The number of employees in the UK increased by 352,800 (1.2%) between 2016 and 2017, from 30.0 million to 30.3 million.
Between 2016 and 2017, the total number of employees increased in all regions except the South East, which decreased by 44,200 (1.1%) and Wales, which decreased by 14,300 (1.1%); London again showed the greatest increase in terms of the total number of employees, with 115,100 (2.3%).
In percentage terms, the strongest growth was in the West Midlands, up 2.9% (73,100), and the North East, up 2.6% (27,200).
Between 2016 and 2017, the largest increase in employees by broad industrial grouping has been in the construction industry (up 77,700, or 5.6%), closely followed by business administration and support services (up 72,300, or 2.7%).
Between 2016 and 2017, in the UK, the total number of employees decreased for the following industries: professional, scientific and technical (down 45,800, or 1.8%); wholesale (down 25,600, or 2.2%); transport and storage including postal (down 26,000, or 1.8%); motor trades (down 13,300, or 2.5%); and finance and insurance (down 5,100, or 0.5%).
Between 2016 and 2017, for Great Britain, the number of private sector employees increased by 315,300; the number of public sector employees increased by 20,500.
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 structural information on the Inter-Departmental Business Register, the main sampling frame for business surveys used to produce UK official statistics.
This statistical bulletin focuses on the strengths of BRES, giving employee estimates by region level and below and by broad industry group and below. There is also a section that looks at public and private sector estimates of employees.
The survey collects employment information from businesses across the whole of the Great Britain economy for each site that they operate. The Department of Finance and Personnel Northern Ireland (DFPNI) collects the same BRES information independently in Northern Ireland. Both data sources are then combined to produce estimates on a UK basis. This allows us to produce UK workplace-based employee and employment estimates by detailed geography and industry, full-time or part-time workers and whether the business is in the public or the private sector.
Due to the survey’s large sample size (currently approximately 85,000 businesses), BRES is able to produce good-quality estimates for detailed breakdowns by industry and geography. Indeed, no other Office for National Statistics (ONS) survey of regional and subregional employment data can provide the same level of industry detail. Furthermore, being a business survey, the quality of this industry data is very good and is recommended in preference to industry data from household surveys such as the Annual Population Survey. BRES provides both employee and employment data and is particularly recommended for analysis of employee data. All analysis in this bulletin is for data on employees.
The employment data in BRES is the number of employees added to the number of working owners (for example, sole proprietors and partners). However, BRES does not cover the very small businesses that are not registered for Value Added Tax (VAT) or Pay As You Earn (PAYE), which make up a small part of the economy. As a result, there is a difference between the BRES UK estimate of employment and the estimate from the ONS workforce jobs series. So, for total employment figures, other ONS sources such as workforce jobs (regional) and the Annual Population Survey (subregional) can provide fuller coverage of total employment, albeit with a less detailed industrial breakdown.
Since BRES is based on a sample of businesses, it can be affected by sampling variability. In particular, the quality of the estimates may deteriorate for smaller geographies and this should be taken into account when making inferences about the figures. Quality measures accompany the BRES datasets on our website.Nôl i'r tabl cynnwys
Figure 1 shows the percentage change in the number of employees between 2016 and 2017 by region. Between 2016 and 2017, the West Midlands (up 2.9%), the North East (up 2.6%), Northern Ireland (up 2.3%) and London (up 2.3%) saw the largest percentage increases in total employees. Between 2016 and 2017, only the South East and Wales saw percentage decreases in the number of employees (both down 1.1%).
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Figure 2 shows the percentage change in employees by broad industry group (BIG) between 2016 and 2017 for the UK.
Between 2016 and 2017, there were percentage increases in all but five groups. The largest percentage increases were in construction (up 5.6%), information and communication (up 4.6%) and mining, quarrying and utilities (up 4.5%). Between 2016 and 2017, motor trades showed the largest percentage decrease (down 2.5%). There were also decreases in wholesale (down 2.2%), the professional, scientific and technical sector (down 1.8%), transport and storage including postal (down 1.8%) and the finance and insurance sector (down 0.5%).
The rest of this section looks at these industries in more detail. Figure 3a shows five divisions with large percentage increases in employees between 2016 and 2017. Note that this analysis excludes the smallest industries.
Figure 3b shows the five divisions with the largest falls over this period. In the year to September 2017, the top five percentage decreases all exceeded 10%. The largest percentage decrease was in the repair of computers and personal and household goods division, which decreased by 30%.
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The analysis in this section focuses on changes in employees at a local authority (LA) district level. Although regional estimates show interesting patterns and shifts over time, they can mask some of the subregional variation in the geographical distribution of employees. For example, strong growth in the North East of England in the number of employees between 2016 and 2017 was driven by growth across many LAs including County Durham, Newcastle upon Tyne, Stockton on Tees and North Tyneside; whereas the growth seen in the North West of England was driven by the Greater Manchester Metropolitan County. In percentage terms, the greatest level of growth was in the West Midlands, up 2.9% (73,100).
Since the overall regional growth can be greatly affected by the growth in a small number of LAs, Figure 4 looks at the percentage of LAs within a region that have shown an increase or a decrease in the number of employees. This needs to be compared with Figure 1 to give an indication of how well the growth is spread across all LAs within the region. Northern Ireland, the West Midlands and London were the regions with the highest proportion of LAs that showed an increase in the number of employees in the year to September 2017.
Figure 5a shows large increases in employees in Welwyn Hatfield (15.5%), while Figure 5b shows that the largest decrease was seen in Spelthorne (South East) (8.6%).
Note that we have excluded local authorities where the impact of “umbrella companies” on the growth is very significant. See the Quality and methodology section for a definition of umbrella companies.Nôl i'r tabl cynnwys
Figures 6 and 7 show the movements in public and private sector employees by region between 2016 and 2017 respectively.
Out of the 12 UK government regions, seven regions saw an increase in the number of public sector employees and five regions saw a decrease. Increases were largest in London (up 2.8%) and Northern Ireland (up 1.3%). The largest decreases in public sector employees were in Yorkshire and The Humber (down 1.3%) and the North East of England (down 1.1%). Overall, there was a small increase in public sector employees by 0.4%.
All regions except the South East and Wales saw a percentage increase in private sector employees between 2016 and 2017. The largest increases were for the North East (up 3.7%) and the West Midlands (up 3.5%).Nôl i'r tabl cynnwys
To support this release datasets providing greater geographical and industrial detail are available.
Estimates presented in this release and associated datasets are rounded to prevent disclosure. Differences may exist in totals across tables due to rounding of estimates and disclosure methods used.
For 2017, employee job numbers are estimated as at 15 September 2017.
Subregional estimates are based on the county and district geography boundaries at the time the survey sample was selected (August 2017).
Although this bulletin focuses on employees, the Business Register and Employment Survey (BRES) collects information on employees and employment (employees plus working owners). BRES therefore includes self-employed workers (within the employment estimates) as long as they are registered for Value Added Tax (VAT) or Pay As You Earn (PAYE) schemes. Self-employed people who are not registered for these, along with HM Armed Forces and government-supported trainees are not included.
Employee jobs are allocated to the area in which the businesses completing the survey questionnaire say the employee works. Therefore, geographic estimates are on a workplace basis and do not reflect where the person lives. Jobs at local hospitals, for example, may be situated in one local authority while the employees or people may reside in another.
The public sector comprises central government, local government and public corporations. The private sector comprises companies, sole proprietors, partnerships and non-profit bodies.
An employee is defined as anyone aged 16 years or over that is paid directly from the payroll, in return for carrying out a full-time or part-time job or being on a training scheme. Employment includes employees plus the number of working owners who receive drawings or a share of the profits. Full-time is defined as working more than 30 hours per week with part-time defined as working 30 hours or less per week.
Farm agriculture data are either provided or taken from existing publications by the Department for Environment, Food and Rural Affairs, the Scottish Government, the Welsh Government and the Department for Agriculture and Rural Development Northern Ireland. These figures are not available for all sub-regions so for consistency they have not been included in estimates below region level. The figures have only been included at a two-digit Standard Industrial Classification 2007: SIC 2007 level and above. Where employment in farm agriculture has been included in estimates, it has been included within the private sector. Farm data are, however, now incorporated at the local authority district level into the BRES datasets, made available on the NOMIS website.
Alternative employment estimates are available from the Labour Force Survey (LFS) and workforce jobs (WFJ). BRES is the primary source for employee estimates at a detailed regional and industrial level. Workforce jobs benchmarks the private sector employee component to the BRES private sector employee estimates on an annual basis. The WFJ series, which is compiled mainly from surveys of businesses, is the preferred source of statistics when comparing changes in employment over time. The LFS, which collects information mainly from residents of private households, is the preferred source of statistics on employment at the whole economy level.
The concept of employment (measured by the LFS as the number of people working at least one hour during the survey reference week) differs from the concept of jobs, since a person can have more than one job, and some jobs may be shared by more than one person. The LFS can also be used to produce estimates of the total number of jobs in the UK, by adding together the headline employment figures (which are equivalent to main jobs) and those for workers with a second job.
The public sector employee job figures from BRES aggregated to regional or national level will not match those produced from the Public sector employment release, which is the recommended source for public sector employment figures.
A further breakdown of the number of employees, by region and industry, is provided on the Nomis website.
Figures are classified to the 2007 revision to the Standard Industrial Classification (SIC). BRES includes breakdowns by public and private sector according to the legal status of employees for national accounts classification purposes.
We apply statistical methods to the survey returns to ensure that the estimates derived are as representative of the population as possible. Nevertheless, there is still some error associated with these estimates and we measure this by calculating coefficients of variation (CV), which are defined as the ratio of the standard error of an estimate to the estimate itself.
For example, an estimate with a CV of 5% will have a standard error that is 5% of the estimate. The smaller the coefficient of variation, the greater the accuracy of the estimate. CVs that are greater than or equal to 20% should be used with caution. CVs are provided within the published tables that accompany this release.
An umbrella company is an organisation that acts as an employer to staff on fixed-term contracts, and are single companies employing many contractors. Umbrella companies tend to be structured with a single site, based on where the administrative staff are located. The contractors employed by the umbrella company are all attached to the same local unit at a single postcode, even though the site at which they actually work may be somewhere completely different. The phenomenon of umbrella companies can lead to distortions in employment statistics at the subnational level.
BRES is a sample survey. For the 2017 survey period, approximately 85,000 businesses were sampled for Great Britain. Further details of the sample design can be found in the BRES Quality and Methodology Information (QMI) report to be updated by the end of the year. The response rate for the 2017 BRES survey was 86.2%. Northern Ireland data were collected independently by the Northern Ireland Statistics and Research Agency.
The BRES Quality and Methodology Information report contains important information on:
the strengths and limitations of the data and how it compares with related data
uses and users of the data
how the output was created
the quality of the output including the accuracy of the data
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