Official Statistics

Economic Estimates: Earnings in the DCMS sectors, 2025 - Technical and quality assurance report

Published 23 April 2026

1. Introduction

This document sets out the data sources, methodology, definitions, and quality assurance processes underlying the DCMS Sectors Economic Estimates: Earnings 2025 publication.

This publication provides estimates of the earnings of employees in DCMS sectors in the UK as of April 2025 and estimates of the Gender Pay Gap (GPG) in DCMS sectors.

1.1 What is reported?

This release contains new, provisional, data for 2025 alongside revised data for the year 2024.

These statistics cover the following areas:

• DCMS sector earnings - this looks at the breakdown of median annual and weekly earnings by employment status e.g. full time and part time, age, sub-sector and by place of work (English regions, Scotland, Wales and Northern Ireland). 
• Gender pay gap - looking at the percentage difference between men’s and women’s earnings in DCMS sectors (based on hourly pay excluding overtime)

Estimates for median annual earnings and median weekly earnings for DCMS sector employees are based on the Annual Survey of Hours and Earnings (ASHE) dataset. This dataset is provided by the Office for National Statistics (ONS) and is the most robust source of earnings information in the UK.

DCMS has also previously published earnings estimates using the Annual Population Survey (APS), which contains breakdowns including, but not limited to, employment type (i.e. employed or self-employed), region of work, nationality, sex and ethnicity. As the APS provides self-reported earnings figures, users should be aware the APS is not the preferred source for earnings estimates at the aggregate level, with estimates based on the ASHE (Annual Survey for Hours and Earnings) providing a more robust measure.

We have decided to pause our earnings publications using the APS due to quality issues with the underlying data source. We will continue to publish only the earnings publications using the ASHE dataset and will consider whether to resume the APS earnings as the quality of the underlying data improves, in line with user needs.

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

1.2 Official Statistics Accreditation

Earnings estimates are official statistics that have not yet been reviewed and accredited by the Office for Statistics Regulation (OSR) but are produced in line with the standards of trustworthiness, quality and value in the Code of Practice for Statistics.

Our statistical practice is regulated by the OSR. OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

You are welcome to contact us directly with any comments about how we meet these standards by emailing evidence@dcms.gov.uk. 

Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the OSR website.

1.3 Users

The users of these statistics fall into five broad categories:

• Ministers and other political figures
• Policy and other professionals in DCMS 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 DCMS sectors, helping to understand how current and future policy interventions can be most effective.

2. Sector definitions

In order to measure the size of the economy it is important to be able to define it. DCMS uses a range of definitions based on internal or UK agreed definitions. Definitions are predominantly based on the Standard Industrial Classification 2007 (SIC) codes. This means nationally consistent sources of data can be used and enables international comparisons.

2.1 Overview of DCMS sectors

The sectors for which DCMS has responsibility are:

• Civil Society
• Creative Industries
• Culture
• Gambling
• Sport
• Tourism

Earnings estimates for the tourism sector are not available for 2025. The tourism sector definition uses data from the ONS Tourism satellite account, which is available up to 2023 and provisionally for 2024.

Each sector definition has been designed to be the best possible measure of that individual sector. There are overlaps between DCMS sectors, whereby an industry (as defined by 4-digit Standard Industrial Classification, or SIC, codes) may be used in two sector definitions. In particular, the cultural sector is defined using SIC codes that are nearly all within the creative industries and the tourism industries and civil society overlap with other DCMS sectors. These overlaps are accounted for in the Economic Estimates series to avoid double counting in DCMS sector totals.

Figure 1 below visually shows the overlap between DCMS sectors in terms of SIC codes. Users should note that this does not give an indication of the magnitude of the value of overlap.

Figure 1: Overlap of SIC codes within DCMS Sectors

Other sector definitions

Additional analysis is presented for the audio-visual sector, computer games sector and the art and antiques market. 

2.2 Details of DCMS sector definitions

This section looks at sector definitions used in this release in more detail and provides an overview of limitations. These sector definitions have been independently reviewed by the Office for Statistics Regulation (OSR) as part of their accreditation of a number of DCMS Sector Economic Estimates.

DCMS sector definitions are mostly based on the Standard Industrial Classification (SIC) framework which is used to classify business establishments and other statistical units by the type of economic activity in which they are engaged. The SIC system is internationally recognised, making it useful for comparisons across sectors, countries and over time. However, there are known limitations with the classification framework. As the balance and make-up of the economy changes, the SIC, finalised in 2007, is less able to provide the detail for important elements of the UK economy related to DCMS sectors. We will engage throughout 2025/26 with the Office for National Statistics (ONS) on their revision of the UK-SIC framework. 

The SIC codes used to produce DCMS sector definitions are a ‘best fit’, subject to the limitations described in the following section.

Creative industries

The creative industries were defined in the Government’s 2001 creative industries Mapping Document as “those industries which have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property”. Based on this definition, DCMS worked closely with stakeholders to determine which occupations and industries should be considered creative.

  The creative industries were determined on the basis of creative intensity (the proportion of occupations in an industry that are creative), following the dynamic mapping process set out in a 2013 paper published by Nesta:

• Through consultation, a list of creative occupations was identified.
• The proportion of creative jobs in each industry was calculated (the creative intensity)
• Industries with creative intensity above a specified threshold are considered creative industries

The definition is a UK definition based on internationally consistent industrial classifications which means estimates are comparable to the wider economy and useful internationally.. The SIC codes used to capture the creative industries sector and sub-sectors are shown in the accompanying tables. See the creative industries Economic Estimates methodology note for a more detailed explanation of how the definition has been derived.

Earnings estimates for the number of filled jobs in the creative occupations and their respective standard occupation classification (SOC2020) codes are not included in this release. This is because DCMS is in the process of defining which SOC2020 codes should be included in the creative occupations, following the ONS revision of SOC2020 data published in July 2023.

Cultural Sector

DCMS defines the cultural sector as those industries with a cultural object at the centre of the industry. DCMS proposed and consulted on a definition of the cultural sector in 2016, based on the availability of data through the SIC framework. There are limitations with the DCMS measurement of the cultural sector arising from the lack of detailed disaggregation possible using the standard industrial classifications. There are some cases where culture forms a small part of an industry classification and therefore cannot be separately identified and assigned as culture using standard data sources, this is particularly the case for the heritage sector.

It is recognised that, due to the limitations associated with SIC codes, the SIC code used in past publications as a proxy for the Heritage sector (91.03 - Operation of historical sites and building and similar visitor attractions) is likely to be an underestimate of this sector’s value. We have changed the name of the Heritage sector to ‘Operation for historical sites and similar visitor attractions’ to reflect this. We have been working on assessing methodologies for producing heritage sector economic estimates based on a broader definition which more accurately reflects the heritage sector. We are continuing to develop this methodology to produce robust heritage sector estimates.

Sport

For the purpose of this publication, the statistical definition of sport has been used. This incorporates only those 4-digit Standard Industrial Classification (SIC) codes which are predominantly sport (see the definitions Table 1a in the published data tables). This aligns with the international statistical definition of sport, based on the EU agreed Vilnius definition, and allows the contribution of sport to be considered in a way which is consistent with other DCMS sectors.

Gambling

The definition of gambling used in DCMS sectors Economic Estimates is consistent with the internationally agreed definition, SIC 92 (‘Gambling and betting activities’).

Civil society

In DCMS ASHE based earnings estimates, jobs are considered to be part of the civil society sector if they are classified as ‘Not for Profit’ across all industries.

Tourism

Tourism is defined by the characteristics of the consumer in terms of whether they are a tourist or resident. This, therefore, differs from “traditional” industries such as gambling which are defined by the goods and services produced themselves, and means that a different approach to defining the industry must be used.

To estimate earnings in the Tourism sector, ratios calculated from the Tourism Satellite Account (TSA) are applied to the ASHE weightings. This allows an estimate of the earnings of those directly employed in the Tourism industry.

2.3 Additional Sector Definitions 

Additional analysis is presented in the data tables of this release for the audio-visual sector, the computer games sector and the arts and antiques market. 

Audio-visual sector

The definition of the audio-visual sector (see below) is intended to reflect the sectors covered by the EU Audio-Visual Media Services Directive.

• 59.11 - Motion picture, video and television programme production activities
• 59.12 - Motion picture, video and television programme post-production activities
• 59.13 - Motion picture, video and television programme distribution activities
• 59.2 - Sound recording and music publishing activities
• 60.1 - Radio broadcasting
• 60.2 - Television programming and broadcasting activities
• 63.91 - News agency activities
• 63.99 - Other information service activities n.e.c.
• 77.22 - Renting of video tapes and disks
• 77.4 - Leasing of intellectual property and similar products, except copyrighted works

Computer Games sector

The computer games sector combines the 4-digit SIC code 58.21 (Publishing of Computer Games) and 62.01/1 (Ready-made interactive leisure and entertainment software development).

A number of software programming companies in the whole SIC code 62.01 – ‘Computer programming activities’ may also contribute to the output of computer games, as part of a range of programming activities. Only a subset of these (those in 62.01/1) are included in these computer games estimates, however, they will all have been implicitly included in the ‘IT, software and computer services’ creative industries sub-sector in the main estimates.

Arts and antiques market

The arts and antiques market combines two 5-digit SIC codes:

• 47.78/1 - Retail sale in commercial art galleries
• 47.79/1 - Retail sale of antiques including antique books, in stores

3. Methodology

3.1 Data sources

Annual Survey of Hours and Earnings (ASHE)

This release presents analysis on median annual and weekly earnings for DCMS sector employees based on the ONS Annual Survey of Hours and Earnings (ASHE) dataset. The Annual Survey of Hours and Earnings (ASHE) is a sample taken from the PAYE system and provides the most reliable data on earnings for UK employees, however, it has limited demographic information.

Provisional (p) results for 2025 are available and are subject to change once finalised. Data for 2024 have been revised in this release and are final. The estimates in the publication are consistent with national (UK) estimates, published by ONS.

The ASHE dataset includes information about the levels, distribution and make-up of earnings and hours paid for employees in all industries and occupations across the UK.

Businesses are surveyed in April of each year. The survey uses a random sample of 1% of all employee jobs from HM Revenue and Customs’ (HMRC’s) Pay As You Earn (PAYE) records to identify an individual’s current employer. 

Since ASHE is a survey of employee jobs, it does not cover the self-employed or any jobs within the armed forces. Given the survey reference date in April, the survey does not fully cover certain types of seasonal work, for example, employees taken on for only summer or winter work.

Tourism Satellite Account

The UK Tourism Satellite Account (TSA) is an extension to a System of National Accounts (SNA) produced by the ONS containing annual inbound, outbound and domestic expenditure on tourism, internal tourism consumption and employment for the tourism industries. It enables users to gain an understanding of the size and role of tourism-related economic activity, which is usually “hidden” within standard national accounts. Data is available up to 2023.

For 2024, a provisional indicator for the TSA has been produced by the ONS to provide a more timely estimate of the TSA. 

3.2 Method 

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 data tables derived from the ASHE use three different measures of earnings. The filters used are consistent with ONS analysis:

• The weekly filter is employees on adult rates whose earnings for the pay period were not affected by absence. Additionally, employees who do not have a valid work region and who are less than 16 years old are filtered out because the age and region variables are required for weighting.
• The annual filter is employees on adult rates who have been in the same job for more than one year. Additionally, employees who do not have a valid work region and who are less than 16 years old are filtered out. Employees with missing or zero annual gross salaries are also filtered out.
• Hourly pay excluding overtime is used to calculate the Gender Pay Gap (GPG), and uses the same filters as weekly pay.

The headline statistics for ASHE are based on the median rather than the mean. The median is the value below which 50% of employees fall. It is ONS’s preferred measure of average earnings as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings, so provides a better indication of typical pay than the mean.

3.3 Strengths and limitations of the data

The ASHE data used for this analysis are robust and have a number of strengths:

• Size and coverage - the 2025 ASHE dataset contains information on approximately 170,000 jobs in all industries, occupations and regions, making it the most comprehensive source of earnings information in the UK and enabling a vast range of analyses.
• Quality - alternative sources of earnings information such as the APS rely on self-report or proxy data, which are known to be less reliable than information from employers’ administrative systems.

but there are some limitations of which users should be aware:

• Due to data collection difficulties during the 2020 COVID-19 pandemic, the sample achieved in the 2020 ASHE was about 20% smaller than usual, dropping from around 180,000 to 144,000 jobs. Given the challenges to data collection during the pandemic, the final achieved sample sizes fell to a low of 142,000 in 2021. The achieved sample has since almost recovered to pre-covid levels with a 5-year high of 174,000. A full breakdown of achieved samples since 2020 are available in Table 1. Further details are available in the ONS’s bulletin for ASHE 2025.

Year	Achieved Sample
2020	144,000
2021	142,000
2022	148,000
2023	164,000
2024	173,000
2025	174,000

Table 1. Achieved samples of the Annual Survey of Hours and Earnings for the years 2020-2025.

• Due to minimal differences in the methodology and analysis used to calculate the median, results in this report may not match the ONS published results, in particular when looking at further breakdowns to some data e.g. by region or age. These differences are small but should be treated with caution.
• Lack of personal demographic information - characteristics such as ethnicity, religion, education, disability and pregnancy are not recorded in the ASHE dataset. 
• The quality of estimates at low levels of disaggregation can be poor.
• The dataset does not cover those who are self-employed or not within the PAYE scheme, meaning that lower-paying jobs may be excluded.

A fuller description of the strengths and limitations of the Annual Survey of Hours and Earnings (ASHE) can be found in the Quality and Methodology Information report, the Guide to sources of data of earnings and income, and the Guide to interpreting Annual Survey of Hours and Earnings (ASHE) estimates.

Disclosure control

As part of the production process, we also apply disclosure control measures to prevent the identification of any respondents. We suppress values where the number of respondents for a cell is below a set threshold. 

4. Quality assurance processes

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

4.1 Quality assurance processes at the ONS

Quality assurance at ONS takes place at a number of stages. The various stages and the processes in place to ensure quality for the data sources are outlined below. It is worth noting that information presented here on data sources are taken from the ASHE quality information report. This work should be credited to colleagues at the ONS.

Sampling and data collection

ASHE is based on a 1% sample of employee jobs taken from HM Revenue and Customs (HMRC) Pay As You Earn (PAYE) records. The sample is matched against the ONS’ Inter-Departmental Business Register (IDBR) in order to obtain contact and address details for the employers. Information on the hours paid and earnings of employees is obtained from employers and treated confidentially. Please note that ASHE does not cover the self-employed, nor does it cover employees not paid during the reference period.

A specific date in April is chosen so that all respondents refer to the same point in time. This reference date is not the same every year. Given the survey reference date in April, the survey does not fully cover certain types of seasonal work, for example, employees taken on for only summer or winter work.

The ASHE dataset contains information on approximately 170,000 jobs in all industries, occupations and regions, making it the most comprehensive source of earnings information in the UK and enabling a vast range of analyses.

Validation and quality assurance

• Accuracy is the degree of closeness between an estimate and the true value. As the survey is a sample survey, it provides estimates of population characteristics rather than exact measures. At ONS, coefficients of variation (cv) are published alongside ASHE outputs to present the sampling variability of the survey. 
• The ONS applies imputation and weighting to compensate for missing values and low responses. More information is available in the Annual Survey of Hours and Earnings QMI
• Various procedures are in place to minimise errors in returned data. Returns undergo a range of checks that include validation against previous returns and expected values, selective editing (a technique for prioritising suspicious values for follow-up based on their impact on published results) and re-contacting businesses for verification. Similar checks are also made at the aggregate level for main results.

4.2 Quality assurance processes at DCMS

The majority of quality assurance of the data underpinning this DCMS sectors Economic Estimates release takes place at ONS, through the processes described above. However, further quality assurance checks are carried out within DCMS at various stages.

Production of the report is typically carried out by one member of staff, whilst quality assurance is completed by at least one other, to ensure an independent evaluation of the work.

Data requirements

DCMS discusses its data requirements for ASHE data with ONS and these are formalised as a Data Access Agreement (DAA). The DAA covers which data are required, the purpose of the data, and the conditions under which ONS provide the data. Discussions of requirements and purpose with ONS improve the understanding of the data at DCMS, helping us to ensure we receive the correct data and use it appropriately.

The DAA covers which data are required, the purpose for accessing the data, and the conditions under which ONS provide the data. Discussions of requirements and purpose with ONS improved the understanding of the data at DCMS, helping us to ensure we receive the correct data and use it appropriately.

Production and data analysis

At the production stage, the data is aggregated up to produce information about DCMS sectors and sub-sectors before inputting the data into the formal data tables ready for analysis. Disclosure control is also applied as part of this process.

The statistical lead ensures a number of quality assurance checks are undertaken during this process. Where relevant these checks typically include:

• whether disaggregations sum to the overall total. E.g:
  • Do sub-sectors within the creative industries sum to the creative industries total?
  • Do the individual regional breakdowns sum up to the total for that sector?
• “Sense checks” of the data. E.g.:
  • Are the estimates similar from one year to the next? How do the figures compare with ONS published totals?
  • Looking at any large differences between the data and possible causes to these.
• Checking that the correct SIC codes have been aggregated together to form DCMS sector (and sub-sector) estimates. Are all SIC codes we require included? Are there any non-DCMS SIC codes that have been included by accident?
• Checking it is not possible to derive disclosive data from the figures that will be published.
• Making sure the correct data has been pasted to the final tables for publication, is accessible, formatted correctly, and has appropriate documentation.
• Having checked the quality of the data, analysis is then conducted to outline the key trends and patterns. This is then checked to ensure all statements, figures and charts are correct.

Dissemination

Finalised figures are published as OpenDocument spreadsheets on GOV.UK, with summary text on the webpage. These are produced by the workforce statistics lead who, beforehand, checks with the ONS on details of how to interpret the statistics. Before publishing, a quality assurer checks the figures match between the tables and the GOV.UK page summary. The quality assurer also makes sure any statements made about the figures (e.g. regarding trends) are correct according to the analysis and checks spelling or grammar errors.

Post publication

Once the publication is released, DCMS reviews the processes and procedures followed via a wash up meeting. This occurs usually a week after the publication release date and discusses:

• What went well and what issues were encountered
• What improvements can be made for next time
• Engaging with users of the publication to get feedback

5. 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. The government generally favours classification systems which are

• rigorously measured,
• internationally comparable,
• nationally consistent, and
• ideally applicable to specific policy interventions.

These are the main reasons for DCMS constructing sector classifications from Standard Industrial Classification (SIC) codes. However, DCMS accepts that there are limitations with this approach and alternative definitions can be useful where a policy-relevant grouping of businesses crosses existing Standard Industrial Classification (SIC) codes. DCMS is aware of other estimates relevant to DCMS sectors. These estimates use various methods and data sources and can be useful for serving several purposes, e.g. monitoring progress under specific policy themes such as community health or the environment, or measuring activities subsumed across a range of SICs. We encourage statistics producers within DCMS sectors to contact the economic estimates team at evidence@dcms.gov.uk.

6. Further information

For enquiries on this release, please email evidence@dcms.gov.uk.

For general enquiries contact:

Department for Culture, Media and Sport
100 Parliament Street London
SW1A 2BQ

Telephone: 020 7211 6000 

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to. You are welcome to contact us directly with any comments about how we meet these standards. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the OSR website.