United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data was reported at -49.000 Person th in Feb 2025. This records a decrease from the previous number of -32.000 Person th for Jan 2025. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data is updated monthly, averaging 10.000 Person th from Jan 1979 (Median) to Feb 2025, with 552 observations. The data reached an all-time high of 437.000 Person th in Nov 2021 and a record low of -672.000 Person th in Mar 2020. United States Employment: NF: sa: Over-the-Month Change: Revision: 3rd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

Non Farm Payrolls in the United States increased by 139 thousand in May of 2025. This dataset provides the latest reported value for - United States Non Farm Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In October 2024, the total nonfarm payroll employment increased by around 12,000 people in the United States. The data are seasonally adjusted. According to the BLS, the data is derived from the Current Employment Statistics (CES) program which surveys about 140,000 businesses and government agencies each month, representing approximately 440,000 individual worksites, in order to provide detailed industry data on employment.

All Employees: Total Nonfarm, commonly known as Total Nonfarm Payroll, is a measure of the number of U.S. workers in the economy that excludes proprietors, private household employees, unpaid volunteers, farm employees, and the unincorporated self-employed. This measure accounts for approximately 80 percent of the workers who contribute to Gross Domestic Product (GDP).

This measure provides useful insights into the current economic situation because it can represent the number of jobs added or lost in an economy. Increases in employment might indicate that businesses are hiring which might also suggest that businesses are growing. Additionally, those who are newly employed have increased their personal incomes, which means (all else constant) their disposable incomes have also increased, thus fostering further economic expansion.

Generally, the U.S. labor force and levels of employment and unemployment are subject to fluctuations due to seasonal changes in weather, major holidays, and the opening and closing of schools. The Bureau of Labor Statistics (BLS) adjusts the data to offset the seasonal effects to show non-seasonal changes: for example, women's participation in the labor force; or a general decline in the number of employees, a possible indication of a downturn in the economy. To closely examine seasonal and non-seasonal changes, the BLS releases two monthly statistical measures: the seasonally adjusted All Employees: Total Nonfarm (PAYEMS) and All Employees: Total Nonfarm (PAYNSA), which is not seasonally adjusted.

The series comes from the 'Current Employment Statistics (Establishment Survey).'

The source code is: CES0000000001

Employment: NF: Over-the-Month Change: Revision: 2nd-1st data was reported at -89.000 Person th in Mar 2025. This records a decrease from the previous number of -36.000 Person th for Feb 2025. Employment: NF: Over-the-Month Change: Revision: 2nd-1st data is updated monthly, averaging 1.000 Person th from Jan 1979 (Median) to Mar 2025, with 554 observations. The data reached an all-time high of 283.000 Person th in Sep 1983 and a record low of -242.000 Person th in Mar 2020. Employment: NF: Over-the-Month Change: Revision: 2nd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll.

Revisions of earnings and employment statistics from Pay As You Earn (PAYE) Real Time Information (RTI), UK, monthly. These are official statistics in development.

Graph and download economic data for Total Nonfarm Private Payroll Employment (ADPMNUSNERSA) from Jan 2010 to May 2025 about payrolls, nonfarm, private, employment, and USA.

United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data was reported at -43.000 Person th in Mar 2025. This records a decrease from the previous number of -34.000 Person th for Feb 2025. United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data is updated monthly, averaging 2.000 Person th from Jan 1979 (Median) to Mar 2025, with 554 observations. The data reached an all-time high of 311.000 Person th in Dec 2021 and a record low of -186.000 Person th in Dec 1979. United States Employment: NF: sa: Over-the-Month Change: Revision: 2nd-1st data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Employment: Non Farm Payroll: Seasonally Adjusted.

Private businesses in the United States hired 37 thousand workers in May of 2025 compared to 60 thousand in April of 2025. This dataset provides the latest reported value for - United States ADP Employment Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Nonfarm Payrolls Private in the United States increased by 140 thousand in May of 2025. This dataset provides the latest reported value for - United States Nonfarm Payrolls - Private - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data was reported at -6.000 Person th in Feb 2025. This records a decrease from the previous number of 3.000 Person th for Jan 2025. United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data is updated monthly, averaging 6.000 Person th from Jan 1979 (Median) to Feb 2025, with 552 observations. The data reached an all-time high of 796.000 Person th in Mar 1996 and a record low of -716.000 Person th in Mar 1992. United States Employment: NF: Over-the-Month Change: Revision: 3rd-2nd data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G056: Current Employment Statistics: Employment: Non Farm Payroll.

The Productivity and Costs release on August 7, 2003, will reflect the June 2003 benchmark revision to payroll employment. Since employment is now reported on a North American Industry Classification System (NAICS) basis, all of the historical data will be revised. Changes as a consequence of the move to NAICS should not be significant since this release carries data at high levels of aggregation.

The current year’s January report reflects the scheduled annual revision of the ADP National Employment Report (NER). The data series has been reweighted to match annual Quarterly Census of Employment and Wages (QCEW) benchmark data through March of the previous year. This is a recurring process that happens every year in February and is a common practice for reports of this nature. More information about this report can be found at ADP National Employment Report website.

We construct a latent employment estimate for the U.S. which both reconciles the information from separate payroll and household surveys, and incorporates the preliminary data revision process of the payroll data. We find that our reconciled latent employment series looks somewhat different than the initial release of payroll employment and is closer to the fully-revised data that is benchmarked to a near census of employment. A real-time exercise, however, suggests that the reconciled employment estimate is remarkably similar to the initial release of payroll employment with near zero weight on the household survey information.

According to a survey among private companies in Japan, wage revisions resulted in the monthly scheduled wage per person increasing by an average of 4.1 percent in 2024. The figure includes companies with implemented and planned salary cuts and increases, as well as companies, which have decided not to revise wages.

According to a survey among private companies in Japan, wage revisions resulted in the monthly scheduled wage person increasing by an average of almost 12 thousand Japanese yen in 2024. The figure includes companies with implemented and planned salary cuts and increases, as well as companies, which have decided not to revise wages.

Economic forecasters pay especially close attention to labor market indicators during periods of economic uncertainty. Labor market data are thought to provide early evidence about changes in the course of the economy. This article examines whether monthly changes in labor market indicators are useful for predicting real GDP. It then examines whether weekly changes in initial and continuing unemployment insurance claims are useful for helping to predict changes in important labor market indicators. Incoming monthly data on nonfarm payroll jobs and the index of aggregate weekly hours help predict changes in real GDP growth, but data on the civilian unemployment rate do not. The authors also find that unemployment insurance claims help to predict changes in monthly labor variables. As others have found, these predictions work best in periods of recession. However, this article shows that there was also some predictive ability during the 1990s expansion.

The series comes from the 'Current Employment Statistics (Establishment Survey).' The source code is: CES0500000003

The Average Hourly Earnings of All Private Employees is a measure of the average hourly earnings of all private employees on a “gross” basis, including premium pay for overtime and late-shift work. These differ from wage rates in that average hourly earnings measure the actual return to a worker for a set period of time, rather than the amount contracted for a unit of work, the wage rate. This measure excludes benefits, irregular bonuses, retroactive pay, and payroll taxes paid by the employer.

Average Hourly Earnings are collected in the Current Employment Statistics (CES) program and published by the BLS. It is provided on a monthly basis, so this data is used in part by macroeconomists as an initial economic indicator of current trends. Progressions in earnings specifically help policy makers understand some of the pressures driving inflation.

It is important to note that this series measures the average hourly earnings of the pool of workers in each period. Thus, changes in average hourly earnings can be due to either changes in the set of workers observed in a given period, or due to changes in earnings. For instance, in recessions that lead to the disproportionate increase of unemployment in lower-wage jobs, average hourly earnings can increase due to changes in the pool of workers rather than due to the widespread increase of hourly earnings at the worker-level.

For more information, see: U.S. Bureau of Labor Statistics, CES Overview (https://www.bls.gov/web/empsit/cesprog.htm) U.S. Bureau of Labor Statistics, BLS Handbook of Methods: Chapter 2. Employment, Hours, and Earnings from the Establishment Survey (https://www.bls.gov/opub/hom/pdf/ces-20110307.pdf)

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. The LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution.LFS revisions: Labour force surveys are revised on a periodic basis. The most recent revisions took place in 2025. As of January 2025, LFS microdata and estimates have been adjusted to reflect population counts from the 2021 Census, with revisions going back to 2011. Additionally, several changes were made to key variables on the PUMFs: Survey weights (FINALWT) have been updated to use 2021 Census population control totals. Sub-provincial geography (CMA) has been updated to the 2021 Standard Geographical Classification (SGC) boundaries. All industry data (NAICS_21) was revised to use the latest standard, North American Industry Classification System (NAICS) 2022. Coding enhancements were applied to improve longitudinal consistency of detailed National Occupational Classification data (NOC_10 and NOC_43). Data were revised to use the gender of person instead of sex (GENDER).

The goal for Payroll Data Feed is to securely acquire pay data for all Federal Civilian employees by leveraging existing data extraction processes to the extent possible.Depending on the source of pay related data, one provider may submit payroll data for many agencies. Payroll data submissions from providers to EHRI represent actual payroll records in a given pay period. When a payroll data provider makes major system changes, it is responsible for ensuring that data accuracy and completeness are maintained. The Office of Personnel Management should be notified when any major system changes are planned. Then, the Office of Personnel Management will decide whether the payroll data provider should submit test data or continue to submit publication data.