Accredited official statistics

Economic Estimates: Digital Sector Annual (2010 to 2024) and Regional (2010 to 2022) Gross Value Added – Technical and quality assurance report

Published 12 February 2026

1. Overview of release

This technical report covers ‘Economic Estimates: Digital Sector Annual (2010 to 2024) and Regional (2010 to 2022) Gross Value Added’ a combination of the Annual GVA and Regional GVA releases from the Digital Economic Estimates Gross Value Added collection.

These statistics provide an estimate of the annual contribution of the Digital Sector and its associated subsectors to the UK and ITL1 regional economy measured by gross value added (GVA). GVA is the measure of the value of goods and services produced in an area, industry or sector of an economy, defined by the value of output minus the value of intermediate consumption. It is used in the estimation of gross domestic product (GDP):

GVA + Taxes on Products − Subsidies on Products = GDP

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

The release reports GVA expressed as both:

• Current price GVA (i.e. ‘nominal GVA’), which gives the best ‘instantaneous’ measure of the value to the economy, but is not adjusted for inflation.
• Chained volume measures (CVM) GVA (i.e. ‘real terms GVA’), where the effect of inflation is accounted for.

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

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 since April 2024. The DSIT statistics for the Digital Sector continue to follow a consistent methodology with the DCMS sectors. Previous releases of the Economic Estimates in the DCMS and Digital Sectors series can be found on the DCMS webpage.

1.1 Code of Practice for Statistics 

The ‘Economic Estimates: Digital Sector Annual Gross Value Added’ series and ‘Economic Estimates: Digital Sector Regional Gross Value Added’ series contain statistics classified as Accredited Official Statistics. These accredited official statistics were independently reviewed by the Office for Statistics Regulation in June 2019. They comply with the standards of trustworthiness, quality and value in the Code of Practice for Statistics and should be labelled ‘accredited official statistics’.

Since their accreditation, DCMS improved 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 statistics have not been formally assessed for compliance with the Code of Practice for Statistics since their transfer from DCMS. The OSR is planning to assess the statistics for compliance with the Code of Practice for Statistics in the near future. We commit to producing and publishing the statistics in line with the Code pillars of Trustworthiness, Quality and Value. Accredited Official Statistics are referred to as National Statistics in the Statistics and Registration Service Act 2007.

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.

DSIT is actively considering how to continue to improve the series, in line with the recommendations of the OSR report. We previously consulted on pausing or ceasing some of the statistical releases within the Economic Estimates series, the response to which can be found here, so that we can prioritise improvements to our key statistical releases. The combination of the Annual and Regional GVA series, as has been done in this release, was a decision made as a result of this consultation.

As part of our continuing review process, we previously made improvements to annual GVA estimates by incorporating balanced deflators and providing additional detail to our chained volume measure calculations methodology. These improvements have now also been applied to our regional GVA estimates and are discussed in the methodology section.

As we progress with the improvements, we will clearly state where this results in a divergence of methodology with the DCMS produced statistics. We continue to encourage our users to engage with us as we improve our statistics and look to identify gaps in the statistics that we produce.

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 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. 

The UK SIC is a hierarchical five-digit system. From order of highest to lowest level of aggregation, where each level is divided into the next, the UK SIC hierarchy is defined by:

• Section, denoted by letters, which are collections of divisions.
• Division, denoted by 2-digit SIC codes.
• Group, denoted by 3-digit SIC codes.
• Class, denoted by 4-digit SIC codes.
• Subclass, denoted by 5-digit SIC codes.

There are 21 sections, 88 divisions, 272 groups, 615 classes and 191 subclasses in the UK SIC hierarchy.

As an illustrative example of the SIC hierarchy, in Section J (SIC 58-63), the division “Information service activities” (SIC 63), is comprised of the groups “Data processing, hosting and related activities; web portals” (SIC 63.1) and “Other information service activities” (SIC 63.9). The group defined by SIC 63.1 is then further broken down into the classes “Data processing, hosting and related activities” (SIC 63.11) and “Web portals” (63.12).

2.1 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).  In effect, the Digital Sector definition used in this publication is defined at the four-digit SIC code level:

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, 26.20, 26.30, 26.40, 26.80
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, 59.20, 60.10, 60.20
Telecommunications	61.10, 61.20, 61.30, 61.90
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

2.2 Details and limitations of sector definition

This section looks at sector definitions in more detail and provides an overview of limitations.

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. By not including the value added to the economy from digital services, our definition is likely to underestimate the size of the Digital Sector.

There are also limitations to the underlying SIC classifications and its application. As the SIC codes were finalised in 2007,  subsequent changes to the balance and make-up of the UK’s economy have decreased the relevance of SIC codes for important elements of the economy related to the Digital Sector; so, making the use of SIC codes less robust. This is particularly relevant for the Digital Sector, within which there are several emerging sectors that are not accurately identified by SIC codes, such as cyber security and artificial intelligence. In the UK, companies select a SIC code on their incorporation, with limited external verification of the accuracy of this selection. Therefore, SIC codes used to produce these estimates are a ‘best fit’, subject to these limitations. The SIC classification system is currently being updated and will be released later this year.

3. Revised and provisional estimates

This release contains revised and provisional Gross Value Added (GVA) estimates. GVA estimates are updated as Annual Business Survey (ABS) or current price GVA data becomes available. As discussed in the methodology section, ABS data is used to apportion division level current price GVA data to the class level. Current price GVA data is used in output data tables and calculation of implied deflators.

In this release, revised estimates use the relevant year of ABS data and balanced current price data from Supply and Use Tables (SUT). Revised estimates use the most accurate underlying data that are available and are therefore considered more accurate than provisional estimates. However, revised estimates may be further revised as underlying ABS or current price GVA data is updated. ONS have produced this report on why ONS figures are revised.

Provisional regional GVA estimates for 2023 have not been included in this release. As described by ONS, regional industry estimates for the components of income and production in 2023 have been calculated by applying growth in gross domestic product (output) industry figures and then constraining these to sum to the income and production component totals. The figures used in this process are consistent with those published in the UK National Accounts, The Blue Book: 2024. Given that we have seen substantial revisions to national GVA estimates from Blue Book 2024 to Blue Book 2025, as described in Section 4.3, we can expect substantial revisions to provisional regional GVA estimates in the next release. Provisional regional GVA estimates would therefore have limited value.

Annual GVA provisional estimates use output current price data, which has not yet been through the balancing process, from GDP low-level aggregates. Annual GVA provisional estimates also use the previous year’s ABS data.

Provisional estimates are therefore considered less accurate than revised estimates as they rely on more timely but less accurate output current price data and/or are produced before relevant ABS data is available. Consequently, provisional estimates regularly undergo revisions in the release following their initial publication.

It is DSIT practice to align economic statistics with ONS National Accounts where possible and keep the statistics representative of the structure of the UK economy. Annual GVA figures from 2010 to 2023, and Regional GVA figures from 2010 to 2022 have been revised as part of standard ONS yearly revisions to data. Revisions take into account more recent survey and administrative information, together with methodological improvements. This year, revisions to underlying GVA data and therefore Annual and Regional GVA estimates in this release are larger than usual.

Updates to survey and administrative data and changes to how ONS estimate research and development had a particularly large effect on gross domestic product (GDP) data for all industries. Some of these updates may have a particularly large effect on Digital Sector GVA estimates. For example, more recent survey data for the information and communication sector, used to derive Digital Sector GVA estimates, is responsible for a strong upward contribution to GDP revisions. Additionally, ONS introduced an update to the data used to estimate the value of software developed by companies which has led to an upward revision to GDP from 2021 onwards. Given that GDP is the sum of GVA across all industries, plus net taxes on production, revisions to GDP are likely to affect GVA. ONS provide further, more detailed information on Blue Book 2025 revisions. Further revisions can be expected if future updates are made to underlying ONS data.

4. Methodology

4.1 GVA - current prices

This first section presents the methodology for estimates of Annual and Regional GVA expressed in current prices, i.e. ‘nominal GVA’, which does not take into account the effect of inflation.

Data sources (current prices, Annual GVA)

The following data sources were used in the production of Annual GVA (current prices) for the Digital Sector:

• Blue Book 2025 consistent Supply and Use Tables (SUT) (published 31 October 2025)
• GDP low-level aggregates from the latest Quarterly GDP National accounts (published 13 November 2025)
• Unsuppressed Annual Business Survey (ABS) approximate GVA (aGVA) estimates.

Data sources (current prices, Regional GVA)

The following data sources were used in the production of Regional GVA (current prices) for the Digital Sector:

• Office for National Statistics Regional Gross Value Added balanced tables (published 17 April 2025).
• Unsuppressed Annual Business Survey (ABS) aGVA estimates.

Method (current prices)

The most reliable estimate of Annual GVA comes from the Supply and Use Tables (SUT) produced annually by ONS and made consistent with the latest Blue Book release. Producing this estimate involves balancing data drawn from many different sources, forming one robust estimate for each of the 112 industries in the SUT matrix up to and including 2023. ONS produce this ‘balanced’ data through their supply and use framework, which involves data confrontation and validation.

The latest GDP low-level aggregates release contains annual output GVA estimates for 2024. Output GVA is more timely but is not balanced to the income and expenditure measurements of GVA, making it less accurate. To form a 2010 to 2024 current price timeseries of Annual GVA, we therefore append unbalanced 2024 output GVA estimates to balanced 2010 to 2023 GVA estimates from SUT. Estimates derived from unbalanced output GVA, i.e. for 2024, are marked as provisional.

The most reliable estimate of regional GVA comes from the Regional Gross Value Added (balanced) tables produced annually by ONS. National aggregates for the components of GVA are allocated to regions using the most appropriate regional indicator available. The Regional Accounts Methodology Guide contains more information about the construction of the regional accounts.

These Regional GVA tables are consistent with the UK National Accounts. Note that current regional tables are based on the previous year’s National Accounts. Therefore, the Regional GVA estimates used in this release are consistent with the 2024 National Accounts, which provided balanced GVA data for years up to and including 2022. Usually, estimates for 2023 would be derived from unbalanced output GVA and marked provisional but provisional Regional GVA estimates have not been included in this release. See Section 3 for further information.

The SUT matrix and GDP low-level aggregates report GVA at Division level (2-digit SIC codes), but the Digital Sector and its subsectors are defined at the Class level (4-digit SIC codes). This means a method for apportioning the GVA from the division level to the class 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 the Class level (e.g. 4-digit, SIC 46.51).
• Calculating aGVA from the ABS at Division level (e.g. 2-digit, SIC 46), by aggregating industries in the division.
• Calculating the proportion of the division aGVA that each Class accounts for (e.g. aGVA for 4-digit SIC 46.51 as a proportion of 2-digit SIC 46).
• Applying the proportion for each class to the division GVA in the SUT, to get the GVA estimate for each Class. These estimates are then consistent with the National Accounts.

At the time of release, ABS data is only available for years 2010-2023. To apportion 2024 Annual GVA data, we use ABS data from the nearest available year, i.e. 2023. This data is considered provisional and subject to revisions in the next release.

In the case of there being no ABS data available for specific SIC codes and years of interest, due to lack of coverage or otherwise, we opt to use ABS data for those SIC codes from an alternate year in which ABS data is available. Hence, we would apportion the current price GVA data for a given SIC code and year by the ABS aGVA data from the most suitable year we have available, likely the previous year. If no value exists in any of the previous 3 years, we assume this value to be 0.

In this release, SIC code 26.80 has no National aGVA estimate reported in the 2021 ABS. As such, we use the 2020 ABS aGVA estimate for SIC code 26.80 for National data. The rest of SIC 26 is unaffected. Many Regional GVA values are affected by missing ABS values. SIC code 26.80, Northern Ireland and the North East of England in particular have a high number of missing regional ABS values.

Following the apportioning process, we then aggregate the produced GVA for each Class (4-digit SIC code) into the Digital Sector and subsectors.

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

There are also conceptual differences between the two measures of GVA. 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 balanced GVA makes comparison with the wider UK economy more straightforward and ensures that non-market production is included in the Digital Sector 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’ from the ONS.

Method limitations (current prices)

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 Sector. Further information on the quality of the ABS data is published by the ONS in the ABS quality measures and the ABS QMI. Users may also refer to the discussion of uncertainty in surveys published by the ONS.

There have also been two survey design changes (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 comparisons with historical Digital Sector GVA.

As described by ONS, for the 2019, 2020 and 2021 collections, the Annual Business Survey achieved smaller than usual sample sizes, meaning that results for those years are less certain. This will increase uncertainty in our Annual and Regional GVA estimates in these years, particularly for smaller subsectors such as ‘Repair of computers and communication equipment’ or ‘Software publishing’.

4.2 GVA - chained volume measures

This section presents the methodology for estimates of Annual gross value added (GVA) for the Digital Sector, expressed in Chained Volume Measures (CVMs), i.e. ‘real-terms GVA’, which takes into account the effect of inflation. For further information on CVM background and methodology, visit the ONS website.

CVMs estimates are volume measures that are obtained by chain-linking. Volume measure (also referred to as constant price) series, are the current price data deflated using a price index (deflator) from a single base period, effectively removing the influence of changes in prices over time (i.e. inflation or deflation).

In CVMs, base periods are typically updated each year and CVM series are created by linking together individual series with different base years that overlap in one period, which is considered to reflect more accurately volume changes over time. The methodology for deriving a CVM series in this publication is consistent with the methodology used in the National and Regional Accounts.

Data sources (chained volume measures, annual GVA)

The following data sources are used in the production of Annual GVA (chained volume measures) for the Digital Sector and its subsectors:

• Blue Book 2025 consistent Supply and Use Tables (SUT) (published 31 October 2025).
• GDP low-level aggregates from the latest Quarterly GDP National accounts (published 13 November 2025).
• Unsuppressed Annual Business Survey (ABS) approximate GVA (aGVA) estimates.

Data sources (chained volume measures, regional GVA)

The following data sources were used in the production of Regional GVA (chained volume measures) for the Digital Sector and its subsectors:

• Office for National Statistics Regional Gross Value Added balanced tables.
• Unsuppressed Annual Business Survey (ABS) approximate Gross Value Added estimates.

Method (chained volume measures)

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

value = volume x price

Current price estimates, discussed in the section prior, are the ‘value’ component of this equation. The current price data is broken down by industry for each of the aggregated industries included within the Digital Sector remit. The ‘price’ component of this equation in our method comes from implied deflators, calculated from ONS SUT and GDP low-level aggregates.

The implied deflators are calculated by dividing the current price (CP) series by the chained volume measure (CVM) series and multiplying by 100 to produce a percentage value:

implied deflator = CP / CVM

These implied deflators therefore incorporate the balancing process used to produce the National Accounts and are produced using the same methodology as the implied regional deflators published alongside the Regional Accounts. This method is an update on our previous use of unbalanced output industry deflators, see section 4.3 for more details.

For each 4-digit SIC code in the Digital Sector, the ‘volume’ (written here as KP, or constant price) series is obtained by dividing the current price series (written here as CP) by the deflator (price) series.

KP = CP / price

To create a chained volume measure, the value series in previous year’s prices (PYP) and current year’s prices (CYP) is calculated. The definition of the PYP and CYP series changes depending on whether the year in question is before, or after the selected chain-linking base year.  In our methodology, the chain-linking base year is defined to be the last year which has been balanced through input-output supply and use tables (SUT). In this publication, the chain-linking base year is 2023 for Annual GVA and 2022 for Regional GVA to remain in line with National Accounts data published by ONS.

For years up to and including the chain-linking base year, the CYP series is the current price (CP) series:

CYP_t = KP_t x price_t= CP_t

where the subscript t denotes time (year).

The Previous Year Price (PYP) series is given by:

PYP_t = KP_t x price_t-1

Due to missing ABS values, some 4-digit SIC code level PYP series cannot be calculated, as there is no price data for the previous year following ABS apportionment. A PYP series is therefore calculated for 2-digit SIC code level divisions as a whole. The difference between this 2-digit SIC code level PYP series and the sum of the known PYP series for 4-digit SIC code level classes within that 2-digit SIC code level division is calculated. This difference is then apportioned equally to all 4-digit SIC code level classes with missing PYP values. This ensures that our division level CVM totals are consistent with ONS totals even when there are missing ABS values for that division.

When constructing a CVM series, the selected chain-linking base year also defines the reference year for the series, and as such the constant price (KP) series equals the current price (CP) series for the chain-linking base year.

For years after the chain-linking base year, both the PYP and CYP series are defined to be constant price (KP) series for that year, divided by the value of the constant price (KP) series for the base year, multiplied by the current price (CP) series of the chain-linking base year.  In effect, this means that for years following the chain-linking base year, the PYP, CYP and KP series are equivalent:

PYP_t = CYP_t = KP_t

The PYP series and CYP series are then summed across relevant SIC codes for each year, to give a PYP and CYP aggregate series for the Digital Sector and its subsectors.

These are used to obtain scaling factors at sector and subsector level. When t ≥ base year, the scaling factor is one. When t < base year, the scaling factor is given by:

SF_t = (CYP_t+1 / PYP_t+1) x SF_t+1

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

CVM_t = SF_t x CYP_t

When t > base year, CVM is given by:

CVM_t = SF_t x PYP_t

The output is a CVM series from 2010 to 2024 for Annual GVA and 2010 to 2022 for Regional GVA, 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 would not equal Digital Sector values prior to 2023 for Annual GVA and 2022 for Regional GVA.

CVM reference year

Notionally, a reference year in a chained volume measure (CVM) series means that the CVM values for the reference year (in monetary value) will be equal to the corresponding current price values for the same period. Equivalently, in a CVM index series, the index for the reference year would be equal to 100. When constructing a CVM series, usually the selected chain-linking base year and the reference year are the same. In this publication, the base year and reference year are both 2023 for Annual GVA and 2022 for Regional GVA.

4.3 Changes in this release

Annual and Regional GVA figures for 2019 onwards have been revised since the previous Economic Estimates: Digital Sector Annual Gross Value Added and Economic Estimates: Digital Sector Regional Gross Value Added publications. Annual and Regional GVA figures for 2010 to 2019 have also been revised since last published in the DCMS Economic Estimates: Annual GVA and Regional GVA publications February 2024 and July 2023 respectively. These revisions take into account the latest balancing of the National Accounts, revisions to Annual Business Survey (ABS) data and revisions to underlying current price GVA data.

National Accounts GVA is open to revisions back to 1997 each year. These are planned revisions and an integral part of the balancing process. Revisions made to underlying current price GVA data are as a result of improvements to annual survey, research and development, and administrative data, which have affected 2021 and 2022 GVA estimates in particular.

Revisions to Annual GVA estimates for 2019 to 2023 are likely to be slightly larger than usual due to the compounding effect of National Accounts balancing, revisions to ABS data and underlying current price GVA data. Tables 3 and 4 show a breakdown of the impact of National Accounts revisions, inclusive of current price revisions, and ABS revisions on Annual GVA estimates for 2019 to 2023.

Revisions to Annual GVA estimates for 2010 to 2019 and Regional GVA estimates for 2010 to 2022 are likely to be substantially larger due to changes in the frequency of National Accounts base year updates and changes in our deflator methodology described in the previous Annual GVA technical report.

In the Blue Book  2022 and Blue Book 2023, the last base year remained at 2019 due to the effects of the COVID-19 pandemic on the structure of the economy. In the Blue Book 2024, ONS returned to their pre-pandemic approach to chain-linking by moving the last base year on to 2022. This approach has continued in the Blue Book 2025 used in this release. The base year has been moved forward over a longer time period than usual for 2010 to 2022 Regional GVA estimates and 2010 to 2019 Annual GVA estimates which when last published were based on Blue Book 2022 or Blue Book 2023 data. There are therefore larger revisions to these GVA estimates.

In the previous Annual GVA release we updated the deflators we use in producing volume estimates to be implied deflators, calculated from GVA reported in the SUT and GDP low-level aggregates. These replaced the (formerly experimental) domestic output industry deflators used in earlier releases. The revisions report included in the previous Annual GVA release discussed the impact of this methodology update on GVA estimates. In this release the updated deflator methodology has also been applied to Annual GVA estimates for 2010 to 2019 and to Regional GVA estimates, bringing it in line with Annual GVA estimates. Similar revisions to those described in the previous Annual GVA revisions report can therefore be expected for Regional GVA estimates in this release.

Due to the methodological changes described here, estimates in this release should not be compared with estimates provided in previous releases.

Annual GVA revisions

Annual GVA estimates in this release have been affected by revisions to ONS National Accounts data and ABS data, which has caused a large change in GVA values compared to the previous release. As noted in the main report, this has caused large changes to headline figures from the previous release. ONS suggest that ‘new and revised annual survey and administrative data’ and ‘other method and data improvements’ had a particularly large influence on the size of revisions to National Accounts data in recent years.

Overall, Digital Sector current price GVA for 2023 has been revised up by 9.8% since the previous release. Below are tables showing the amount of change in reported current price GVA for each sector due to revisions to National Accounts data (Table 3) and revisions to ABS data (Table 4).

Table 3: Percentage change from Economic Estimates: Digital Sector Annual Gross Value Added (2019 to 2023) due to National Accounts revisions where positive values have been revised upwards

Year	2019	2020	2021	2022	2023
All industries	1.0	1.1	1.9	2.5	5.0
Computer programming, consultancy and related activities	-0.3	-0.5	0.2	2.0	12.8
Digital Sector	1.7	1.6	1.8	3.9	9.3
Film, TV, video, radio and music	4.5	5.6	7.2	3.8	7.5
Information service activities	1.1	1.5	6.4	8.5	16.9
Manufacturing of electronics and computers	10.6	5.3	-1.6	6.4	11.5
Publishing (excluding translation and interpretation activities)	4.6	4.1	4.9	2.9	6.8
Repair of computers and communication equipment	4.0	6.6	2.1	6.8	5.5
Software publishing	4.7	4.1	4.9	2.8	6.7
Telecommunications	0.3	0.5	-0.7	4.4	2.5
Wholesale of computers and electronics	3.2	3.5	3.0	12.5	10.7

Note that ABS revisions only affect years 2022 and 2023. This includes the change in 2023 figures due to 2023 ABS data becoming available and replacing the use of 2022 ABS data to apportion 2023 GVA data.

Table 4: Percentage change from Economic Estimates: Digital Sector Annual Gross Value Added (2019 to 2023) due to Annual Business Survey revisions where positive values have been revised upwards

Year	2019	2020	2021	2022	2023
All industries	0.0	0.0	0.0	0.0	0.0
Computer programming, consultancy and related activities	0.0	0.0	0.0	0.0	0.0
Digital Sector	0.0	0.0	0.0	0.3	0.5
Film, TV, video, radio and music	0.0	0.0	0.0	0.0	0.0
Information service activities	0.0	0.0	0.0	0.0	0.0
Manufacturing of electronics and computers	0.0	0.0	0.0	0.7	-3.3
Publishing (excluding translation and interpretation activities)	0.0	0.0	0.0	4.3	-4.2
Repair of computers and communication equipment	0.0	0.0	0.0	0.6	3.9
Software publishing	0.0	0.0	0.0	-16.8	16.5
Telecommunications	0.0	0.0	0.0	0.0	0.0
Wholesale of computers and electronics	0.0	0.0	0.0	5.6	13.3

4.4 Summary of data sources

In summary, the data presented in this report on annual and regional GVA are based on:

• Official Statistics data sources.
• Internationally harmonised codes and geographies.
• Survey data (Annual Business Survey and Regional Accounts) and, as with all data from surveys, there will be an associated error margin surrounding these estimates.

This means the estimates are both comparable:

• At a national and international level.
• Over time, allowing trends to be measured and monitored.

However, this also means 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 are expected to be revised later this year. Emerging sectors, such as artificial intelligence and cyber security, are therefore hard to capture and may be excluded or mis-coded.

5. Quality assurance processes

5.1 Quality assurance processes at ONS

Quality assurance at ONS takes place at a number of stages. The validation and accuracy of the source data, as well as the various processes in place to ensure quality for the data sources used in the annual and regional GVA publication, are outlined in the relevant links below.

National balanced GVA tables

Section 6 (‘Important quality issues’) and Section 7 (‘The quality of Blue Book estimates’) of the Blue Book 2025 background notes detail some of the quality issues associated with National Accounts, whilst Section 10 (‘Code of Practice’) outlines that quality assurance reviews are performed in line with the Code of Practice for Statistics.

Regional balanced GVA tables

Section 6 of the Regional gross value added (balanced) Quality and Methodology Information (QMI) details how the ONS collects the data for the regional balanced GVA tables, the main data sources, and the validation and accuracy of the estimates.

Annual Business Survey (ABS)

For more information on quality assurance processes used during the production and analysis of ABS, as well as validation and accuracy of the estimates, see the Annual Business Survey QMI and the Annual Business Survey technical report.

5.2 Quality assurance processes at DSIT

The majority of quality assurance of the data underpinning the release takes place at ONS. Further quality assurance checks are carried out within DSIT. These include checking:

• Growth rates are comparable to previous publications, and if not, that the differences are justified and explainable.
• The proportion of the Digital Sector accounted for by each subsector are comparable to previous publications.
• Current prices and CVM GVA data matches the National Accounts at a 2-digit level, where comparable, and for UK totals.

6. 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.