Accredited official statistics

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

Updated 1 September 2023

1. Overview of release

The statistics release ‘Digital Sector Economic Estimates: Regional GVA 2020’ provides an estimate of the contribution of the digital sector to each region in the UK, measured by GVA (gross value added). 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 (GDP):

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 Code of Practice for Statistics

In June 2019, the DCMS Sector Economic Estimates: Regional GVA were badged as National Statistics. This affirms that the statistics have met the requirements of the Code of Practice for Statistics.

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.

1.2 Users

The users of these statistics fall into five broad categories:

• Ministers and other political figures
• Policy and other professionals in DCMS/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 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. 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 Overview of reported sectors

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

Other sector definitions

Additional analysis is presented in the regional GVA release for the audio visual sector and the computer games 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

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 definition

This section looks at sector definitions in more detail, and provides an overview of limitations. 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. The SIC codes used to produce these estimates are a ‘best fit’, subject to the limitations described in the following section.

Digital sector

The definition of the digital sector used by DCMS is based on the OECD definition of the ‘information society’. This is a combination of the OECD definition for the “ICT sector” as well as including the definition of the “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 2011 (see Box 7.A1.2 on page 159 and Box 7.A1.3 on page 164).

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. DSIT policy responsibility is for digital across the economy and therefore this is a significant weakness in the current approach.

Telecoms

The definition of the telecoms sector is consistent with the internationally agreed definition, SIC 61, Telecommunications. Please note that as well as appearing as a sector on its own, telecoms is also entirely included within the digital sector as one of the sub-sectors.

1. Methodology

This chapter summarises the methodology used to produce regional GVA estimates, both in current prices and chained volume measures.

3.1 GVA - current prices

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

Data sources (current prices)

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

• ONS Regional Gross Value Added balanced tables (published 25 April 2023) – containing data up to 2021.
• Unsuppressed Annual Business Survey (ABS) approximate GVA estimates at the lowest level available

Method (current prices)

The most reliable estimate of regional GVA comes from the Regional gross value added (balanced) tables produced annually by ONS. These estimates are consistent with the UK National Accounts. 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.

The balanced GVA tables report GVA at division level (2 digit SIC codes), but the digital sector is defined at industry level (3 or 4 digit SIC codes). This means a method for breaking down the GVA to industry level must be applied.

This is achieved by using approximate Gross Value Added (aGVA) regional 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) for each region
• calculating aGVA from the ABS at division level (e.g. SIC 32, by aggregating industries in the division) for each region
• 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) for each region
• applying the proportion for each industry to the division GVA in the balanced regional GVA tables, to get a National Accounts consistent estimate of regional GVA for each industry.

This method, using the National Accounts consistent GVA, is preferable to only using aGVA from the ABS. There are differences between the two measures of gross value added in 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 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’.

Regional GVA figures for 2010 to 2019 have been revised since the last DCMS Economic Estimates: Regional GVA publication in August 2021. These revisions take into account the latest balancing of the National Accounts and finalisation of the Annual Business Survey data. Regional Accounts GVA is open to revisions back to 1997 each year. These are planned revisions and an integral part of the balancing process.

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 sector. 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 Digital sector GVA.

Constraining sector and subsector totals

We use different versions of ABS data in our national and regional GVA publications. The national GVA publication, usually published in December (most recently in April 2023), uses provisional ABS data for the latest year. The regional GVA publication, usually published in Spring/Summer, uses revised ABS results for the latest year. This means that the sum of regional GVA for each sector would not usually match the national GVA totals published in December. We therefore constrain the current price regional GVA figures for each sector to the national totals published in December.

There are minimal differences when the individual regional data for a sector is summed together compared to the UK total for that sector. This is because the UK totals presented are constrained to the totals that we published in the annual GVA release for total GVA for each sector.

3.2 GVA - chained volume measure

This second section presents the methodology for estimates of regional gross value added (GVA) for the digital sector, expressed in chained volume measures (i.e. taking into account inflation).

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). 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.

Data sources

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

• Current prices data (see previous chapter, GVA - current prices, for data sources and methodology).
• Experimental national industry level deflators

Method (chained volume measure)

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

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, published on the ONS website (Industry Level Deflators).

These are the same deflators used to produce national chained volume measure estimates of Digital sector GVA. National deflators are used because no regional price indices are currently available. The Eurostat Manual on regional accounts methods (PDF, 1.26MB) recommends that in the absence of regional prices, the use of national deflators is acceptable. The availability of a greater level of industrial detail allows the deflation to take account of regional variation in industrial composition and hence the composition of products and services produced in each region.

The industry deflators used in this release are a mixture of product and implied industry (division) level deflators. These are not consistent with the deflators used in the national accounts, or the implied regional deflators published alongside the regional accounts. The industry deflators used to derive chained volume measures in this release are consistent with the deflators used in the national DCMS and digital sector GVA releases. These deflators are preferred due to maintaining a closer relationship between current price and chained volume measures.

Experimental industry level deflators are not available for all of the SIC codes in the digital sector, therefore deflators are used which match as closely as possible to each industry. All were in the form of a price index with 2019 = 100.

For each 3 or 4 digit SIC code in the digital sector, 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 DCMS sector and subsector, and the Digital sector total, for each UK region.

These are 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 for each region 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 digital sector values prior to 2019.

Constraining sector totals

Similarly to the current price estimates, we constrain the regional CVM series to the national CVM series used in the national GVA release in April.

3.3 Summary of data sources

In summary, the data presented in this report on regional 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.

4. Validation, accuracy, and quality assurance processes

This chapter summarises the validation, accuracy and quality assurance processes applied during the production of the Digital Sector Economic Estimates: Regional GVA 2020 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.

4.1 Validation, accuracy and 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 regional GVA publication, are outlined in the relevant links below.

Regional balanced GVA tables

Section 6 of the Regional gross value added QMI details how 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: August 2018.

4.2 Quality assurance processes at DCMS

The majority of quality assurance of the data underpinning the Digital Sector Economic Estimates: Regional GVA 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.

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 regional 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

Data Analysis quality assurance checks

At the analysis stage, data are aggregated to produce information about the Digital sector 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 Regional Accounts data has been used, including the revised back series data
• the correct SIC codes have been aggregated together to form digital sector and sub-sector estimates

Publication quality assurance checks

Finalised figures are disseminated within OpenDocument Format tables and a written headline report, 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
• contacting press office to ensure they are aware of the release date
• checking the published GOV.UK page again after publishing

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
• what feedback have we received from engaging with users

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
• ideally applicable to specific policy interventions

These are the main reasons for 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 of the digital sector. 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.

Table 1 shows a different source of analysis measuring the economic contribution of computer games from one of our arm’s-length bodies. It is recognised that there will be many other sources of evidence from industry bodies, for example, which have not been included in this table. This will be developed over time to capture a wider spectrum of stakeholder’s releases. We encourage statistics producers within the digital sector who are not represented in the table to contact the economic estimates team at evidence@dcms.gov.uk.

Table 1. Alternative data source measuring economic contribution of Computer Games

Sector	Sub-sector	Organisation	Summary of use
Computer Games	Computer Games	UKIE and NESTA	UKIE has a website dedicated to statistics and other useful information about the UK games industry. This includes statistics on GVA (national and regional), employment, exports and imports, number of businesses, and investment, which are based on their latest official publications. In partnership with UKIE, NESTA has produced national and regional estimates of the economic contribution of the computer games industry, including number of businesses and GVA. This is based on a ‘big data’ modelling approach where researchers identified games companies through their digital footprint, rather than using official industrial (SIC) codes or surveys. The latest estimate is for 2014, so is more outdated than DCMS estimates.

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

DCMS statisticians can be followed on Twitter via @DCMSInsight.

The Economic Estimates of DCMS Sectors release is an Official Statistics publication and has been produced to the standards set out in the Code of Practice for Statistics. For more information, see https://www.statisticsauthority.gov.uk/code-of-practice/.

1. Sampling error is the error caused by observing a sample (as in a survey) instead of the whole population (as in a census). While each sample is designed to produce the “best” estimate of the true population value, a number of equal-sized samples covering the population would generally produce varying population estimates. This means we cannot say an estimate of, for example, 20% is very accurate for the whole population. Our best estimates, from the survey sample, suggest that the figure is 20%, but due to the degree of error, the true population figure could perhaps be 18% or 22%. This is not an issue with the quality of the data or analysis; rather it is an inherent principle when using survey data to inform estimates. ↩