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

Job Growth Statistics: Statistics on job growth are essential in understanding the state and trajectory of an economy because they offer insight into the shifting dynamics of labor markets. By measuring net job addition or subtraction over a certain timeframe, employment growth statistics allow policymakers, companies, and individuals to make well-informed decisions regarding workforce planning, investment decisions, or career choices. Statistics on job growth provide a key measure of economic development as they show whether an economy is expanding, contracting, or remaining stable. Positive employment growth numbers often signal healthy economies with increased consumer spending and company confidence. Conversely, negative or stagnant job growth indicates a slowdown or recession. Furthermore, statistics on employment growth may also be used to highlight developing markets and professions for policymakers as well as job seekers in finding prospective development areas. As such, employment data provides an essential means of measuring an economy's current state and future direction, as well as helping shape policies and initiatives within it. Editor’s Choice From 2020-2030; job growth in the US is anticipated to be 5.3%. Nurse practitioners are predicted to experience the highest job growth; between 2021-2031 at 45.7%; 2019 alone saw sectors producing goods create 188,000 new jobs. Leisure and hospitality job creation decreased by 47% year-on-year between April 2020 and March 2021. President Clinton created 19 million new employment opportunities between June and July of 2022 and 528,000 nonfarm payroll employees were gained; yet by April 2020 20.5 million jobs had been lost from the economy as a whole. By 2031, it is projected that employment opportunities across the nation will reach 166.5 million; over that same timeframe childcare service workers have seen their ranks decline by 336,000. Since the COVID-19 outbreak, healthcare employment levels have suffered a dramatic decrease. By some accounts, over one and a half million employees may have left healthcare jobs since 2016. (Source: zippia.com)

In 2022, half of the young Poles surveyed were looking for a job on the labor market that matches their education profile. However, nearly ** percent of surveyed were looking for a job with the possibility of employment under a contract.

Employment Rate in the United States increased to 59.70 percent in September from 59.60 percent in August of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In April 2020, the Mexican labor market took the hardest hit from the COVID-19 pandemic. That month, nearly **** million jobs were lost in the North American country. The labor market slowly recovered in the following months, with June 2020 registering the largest job creation since the outbreak of the pandemic: the number of employed persons grew in **** million that month. In August 2023, the latest data available, approximately ******* new jobs were created.

Introducing the Indeed Job Postings Index

Hiring Lab's Job Postings Tracker is being re-released as the Indeed Job Postings Index. By Chris Glynn

Indeed Hiring Lab is re-releasing our Job Postings Tracker as the Indeed Job Postings Index, a daily measure of labor market activity that is updated and will continue to be released weekly. Covering seven national markets in the US, Canada, United Kingdom, Ireland, France, Germany, and Australia, the Indeed Job Postings Index meets one of Hiring Lab’s primary goals: produce high quality and high frequency labor market metrics using Indeed’s proprietary data.

The primary difference between the Indeed Job Postings Index and the legacy Job Postings Tracker is the level. The Indeed Job Postings Index is set to 100 on February 1, 2020, and this effectively provides a uniform level shift of 100 to the existing Job Postings Tracker across all time points.The Job Postings Tracker measured the percent change in postings from February 1st, 2020. For example, if the Job Postings Tracker were 40%, the corresponding Indeed Job Postings Index on the same date would be 140. Additionally, we are now including year-over-year and month-over-month percent changes in the Indeed Job Postings Index as part of our data portal on hiringlab.org/data and on our GitHub page. Month-over-month changes are calculated as 28 day (4 week) differences to control for day of week.

As Covid-19 fades from the global labor market discussion, moving to an index better reflects current economic conditions. The Indeed Job Postings Index allows us to compare job postings more naturally across flexible date ranges as opposed to comparing to the pre-pandemic baseline. It also places Indeed’s job postings metric in a broader class of macroeconomic indexes such as the Case Shiller Index that measures house price appreciation and the Consumer Price Index that measures inflation.

Data Schema Each market covered by a Hiring Lab economist has a folder in this repo. Each folder contains the following files:

aggregate_job_postings_{country_code}.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings and new jobs postings (on Indeed for 7 days or fewer) for that market, as well as non-seasonally adjusted postings since February 1, 2020 for total job postings.

job_postings_by_sector_{country_code}.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for occupational sectors for that market. We do not share sectoral data for Ireland.

For certain markets, we also share subnational job postings trends. In the United States, we provide:

metro_job_postings_us.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in US metropolitan areas with a population of at least 500,000 people.

state_job_postings_us.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in the US states and the District of Columbia.

In Canada, we provide:

provincial_postings_ca.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each Canadian provinces. In the United Kingdom, we provide:

regional_postings_gb.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each region in the UK.

city_postings_gb.csv This file contains the % change in seasonally-adjusted postings since February 1, 2020 for total job postings in each city in the UK.

Github link: https://github.com/hiring-lab/job_postings_tracker#data-schema Hiring Lab Link: https://www.hiringlab.org/2022/12/15/introducing-the-indeed-job-postings-index/

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (StatsSA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa. Since 2008, StatsSA have produced an annual dataset based on the QLFS data, "Labour Market Dynamics in South Africa". The dataset is constructed using data from all all four QLFS datasets in the year. The dataset also includes a number of variables (including income) that are not available in any of the QLFS datasets from 2010.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population except for those in workers' hostels. However, persons living in private dwelling units within institutions are enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

Each year the LMDSA is created by combining the QLFS waves for that year and then including some additional variables. The QLFS master frame for this LMDSA was based on the 2011 population census by Stas SA. The sampling is stratified by province, district, and geographic type (urban, traditional, farm). There are 3324 PSUs drawn each year, using probability proportional to size (PPS) sampling. In the second stage Dwelling Units (DUs) are systematically selected from PSUs. The 3324 PSU are split into four groups for the year, and at each quarter the DUs from the given group are replaced by substitute DUs from the same PSU or the next PSU on the list (in the same group). It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for two more quarters until the DU is rotated out. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The survey questionnaire consists of the following sections: - Particulars of each person in the household - Economic activities in the last week for persons aged 15 years - Unemployment and economic inactivity for persons aged 15 years - Main work activity in the last week for persons aged 15 years - Earnings in the main job for employees, employers and own-account workers aged 15 years - Migration for all persons aged 15 years

Data appraisal

The statistical release notes that missing values were "generally imputed" for item non-response but provides no detail on how Statistics SA did so.

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, 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, either to adopt the most recent geography, industry and occupation classifications; to use new observations to fine-tune seasonal adjustment factors; or to introduce methodological enhancement. Prior LFS revisions were conducted in 2011, 2015 and 2021. The most recent revisions to the LFS were conducted in 2023. The first major change was a transition to the National Occupational Classification (NOC) 2021 V1.0, with all LFS series from 1987 onwards having been revised to the new classification. The second major change were methodological enhancements to LFS data processing, applied to all LFS series beginning Jan 2006. The third major change was a revision of seasonal adjustment factors, applied to LFS series Jan 2002 onward. A list of prior versions of this LFS dataset can be found under the ‘Versions’ tab.

This statistic reflects the perception of the Spanish population regarding the severity of the economic and labor consequences caused by the coronavirus (COVID-19). In April 2020, more than three quarters of those surveyed, specifically 80 percent, thought that the consequences of the crisis caused by this pandemic could be very serious.

Italy's public expenditure on the labor market accounted for ***** percent of the GDP in 2020. The public spending on the job market includes public employment services (PES), training, hiring subsidies, job creations in the public sector, as well as unemployment benefits. Compared to the period from 2007 to 2019, the spending drastically increased in 2020, following the consequences brought in by the Coronavirus pandemic. In Italy, the total social expenditure amounts to **** percent of the country's GDP, some of the highest among the OECD countries.

Increasing workers’ access to jobs has been found to significantly decrease the duration of joblessness among lower-income unemployed workers. Policies that influence the location of employment growth within a metro area could impact the pace of the labor market recovery from the COVID-19-induced recession. By studying trends in job access, we discern developments that might inform our policy choices.

An area of employment is a geographical area within which most of the workers reside and work, and in which establishments can find the bulk of the labour force needed to fill the jobs offered. The division into employment areas is a partition of the territory adapted to local labour market studies. It serves as a reference for the dissemination of localised unemployment rates and job estimates.Zoning also defines territories relevant to local diagnostics and can guide the delimitation of territories for the implementation of territorial policies initiated by public authorities or local actors. This zoning is defined for both metropolitan France and the French overseas departments. The updated breakdown is based on the commuting flows of the observed workers. An area of employment is a geographical area within which most of the workers reside and work, and in which establishments can find the bulk of the labour force needed to fill the jobs offered. The division into employment areas is a partition of the territory adapted to local labour market studies. It serves as a reference for the dissemination of localised unemployment rates and job estimates. Zoning also defines territories relevant to local diagnostics and can guide the delimitation of territories for the implementation of territorial policies initiated by public authorities or local actors. This zoning is defined for both metropolitan France and the French overseas departments.

The updated breakdown is based on the commuting flows of the observed workers.

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Comprehensive global job posting datasets since 2020, enabling insights into job market trends, skill requirements, and industry changes.

Number of persons in the labour force (employment and unemployment) and unemployment rate, by North American Industry Classification System (NAICS), gender and age group.

United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Labour Market: Unemployment Insurance: Unemployment Rate: sa data was reported at 0.084 % in 01 Dec 2025. This records a decrease from the previous number of 0.087 % for 24 Nov 2025. United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Labour Market: Unemployment Insurance: Unemployment Rate: sa data is updated weekly, averaging 0.029 % from Jan 2020 (Median) to 01 Dec 2025, with 306 observations. The data reached an all-time high of 40.397 % in 06 Apr 2020 and a record low of 0.000 % in 28 Jul 2025. United States Non Farm Payroll Nowcast: sa: MoM: Contribution: Labour Market: Unemployment Insurance: Unemployment Rate: sa data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Employment: Non Farm Payroll.

LABOR MARKET ENGAGEMENT INDEXSummary

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 (i). Formally, the labor market index is a linear combination of three standardized vectors: unemployment rate (u), labor-force participation rate (l), and percent with a bachelor’s degree or higher (b), using the following formula:

Where means and standard errors are estimated over the national distribution. Also, the value for the standardized unemployment rate is multiplied by -1.

Interpretation

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.

Data Source: American Community Survey, 2011-2015Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 9.

To learn more about the Labor Market Engagement Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

Abstract The Covid-19 pandemic had several consequences for economies around the world, especially in the labor market. Considering this context, the present study analyzes which personal and socioeconomic characteristics are associated with the formal participation of individuals in the Brazilian labor market in a pandemic scenario. For this purpose, data from the PNAD Covid-19 for the year 2020 were used with the application of logistic regressions. The results indicated different relationships between the variables of gender, race and family responsibility with the probability of the individual having a formal job. In addition, it was also verified that individuals diagnosed with some health risk factor are less likely to be in a formal occupation situation. Finally, it was found that this heterogeneity also exists when considering sectoral differences.