The statistic shows the distribution of the workforce across economic sectors in the United Kingdom from 2013 to 2023. In 2023, 0.99 percent of the workforce were employed in agriculture, 17.77 percent in manufacturing and 81.25 percent in services. The same year, the total UK population amounted to about 81 million people.

Throughout the 20th century, employment structures in Western Europe gradually transitioned from being primarily agriculture and industry based, to then being dominated by service industries. The agriculture, forestry, and fishing sector saw the most drastic change over this period, with its share of the total workforce dropping from over 38 percent to less than 3 percent between 1900 and 2000. Employment in industrial sectors saw most growth between 1900 and 1973, before dropping significantly in the last quarter century. It was in the second half of the 1900s when the service sector became the largest employer in Western Europe, jumping from 36 percent of the workforce in 1950 to 69 percent in 2000. Generally speaking, reduced employment in agricultural and, later, industrial sectors was largely due to mechanization and automation, which meant that output from these sectors remained relatively healthy despite having a lower share of the labor force.

The Business Register and Employment Survey (BRES) is the official source of employee and employment estimates by detailed geography and industry. It is also used to update the Inter-Departmental Business Register (IDBR), the main sampling frame for business surveys conducted by the Office for National Statistics (ONS), with information on the structure of businesses in the UK.

The survey collects employment information from businesses across the whole of the UK economy for each site that they operate. This allows the ONS to produce employee and employment estimates by detailed geography and industry split by full-time/part-time workers and whether the business is public/private.

The ONS produces a number of different measures of employment including Workforce Jobs and the Annual Population Survey/Labour Force Survey. However, BRES is the recommended source of information on employment by detailed geography and industry.

The BRES has two purposes: collecting data to update local unit information and business structures on the IDBR, and producing published annual employment statistics.

The BRES sample does not include Northern Ireland. Northern Ireland data are received direct from the Northern Ireland Department of Enterprise, Trade and Investment (DETINI) which are used to create UK estimates. The UK Data Archive holds data only for Great Britain.

The BRES replaced the Annual Business Inquiry, Part 1 (ABI/1) in 2009. ABI/1 data for 2009 and earlier are held as part of the Annual Respondents Database under UK Data Archive SN 6644.

Change in sampling from 2015-2016
In 2015, ONS made a strategic decision to include business units with a single PAYE code for which VAT data are available. Prior to 2015, such units were excluded from the sampling frame and therefore not estimated for in ONS outputs. So from January 2016, the coverage of BRES was extended to include a population of solely PAYE based businesses. This improvement in coverage is estimated to have increased the business survey population by around 100,000 businesses, with a total of around 300,000 employment and 200,000 employees between December 2015 and January 2016. The increase in business population has led to an increase in the estimate of employment and employees for the 2015 dataset. Further information is available in documentation file '7463_bres_2015_change_in_firm_sampling.pdf'.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

Latest edition information
For the thirteenth edition (February 2024), the 'revised 2021' and 'provisional 2022' data files have been added.

Forecast: Employment in Manufacture of Structural Metal Products Sector in the UK 2024 - 2028 Discover more data with ReportLinker!

Abstract copyright UK Data Service and data collection copyright owner.

The purpose of these data is to summarise as concisely as possible the diversity of residential conditions found within Great Britain in 1971.

Scores on an Edited Set of Variables from the 1971 Census: All Enumeration Districts of Great Britain

There are no variable or value labels available in the setup syntax to add metadata, and the user guide does not really give a clear indication of the contents of the individual variable contents.

Main Topics:
Variables
A total of forty variables including information on age structure, housing structure, housing conditions, socio-economic profile, employment structure and travel to work patterns of the residential population.

This dataset provides data on the structure of enterprises active in Wales, including estimates for the very smallest businesses that operate below the VAT threshold. The variables analysed are counts of the enterprises active in each area, together with related employment and turnover aggregates in each of the given size bands, based on the number of UK employees in the enterprise as a whole.

In 2023, agriculture contributed around 0.58 percent to the United Kingdom’s GDP, 17.5 percent came from the manufacturing industry, and 72.53 percent from the services sector. The UK is not a farmer’s marketThe vast majority of the UK’s GDP is generated by the services sector, and tourism in particular keeps the economy going. In 2017, almost 214 billion British Pounds were contributed to the GDP through travel and tourism – about 277 billion U.S. dollars – and the forecasts see an upwards trend. For comparison, only an estimated 10.3 billion GBP were generated by the agriculture sector in the same year. But is it a tourist’s destination still? Though forecasts are not in yet, it is unclear whether travel and tourism can keep the UK’s economy afloat in the future, especially after Brexit and all its consequences. Higher travel costs, having to wait for visas, and overall more complicated travel arrangements are just some of the concerns tourists have when considering vacationing in the UK after Brexit. Consequences of the referendum are already observable in the domestic travel industry: In 2017, about 37 percent of British travelers said Brexit caused them to cut their holidays short by a few days, and about 14 percent said they did not leave the UK for their holidays because of it.

Abstract copyright UK Data Service and data collection copyright owner.

The Improving Survey Measurement of Income and Employment (ISMIE) survey was undertaken to analyse issues of data validation and dependent interviewing. The end of funding for the European Community Household Panel (ECHP) study in 2001 presented a rare opportunity to collect data for this purpose. The validation exercise had two parts: comparisons of survey reports of social security benefit income with administrative records, and of survey reports of employment characteristics (pay, hours, status, etc.) with employer records. The survey also contained an experiment to test alternative dependent interviewing strategies, and compare them with traditional independent interviewing, in terms of impact on validity and accuracy. The data currently deposited are the household survey and the validation data collected from employers.

The documentation for this study describes the survey design, methodological work and data structure, in so far as it differs from standard practices for the British Household Panel Survey (BHPS). Dataset users are referred to the BHPS documentation for background information on the ECHP subsample and general survey processes and data characteristics. The BHPS documentation is available from the Institute for Social and Economic Research (ISER) web site.

For the second edition, files 'lincom' and 'lincpay' were re-deposited due to previous double reporting problems, and the user guide was updated accordingly.

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The dataset covers a broader range of thematic areas including household composition, housing conditions, residential mobility, education and training, health, socio-economic values, income from employment, benefits and pensions. Furthermore, detailed information was collected about respondents' economic activities and activity spells since the previous interview.

With regard to the structure of the records, one set contains information at the household level, another set includes information at the individual level, and a third set is organised by substantive contents, for example job spells or income sources. In addition, for the sections subject to the dependent interviewing experiment, there are separate files for each treatment group.

Abstract copyright UK Data Service and data collection copyright owner.

The principal emphasis of the programme was to examine the attitude of the population to changes in the employment structure of British society, including occupational structure changes in the gender composition of the workforce, increased unemployment and increases in the use of casual employment. These changes influence both the nature of working lives and the time spent outside work.
A follow-up to the SCELI survey, in which some original respondents were re-interviewed, Individual and Household Strategies: A Decade of Change 1986-1997 (also known as the Decade of Change Survey) was conducted in 1997. This study is held at the Archive under SN:4038.

Some teaching materials using these data have been developed. Details are available at the following website:
http://tramss.data-archive.ac.uk .
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Variables
Work Attitudes/Histories Survey
The fieldwork for the Work Attitudes/Histories Survey was carried out between June 1986 and November 1986, with approximately 1000 respondents in each area, (making 6111 cases in all). Each area questionnaire included Life and Work Histories plus core questions (551 variables) which were common across all areas. In addition a number of questions were asked that were specific to respondents in particular areas.
Household and Community Survey
In 1987 (fieldwork, March - July) a follow-up survey was carried out on approximately one third of the respondents to the 1986 Work Attitudes/Histories Survey, in each of the six areas. This survey consisted of 1816 respondents, 1218 of whom were living in partnerships and 598 of whom were single. Where applicable, partners were interviewed as well as the original respondent.
The questionnaire for this survey consisted of three sections; an interview schedule including questions to both respondents and partners, a respondent's self-completion and partner's self-completion. Partners' data is coded under the respondents' identification number. For single people the interview schedule is shorter and there is no partners self-completion. These questionnaires include life history and work history updates for the original respondents, work history schedules for partners, core questions (1372 variables) and area-specific questions.
Employers Surveys
Between October 1986 and February 1987 a survey was carried out on employers (n=1308) of the respondents in the Work Attitudes/Histories survey. Different questionnaires (designed to provide functionally equivalent questions for different types of organisations) were used for large and small employers, for public and private enterprises, and for different industries. These questionnaires are in three parts. Part A varies by whether the enterprise is public or corporate. Part B varies by the size and public or private status of employers. Part C varies according to the industry of the employer: 1. manufacturing, wholesale, haulage, extractive, agriculture and fisheries; 2. retail, hotel and catering, personal and other consumer services; 3. banks, financial and business services; 4. construction.

These data were collected as part of a research project run by Dr Leigh Shaw-Taylor and Professor E.A. Wrigley and funded by the Economic and Social Research Council: Male occupational structure and economic growth in England 1750-1851 (RES-000-23-0131).

The aim of this project was to reconstruct the evolution of England's male occupational structure from c.1750 to 1851. The underlying aim was to improve our understanding of the industrial revolution. The results of the project have not, at the time of writing, been published.

BackgroundPrevious investigations suggest that the COVID-19 pandemic effects on alcohol consumption were heterogenous and may vary as a function of structural and psychological factors. Research examining mediating or moderating factors implicated in pandemic-occasioned changes in drinking have also tended to use single-study cross-sectional designs and convenience samples. Aims: First, to explore structural (changed employment or unemployment) and psychological (subjective mental health and drinking motives) correlates of consumption reported during the COVID-19 pandemic using a UK nationally representative (quota sampled) dataset. Second, to determine whether population-level differences in drinking during the COVID-19 pandemic (versus pre-pandemic levels) could be attributable to drinking motives. Method: Data collected from samples of UK adults before and during the pandemic were obtained and analysed: Step1 carried out structural equation modelling (SEM) to explore data gathered during a period of social restrictions after the UK’s first COVID-19-related lockdown (27 August-15 September, 2020; n = 3,798). It assessed whether drinking motives (enhancement, social, conformity, coping), employment and the perceived impact of the pandemic on subjective mental health may explain between-person differences in self-reported alcohol consumption. Step 2 multigroup SEM evaluated data gathered pre-pandemic (2018; n = 7,902) in concert with the pandemic data from step 1, to test the theory that population-level differences in alcohol consumption are attributable to variances in drinking motives. Results: Analyses of the 2020 dataset detected both direct and indirect effects of subjective mental health, drinking motives, and employment matters (e.g., having been furloughed) on alcohol use. Findings from a multigroup SEM were consistent with the theory that drinking motives explain not only individual differences in alcohol use at both time points, but also population-level increases in use during the pandemic. Conclusion: This work highlights socioeconomic and employment considerations when seeking to understand COVID-19-related drinking. It also indicates that drinking motives may be particularly important in explaining the apparent trend of heightened drinking during the pandemic. Limitations related to causal inference are discussed.

Abstract copyright UK Data Service and data collection copyright owner.

This study was undertaken by a team based at Leicester Business School, De Montfort University, Warwick Business School and King's College, London. It aimed to investigate employment practices in multinational companies' operations in the United Kingdom, and explored how these are influenced by organisational characteristics. It was the first survey based on a representative sample of multinationals operating in UK.

The sampled population included multinational companies with at least 500 employees in total. For UK-owned firms, eligibility was also based on a minimum of 100 employees in UK, and for overseas-owned firms, at least 100 employees in at least one other country. An initial brief telephone screening survey produced responses from 903 firms. For the main survey, data were collected through 302 structured face-to-face interviews with senior human resources (HR) managers responsible for the UK operations of multinational companies. Fieldwork was carried out by a survey research organisation, GfK NOP. Of the 302 responses, 258 were from operations of foreign-owned multinationals operating in UK, the remaining 44 from UK-owned multinationals.

The survey findings have been used to test propositions concerning the association between a company's employment practices and organisational factors, such as corporate structure, international integration of operations, nationality of ownership, and sector.

Further information about the study may be found on the Warwick Business School Employment Practices of Multinational Companies in Organisational Context project web page and the Economic and Social Research Council's (ESRC) Employment Practices of Multinational Companies (MNCs) in Organisational Context: a Large-scale Survey project web page.

The Principal Investigators request that, rather than using the shortened form "Edwards, P. et al.", users list all five authors when citing the study, as follows: "Edwards, P., Edwards, T., Ferner, A., Marginson, P. and Tregaskis, O. Employment Practices of Multinational Companies in Organisational Context, 2005-2006 [computer file]. Colchester, Essex: UK Data Archive [distributor], November 2007. SN: 5748."

Main Topics:

The survey covered the strategy, structure and control mechanisms of companies, and the international structure and role of the human resource management function. It also examined four substantive areas of employment practice: performance management and reward systems; organisational learning; employee involvement and communication; and employee representation.

The survey distinguished practice for three groups among the workforce: managers; the largest occupational group (LOG) among non-managerial employees; and (an innovation in the survey) a key group of employees critical to the firm’s core competence.

Presents the number of enterprises (businesses) in the UK along with the turnover and employment in these enterprises. Source agency: Business, Innovation and Skills Designation: National Statistics Language: English Alternative title: SME Statistics

Forecast: Metal Structures Turnover Per Employee in the UK 2024 - 2028 Discover more data with ReportLinker!

The UK's median gender pay gap has substantially reduced from 36.4% in the 1970s to around 18%, yet it remains one of the highest in the EU and OECD. Previously attributed to differences in education and work experience, this explanation is outdated as women now frequently outpace men in education and are less likely to leave the workforce. However, women still earn about 10% less than men, even with similar work and qualifications. Research has shifted focus from productivity differences to the potential role of employer wage-setting practices. This research suggests that women's negotiating power may be undermined by familial responsibilities, leading to lower mobility in the job market and consequently lower wages. The study will explore how employer wage-setting power and job-to-job mobility contribute to the gender pay gap, aiming to inform effective policies.

The collection contains a set of syntax files used to construct an alternative employment concentration index that takes into account commuting costs. The files are based on the Stata language and use the Business Structure Dataset and the UK Longitudinal Household Study to derive the index.

The median gender pay gap has declined dramatically in the UK from 36.4% in the 1970 (O'Reilly, Smith et al. 2015) to around 18% in the most recent data (ONS 2018). Still, by international standards the pay gap is high: the UK has the fourth largest gender pay gap in the EU and the eighth largest of OECD countries (OECD 2019). Researchers and policy makers have focused on gender differences in education and labour market experience as the likely drivers of the pay gap. However, today these explanations no longer stand up to scrutiny. Women are on average better educated than men and they are much less likely to withdraw from the labour market for long periods of time. Nevertheless, women earn on average about 10% less than men even when they work full-time and have similar education and labour market experience. While explanations focusing on women's potential lower productivity as the cause of the gender pay gap have been thoroughly investigated and found inadequate, there is less evidence on the role played by employers. This research will contribute to addressing this gap. The standard economic model of the labour market assumes that wages are determined by the market and that individual employers cannot choose the wages they offer to their employees. A different model assumes that for a variety of reasons competition is not perfect and employers have some discretion over the wages they offer. This wage setting power is likely to be weaker when workers are mobile. Mobile workers will leave an employer offering wages below the market rate. However, if workers are relatively immobile, employers can exploit this 'immobility' by offering them lower wages. If women are more constrained by family responsibilities in the types of jobs that they will take-up or in the amount of time and effort they can devote to job search, they will generally be more immobile and thus at a disadvantage. Women's family responsibilities might be ultimately responsible for the gender pay gap but not because they limit their productivity but rather because they reduce their bargaining power with firms. This research project will examine the role of employer wage-setting power in driving the gender pay gap in two ways. First, using data from the UK's largest longitudinal study, it will investigate the extent to which job-to-job mobility patterns differ between men and women, and whether any differences can explain the observed gender gap in pay progression. Second, it will develop an index of employer wage-setting power based on geographical location, industry and cost of travel and test whether the index can explain gender differences in pay progression. Tackling the gender pay gap is a widely shared goal among policy makers, political parties, women's groups, trade-unions and employer organizations. A better understanding of the factors driving the gap is essential to design effective policies. For example, in April 2017, the UK government has mandated large employers report annually on the pay gap in their organization. If women's lower productivity is to blame for the gender pay gap, such legislation is likely to be ineffective and even counterproductive. On the other hand, mandatory reporting is likely to be more effective if employers' stronger wage-setting power is a significant factor behind the pay gap. More generally, if employers enjoy significant wage setting power relative to some of their employees, this has implications for legislation on anti-discrimination, the minimum wage, trade-unions and family policy.

Abstract copyright UK Data Service and data collection copyright owner.

The aim of this survey was to examine factors affecting the employment prospects of young people in four rural areas with particular reference to employers in these areas.
Main Topics:

Variables describe:

• Characteristics of firms: ownership, size, location, markets.
• Employment structure: young people, growth and decline, gender, part- time, full-time, etc.
• Recruitment factors: transport, costs, pay rates.
• Training: who gets trained, on and off job, use of colleges.

The number of hospital employees in the health sector in the United Kingdom increased by 84,452.6 employees (+5.36 percent) in 2021 in comparison to the previous year. Therefore, the number of hospital employees in the United Kingdom reached a peak in 2021 with 1,660,883.41 employees. Total hospital employment includes the headcount of all people employed in a hospital structure and the number of full-time equivalents (FTE). These broad employment figures encompass general or specialty hospitals and self-employment or service contracts.Find more key insights for the number of hospital employees in the health sector in countries like Denmark, Spain, and Greece.