Unemployment by previous industrial sector. These estimates are sourced from the Labour Force Survey, a survey of households. These are official statistics in development.

Employment, unemployment and economic inactivity levels and rates by age group, UK, rolling three-monthly figures, seasonally adjusted. Labour Force Survey. These are official statistics in development.

Employment by age and sex for UK regions and countries, rolling three-monthly figures published monthly, not seasonally adjusted. Labour Force Survey.

Labour market activity by nationality, country of birth and age, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

In 1990, the unemployment rate of the United States stood at 5.6 percent. Since then there have been many significant fluctuations to this number - the 2008 financial crisis left millions of people without work, as did the COVID-19 pandemic. By the end of 2022 and throughout 2023, the unemployment rate came to 3.6 percent, the lowest rate seen for decades. However, 2024 saw an increase up to four percent. For monthly updates on unemployment in the United States visit either the monthly national unemployment rate here, or the monthly state unemployment rate here. Both are seasonally adjusted. UnemploymentUnemployment is defined as a situation when an employed person is laid off, fired or quits his work and is still actively looking for a job. Unemployment can be found even in the healthiest economies, and many economists consider an unemployment rate at or below five percent to mean there is 'full employment' within an economy. If former employed persons go back to school or leave the job to take care of children they are no longer part of the active labor force and therefore not counted among the unemployed. Unemployment can also be the effect of events that are not part of the normal dynamics of an economy. Layoffs can be the result of technological progress, for example when robots replace workers in automobile production. Sometimes unemployment is caused by job outsourcing, due to the fact that employers often search for cheap labor around the globe and not only domestically. In 2022, the tech sector in the U.S. experienced significant lay-offs amid growing economic uncertainty. In the fourth quarter of 2022, more than 70,000 workers were laid off, despite low unemployment nationwide. The unemployment rate in the United States varies from state to state. In 2021, California had the highest number of unemployed persons with 1.38 million out of work.

Unemployment numbers and rates for those aged 16 or over. The unemployed population consists of those people out of work, who are actively looking for work and are available to start immediately.

Unemployed numbers and rates also shown for equalities groups, by age, sex, ethnic group, and disability. Economic inactivity rates and numbers for regions.

The data are taken from the Labour Force Survey and Annual Population Survey, produced by the Office for National Statistics.

The data are produced monthly on a rolling quarterly basis. The month shown is the month the quarter ends on.

International Labour Organization define unemployed people as: without a job, want a job, have actively sought work in the last 4 weeks and are available to start work in the next 2 weeks, or, out of work, have found a job and are waiting to start it in the next 2 weeks.

The figures in this dataset are adjusted to compensate for seasonal variations in employment (Seasonally adjusted).

Data by equalities groups has a longer time lag and is only available quarterly from the Annual Population Survey, which is not seasonally adjusted.

Click http://www.ons.gov.uk/ons/rel/subnational-labour/regional-labour-market-statistics/index.html">here for Regional labour market statistics from the Office for National Statistics

Click http://www.ons.gov.uk/ons/rel/lms/labour-market-statistics/index.html">here for Labour market statistics from the Office for National Statistics

Single-month estimates of employment, unemployment and economic inactivity, UK, rolling three-monthly figures published monthly, seasonally adjusted. Labour Force Survey.

Unemployment by age and duration (seasonally adjusted). These estimates are sourced from the Labour Force Survey, a survey of households. These are official statistics in development.

Unemployment numbers and rates for those aged 16 or over. The unemployed population consists of those people out of work, who are actively looking for work and are available to start immediately.

Unemployed numbers and rates also shown for equalities groups, by age, sex, ethnic group, and disability.

The data are taken from the Labour Force Survey and Annual Population Survey, produced by the Office for National Statistics.

The data are produced monthly on a rolling quarterly basis. The month shown is the month the quarter ends on.

The International Labour Organization defines unemployed people as: without a job, want a job, have actively sought work in the last 4 weeks and are available to start work in the next 2 weeks, or, out of work, have found a job and are waiting to start it in the next 2 weeks.

The figures in this dataset are adjusted to compensate for seasonal variations in employment (seasonally adjusted).

Data by equalities groups has a longer time lag and is only available quarterly from the Annual Population Survey, which is not seasonally adjusted.

Useful links

Click here for Regional labour market statistics from the Office for National Statistics.

Click here for Labour market statistics from the Office for National Statistics.

See here for GLA Economics' Labour Market Analysis.

See here for Economic Inactivity statistics.

See here for Employment rates.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In August 2025, the national unemployment rate was at 4.3 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends.

In August 2025, the unemployment rate for those aged 16 and over in the United States came to 4.5 percent. Service occupations had an unemployment rate of 5.7 percent in that month. The underemployment rate of the country can be accessed here and the monthly unemployment rate here. Unemployment by occupation in the U.S. The United States Bureau of Labor Statistics publish data on the unemployment situation within certain occupations in the United States on a monthly basis. According to latest data released from May 2023, transportation and material moving occupations experienced the highest level of unemployment that month, with a rate of around 5.6 percent. Second ranked was farming, fishing, and forestry occupations with a rate of 4.9 percent. Total (not seasonally adjusted) unemployment was reported at 3.6 percent in March 2023. Other data on the U.S. unemployment rate by industry and class of worker shows comparable results. It should be noted that the data were not seasonally adjusted to account for normal seasonal fluctuations in unemployment. The monthly unemployment by occupation data can be compared to the seasonally adjusted monthly unemployment rate. In March 2023, the seasonally adjusted unemployment rate was 3.5 percent, which was an increase from the previous month. The annual unemployment rate in 2022 was 3.6 percent, down from a high of 9.6 in 2010. Unemployment in the United States trended downward after the coronavirus pandemic, and is now experiencing consistently low rates - a sign of economic stability. Individuals who opt to leave the workforce and stop looking for employment are not included among the unemployed. The civilian labor force participation rate in the U.S. rose to 62.2 percent in 2022, down from 67.1 percent in 2000, before the financial crisis.

The 'LFS main indicators' section presents a selection of the main statistics on the labour market. They encompass indicators of activity, employment and unemployment. Those indicators are based on the results of the European Labour Force Survey (EU-LFS), in few cases integrated with data sources like national accounts employment or registered unemployment. As a result of the application of adjustments, corrections and reconciliation of EU Labour Force Survey (EU-LFS) data, the 'LFS main indicators' is the most complete and reliable collection of employment and unemployment data available in the sub-domain 'Employment and unemployment'.

The EU-LFS data used for 'LFS main indicators' are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. The most common adjustments cover:

• estimation of missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using interpolations of EU Labour Force Survey data with reference to the available quarter(s).
• for all quarterly indicators seasonally adjusted data are available.
• correction of the main breaks in the LFS series.

Those adjustments may produce some differences between data published under 'LFS main indicators' and 'LFS series – detailed quarterly/annual survey results', particularly for back data. For the most recent years, the different series converge, due to the implementation of a continuous quarterly survey and the improved quality of the data.

This page focuses on the 'LFS main indicators' in general. There are special pages for indicators that are listed below:

• Monthly Unemployment: une_rt_m.

Quarterly and annual unemployment figures are derived in line with all other LFS Main Indciators, and no longer aggregated from monthly unemployment series.

• Duration of working life - annual data: lfsi_dwl_a;
• Population in jobless households - annual data: lfsi_jhh_a;
• Labour market transitions - LFS longitudinal data: lfsi_long.

The entry of the new Framework regulation on Social Statistics (IESS) in 2021 created changes in the LFS Main Indicators. Most countries expected breaks for a number of series derived from LFS microdata, therefore Eurostat and participating countries launched a joint break correction exercise to produce comparable data before and under IESS. The 'LFS main indicators' section therefore contains two type of datasets depending on the underlying regulation. The first type of datasets are historical series under the pre-IESS regulation, and include the suffix ‘_h’ for historical series at the end of the table titles. Historical series will remain accessible and are continued until 2020Q4 LFS microdata revisions of previously released EU-LFS series. Reasons for revisions are for example weight revisions due to revised weighting routines, or census revisions. The second type of datasets are new tables that are filled with data under IESS from 2021Q1 on. These tables also include the break-corrected 2009Q1-2020Q4 data that are produced in the break correction exercise. If countries send longer complete time series than starting in 2009, that data will also be used and published. Until fully back-estimated series in line with IESS are available for all countries, EU and EA aggregates were based on the data that is available at the time and was flagged with a break flag. Fully break-free EU and EA aggregates were published for the first time in February 2022. More information can be found on the EU-LFS Breaks in Time Series (Statistics Explained) webpage.

General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Statistics on Labour Force, Unemployment and Underemployment - Table 210-06407 : Unemployed persons with a previous job and unemployment rate by previous occupation, age and sex

This dataset uses ONS Claimant Count estimates to monitor unemployment in Leicester.Claimant Count is the number of people claiming Universal Credit or Jobseekers' Allowance principally for the reason of being unemployed.Claimant Count is a useful proxy for unemployment because it is the most comprehensive unemployment-related dataset published at geographies smaller than the local authority level. While there is significant overlap, it is not the same as the official measure for unemployment, which is based on estimates from the Labour Force Survey and Annual Population Survey.Claimant Count is best used for understanding short term changes in the labour market and the relative position of small areas.Rates are calculated using ONS mid-year or census based population estimates for the 16-64 year old population as a denominator.A dashboard has also been produced summarising this data into a single page. Click here to view: DashboardFurther information: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/methodologies/aguidetolabourmarketstatistics#introduction

The Office for National Statistics (ONS) has jointly developed with Professor Ray Chambers of the University of Southampton, a new modelling methodology to produce modelled estimates of unemployment levels and rates on the International Labour Organisation (ILO) definition for local authority districts and unitary authorities (LAD/UAs). The unemployed population consists of those people out of work, who are actively looking for work and are available to start immediately. The data are taken from the Annual Population Survey, produced by the Office for National Statistics.

The unemployment rate is based on persons aged 16 and over.

The methodology is on the ONS website.

Regional level data can also be found on the ONS website.

This dataset uses ONS Claimant Count estimates to monitor unemployment in Leicester. Claimant data by age and sex are presented here for Leicester and England to allow for comparison. This dataset shows data for the latest available month only.Claimant Count is the number of people claiming Universal Credit or Jobseekers' Allowance principally for the reason of being unemployed.Claimant Count is a useful proxy for unemployment because it is the most comprehensive unemployment-related dataset published at geographies smaller than the local authority level. While there is significant overlap, it is not the same as the national measure for unemployment, which is based on estimates from the Labour Force Survey and Annual Population Survey.Claimant Count is best used for understanding short term changes in the labour market and the relative position of small areas.Rates are calculated using ONS mid-year estimates for the 16-64 year old population as a denominator.The ONS does not publish claimant count rate estimates for the age bands presented here, so these are not official estimates and should be treated with caution.Further information: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/methodologies/aguidetolabourmarketstatistics#introduction

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.

Labour market statistics time series

🌍 This dataset provides global youth unemployment rates for individuals aged 15–24 across all available countries and years, giving a comprehensive view of labor market conditions for young people worldwide.

🔍 Youth unemployment measures young people who are actively looking for work but cannot find a job. According to World Bank standards, students who are not participating in the labor force are not included, while students who are actively job-seeking are counted. Only individuals who are available for work and searching for employment are considered unemployed. This makes the dataset a precise reflection of labor market pressure among young job seekers.

📊 This dataset contains 17,290 rows and 4 columns: Country, CountryCode, Year, and YouthUnemployment. It includes data for all available countries and territories and spans the years 1960–2023. Some values are missing for certain countries and years where data is not available.

💹 Youth unemployment is an important indicator of economic health, social development, and workforce stability. Monitoring these rates helps reveal patterns in youth labor markets, including regional disparities, historical trends, and the effects of economic policies. The dataset allows for cross-country comparisons, time-series analysis, and identification of long-term shifts in youth employment opportunities. It is a valuable resource for researchers, policymakers, educators, and analysts seeking to understand the challenges faced by young populations as they transition from education to the workforce.

Statistics on Labour Force, Unemployment and Underemployment - Table 210-06103 : Unemployment rate and underemployment rate by age and sex