Unemployment Rate in the United Kingdom remained unchanged at 4.70 percent in June. This dataset provides the latest reported value for - United Kingdom Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The unemployment rate of the United Kingdom was 4.7 percent in June 2025, unchanged from the previous month. Before the arrival of the COVID-19 pandemic, the UK had relatively low levels of unemployment, comparable with the mid-1970s. Between January 2000 and the most recent month, unemployment was highest in November 2011, when the unemployment rate hit 8.5 percent. Will unemployment continue to rise in 2025? Although low by historic standards, there has been a noticeable uptick in the UK's unemployment rate, with other labor market indicators also pointing to further loosening. In December 2024, the number of job vacancies in the UK fell to its lowest level since May 2021, while payrolled employment declined by 47,000 compared with November. Whether this is a continuation of a broader cooling of the labor market since 2022 or a reaction to more recent economic developments, such as upcoming tax rises for employers, remains to be seen. Forecasts made in late 2024 suggest that the unemployment rate will remain relatively stable in 2025, averaging out at 4.1 percent and falling again to four percent in 2026.
Demographics of the unemployed As of the third quarter of 2024, the unemployment rate for men was slightly higher than that of women, at 4.4 percent, compared to 4.1 percent. During the financial crisis at the end of the 2000s, the unemployment rate for women peaked at a quarterly rate of 7.7 percent, whereas for men, the rate was 9.1 percent. Unemployment is also heavily associated with age, and young people in general are far more vulnerable to unemployment than older age groups. In late 2011, for example, the unemployment rate for those aged between 16 and 24 reached 22.3 percent, compared with 8.2 percent for people aged 25 to 34, while older age groups had even lower peaks during this time.

Quarterly estimates for young people (aged 16 to 24 years) who are not in education, employment or training (NEET) in the UK. These are official statistics in development.

In June 2025, the employment rate in the United Kingdom was 75.3 percent, up from 75.2 percent in the previous month. After almost dropping below 70 percent in 2011, the employment rate in the United Kingdom started to climb at a relatively fast pace, peaking in early 2020. Due to the onset of the COVID-19 pandemic, however, employment declined to 74.6 percent by January 2021. Although not quite at pre-pandemic levels, the employment rate has since recovered. Labor market trouble in 2025? Although unemployment in the UK spiked at 5.3 percent in the aftermath of the COVID-19 pandemic, it fell throughout most of 2022, to just 3.6 percent in August 2022. Around that time, the number of job vacancies in the UK was also at quite high levels, reaching a peak of 1.3 million by May 2022. The strong labor market put employees in quite a strong position, perhaps encouraging the high number of resignations that took place around that time. Since 2023, however, the previously hot labor market has cooled, with unemployment reaching 4.6 percent in April 2025 and job vacancies falling to a four-year low of 736,000 in May 2025. Furthermore, the number of employees on UK payrolls has fallen by 227,500 in the first five months of the year, indicating that 2025 will be a tough one for the labor market. Headline economic measures revised in early 2025 Along with the unemployment rate, the UK's inflation rate is also expected to be higher than initially thought in 2025, reaching a rate of 3.2 percent for the year. The economy will also grow at a slower pace of one percent rather than the initial prediction of two percent. Though these negative trends are not expected to continue in the long term, the current government has already expended significant political capital on unpopular decisions, such as the cutting of Winter Fuel Payments to pensioners in 2024. As of June 2025, they are almost as unpopular as the previous government, with a net approval rating of -52 percent.

Abstract

The Labour Force Survey (LFS) is a study of the employment circumstances of the UK population. It is the largest household study in the UK and provides the official measures of employment and unemployment.The first Labour Force Survey (LFS) in the United Kingdom was conducted in 1973, under the terms of a Regulation derived from the Treaty of Rome. The provision of information for the Statistical Office of the European Communities (SOEC) continued to be one of the reasons for carrying out the survey on an annual basis. SOEC co-ordinated information from labour force surveys in the member states in order to assist the EC in such matters as the allocation of the Social Fund. The survey was carried out biennially from 1973 to 1983 and was increasingly used by UK government departments to obtain information which would assist in the framing of social and economic policy. By 1983 it was being used by the Employment Department (now the Department for Work and Pensions) to obtain information which was not available from other sources or was only available for Census years. From 1984 the survey was carried out annually, and since that time the LFS has consisted of two elements:

• a quarterly survey conducted in Great Britain throughout the year, in which each sampled address was called on five times at quarterly intervals, and which yielded about 15,000 responding households in every quarter;
• a 'boost' survey in the spring quarter (March-May), which produced interviews at over 44,000 households in Great Britain and over 4,000 households in Northern Ireland.

Users should note that only the data from the spring quarter and the 'boost' survey were included in the annual datasets for public release, and that only data from 1975-1991 are available from the UK Data Archive. The depositor recommends only considered use of data for 1975 and 1977 (SNs 1757 and 1758), as the concepts behind the definitions of economic activity changed and are not comparable with later years. Also the survey methodology was being developed at the time and so the estimates may not be reliable enough to use.

During 1991 the survey was developed, so that from spring 1992 the data were made available quarterly, with a quarterly sample size approximately equivalent to that of the previous annual data. The Quarterly Labour Force Survey series therefore superseded the annual LFS series, and is held at the Data Archive under GN 33246.

The study is being conducted by the Office for National Statistics (ONS), the government's largest producer of statistics. They compile independent information about the UK's society and economy which provides evidence for policy and decision making, and for directing resources to where they are needed most. The ten-yearly census, measures of inflation, the National Accounts, and population and migration statistics are some of our highest-profile outputs.

Geographic coverage

The whole country.

Analysis unit

• Individuals
• Families/households

Universe

• Households
• All persons normally resident in private households in the United Kingdom

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified multi-stage sample; for further details see annual reports. Until 1983 two sampling frames were used; in England, Northern Ireland and Wales, the Valuation Roll provided the basis for a sample which, in England and Wales, included all 69 metropolitan districts, and a two-stage selection from among the remaining non-metropolitan districts. In Northern Ireland wards were the primary sampling units. In Scotland, the Address File (i.e. post codes) was used as the basis for a stratified sample.From 1983 the Postoffice Address File has been used instead of the Valuation Roll in England and Wales. In 1984 sample rotation was introduced along with a panel element, the quarterly survey, which uses a two-stage clustered sample design.

The sample comprises about 90,000 addresses drawn at random from the rating lists in 190 different areas of England and Wales With such a large sample, it Will happen by chance that a small number of addresses which were selected at random for the 1979 survey Will come up again In addition 2,000 addresses in 8 of the areas selected in 1979 have been deliberately re-selected again this time (me Interviewers who get these addresses In their work w,ll receive a special letter to take with them.)

The sample is drawn from the "small users" sub-file of the Postcode Address File (PAF), which is a list of all addresses (delivery points) to which mail is delivered, prepared by the Post OffIce and held on computer. "Small users" are delivery points that receive less than 25 afiicles of mail a day and include all but a small proportion of private households. The PAF is updated regularly by the Post Office but, as mentioned in Chapter 1, there was an interruption in the supply of updates in the period leading up to the 1988 msurvey. As a result one third of the sample was drawn from the PAF as at March 1986 and two thirds from the sample as at September 1986.

Sample sizes and response rates Numbers of households who answered the questions in the Housing. Trailer were 37,761 in 1988. The corresponding response rates were 82.5 percent. Response rates were highest in East Anglia with nearly 89 percent in 1988, lowest in Inner London with 73 percent in 1988.

Sampling deviation

One of the limitations of the LFS is that the sample design provides no guarantee of adequate coverage of any industry, as the survey is not industrially stratified. The LFS coverage also omits communal establishments, except NHS housing, students in halls of residence and at boarding schools. Members of the armed forces are only included if they live in private accommodation. Also, workers under 16 are not covered. As in previous years, the sample for the boost survey was drawn in a single stage in the most densely populated areas, in two stages elsewhere. The areas where the sample was drawn in a single stage were:

(I) local authority districts in the metropolitan counties and Greater London; (II) districts which, based on the 1981 Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

All questions in the specification are laid out using the same format. Some questions (for instance USUWRKM) have a main group routed to them, but subsets of this group are asked variations of the question. In such cases the main routing is at the foot of the question as usual, and the subsets are listed separately above it, with the individual aspect of the routing indented slightly from the left of the page.

In addition to the information on the address list, the address and serial number is also pre-printed on the E questionnaire to save time and increase accuracy. You will see that each E questionnaire has been pre-printed with household number 01. Where there is more than one household to be interviewed, you will need to enter the information on the blank E questionnaires provided.

Cleaning operations

Information Technology Centres provides one-year training and practical work experience course in the use of computers and word processors and other aspects of information technology (eg teletex, editing, computer maintenance).

Response rate

Method of calculating response rates The response rate indicates how many interviews were achieved as a proportion of those eligible for the survey. The formula used is as follows: RR = (FR + PR)/(FR + PR + OR + CR + RHQ + NC + RRI*) where RR = response rate, FR = full response, PR = partial response, OR = outright refusal, CR = circumstantial refusal, RHQ = refusal to HQ, NC = non contact, RRI = refusal to re-interview, *applies to waves two to five only.

The combined sample for tne UK IS over 63,00U householrls (60,000 for Great Britain). the sample size is intended to be sufficiently large to allow reliable informatlon to be produced at th national and regional levels, and also to allow analysls of fairly small subgroups of the population. The response rate achieved averaged between 80 and 85 percent.

Sampling error estimates

As with any sample survey, the results of the Labour Force Survey are subject to sampling errors. In addition, the results of any sample survey are affected by non-sampling errors, i.e. the whole variety of errors other then those due to sampling. As with all sample surveys, Labour Force Survey results are subject to sarnphng error. The survey consists of only one of a number of possible samples, and had a different sample been taKen a different estimate would probably leave resulted sampling error is the measure of this variatlon. Sampling error can be reduced by stratifying the sample (although the increased error caused by clustering cannot be ehmmated by tires means). The stratum III boost survey PSUS were stratified by the proportion of economically actwe men who were unemployed in the local authorrty district according to the 1981 Census, while in Scotland the strata II and Ill sample was stratified by the percentage of persons in employment who were working in manual occupations These stratificatlon’s tend to reduce samping error in relahon to measurements of charactenshcs related to the factors used in strahficatlon. Hence lt is unappropriate to calculate sampling error for the LFS assuming simple random sampling, and errors are, therefore, estimated taking account of the sample design Standard errors for Great Bntam were estrmated (taking the complex sample design into account) by combining the variances for the major strata of the

Recessions are periods of economic contraction having a significant impact on various industries. Typically, a recession is characterized by a significant decline in the gross domestic product (GDP) over a time period, leading to widespread unemployment, loss of income, and reduced business activity.

Here is a dataset of the monthly GDP of the United Kingdom from 2020 to 2022. Below are all the features in the dataset:

1- Time Period: Monthly time period 2- GDP Growth: The growth rate of GDP every month

Abstract copyright UK Data Service and data collection copyright owner. The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS) (held at the UK Data Archive under GN 33246), all of its associated LFS boosts and the APS boost. Thus, the APS combines results from five different sources: the LFS (waves 1 and 5); the English Local Labour Force Survey (LLFS), the Welsh Labour Force Survey (WLFS), the Scottish Labour Force Survey (SLFS) and the Annual Population Survey Boost Sample (APS(B) - however, this ceased to exist at the end of December 2005, so APS data from January 2006 onwards will contain all the above data apart from APS(B)). Users should note that the LLFS, WLFS, SLFS and APS(B) are not held separately at the UK Data Archive. For further detailed information about methodology, users should consult the Labour Force Survey User Guide, selected volumes of which have been included with the APS documentation for reference purposes (see 'Documentation' table below). The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples such as the WLFS and SLFS, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom. APS Well-Being data Since April 2011, the APS has included questions about personal and subjective well-being. The responses to these questions have been made available as annual sub-sets to the APS Person level files. It is important to note that the size of the achieved sample of the well-being questions within the dataset is approximately 165,000 people. This reduction is due to the well-being questions being only asked of persons aged 16 and above, who gave a personal interview and proxy answers are not accepted. As a result some caution should be used when using analysis of responses to well-being questions at detailed geography areas and also in relation to any other variables where respondent numbers are relatively small. It is recommended that for lower level geography analysis that the variable UACNTY09 is used. As well as annual datasets, three-year pooled datasets are available. When combining multiple APS datasets together, it is important to account for the rotational design of the APS and ensure that no person appears more than once in the multiple year dataset. This is because the well-being datasets are not designed to be longitudinal e.g. they are not designed to track individuals over time/be used for longitudinal analysis. They are instead cross-sectional, and are designed to use a cross-section of the population to make inferences about the whole population. For this reason, the three-year dataset has been designed to include only a selection of the cases from the individual year APS datasets, chosen in such a way that no individuals are included more than once, and the cases included are approximately equally spread across the three years. Further information is available in the 'Documentation' section below. Secure Access APS Well-Being data Secure Access datasets for the APS Well-Being include additional variables not included in either the standard End User Licence (EUL) versions (see under GN 33357) or the Special Licence (SL) access versions (see under GN 33376). Extra variables that typically can be found in the Secure Access version but not in the EUL or SL versions relate to:geography, including:Postcodes Census Area Statistics (CAS) WardsCensus Output AreasNomenclature of Units for Territorial Statistics (NUTS) level 2 and 3 areasLower and Middle Layer Super Output AreasTravel to Work AreasUnitary authority / Local Authority District of place of work (main job)region of place of work for first and second jobsqualifications, education and training including level of highest qualification, qualifications from Government schemes, qualifications related to work, qualifications from school, qualifications from university of college and qualifications gained from outside the UK detailed ethnic group for Scottish respondentsdetailed religious denomination for Northern Irish respondentslength health problem has limited activity learning difficulty or learning disabilityoccupation in apprenticeship or second job number of bedrooms number of dependent children in household aged under 19Prospective users of the Secure Access version of the APS Well-Being will need to fulfil additional requirements, commencing with the completion of an extra application form to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access data users must also complete face-to-face training and agree to the Secure Access User Agreement and Licence Compliance Policy (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL version of the data prior to ordering the Secure Access (or SL) version. Further details and links to all APS studies available from the UK Data Archive can be found via the APS Key Data series webpage. APS Well-Being Datasets: Information, July 2016 From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Users should no longer use the bespoke well-being datasets (SNs 6994, 6999, 7091, 7092, 7364, 7365, 7565, 7566 and 7961, but should now use the variables included on the April-March APS person datasets instead. Further information on the transition can be found on the Personal well-being in the UK: 2015 to 2016 Documentation and coding frames The APS is compiled from variables present in the LFS. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation (e.g. coding frames for education, industrial and geographic variables, which are held in LFS User Guide Vol.5, Classifications), users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages. May 2018 Update Due to a change in the Travel-to-Work Area coding structure from 2001 to 2011, the variable TTWA9D has been relabelled in the pooled data file for 2012-2015. Main Topics: Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS. Multi-stage stratified random sample Face-to-face interview Telephone interview 2011 2015 ACADEMIC ACHIEVEMENT ADULT EDUCATION ADVANCED LEVEL EXAM... ADVANCED SUPPLEMENT... AGE ANXIETY APPLICATION FOR EMP... APPRENTICESHIP ARMED FORCES ATTITUDES BEDROOMS BUSINESS AND TECHNO... CARE OF DEPENDANTS CERTIFICATE OF SECO... CERTIFICATE OF SIXT... CHILDREN CITY AND GUILDS OF ... COHABITATION Censuses DEBILITATIVE ILLNESS DEGREES DISABILITIES DISABLED PERSONS ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL CERTIFI... EDUCATIONAL COURSES EDUCATIONAL STATUS EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES EMPLOYMENT SERVICES ETHNIC GROUPS FAMILIES FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER GENERAL CERTIFICATE... GENERAL NATIONAL VO... GENERAL SCOTTISH VO... HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH STATUS HIGHER EDUCATION HIGHER NATIONAL CER... HOURS OF WORK HOUSEHOLDS HOUSING HOUSING TENURE ILL HEALTH INCOME INDUSTRIES JOB CHANGING JOB HUNTING LANDLORDS LEARNING DISABILITIES LONGTERM UNEMPLOYMENT Labour and employment MANAGERS MARITAL STATUS NATIONAL IDENTITY NATIONAL VOCATIONAL... NATIONALITY NURSING EDUCATION OCCUPATIONAL QUALIF... OCCUPATIONS ORDINARY LEVEL EXAM... ORDINARY NATIONAL C... OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE SECTOR PUBLIC SECTOR QUALIFICATIONS REDUNDANCY RELIGIOUS AFFILIATION RESIDENTIAL MOBILITY ROYAL SOCIETY OF AR... RURAL AREAS SCOTTISH CERTIFICAT... SCOTTISH VOCATIONAL... SCOTTISH VOCATIONAL... SELF EMPLOYED SICK LEAVE SMOKING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TRAINING TRAINING COURSES UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... UNWAGED WORKERS URBAN AREAS United Kingdom VOCATIONAL EDUCATIO... WAGES WELL BEING SOCIETY WORKING CONDITIONS WORKPLACE

The surge in academic research and increased media spotlight on the toll that illness and injury can take on businesses has boosted wellness services. Companies have come to appreciate the importance of corporate wellness services in trimming down these cost, saving money on an unhealthy workforce. More and more businesses have been investing in wellness services in recent years. This growing trend has been propelled by a drop in the UK unemployment rate during the same period. Massive layoffs in the financial services sector since Brexit, sluggish demand from public-sector entities, and stiff competition from gyms and in-house services have somewhat stifled growth. On top of that, the COVID-19 outbreak significantly impacted revenue in 2020-21. Despite some of these challenges, the industry revenue is projected to grow at a compound annual rate of 1.4% over the five years through 2024-25 to £679.2 million. The COVID-19 outbreak threw a spanner in the works, causing revenue to contract significantly by 9% in 2020-21. Factors such as rising unemployment, reduced employer confidence, and tight corporate budgets dented the demand for wellness services. The shift to remote work since the outbreak in 2020 continues to be a challenge to services in unprecedented ways. The corporate wellness industry has rebounded, with an anticipated 5.0% growth rate in 2024-25 and has a bright future ahead. However, poor economic conditions, including high inflation in the three years through 2024-25, have caused businesses to cut their spending budgets and hamper industry demand. The sector is expected to see a compound annual growth rate of 5.4% over the five years through 2029-30 to £885 million. Higher levels of health consciousness and efforts by businesses to enhance productivity by reducing the costs of poor health, and growth in the online delivery of industry services will boost demand. Britain's ageing workforce and greater emphasis on tacking mental health problems will aid growth. However, corporate budgets are constrained in the short term due to macroeconomic headwinds, limiting revenue growth. Profit will widen over the coming period.

The research project is a subproject of the research association “Strengthening of integration potentials within a modern society” (Scientific head: Prof. Dr. Wilhelm Heitmeyer, Bielefeld) which contains 17 subprojects and is supported by the ministry of education and research. In almost all the economically highly developed countries violent crime increased significantly in the second part of the last century - in contrast to the long term trend of decline of individual (non-governmental) violence since the beginning of modern times. The authors develop an explanatory approach for these facts which is inspired mainly by Norbert Elias´s civilization theory and Emil Durkheim´s theory on society. Detailed time series on the development of different forms of violent crime are presented and set in relation with certain aspects of economic and social structural changes in three countries and also refer to the changes in integration of modern societies. The analysis deals especially with effectivity and legitimacy of the governmental monopoly of violence, the public beneficial security and power system, forms of building social capital, economic and social inequality, precarity of employment, different aspects of increasing economization of society, changes in family structures and usage of mass media and modern communication technologies. Register of tables in HISTAT: A: Crime statistics A.01 Frequency of types of crimes in different countries (1953-2000) A.02 Suspects by crimes of 100.000 inhabitants of Germany, England and Sweden (1955-1998) A.03 Murders, manslaughter and intentional injuries by other persons by sex of 100.000 persons after the statistics of causes of death (1953-2000) A.04 Clearance rate by types of crimes in Germany, England and Sweden (1953-1997) A.05 Prisoners of 100.000 inhabitants of Germany, Great Britain and Sweden (1950-2000) B: Key indicators for economic development in Germany, Great Britain, Sweden and the USA B1: Data on the overall economic framework B1.01 Percent changes in the real GDP per capita in purchasing power parities (1956-1987) B1.02 Percent changes in GDP per capita in prices from 2000 (1955-1998) B1.03 GDP of Germany, Sweden and the United Kingdom in purchasing power parities in percent og the US GDP (1950-1992) B1.04 Labor productivity index for different countries, base: USA 1996 = 100 (1950-1999) B1.05 GDP per hour of labor in different countries in EKS-$ from 1999 (1950-2003) B1.06 Foreign trade - exports and imports in percent of the GDP of different countries (1949-2003) B1.07 GDP, wages and Unit-Labor-Cost in different countries (1960-2003) B2: Unemployment B2.01 Standardized unemployment rate in different countries with regard to the entire working population (1960-2003) B2.02 Share of long-term unemployed of the total number of unemployed in different countries in percent (1992-2004) B2.03 Youth unemployment in different countries in percent (1970-2004) B2.04 Unemployment rate in percent by sex in different countries (1963-2000) B3: Employment B3.01 Employment rate in percent in different countries (1960-2000) B3.02 Share of fixed-term employees and persons in dependent employment in percent in different countries (1983-2004) B3.03 Share of part-time employees by sex compared to the entire working population in different countries (1973-2000) B3.04 Share of un-voluntarily part-time employees by sex in different countries (1983-2003) B3.05 Share of contract workers in different countries in percent of the entire working population (1975-2002) B3.06 Share of self-employed persons in different countries in percent of the entire working population (1970-2004) B3.07 Shift worker rate in different countries in percent (1992-2005) B3.08 Yearly working hours per employee in different countries (1950-2004) B3.09 Employment by sectors in different countries (1950-2003) B3.10 Share of employees in public civil services in percent of the population between 15 and 64 years in different countries (1960-1999) B3.11 Female population, female employees and female workers in percent of the population between 16 and 64 years in different countries (1960-2000) B3.12 Employees, self-employed persons in percent of the entire working population in different countries (1960-2000) B4: Taxes and duties B4.01 Taxes and social security contributions in percent of the GDP (1965-2002) B4.02 Social expenditure in percent of the GDP (1965-2002) B4.03 Social expenditure in percent of the GDP (1960-2000) B4.04 Public expenditure in percent of the GDP in different countries (1960-2003) B4.05 Education expenditure in percent of GDP (1950-2001) B5: Debt B5.01 Insolvencies in Germany and England (1960-2004) B5.02 Insolvencies with regard to total population in different countries (1950-2002) B5.03 Consumer credits in different countries (1960-2002) C: Income distribution in Germany, Great Britain and Sweden C.01 Income inequality in different countries Einkommensungleicheit in verschiedenen Ländern (1949-2000) C.02 Income inequality after different indices and calculations in different countries (1969-2000) C.03 Redistribution: Decline in Gini-Index through transfers and taxes in percent in different countries (1969-2000) C.04 Redistribution: Decline in Gini-Index through transfers and taxes in percent with a population structure as in the United Kingdom in 1969 in different countries (1969-2000) C.05 Redistribution efficiency: Decline in Gini-/ Atkinson-Index through transfers and the share of social expenditure of the GDP in different countries (1969-2000) C.06 Index for concentration of transfers in different countries (1981-2000) C.07 Distribution of wealth in West-Germany (1953-1998) C.08 Distribution of wealth in the United Kingdom (1950-2000) C.09 Distribution of wealth in Sweden (1951-1999) C.10 Relative income poverty in different countries (1969-2000) C.11 Reduction of poverty in different countries (1969-2000) C.12 Neocorporalism index in different countries (1960-1994) D: Perception of safety D.01 Satisfaction with democracy in different countries (1976-2004) D.02 Revenues and employees in the private security sector in different countries (1950-2001) D.03 Decommodification-Score in different countries (1971-2002) E: Demographics E.01 Birth rates: Birth per 1000 women between 15 and 49 years in different countries (1951-2001) E.02 Fertility rate in different countries (1950-2004) E.03 Marriages per 100.000 persons in different countries (1950-2003) E.04 Share of foreigners of the entire population in different countries (1951-2002) E.05 Internal migration in different countries (1952-2001)

As of June 2024, Spain had the highest youth unemployment rate in Europe, at 25.8 percent, with Sweden having the second-highest youth unemployment rate as of this month, at 23.8 percent. Across the 27 member states of the European Union, the overall youth unemployment rate was 14.6 percent, with Germany having the lowest youth unemployment rate of 6.8 percent.

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The Special Licence version of the QLFS October - December, 2010 is held under SN 6718. For the second edition (November 2014) an updated version of the data file was deposited, weighted to 2014 population figures (based on Census 2011). The new weighting variables are PIWT14 (income weight) and PWT14 (person weight). Also, non-responders are no longer included in the data due to a change in ONS database systems, so the number of cases is now reduced. Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire. Four sampling frames are used. See documentation for details.

In 2019, the UK pledged to achieve a net-zero carbon emission economy by 2050. While the so-called ‘green finance gap’ is generally acknowledged in this context, tailored policy recommendations on how to address it are missing. The focus of this project lies on the upscaling of private finance (e.g. from institutional investors) and represents a new system dynamics energy-economy model – called the Green Investment Barrier Model (GIBM) – that includes as a main novelty the representation of a green finance gap. System dynamics is most appropriate to model complex systems and to understand the likely long-term trends. In terms of key contributions, first the qualitative investigation demonstrates that key investment barriers form a complex system characterised by path dependency, lock-in and non-linearity. Therefore, the adoption of a systems policy, drawing on a long-term and holistic systems perspective and tackling identified key green investment barriers is recommended to close the green finance gap. Second, in terms of modelling contributions and as shown by GIBM, when a green finance gap exists, the introduction of a finance systems policy leads to multiple co-benefits, including an emission reduction, a decline in unemployment and a drop in the unit costs of energy, while increasing GDP by 2050. Further, GIBM results reveal that reaching the UK zero carbon targets for the electricity sector by 2050 requires the implementation of additional low-carbon energy policies besides a finance system policy. Finally in terms of modelling results, the recommended energy policy scenario includes a step-wise linear halt in brown energy infrastructure until 2050. Co-benefits of this latter policy scenario include higher GDP, lower energy system costs and lower unemployment. Third, in terms of theoretical contributions, it is demonstrated that the theoretical underpinning of models influences not only the magnitude of the impact but also the sign of their results and consequently policy formulation, it is therefore argued that more transparency on this among policy-makers is required, along with increased knowledge on how models with different theoretical frameworks should or should not be applied in combination.

In the three months to June 2025, there were around ******* redundancies made in the United Kingdom, compared with ******* in the three months to May. During this time period, the highest number of redundancies occurred in the three months to November 2020, when there were approximately ******* redundancies.

With the collapse of the U.S. housing market and the subsequent financial crisis on Wall Street in 2007 and 2008, economies across the globe began to enter into deep recessions. What had started out as a crisis centered on the United States quickly became global in nature, as it became apparent that not only had the economies of other advanced countries (grouped together as the G7) become intimately tied to the U.S. financial system, but that many of them had experienced housing and asset price bubbles similar to that in the U.S.. The United Kingdom had experienced a huge inflation of housing prices since the 1990s, while Eurozone members (such as Germany, France and Italy) had financial sectors which had become involved in reckless lending to economies on the periphery of the EU, such as Greece, Ireland and Portugal. Other countries, such as Japan, were hit heavily due their export-led growth models which suffered from the decline in international trade. Unemployment during the Great Recession As business and consumer confidence crashed, credit markets froze, and international trade contracted, the unemployment rate in the most advanced economies shot up. While four to five percent is generally considered to be a healthy unemployment rate, nearing full employment in the economy (when any remaining unemployment is not related to a lack of consumer demand), many of these countries experienced rates at least double that, with unemployment in the United States peaking at almost 10 percent in 2010. In large countries, unemployment rates of this level meant millions or tens of millions of people being out of work, which led to political pressures to stimulate economies and create jobs. By 2012, many of these countries were seeing declining unemployment rates, however, in France and Italy rates of joblessness continued to increase as the Euro crisis took hold. These countries suffered from having a monetary policy which was too tight for their economies (due to the ECB controlling interest rates) and fiscal policy which was constrained by EU debt rules. Left with the option of deregulating their labor markets and pursuing austerity policies, their unemployment rates remained over 10 percent well into the 2010s. Differences in labor markets The differences in unemployment rates at the peak of the crisis (2009-2010) reflect not only the differences in how economies were affected by the downturn, but also the differing labor market institutions and programs in the various countries. Countries with more 'liberalized' labor markets, such as the United States and United Kingdom experienced sharp jumps in their unemployment rate due to the ease at which employers can lay off workers in these countries. When the crisis subsided in these countries, however, their unemployment rates quickly began to drop below those of the other countries, due to their more dynamic labor markets which make it easier to hire workers when the economy is doing well. On the other hand, countries with more 'coordinated' labor market institutions, such as Germany and Japan, experiences lower rates of unemployment during the crisis, as programs such as short-time work, job sharing, and wage restraint agreements were used to keep workers in their jobs. While these countries are less likely to experience spikes in unemployment during crises, the highly regulated nature of their labor markets mean that they are slower to add jobs during periods of economic prosperity.

There are approximately 500,000 autistic adults currently living in the UK. The Office for National Statistics published a report in 2021 indicating that only 22% of autistic adults are in any kind of employment compared to 80% of non-autistic and non-disabled adults. Autistic people are at greater risk of social isolation, poor mental health, and premature mortality (Schiltz et al. 2021; Cassidy et al. 2022). Employment provides numerous opportunities for social interaction, increases financial independence, provides a sense of accomplishment and is known to be associated with improved mental health in the general population (Evans & Repper, 2000). Once in employment, job satisfaction is associated with improved health, well-being, and reduced anxiety in autistic people (Harkry et al., 2017). The UK government has identified “supporting more autistic people into employment” as one of six major priorities via their National Autism Strategy (2021-2026). The strategy highlights the importance of supporting autistic adults to find and stay in work. This includes the desire to help make employers more confident hiring and supporting autistic employees.

Many unemployed autistic people would like to be in employment, can have successful and fulfilling careers and make substantial contributions to the workplace. If suitable accommodations are made, autistic employees can succeed in their workplaces (Tomczak et al., 2021). A significant factor in the unemployment of autistic people is employers’ attitudes towards hiring, retaining, and promoting people with a disability. There is significant stigma against autistic people with employers incorrectly assuming there will be additional supervision, training and accommodation costs and reduced output. Scott et al. (2017) demonstrated that whilst there are different workplace modifications, training and supervision costs associated with employing autistic people, they were not significantly greater than those associated with their non-autistic colleagues. Furthermore, autistic employees demonstrated above average workplace performance compared to their non-autistic colleagues, performing particularly well in work quality, attention to detail and work ethic.

This project takes the findings from a previous part of the study (Day et al., 2023; OSF registration: Osf.io/x8tm3) where employers were surveyed to explore the perceived barriers they experience to hiring autistic people. These findings have been used to develop a targeted intervention aimed at the key barriers we identified and supporting those factors which were most associated with intentions to hire autistic people. This part of the project will evaluate this brief online intervention in terms of its acceptability, feasibility, and preliminary impacts on outcome variables (e.g., intentions to hire autistic people, attitudes towards hiring autistic people).

References

Cassidy, S., Au-Yeung, S., Robertson, A., Cogger-Ward, H., Richards, G., Allison, C., ... & Baron-Cohen, S. (2022). Autism and autistic traits in those who died by suicide in England. The British Journal of Psychiatry, 1-9.

Day, M., Freeth, M., Wood, C., & Corker, E. (2023, October 27). Understanding and Tackling the Barriers to Employment Experienced by Autistic Adults. https://doi.org/10.17605/OSF.IO/X8TM3

Evans, J., & Repper, J. (2000). Employment, social inclusion, and mental health. Journal of psychiatric and mental health nursing, 7(1), 15-24.

Harkry, L. C. (2017). The effects of employment on the mental health and executive functions of adults with autism spectrum disorder (ASD) [Doctoral, Goldsmiths, University of London]. http://eprints.leedsbeckett.ac.uk/id/eprint/4783/.

Schiltz, H. K., McVey, A. J., Dolan Wozniak, B., Haendel, A. D., Stanley, R., Arias, A., ... & Van Hecke, A. V. (2021). The role of loneliness as a mediator between autism features and mental health among autistic young adults. Autism, 25(2), 545-555.

Scott, M., Jacob, A., Hendrie, D., Parsons, R., Girdler, S., Falkmer, T., & Falkmer, M. (2017). Employers’ perception of the costs and the benefits of hiring individuals with autism spectrum disorder in open employment in Australia. PloS One, 12(5), e0177607.

Tomczak, M. T., Szulc, J. M., & Szczerska, M. (2021). Inclusive communication model supporting the employment cycle of individuals with autism spectrum disorders. International journal of environmental research and public health, 18(9), 4696.

Once a major powerhouse of the British economy, the coal mining industry was the lifeblood of several regions, providing employment to more than *********** workers before the 1930s. Since that time, shifting attitudes towards coal and the emergence of alternative energy sources such as wind and solar have seen coal's role in the UK's energy mix diminish. By 1990, the coal industry was still an employer to some ****** people, however from 2016 onwards, this figure had fallen to less than ************. Coal mines in the UK As of 2023, there were ***** UK coal mines left in operation. Of these, *** was an opencast site and *** were deep mines. The British government has made it clear that phasing out coal is necessary for the country to reach its goal of carbon neutrality by 2050. The industry is thus set to further contract in the future. Coal job cuts globally The shrinking number of jobs has not been isolated to the UK, with similar coal mining employment reductions in the United States. In some U.S. states, such as Kentucky, coal mining jobs had fallen by more than ************** in the past *** years. In Australia, where coal mining has traditionally been as strong contributor to the economy, this decreasing trend is also visible.

Due to the impact of the coronavirus (COVID-19) pandemic, it was estimated that the global travel and tourism market had lost roughly 63 million jobs in 2020. While this scenario improved significantly in 2022, the sector still reported around 39 million fewer jobs worldwide compared to 2019. Overall, the Asia-Pacific region recorded the most significant employment loss due to the COVID-19 pandemic, with approximately 28 million fewer travel and tourism jobs in 2022 compared to 2019.

Abstract copyright UK Data Service and data collection copyright owner. To explore social attitudes in Britain at the end of the 1970's and expectations of life in the next decade. Main Topics: Attitudinal/Behavioural Questions Whether Britain is a reasonably good place to live in, whether changes in the past ten years have been for the worse or for the better, expectations for next ten years, whether people are more inclined to selfishness or altruism and expectation for future, whether respondent feels able to determine own future, whether changes will accelerate/decelerate/stay same over next ten years, whether people whould consider their future or take each day as it comes. Attitude towards class hostility/individual freedom/noise and pollution/leisure time/government bureaucracy/self-help/materialism/violence and lawlessness/honesty/readiness to work hard - how these have changed in past decade and will change in future. Other expected social changes, e.g. more drug addiction/reduction in working week/less unemployment/sexual equality/acceptance of immigrants/armed police force/more poverty. Likelihood of disasters occurring during the 1980's, e.g., race riots/political terrorism/economic depression/ nuclear accident/nuclear war/serious oil shortage/breakdown of law and order. Whether believes Britain is well governed in comparison with other European countries and expectation for future. Party respondent would support in the event of a General Election. Whether Britain will be a good place for children to grow up in ten years' time. Background Variables Accommodation tenure, sex, marital status, number of children in household, union membership and whether active, social class, age completed full-time education, employment status, size of establishment, whether employee or self employed, whether organization is private company/nationalised industry/public corporation/ public service, degree of responsibility. Quota sample Face-to-face interview