period of time. With the updated methodology, the dollars shown on the Open Data site will continue to be inclusive of both types of overtime, but the OT hours will now reflect a singular block of time, which will result in a more representative total of employee OT hours worked. The updated methodology will primarily impact the OT hours associated with City employees in uniformed civil service titles. The updated methodology will be applied to the Open Data posting for Fiscal Year 2023 and cannot be applied to prior postings and, as a result, the reader of this data should not compare OT hours prior to the 2023 report against OT hours published starting Fiscal Year 2023. The reader of this data may continue to compare OT dollars across all published Fiscal Years on Open Data.
NOTE 2: As a part of FISA-OPA’s routine process for reviewing and releasing Citywide Payroll Data, data for some agencies (specifically NYC Police Department (NYPD) and the District Attorneys’ Offices (Manhattan, Kings, Queens, Richmond, Bronx, and Special Narcotics)) have been redacted since they are exempt from disclosure pursuant to the Freedom of Information Law, POL § 87(2)(f), on the ground that disclosure of the information could endanger the life and safety of the public servants listed thereon. They are further exempt from disclosure pursuant to POL § 87(2)(e)(iii), on the ground that any release of the information would identify confidential sources or disclose confidential information relating to a criminal investigation, and POL § 87(2)(e)(iv), on the ground that disclosure would reveal non-routine criminal investigative techniques or procedures. Some of these redactions will appear as XXX in the name columns.

Continued Claims for UI released by the CT Department of Labor. Continued Claims are total number of individuals being paid benefits in any particular week. Claims data can be access directly from CT DOL here: https://www1.ctdol.state.ct.us/lmi/claimsdata.asp

Claims are disaggregated by age, education, industry, race/national origin, sex, and wages.

The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

For data on continued claims at the town level, see the dataset "Continued Claims for Unemployment Benefits by Town" here: https://data.ct.gov/Government/Continued-Claims-for-Unemployment-Benefits-by-Town/r83t-9bjm

For data on initial claims see the following two datasets:

"Initial Claims for Unemployment Benefits in Connecticut," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits/j3yj-ek9y

"Initial Claims for Unemployment Benefits by Town," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits-by-Town/twvc-s7wy

This summary table shows, for Budget Receipts, the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for various types of receipts (i.e. individual income tax, corporate income tax, etc.). The Budget Outlays section of the table shows the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for agencies of the federal government. The table also shows the amounts for the budget/surplus deficit categorized as listed above. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

This dataset provides monthly counts of full-time, part-time and temporary employees for within the Executive Branch of the State of Iowa beginning with December 2010.

Explore the total number of employees in the research and development field in Saudi Arabia with this comprehensive dataset. Gain insights into the workforce in private, government, and educational sectors.

Private, Government, Total, Education, Employees, workers, Research and Development Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research.Higher education: Includes government and private higher education entities.

GSA, the nation's largest public real estate organization, provides workspace for over one million federal workers. These employees, along with government property, are housed in space owned by the federal government and in leased properties including buildings, land, antenna sites, etc. across the country.

Data is from Transparent California is provided by the Nevada Policy Research Institute as a public service and is dedicated to providing accurate, comprehensive and easily searchable information on the compensation of public employees in California.

Complete and accurate information is necessary to increase public understanding of government and help decision makers, including elected officials and voters, make informed decisions.

NPRI has been increasing transparency in government since first launching TransparentNevada.com in 2008.

All data on Transparent California has been compiled from public records requested and received from the associated political entity and is provided as a public service. We are not responsible for errors contained in those public records. Some jurisdictions are violating California's public records law and are refusing to provide names or other requested compensation information. In those cases, we have worked to provide as much information as we have received. Government jurisdictions in California do not maintain payroll and pension records in a uniform fashion. As such, and to help make the data easier to comprehend, we have consolidated some compensation categories. For instance, the “Overtime pay” column includes overtime compensation as the reporting agency classifies it. The "Other pay" category includes the compensation in the numerous other pay categories some public employees receive. "Total benefits" only includes benefits directly received by the employee: medical insurance (health, dental, and vision) and employer-paid retirement contributions. The total cost of the employee will be higher than the values reported here as there are associated costs (such as workman's comp, state unemployment insurance, medicare/SS costs, etc) that we do not report as employee compensation. The "Total pay & benefits" column underreports the total compensation of government employees whose government employer did not provided complete salary or benefit information. For pensions, all values reflect the actual monetary value of benefits received during the respective year reported.

This dataset contains annual average CES data for California statewide and areas from 1990 to 2024.

The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States.

CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services.

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

This table contains information on the balance sheet of the general government sector. The information is limited to financial assets and liabilities. For each reporting period the opening and closing stocks, financial transactions and other changes are shown. Transactions are economic flows that are the result of agreements between units. Other changes are changes in the value of assets or liabilities that do not result from transactions such as revaluations or reclassifications. The figures are consolidated which means that flows between units that belong to the same sector are eliminated. As a result, assets and liabilities of subsectors do not add up to total assets or liabilities of general government. For example, loans of the State provided to social security funds are part of loans of the State. However, these are not included in the consolidated assets of general government, because it is an asset of a government unit with a government unit as debtor. Financial assets and liabilities in this table are presented at market value. The terms and definitions used are in accordance with the framework of the Dutch national accounts. National accounts are based on the international definitions of the European System of Accounts (ESA 2010). Small temporary differences with publications of the National Accounts may occur due to the fact that the government finance statistics are sometimes more up to date.

Data available from: Yearly figures from 1995, quarterly figures from 1999.

Status of the figures: The figures for the period 1995-2023 are final. The figures for 2024 and 2025 are provisional.

Changes as of 23 September 2025: Figures for the first quarter of 2025 have been adjusted. The figures for the second quarter of 2025 are available.

Changes as of 10 April 2025: Due to an error made while processing the data, the initial preliminary figures for the government financial balance sheet in 2024 were calculated incorrectly. This causes a downward revision in other accounts payable.

When will new figures be published? Provisional quarterly figures are published three months after the end of the quarter. In September the figures on the first quarter may be revised, in December the figures on the second quarter may be revised and in March the first three quarters may be revised. Yearly figures are published for the first time three months after the end of the year concerned. Yearly figures are revised two times: 6 and 18 months after the end of the year. Please note that there is a possibility that adjustments might take place at the end of March or September, in order to provide the European Commission with the most actual figures. Revised yearly figures are published in June each year. Quarterly figures are aligned to the three revised years at the end of June. More information on the revision policy of Dutch national accounts and government finance statistics can be found under 'relevant articles' under paragraph 3.

Total Number of employees to raise efficiency for them in 2022

The dataset provides information on total full-time equivalents (FTE) for the State of Iowa - Executive Branch (including community based corrections), and those supported by the general fund, federal funds and other state funds starting with the pay period ending 12/23/2010. Counts are shown for the last pay period ending in the month. Two week long pay periods end every other Thursday.

The Employer Costs for Employee Compensation (ECEC) is a measure of the cost of labor. The compensation series includes wages and salaries plus employer costs for individual employee benefits. Employee benefit costs are calculated as cents-per-hour-worked for individual benefits ranging from employer payments for Social Security to paid time off for holidays. The survey covers all occupations in the civilian economy, which includes the total private economy (excluding farms and households), and the public sector (excluding the Federal government). Statistics are published for the private and public sectors separately, and the data are combined in a measure for the civilian economy. For information and data, visit: https://www.bls.gov/ncs/ect/