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GVA for the UK in current basic prices grew by 3.6% between 2016 and 2017; the highest annual nominal growth of NUTS1 areas was in London at 4.2% and the lowest annual growth was in the North East at 1.4%. Estimates of regional gross value added (GVA), which is the value generated by any unit engaged in the production of goods and services.
- Regional Gva(I) by Local Authority in The UK
These tables show gross value added (calculated using the...
- Balanced
Annual estimates of balanced UK regional gross value added...
- All Data Related to Gross Value Added
Keywords: productivity, UK cities, NUTS, GVA, local...
- Regional GVA Nuts3
10 August 2017. As part of our development of a balanced...
- Publications
Keywords: productivity, UK cities, NUTS, GVA, local...
- All Data
Dataset | Released on 24 April 2024. Annual estimates of...
- The industrial analyses
The industrial analysis. Analysis of the 10 broad industrial...
- Regional Gva(I) by Local Authority in The UK
Dataset | Released on 24 April 2024. Annual estimates of balanced UK regional gross value added (GVA (B)). Current price estimates, chained volume measures and implied deflators for combined authorities, city regions, local enterprise partnerships and other economic and enterprise regions, with a detailed industry breakdown.
5 days ago · The drop in sport sector GVA from 2019 to 2020, during the pandemic, and growth prior to and following the pandemic, were driven by changes to GVA in London, which due to the size of its economy ...
Oct 29, 2021 · The industrial analysis. Analysis of the 10 broad industrial groups shows that in 2019, the government, health and education industries provided the largest contribution to gross value added (GVA) at current basic prices. These industries contributed 18.3% to the total GVA of £2,017 billion, with a value of £370 billion.
- 1. Overview of release
- 2. Sector definitions
- 3. Methodology
- 4. Quality assurance processes
- 5. External Data Sources
- 6. Further information
The statistics release ‘DCMS Sectors Economic Estimates: Gross Value Added 2022 (provisional)’ reports gross value added (GVA) for DCMS 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.
2.1 Overview of DCMS Sectors
2.1.1 Main sector definitions The sectors for which DCMS has responsibility are: civil society creative industries cultural sector gambling sport tourism In order to measure the size of the economy it is important to be able to define it. DCMS uses a range of definitions based on internal or UK agreed definitions. All 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. The development of individual sector definitions in isolation as new sectors have fallen within the department’s remit has meant that there is overlap between DCMS sectors. For example, the cultural sector is defined using SIC codes that are nearly all within the creative industries. 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 employment 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. Figure 1 below visually shows the overlap between DCMS sectors in terms of SIC codes. Users should note that this does not give an indication of the magnitude of the value of overlap. For this, users should consult the main report. A list of SIC codes appearing in each sector and subsector can be found in the tables accompanying the release. Figure 1: Overlap of SIC codes within DCMS Sectors 2.1.2 Other sector definitions Additional analysis is presented in the 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 (creative industries) in the main estimates.
2.2 Details and limitations of sector definitions
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 DCMS sectors, and therefore best fit SIC codes have been used to produce these estimates. The following section describes limitations for specific DCMS sector definitions. 2.2.1 Civil society In July 2016, DCMS took on responsibility for the Office for Civil Society, which covers charities, voluntary organisations or trusts, social enterprises, mutuals and community interest companies. The civil society sector is not like a traditional industry and therefore data is not readily available in the usual data sources. Where possible, data is provided from official sources. Civil society sector GVA expressed in current prices is based on NPISH (Non-profit institutions serving households) data. Non-profit institutions serving households are institutions that provide goods and services either for free or below the market prices, mainly derive their income from grants and donations, and are not controlled by the government. NPISH includes non-market charities, universities, trade unions and political parties. Of these, DCMS only covers the charity sector. NPISH does not include market provider charities who have passed the market test and therefore sit in the corporate sector (these data are not currently measured by ONS on a National Accounts basis), mutuals, social enterprises or community interest companies. It is therefore recognised that the published estimates are likely to be an underestimate for the civil society sector. Note that volunteering, a key element of civil society, has not been included in the figures due to being part of the informal economy. As estimated in the ONS published Household Satellite Account, volunteering contributed £24bn in 2016 (this includes only formal volunteering activities). 2.2.2 Creative industries The creative industries were defined in the Government’s 2001 creative industries Mapping Document as “those industries which have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property”. The definition used for the creative industries in this release does not allow consideration of the value added of “creative” to the wider economy, such as Creative Occupations outside the creative industries. DCMS policy responsibility is for creative industries across the economy and therefore this is a significant weakness in the current approach. 2.2.3 Cultural sector There are significant limitations to the DCMS measurement of the cultural sector arising from the lack of detailed disaggregation possible using the standard industrial classifications. There are many cases where Culture forms a small part of an industry classification and therefore cannot be separately identified and assigned as culture using standard data sources. DCMS consulted on the definition of Culture and published a response in April 2017. It is recognised that, due to the limitations associated with SIC codes, the SIC code used in past publications as a proxy for the Heritage sector (91.03 - Operation of historical sites and building and similar visitor attractions) is likely to be an underestimate of this sector’s value. We have changed the name of the Heritage sector to ‘Operation for historical sites and similar visitor attractions’ to reflect this. 2.2.5 Sport For the purpose of this publication, the statistical definition of sport has been used based on the Vilnius definition. This incorporates only those 4-digit Standard Industrial Classification (SIC) codes which are predominantly sport (see the definitions in Table 1a in the published data tables). DCMS has previously published GVA estimates based on the broad Vilnius definition as part of the DCMS sport Satellite Account. This is a more wide-ranging measure of sport which considers the contribution of sport across a range of industries, for example sport advertising, and sport-related construction. However, estimates based on this method are only available up to 2016, and the method has not been used in these estimates. 2.2.6 Tourism For Tourism, a satellite account approach is used, where the element of each industry that is directly supported by tourism is identified by calculating the proportion of consumers that are tourists for each industry.
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 DCMS 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 Latest Tourism Satellite Account (published 18 January 2024 by the ONS Tourism Intelligence Unit) Latest balanced GVA for the non-market charities element of NPISH (Non-profit institutions serving households). 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 DCMS 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 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 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 and 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 DCMS 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 DCMS sector GVA. 3.1.4 Method for SIC 91: Libraries, archives, museums and other cultural activities A different approach is used to break down the SUT matrix to 4 digit level for SIC 91. In the ABS data, the aGVA for aspects of SIC 91 can be negative (most likely due to under coverage in the ABS). For this reason, sales data from the ABS is used instead of aGVA to allocate SIC 91 at the 4-digit level. This is the only SIC where this approach has been used. 3.1.5 Method for Tourism (current prices) The Tourism GVA figures were produced separately by the ONS as part of the Tourism Satellite Account (TSA), based on the methodology and definition set out in the UN International Recommendations for Tourism Statistics 2008 (IRTS 2008). These estimates are also produced to be consistent with National Accounts. Further information on the TSA can be found on the ONS Tourism Satellite Account methodology page. For the 2021 TSA, the availability and quality of source data used to produce the TSA was impacted due to the continuing impact of the COVID-19 pandemic.. Further information can be found in the table background notes of the latest publication. Given the unusual pattern of tourism in 2021 the Nowcast table (2022) published in previous UK-TSA reports is not available this year - as the Nowcast table is heavily based on the previous years trends and the trends seen in 2021 were deemed too exceptional. This means that data for 2022 is not currently available for the tourism sector. 3.1.6 Method for civil society (current prices) The civil society GVA figures are based on NPISH (Non-profit institutions serving households) data. NPISH includes non-market charities, universities, trade unions and political parties. Of these, DCMS only covers the charity sector. As balanced industry data are not available split by source, we have assumed that the balancing adjustment and other inputs used during processing of data, are applied in proportion to the underlying source data. 3.1.7 Accounting for sector overlap As mentioned in the sector definitions chapter, there is an overlap between DCMS sector definitions. This overlap must be estimated in order to avoid double counting and produce a robust estimate for all DCMS sectors. In most cases, the overlap is estimated by looking at which SIC codes appear in multiple sectors. All unique SICs can then be aggregated to give a total figure with no overlap. For Tourism a slightly different approach is required, due to the methodology used to calculate GVA for this sector. The first stage is to identify SIC codes which are part of tourism and appear in other DCMS sectors (90, 91.02, 91.03, 91.04, 77.21, 92, 93.11 and 93.19). As the tourism estimates are not categorised at the class level (4 digit SIC code), an estimate has to be made for the part of tourism which is in each of the SIC codes. This is done using the tourism ratios for the different SIC codes, calculated in the Tourism Satellite Account (TSA) and published in the TDGVA table of the TSA. The total overlap for Tourism is the sum of the GVA for the Tourism component of these SIC codes. The total overlap was deducted from the DCMS sector total to avoid double counting. For civil society, it is not possible to identify the overlap between NPISH sectors and DCMS sectors due to the way the data are processed, unless there is an exact 1:1 match. For example, NPISH data are provided for SICs 68.1 and 68.2 and cannot be separated, but only SIC 68.2 is a DCMS industry. Therefore a slight overlap will be included in the ‘All DCMS Sector’ value. It is estimated that the overlap is a maximum of 0.1% of total UK GVA in 2021. However, given that the estimates for civil society as a whole are an underestimate for the sector (see the sector definitions chapter), the ‘All DCMS Sector’ value is not an overestimate even when compensating for this small overlap.
3.2 GVA - chained volume measure
This second section presents the methodology for estimates of gross value added (GVA) for DCMS 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 DCMS 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 DCMS remit. The exception to this is tourism, which is included as a single aggregated industry. An estimate for the civil society sector expressed in chained volume measures is not currently available. 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 of the SIC codes in DCMS sectors, 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 in DCMS sectors, 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 DCMS Sector total. 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 2022 for each sector and subsector, and the DCMS Sector total. 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. This caveat does not affect summing of sector values to form the All DCMS total, as the All DCMS total is lower than the sum of the individual sectors due to overlap between sectors. 3.2.3 Method for Tourism (chained volume measure) Due to revisions in IPS methodology, current price data for Tourism from 2010 to 2015 is not available. A time series from 2016 to 2021 for the Tourism aggregate was produced. Since Tourism is treated as a single aggregated industry, a single Tourism deflator is required. For each industry within the Tourism aggregate, deflators are collected in the same way as before (i.e. using the experimental deflators). The deflators are then weighted together to form a single deflator. The Tourism industries are omitted from the current price data at an industry level so current price data cannot be used for the weights. Instead ABS data is used for weighting. The weight for each industry, for each year, is the aGVA of the industry as a proportion of Tourism total aGVA, sourced from ABS. Then the deflator (or price index) for each industry is given by weighted deflatort = weightt x pricet The weighted deflator series for each industry is then summed to give a single deflator series for all the tourism industries. The PYP, CYP, scaling factors and CVM series are then calculated for the Tourism sector as described above in 3.2.2 Method (chained volume measure). The same method is also used to calculate a Tourism non-overlap CVM series, which is used to calculate the All DCMS total. To calculate the Tourism non-overlap CVM series, the Tourism non-overlap current prices figure is used (see 3.1.7 Accounting for overlap) and the weighted deflators are based on SICs that are only part of tourism and not in other DCMS sectors. 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 DCMS 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/DCMS 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.
This chapter summarises the quality assurance processes applied during the production of the DCMS Economic Estimates 2022: Gross Value Added 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 ...
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 DCMS constructing sector classifications from Standard Industrial Classification (SIC) codes. However, DCMS accepts that there are limitations with this approach and alternative definitions can be useful where a policy-relevant grouping of businesses crosses existing Standard Industrial Classification (SIC) codes. DCMS is aware of other estimates of DCMS Sectors. These estimates use various methods and data sources, and can be useful for serving several purposes, e.g. monitoring progress under specific policy themes such as community health or the environment, or measuring activities subsumed across a range of SICs.
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
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Jun 11, 2023 · Summary. Gross Value Added measures the value generated in the production of goods and services. It is one measure of overall economic performance. This dataset shows Gross Value Added at current basic prices (which include the effects of inflation), in Pounds (£). The measure shown is Balanced GVA, that is GVA (B).
