Accredited official statistics

Digital Sector Economic Estimates: Annual GVA – Technical and quality assurance report

Updated 3 September 2024

This document covers the following topics:

1. an overview of the content covered in the statistical release ‘Digital Sector Economic Estimates: Annual GVA 2022 (provisional)’ 
2. an overview of the digital and telecoms sectors, how they are defined, and limitations of these definitions
3. the methodology underlying the statistical release, including data sources 
4. the processes used to check that the estimates have been produced correctly
5. other sources of information for the DCMS sectors
6. further information, including contact details for DCMS statisticians.  

1. Overview of release

The statistics release ‘Digital sector Economic Estimates: Annual GVA 2022 (provisional)’ reports gross value added (GVA) for the digital and telecoms sectors. GVA measures the contribution to the economy of each individual producer, industry or sector in the UK. It is used in the estimation of gross domestic product:

GVA + Taxes on Products − Subsidies on Products = GDP

Estimates of taxes and subsidies are not available at an industry level and therefore GVA is used as the headline economic measure at an industry level.

The release reports GVA expressed in both: 

• current basic prices (‘nominal GVA’), which give the best ‘instantaneous’ measure of the value to the economy, but are not adjusted for the effect of inflation.
• chained volume measures (‘real terms GVA’), where the effect of inflation is removed.

The estimates in the publication are consistent with national (UK) estimates, published by the Office for National Statistics (ONS). 

1.1 Official Statistics Accreditation

In June 2019, a suite of DCMS Sector Economic Estimates, including employment estimates, were independently reviewed by the Office for Statistics Regulation (OSR). They comply with the standards of trustworthiness, quality and value in the Code of Practice for Statistics and should be labelled accredited official statistics. Accredited official statistics are called National Statistics in the Statistics and Regulation Service Act 2007.

This followed a report by the Office for Statistics Regulation in December 2018, which stated that the series could be designated as National Statistics subject to meeting certain requirements. Since the report, we have striven to improve our 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. We will continue to improve the series in the future, in line with the recommendations of the report. We encourage our users to engage with us so that we can improve our statistics and identify gaps in the statistics that we produce.

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. 

1.2 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.

2. Sector definitions

In order to measure the size of the economy it is important to be able to define it. The digital and telecoms sector definitions are based on the Standard Industrial Classification 2007 (SIC) codes. This means nationally consistent sources of data can be used and enables international comparisons. 

Although telecoms is considered as a sector in its own right, the telecoms sector is completely contained within the digital sector as defined by SIC codes.

In February 2023, Machinery of Government changes meant that responsibility for the digital and telecoms sectors moved from DCMS to the newly created Department for Science, Innovation and Technology. Although previously included in the DCMS sector estimates, estimates for the digital and telecoms sectors are now presented separately. Following this change, many of the industries included in the digital sector still form part of the DCMS industry definition, as they are included in the definition of the creative industries.

2.1.2 Other sector definitions

Additional analysis is presented in the GVA release for the audio visual sector and the computer games sector. These sectors are included in the annual GVA publications for both the digital sector and DCMS.

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 

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 62.01 – ‘Computer programming activities’ may also contribute to the output of computer games, as part of a range of programming activities. This is not included in these computer games estimates, but will have been implicitly included in the ‘IT, software and computer services’ group in the main estimates.

2.2 Details and limitations of sector definitions

There are substantial limitations to the underlying classifications. 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 the digital sector, and therefore best fit SIC codes have been used to produce these estimates.

The definition used for the digital sector does not allow consideration of the value added of “digital” to the wider economy e.g. in health care or construction. Policy responsibility is for digital across the economy and therefore this is a significant weakness in the current approach.

3. Methodology

This chapter summarises the methodology used to produce GVA estimates, both in current prices and chained volume measures. For the 2022 release, estimates for the digital and telecoms sectors continued to be produced as part of the production of the DCMS annual GVA calculation, although published separately following the changes to the DCMS remit.

3.1 GVA - current prices

This first section presents the methodology for estimates of GVA expressed in current prices (i.e. not taking into account inflation). 

3.1.1 Data sources (current prices)

The following data sources were used in the production of GVA (current prices) for the digital and telecoms sectors:  

• Blue Book 2023 Consistent Supply and Use tables (published 31 October 2023)
• Latest Quarterly National Accounts (published 22 December 2023)
• Unsuppressed Annual Business Survey (ABS) approximate GVA estimates at the lowest level available 

3.1.2 Method (current prices)

The most reliable estimate of GVA comes from the Supply and Use Tables (SUT) produced annually by ONS. This contains balanced data drawn from many different sources, forming one robust estimate for each of the 112 industries in the SUT matrix. 

The SUT matrix reports GVA at division level (2 digit SIC codes), but the digital and telecoms sectors are defined at industry level (3 or 4 digit SIC codes). This means a method for breaking down the SUT to industry level must be applied. 

This is achieved by using approximate Gross Value Added (aGVA) data from the UK non-financial business economy (Annual Business Survey), by: 

• extracting aGVA from the ABS at industry level (e.g. SIC 32.12)
• calculating aGVA from the ABS at division level (e.g. SIC 32, by aggregating industries in the division) 
• calculating the proportion of the division aGVA that each industry accounts for (e.g. aGVA for SIC 32.12 as a proportion of SIC 32)
• applying the proportion for each industry to the division GVA in the SUT, to get a National Accounts consistent estimate of GVA for each industry. 

This method, using the National Accounts consistent SUT matrix, is preferable to only using aGVA from the ABS. There are differences between the two measures of gross value added the SUT and ABS in terms of coverage. For example, GVA covers the whole of the UK economy while aGVA covers the UK Non-Financial Business Economy, a subset of the whole economy that excludes large parts of agriculture, all of public administration and defence, publicly provided health care and education, and the financial sector. 

There are also conceptual differences between the two measures of gross value added. For example, some production activities such as illegal smuggling of goods must be included in the National Accounts but are outside the scope of the ABS. In addition, the national accounts data have gone through the Supply and Use balancing process, which reconciles all three estimates of GDP. Using the SUT matrix makes comparison with the wider UK economy more straightforward, and ensures that non-market production is included in the DCMS estimates. More information on the differences between National Accounts GVA and Approximate GVA can be found in the article, ‘A Comparison between Annual Business Survey and National Accounts Measures of Value Added’.

GVA figures for 2010 to 2020 have been revised since the last DCMS Economic Estimates GVA publication in April 2023. These revisions take into account the latest balancing of the National Accounts and finalisation of the Annual Business Survey data. National Accounts Supply Use Tables are open to revisions back to 1997 each year. These are planned revisions and an integral part of the balancing process. 

A complete time series of GVA is available in the UK GDP(O) low level aggregates table which is published each month alongside the UK GDP publication. This is aligned to average GVA up to and including 2021 but then uses growth in the output measure as a proxy for GVA beyond that. These short term measures tend to use turnover as a proxy for output and have no information on intermediate consumption.

Since the National Accounts SUT tables provide balanced GVA estimates only up to 2021, we use the output GVA in the UK GDP(O) low level aggregates table for 2022 to calculate provisional estimates for 2022 for DCMS sectors. All other aspects of the calculation are the same for all years from 2010 to 2022. These provisional estimates will be updated in the next release, following the publication of  National Accounts in the Blue Book 2024, which will include balanced GVA estimates for 2022.

3.1.3 Method limitations

Estimates from the Annual Business Survey (ABS) are subject to various sources of error, with sampling errors published at a 4-digit SIC level. While these data provide the best available source of information there is often volatility, especially at the 4 digit SIC level which is used to produce estimates for the digital and telecoms sectors. Further information on the quality of the ABS data is published by the Office for National Statistics.

There have also been two survey design changes in recent years (expanding the ABS population in 2015 and re-optimising the sample in 2016), but as the survey outputs are used only to provide a proportion of the SUT, these changes should have a minimal impact on the estimates of GVA.

3.2 GVA - chained volume measure

This second section presents the methodology for estimates of gross value added (GVA) for the Digital and Telecoms sectors, expressed in chained volume measures (i.e. taking into account inflation). A GVA expressed in chained volume measures was published for the first time in November 2017 in response to user demand. 

In Chained Volume Measures (CVMs), inflation is taken into account. CVMs are different to constant prices. Constant prices are simply the current price data deflated using a price from one base period, which is updated every 5 years. For CVMs, the base period is updated each year (for the latest publication, this is 2019), although this has been paused for several years due to the pandemic. CVMs are created by linking together series with different base years. In this analysis we use the CVM price series to calculate volume in terms of previous year prices and current year prices. 

3.2.1 Data Sources

The following data sources were used in the production of GVA (chained volume measures) for the digital and telecoms sectors:  

• Current prices data (see previous chapter, GVA - current prices, for data sources and methodology).
• Experimental industry level deflators (previously published on the ONS website, Industry Level Deflators, but for this release have been updated with the latest data).

3.2.2 Method (chained volume measure)

The current price data is broken down by industry for each of the aggregated industries included within the digital sector.

In order to derive a Chain Volume Measure (CVM) we make use of the relationship

value = volume x price

Current price estimates are the ‘value’ component of this equation. 

The ‘price’ component comes from experimental industry level deflators, previously published on the ONS website (Industry Level Deflators) but for this release have been updated with the latest data. This is a different deflation method than is used within the National Accounts but provides similar results. Deflation at an industry level within National Accounts is carried out by proportioning the industries into their relevant products and then deflating each product separately, before aggregating back up to an industry level.

Experimental industry level deflators are not available for all SIC codes, therefore deflators are used which match as closely as possible to each industry. All were in the form of a price index with 2010 = 100.

For each 3 or 4 digit SIC code, the ‘volume’ series is obtained by dividing the current price series by the deflator (price) series.

volume = value/price

To create a chained volume measure, the value series in previous year’s and current year’s prices is calculated (PYP and CYP respectively). The CYP series is simply the current price (‘value’) series. 

CYPt = volumet x pricet = valuet

where t is time (year). 

The PYP series is given by 

PYPt = volumet x pricet-1

The PYP series and CYP series are then summed across relevant SIC codes to give a PYP and CYP aggregate for each sector and subsector. 

These are then used to obtain scaling factors at sector and subsector level. When t base year, the scaling factor is 1. In this analysis, the base year is 2019 to remain in line with National Accounts data published by ONS. When t < base year, the scaling factor is given by 

SFt = (CYPt+1 / PYPt+1) x SFt+1

The CVM is then calculated for each sector and subsector. When t base year, CVM is 

CVMt = SFt x CYPt 

When t > base year, CVM is given by

CVMt = SFt x PYPt

The output is a CVM series from 2010 to 2020 for each sector and subsector. 

Users should note that the methodology for chained volume measures means they are not additive prior to the base year. This means the sum of subsector values will not equal sector values prior to 2019.

3.2.4 Method for repricing chained volume measures

ONS estimates of GVA are currently based to 2019 (the base year will be updated to 2022 in the National Accounts 2024). Since inflation has been higher in recent years, the digital sector GVA CVM level estimates have been repriced to 2022 prices, so that CP and CVM estimates are equal for 2022. This aligns with our methodology for monthly GVA statistics, which are only available as CVM.

To reprice the CVM series, each sector/subsector/digital total index is set to 2022 = 100. Then level estimates are produced by multiplying the index by the relevant CP value for 2022.

3.3 Summary of data sources

In summary, the data presented in this report on GVA

• are based on official statistics data sources
• are based on internationally-harmonised codes
• are based on survey data (Annual Business Survey and National Accounts) and, as with all data from surveys, there will be an associated error margin surrounding these estimates

This means the estimates are:

• comparable at both a national and international level. 
• comparable over time, allowing trends to be measured and monitored

However, this also means the estimates are subject to limitations of the underlying classifications of the make-up of the UK economy. For example, the standard industrial classification (SIC) codes were developed in 2007 and have not been revised since. Emerging sectors, such as Artificial Intelligence, are therefore hard to capture and may be excluded or mis-coded.  

3.4 Changes in this release

In this release we have:

• re-priced digital sector CVM level estimates to 2022 prices
• returned to the pre-pandemic practice of publishing a provisional year in our annual estimates
• published CVM estimates for computer games for the first time

4. Quality assurance processes

This chapter summarises the quality assurance processes applied during the production of the DCMS and Digital Economic Estimates Gross Value Added 2022 (provisional) statistics. This includes a detailed account of the quality assurance processes and the data checks carried out by our data providers (Office for National Statistics, ONS) as well as by DCMS. Please note that the COVID-19 pandemic and related lock-down measures have impacted timescales and availability of data across many of our sources for 2020 and 2021.

4.1 Quality Assurance Processes at ONS

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

4.1.1 The Blue Book

The Blue Book Annual GDP estimates are published at two different stages. Annual estimates are first available once all quarterly data for a given year is available in the quarterly national accounts. Annual estimates are then available in the UK National Accounts, The Blue Book, which is usually published between July and October each year (please note that The Blue Book is subject to a process of annual reconciliation). Trade statistics, Balance of Payments, public sector accounts and other short-term indicators of economic activity are all integrated within the system of national accounts. 

It is important to emphasise that the national accounts are estimates based on statistical surveys, forecasts and models. For further information on quality and reliability issues for the Blue Book and associated publications, see the National Accounts page. 

4.1.2 Annual Business Survey (ABS)

For more information on quality assurance processes utilised during the production and analysis of ABS, see Annual Business Survey technical report: August 2018.

4.2 Validation and accuracy of data

4.2.1 The Blue Book 

There is no simple way of measuring the accuracy of GDP. All estimates, by definition, are subject to statistical uncertainty and for many well-established statistics we measure and publish the sampling error and non-sampling error associated with the estimate, using this as an indicator of accuracy. 

Since sampling is typically done to determine the characteristics of a whole population, the difference between the sample and population values is considered a sampling error. Nonsampling errors are a result of deviations from the true value that are not a function of the sample chosen, including various systematic errors and any other errors that are not due to sampling. 

The estimate of GDP, however, is currently constructed from a wide variety of data sources, some of which are not based on random samples or do not have published sampling and non-sampling errors available. As such it is very difficult to measure both error aspects and their impact on GDP. 

Sample sizes can vary from 100% (HMRC Self Assessment data) to 1% (HMRC PAYE data). These variations are unavoidable in the collation of reliable time series data for the calculation of GVA. Improvements in the GVA methodology or changes in administrative source data allows for reviewing the available sources for higher quality datasets or more timely publications. This is an ad hoc and continuous process which does not include major revisions to the methodology of GVA. 

The vast majority of source data are annually updated, however, some datasets are published biennially or on an ad hoc basis. These missing values are imputed, using other available information. As with sample size, potential improvements to the methodology are reviewed whenever new data becomes available or when significant changes to the source data affect the final values. Where no recent estimate is available, the previous year’s data may be used. It is important to note however, that these issues are rare because of the completeness of the main source data. 

Estimates of approximate GVA are also published as part of the Annual Business Survey release. These estimates are used in the production of annual Supply and Use Tables for the compilation of the UK gross domestic product (GDP).

4.2.2 Annual Business Survey

The Annual Business Survey (ABS) measures business and financial information from UK businesses, including total turnover, total employment costs, total purchases, capital expenditure, stocks and other aggregates. Variables derived from these statistics, such as approximate gross value added at basic prices are also published by the ABS. For information on the ABS quality, please refer to the ABS QMI.

4.2.3 Approximate gross value added (aGVA) vs GVA in the National Accounts 

aGVA represents the amount that individual businesses, industries or sectors contribute to the economy. Generally, this is measured by the income generated by the business, industry or sector minus their intermediate consumption of goods and services used up in order to produce their output, labour costs (for example, wages and salaries) and an operating surplus (or loss). The latter is a good approximation for profits, from which the cost of capital investment, financial charges and the payment of dividends to shareholders are met. 

There are differences between the approximate measure of aGVA calculated by ABS and the measure of gross value added (GVA) used in the national accounts. The National Accounts carry out coverage adjustments, conceptual adjustments and coherence adjustments. This estimate of GVA uses inputs from a number of surveys and covers the whole UK economy, whereas the ABS does not include some parts of the agriculture and financial activities sectors, or public administration and defence. 

The ABS total aGVA is around two-thirds of the national accounts whole economy GVA because of these differences. Real (inflation-adjusted) estimates of national and regional GVA are published in the national accounts and regional accounts respectively. However, national and regional estimates of aGVA from the ABS are not adjusted for inflation. 

There are also some conceptual differences between the two measures of gross value added. For example, some production activities such as illegal smuggling of goods must be included in the national accounts but are outside the scope of the ABS. 

More information on this can be found in the Annual Business Survey technical report: August 2018.

4.3 Quality Assurance Processes at DCMS

The majority of quality assurance of the data underpinning the DCMS Sectors and Digital Sector Economic Estimates: Gross Value Added release takes place at ONS, through the processes described above. However, further quality assurance checks are carried out within DCMS.

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.

4.3.1 Data requirements and data delivery

For the ABS data, DCMS discussed our data requirements 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 improved the understanding of the data at DCMS, helping us to ensure we receive the correct data and use it appropriately. 

DCMS checks that the data delivered by ONS match what is listed in the Data Access Agreement (DAA). For this particular release we check that: 

• We have received all data at the 4 digit SIC code level, which is required for us to aggregate up to produce estimates for our sectors and sub-sectors. 
• Data at the 4 digit SIC code has not been rounded unexpectedly. This would cause rounding errors when aggregating up to produce estimates for our sectors and subsectors.

4.3.2 Data Analysis quality assurance checks

At the analysis stage, data is aggregated to produce information about the Digital and Telecoms sectors and sub-sectors. The GVA statistics lead checks whether:

• the GVA proportions are similar to last year, and if not, whether this is because of changes to the methodology
• there is any missing data
• the percentage changes each year look similar 
• the updated UK National Accounts data has been used, including the revised back series data. 
• the correct SIC codes have been aggregated together to form sector and sub-sector estimates

4.3.3 Publication quality assurance checks 

Finalised figures are disseminated within Excel tables and a written report (which includes written text, graphs, tables and infographics) published on GOV.UK. These are produced by the GVA statistics lead. Before publishing, a quality assurer checks the data tables as well as the report to ensure minimal errors. This is checked against a QA log where comments can be fed back and actioned accordingly. The quality assurer also makes sure any statements made about the figures (e.g. regarding trends) are correct according to the analysis and checks for spelling or grammatical errors.

Proofreading and publication checks are done at the final stage, including: 

• checking the figures in the publication match the published tables
• checking the footnote numbering is correct
• making sure hyperlinks work
• checking chart/table numbers are in the correct order
• ensuring the publication is signed off by DCMS Head of Profession for Statistics and DCMS Chief Economist
• contacting press office to ensure they are aware of the release date
• checking the published GOV.UK page again after publishing

4.4.4 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. 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 constructing these sector classifications from Standard Industrial Classification (SIC) codes. However, we accept 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.We are aware that other estimates of the economic contribution of the Digital and Telecoms Sectors may be available. These estimates use various methods and data sources, and can be useful for serving several purposes, e.g. monitoring progress under specific policy themes, or measuring activities subsumed across a range of SICs.

6. Further information

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

For general enquiries contact: 

Department for Science, Innovation & Technology,
100 Parliament Street,
London,
SW1A 2BQ.

For media enquiries contact: 020 7215 1000.

DCMS statisticians can be followed on X via @DCMSInsight.

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