Accredited official statistics

Economic Estimates: Employment and Earnings in the Digital Sector, January 2023 to December 2023 - Technical and quality assurance report

Published 11 July 2024

1. Overview of release 

This technical report covers the ‘Economic Estimates: Employment and Earnings in the Digital Sector, January 2023 to December 2023’ release. This release includes two statistical outputs derived from the Annual Population Survey (APS) run by the Office for Statistics (ONS):    

• ‘Economic Estimates: Employment in the Digital Sector, January 2023 to December 2023 (including data from January 2022 to December 2022)’ (Accredited Official Statistics).
• ‘Economic Estimates: Earnings in the Digital Sector, January 2023 to December 2023 (including data from January 2022 to December 2022)’ (Official Statistics in Development).

In February 2023, Machinery of Government changes moved responsibility for the Digital and Telecommunications Sectors from the Department for Culture, Media and Sport (DCMS) to the Department for Science, Innovation and Technology (DSIT). DSIT has been responsible for publishing estimates for the Digital Sector (including the Telecommunications Sector) since April 2024. Previous releases of the Economic Estimates in the DCMS and Digital Sectors series can be found on the DCMS webpage.

This ‘Economic Estimates: Employment and Earnings in the Digital Sector’ release provides estimates of the number of filled jobs (including both employed and self-employed, and both full-time and part-time jobs), and median self-reported gross hourly pay (including only employed) in the Digital Sector and the Telecommunications Sector for the calendar year 12-month period between January 2023 and December 2023. A list of the subsectors  included in both the Digital Sector and Telecommunications Sector is included in Section 4: Sector definitions.

These estimates are derived from the ONS Annual Population Survey (APS) and contain demographic  breakdowns including, but not limited to, employment type (i.e. employed or self-employed), International Territorial Level 1 (ITL1) region of work, nationality, sex, and ethnicity. Employment and Earnings estimates are based on APS data collected over the 12-month period from January 2023 to December 2023.

The Office for National Statistics (ONS) is the provider of the underlying APS data used for the analysis presented within this release. As such, the same data sources are used for the Digital Sector, as those used for national estimates, enabling comparisons to be made on a consistent basis.

2. Code of Practice for Statistics 

The ‘Economic Estimates: Employment in the Digital Sector’ series contains statistics classified as Accredited Official Statistics. These statistics have been produced to the standards set out in the Code of Practice for Statistics.  

In June 2019, a suite of DCMS Sector Economic Estimates, including Employment estimates, were badged as Accredited Official Statistics (previously called National Statistics). This affirms that these statistics have met the requirements of the Code of Practice for Statistics. DSIT will continue to comply with these standards in the estimates that we produce for the Digital Sector.  

This followed a report by the Office for Statistics Regulation (OSR) in December 2018, which stated that the series could be designated as Accredited Official Statistics subject to meeting certain requirements. Since the report, DCMS have striven to improve the publications by providing summaries of other notable sources of data, more detail on the nature and extent of the overlap between the sectors, and further information on the quality and limitations of the data. The development of the Digital element of these publications has been continued at DSIT.

These Accredited Official Statistics have been independently reviewed and regulated by the OSR. They comply with the standards of trustworthiness, quality and value in the Code of Practice for Statistics. Accredited Official Statistics are called National Statistics in the Statistics and Registration Service Act 2007. 

Accreditation signifies their compliance with the authority’s Code of Practice for Statistics which broadly means these statistics are:

• Managed impartially and objectively in the public interest.
• Meet identified user needs.
• Produced according to sound methods.
• Well explained and readily accessible.

You are welcome to contact us directly with any queries about how we meet these standards by emailing economicestimates@dsit.gov.uk. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the OSR website.

The Economic Estimates produced by DSIT follow the same methodology as those produced by DCMS. In future, DSIT will continue to consider how to improve the series, in line with the recommendations of the report. We will clearly state where this results in a divergence of methodology with the DCMS produced statistics. We encourage our users to engage with us so that we can improve our statistics and identify gaps in the statistics that we produce. 

The Earnings estimates are a newer series of Official Statistics in Development (previously called Experimental Statistics) that are produced to the standards of the Code of Practice but have not yet been accredited as Official Statistics. The Earnings estimates produced from the APS are still being evaluated in regard to their usefulness due to the limitations of the APS as a data source for this analysis (please see the ‘Methodology’ section for more details). Further information on Official Statistics in Development is available from the OSR website.

3. Users 

The users of these statistics fall into five broad categories: 

• Ministers and other political figures.
• Policy and other professionals in DSIT and other government departments.
• Industries and their representative bodies.
• Charitable organisations.
• Academics.

The primary use of these statistics is to monitor the performance of the industries in the Digital Sector, helping to understand how current and future policy interventions can be most effective.

4. Sector definitions  

In order to produce these Economic Estimates, it is necessary to define the make-up of the economy and the sectors comprising it. The Digital Sector and Telecommunications Sector definitions are based on the Standard Industrial Classification 2007 (SIC) codes.  This allows data sources to be nationally consistent and enables international comparisons. 

4.1 Digital Sector 

The definition of the Digital Sector is based on the Organisation for Economic Cooperation and Development (OECD) definition of the ‘information society’. This is a combination of the OECD definition for the ‘ICT Sector’ and ‘Content and Media Sector’. An overview of the SIC codes included in each of these sectors is available in the OECD Guide to Measuring the Information Society (see Box 7.A1.2 on page 159 and Box 7.A1.3 on page 164).

Table 1: SIC codes included in the Digital Sector by Digital Subsector (adapted from OECD, 2011)

Digital Subsector	SIC codes included
Manufacturing of electronics and computers	26.11, 26.12, 26.2, 26.3, 26.4, 26.8
Wholesale of computers and electronics	46.51, 46.52
Publishing (excluding translation and interpretation activities)	58.11, 58.12, 58.13, 58.14, 58.19
Software publishing	58.21, 58.29
Film, TV, video, radio and music	59.11, 59.12, 59.13, 59.14, 59.2, 60.1, 60.2
*Telecommunications	61.1, 61.2, 61.3, 61.9
Computer programming, consultancy and related activities	62.01, 62.02, 62.03, 62.09
Information service activities	63.11, 63.12, 63.91, 63.99
Repair of computers and communication equipment	95.11, 95.12

*While Telecommunications is considered a sector in its own right, it is entirely included within the Digital Sector

4.2 Telecommunications 

The definition of the Telecommunications Sector is consistent with the internationally agreed definition, SIC 61, Telecommunications. It should be noted that while Telecommunications is considered a sector in its own right, it is also entirely included within the Digital Sector as one of the subsectors. Aggregates based on the Digital Sector, therefore, include data from the Telecommunications Sector.

4.3 Details and limitations of sector definitions 

DSIT holds policy responsibility for the digital industry and services across the economy and within sectors. The definition we use in this release for the Digital Sector, using SIC codes, does not consider the value added from ‘digital’ services to the wider economy e.g. digital work that takes place in other industries such as health care or construction. There is therefore a considerable limitation in the definition of the Digital Sector used in this methodology, in that it does not include the value added to the economy from digital services. 

There are also substantial limitations to the underlying SIC classifications. As the SIC codes were finalised in 2007, their relevance for important elements of the UK economy related to the Digital Sector is less robust as the balance and make-up of the economy changes. This is particularly relevant for the Digital Sector, in which, there are likely to be several emerging sectors that are not accurately identified by SIC codes, such as cyber-security and artificial intelligence. The SIC codes used to produce these estimates are a ‘best fit’, subject to these limitations.

5. Methodology 

5.1 Data sources 

In this release, both Employment and Earnings estimates are calculated using the Office for National Statistics (ONS) Annual Population Survey (APS). The majority of the data processing is done by the ONS, with DSIT receiving cleaned and weighted respondent-level data. We then process and aggregate the data to give estimates for Employment and Earnings. 

5.2 Annual Population Survey 

The APS is a household survey that combines two waves of the Labour Force Survey (LFS) with an additional sample boost. Information collected includes the details of employment (e.g. location, industry, seniority, occupation, and income), circumstances (e.g. housing tenure and health) and demography (e.g. nationality, age, and ethnicity). Responses are weighted to population totals. 

5.3 Employment estimates 

To produce our Employment estimates we only include respondents that are ‘in work’ from the APS dataset for analysis. The APS provides data on an individual level for both a respondent’s first job, and if applicable, a respondent’s second job as separate variables. Therefore, in the dataset across these two variables, we define ‘in work’ as those with a first or second job who are categorised as an employee or self-employed. The data presented in this report, and the accompanying Employment data tables, therefore includes both employed and self-employed workers.   

As ‘employment’ in this release is estimated as the number of filled jobs, we restructure the data to be on a per job basis, rather than a per respondent basis. We then select entries that are relevant for a particular grouping (e.g. all entries with a SIC code of 26.11 for total employment in the ‘Manufacture of electronic components’ subsector) and aggregate over the associated population weights to generate an estimate of the total number of filled jobs. This means that some respondents may be included in the Employment data tables twice if they have both a first and second job.

Data tables relating to the Employment estimates provide demographic breakdowns across the Digital Sector, UK overall, and the Digital Subsectors (including Telecommunications) for employment status (employed/self-employed), ITL1 region of work, nationality, sex, ethnicity, age, highest level of education, working pattern (full time/part time), managerial status, socio-economic group (National Statistics Socio-economic Classification), and Equality Act disability status. There are additional breakdowns combining these selected specified variables with employment status.   

5.4 Earnings estimates 

The ONS definition of ‘earnings’ is “the payment received by employees in return for employment”. Most analyses of earnings consider only gross earnings, which is earnings before any deductions are made for taxes (including National Insurance contribution), pensions contributions, student loan deductions, and before payment of benefits. Further information is available from the ONS publication: A guide to sources of data on income and earnings. 

The APS provides a self-reported value of gross hourly pay for a respondent’s main (first) job. To produce our Earnings estimates we filter for all employees who have a main job and then select entries that are relevant for a particular grouping (e.g. all entries with a SIC code of 26.11 for total employment in the ‘Manufacture of electronic components’ subsector). In contrast to the Employment estimates, we then aggregate over the respective income weights before producing a median (middle, or 50th percentile) value for each grouping (e.g. median gross hourly pay in the Digital Sector). 

Users should be aware the preferred source for Earnings estimates at an aggregate level used by DCMS, the Annual Survey for Hours and Earnings (ASHE), is not used for this release. DCMS use both ASHE and APS to produce figures for earnings. The data provided in the ASHE dataset is taken from the HM Revenue and Customs’ (HMRC) Pay As You Earn (PAYE) records and provides breakdowns for several earnings variables, including gross hourly pay, gross weekly pay, gross annual pay, and total paid hours. Comparatively, earnings data provided in the APS only provides a breakdown for gross hourly pay and is self-reported by participants, which may impact the accuracy of reported data. As values are self-reported, some values included in analysis may be below minimum wage. There can also be low sample sizes due to response rate and not all respondents being asked the earnings question through question routing. Earnings data is not available for self-employed participants. As such, the ASHE dataset is considered to be a more robust and reliable data source for calculating Earnings estimates at the aggregated level. However, the APS gives access to more detailed demographic information, not available in the ASHE. Therefore, we have chosen to use the APS as the basis for the Earnings estimates within this statistical release, in line with DCMS’s APS Earnings release.  

Data tables relating to the Earnings estimates provide demographic breakdowns across the Digital Sector, UK overall, and the Digital Subsectors (including Telecommunications) for ITL1 region of work, nationality, sex, ethnicity, age, highest level of education, working pattern (full time/part time), managerial status, socio-economic group (National Statistics Socio-economic Classification), and Equality Act disability status.

5.5 Disclosure control 

As part of the production process, we apply disclosure control and quality assurance measures to prevent the identification of any respondents. We suppress values where the number of respondents for a particular demographic breakdown is below a set threshold (below or equal to 3 responses). Where appropriate, we also apply secondary suppression to prevent disclosure via differencing (i.e. being able to calculate the disclosed value from the other values presented). These values are instead replaced with a ‘c’. Additionally, any demographic breakdowns for which there are no respondents or there is missing data are replaced with a ‘w’. Further information is available in the ‘Respondent sample sizes’ sheet in the data release, which also highlights where the number of respondents comprising a value is deemed to be of a small sample size (below 30 responses).

6. Changes in this release 

Some changes have been made to the series now that DSIT are responsible for publishing estimates for the Digital and Telecommunications Sectors, including:

• In the respondent sample sizes sheets of the data outputs for the Employment and Earnings releases, demographic breakdowns with no responses have been distinguished from ‘disclosive’ responses (equal or less than three responses). These were previously only distinguished in the data tables, denoted with a ‘w’.
• Some additional demographic breakdowns have been provided in the data outputs, and some of the demographic classifications have been rephrased for clarity.
• The ‘Audio Visual’ Sector and the ‘Computer Games’ Sector will no longer be published alongside the Economic Estimates for the Digital Sector. These were not previously included in the Digital Sector totals and so will have no impact on the existing tables. These will continue to be published in the Economic Estimates for the DCMS Sectors. The 2023 data for these sectors was published as part of DCMS’s ‘Economic Estimates: Employment and Earnings in the DCMS Sectors, January 2023 to December 2023’ release.

7. Quality assurance processes  

This section summarises the quality assurance processes applied during the production of these statistics by our data providers, the Office for National Statistics (ONS), as well as those applied by DSIT. 

7.1 Quality assurance processes at ONS  

Quality assurance at ONS is carried out during multiple data production stages. Methodological and quality assurance information in regard to the APS can be found in the Annual Population Survey QMI. 

7.2 Validation and quality assurance at DSIT

Disclosure control is also applied as part of this process. Published data tables are thoroughly checked to ensure disclosive values are not included (breakdowns including 3 or fewer responses), and that it is not possible to derive these disclosive values via differencing from the data published. In the respondent sample sizes sheets of each release, breakdowns with no responses (0 responses), those with disclosive values (3 or fewer responses) and those with small sample sizes (fewer than 30 responses) have been highlighted.

8. External data sources 

It is recognised that there are always different ways to define sectors, but their relevance depends on what they are needed for. Government generally favours classification systems which are: 

• Rigorously measured.
• Internationally comparable.
• Nationally consistent.
• Ideally applicable to specific policy interventions.

These are the main reasons for constructing sector classifications in this series from SIC codes. However, we acknowledge that there are limitations with this approach and alternative definitions and methodologies can be useful where a policy-relevant grouping of businesses crosses the existing SIC codes. 

The ONS uses the quarterly Labour Force Survey (LFS) for its estimates of UK-wide employment rates. Our APS Employment estimates of the number of filled jobs in the Digital Sector takes a similar approach. However, as the APS uses two waves of the LFS , the datasets are not directly comparable and result in the ONS published figures for employment in the UK overall differing from our estimates of employment for the UK overall. 

For Employment estimates more broadly, the main alternative data source is the Business Register and Employment Survey (BRES). This has the advantage of asking businesses directly about their employees and is, therefore, more likely to capture employment more accurately than a household survey. However, the BRES does not contain the range of demographic breakdowns and the self-employed data which the APS provides. Use of the APS, therefore, enables us to build a fuller picture of employment in the Digital Sector, using a robust data source. 

For Earnings estimates, the main alternative data source is the Annual Survey for Hours and Earnings (ASHE). This has the advantage of being provided from HM Revenue and Customs’ (HMRC) Pay As You Earn (PAYE) records and hence is likely to capture earnings more accurately than a household survey. While the ASHE provides comprehensive earnings breakdowns and is considered more reliable for aggregate earnings calculations, it does not contain the range of demographic breakdowns which the APS provides. Use of the APS, therefore, enables us to build a fuller picture of earnings in the Digital Sector, using a robust data source. 

It is recognised that there will be other sources of evidence from industry bodies, for example, which have not been included above. We encourage statistics producers within the Digital Sector who have not been referenced to contact the Economic Estimates team at economicestimates@dsit.gov.uk.

9. Further information  

For further details about the estimates or for enquiries on this release, please email: economicestimates@dsit.gov.uk.  

For general queries relating to DSIT Official Statistics, please contact: statistics@dsit.gov.uk

The Economic Estimates: Employment and Earnings in the Digital Sector release contains both Accredited Official Statistics (Employment estimates) and Official Statistics in Development (Earnings estimates).

For more information on the Code of Practice for Statistics see https://code.statisticsauthority.gov.uk/.