Heritage sector economic estimates methodology

Question 1

1. Executive summary

Accepted Answer

1.1 Scope

This study develops and tests a bespoke methodology for estimating the economic contribution of the UK’s heritage sector, with the aim of creating a reliable approach that could be used to produce official statistics for the sector, in line with Department for Culture, Media & Sport’s (DCMS) Sector Economic Estimates. Following completion of the study, DCMS will review the proposed methodology and determine whether it should be adopted as part of routine practice. The heritage sector’s economic impact has historically been difficult to quantify due to its diverse nature and inconsistent classification within the Office for National Statistics’ (ONS) Standard Industrial Classification (SIC) system. The current proxy estimate of the heritage sector produced by DCMS, relies on a single SIC code (91.03 – Operation of historical sites and buildings), widely seen as significantly underestimating the sector’s true contribution.

To address this, earlier research - particularly studies commissioned by Historic England - led to the development of a methodology combining industrial and occupational (per the ONS’s Standard Occupational Classification System, or SOC) data. This was implemented to more accurately capture the sector’s scope, and is referred to as a SIC-SOC methodology. Building on these efforts, DCMS commissioned Alma Economics to assess viable approaches for measuring the economic impact of the tangible heritage sector.^{[footnote 1]} Their feasibility study confirmed the SIC-SOC approach as the most robust available.

The present study enhances this methodology to provide a consistent, reliable estimate of the heritage sector’s direct economic impact, aligned with DCMS Sector Economic Estimates and the UK’s National Accounting Framework.

1.2 Methodology overview

The SIC-SOC methodology ensures a comprehensive representation of the sector by:

selecting relevant SIC and SOC codes for heritage activities
using employment (number of filled jobs) data from the Annual Population Survey (APS) to create a matrix mapping first and second jobs across SIC and SOC classifications
avoiding double counting by ensuring heritage employment is mapped to SIC codes, rather than summing employment across heritage SIC and SOC codes
distinguishing between core heritage SIC codes (industries themselves are defined as being part of the heritage sector) and secondary heritage SIC codes (only jobs in heritage-related occupations are included)

By integrating both SIC and SOC classifications, this methodology provides a more inclusive representation of the heritage sector’s economic contribution compared to traditional SIC-based approaches. Furthermore, mapping occupational employment data to SICs allows for Gross Value Added (GVA) estimates to be produced consistently with other DCMS sector estimates.

GVA estimates are derived by apportioning industry-level GVA data from the National Accounts by the share of employment which is heritage-related in each industry, as discussed further below.

This study builds on the list of SIC codes identified in the Historic England research, which offers the most comprehensive available starting point. These industries form the baseline for analysis and are presented in Table 1 below.

In the Historic England research, for some SIC codes (and as discussed later, SOC codes), only a share of activity is considered heritage related. This can be seen in Table 1, with only 31% of SICs 43.3 and 43.9 included as heritage SIC codes. For these (and other SOC codes for which only a share is included), further calculations are conducted to estimate the appropriate proportion to include, with the rationale and approach for these calculations discussed further, later in the report.

Table 1: The SIC codes and proportions thereof included in research for Historic England

SIC codes	Code description	Proportion included
43.3	Building completion and finishing	31.0%
43.9	Other specialised construction activity	31.0%
91.012	Archive activities	100.0%
91.020	Museum activities	100.0%
91.030	Historical sites and buildings	100.0%

Source: Cebr for Historic England

Recognising that the Historic England definition of the heritage sector remained largely unchanged since 2018, this study re-evaluates SIC classifications using 3 approaches:

1. Analysis of National Lottery Heritage Fund (NLHF) grant data: Grants were compared to turnover to determine if SIC codes should be included in the heritage sector. Ultimately, this approach validated the inclusion of the non-construction SIC codes with highest grants to funding ratio, but did not provide sufficient evidence to warrant the inclusion of additional SIC codes.

2. Review of new research: Notably, the 2024 Historic England Skills Needs Analysis reinforced the importance of heritage construction within the sector and offered updated estimates of the proportion of construction-related SICs attributable to heritage activity.

3. Examination of ‘supported SIC codes’: Drawing on the ESPON methodology for capturing heritage in the EU, this approach identified industries with strong supply chain links to the heritage sector.^{[footnote 2]} While informative, these supported SICs were excluded from the final estimates to ensure consistency with DCMS’s approach to sectoral economic reporting.

The result of these refinement exercises is the final list of SIC codes included in this report. These SIC codes and the proportion of them included as part of the heritage sector are displayed in Table 2.

Table 2: The list of SIC codes and proportion thereof included in this research

SIC codes	Code description	% SIC code included
43.3	Building completion and finishing	24.8%
43.9	Other specialised construction activity	24.8%
91.012	Archive activities	100.0%
91.020	Museums activities	100.0%
91.030	Operation of historical sites and buildings	100.0%

Source: Historic England, ONS data, Cebr analysis

Overall, the approach to refinement validated the prior SIC codes being included within the definition, but did not present sufficient evidence to extend upon this. A notable change is however, that the share of SICs 43.3 and 43.9 included was revised slightly downwards. Adjustments were driven by the combined effects of the explicit inclusion of second jobs within the scope of this research, and updated evidence from Historic England’s Skills Needs Analysis, related to the share of employment within the assessed SICs that was attributable to heritage.

The starting point of this research is the list of SOC codes included in the Historic England research. The list of occupations included in the Historic England report are displayed in Table 3.

Table 3: List of SOC codes deemed part of heritage sector in research for Historic England

SOC 2010 codes	Code description	Proportion Included
2115	Social and humanities scientists^{[footnote 3]}	21.7%
2141	Conservation professionals	100.0%
2431	Architects	20.5%
2432	Town planning officers	20.5%
2434	Chartered surveyors	20.5%
2452	Archivist and curators	100.0%
3114	Building / civil engineers	20.5%
3550	Conservation and environmental associate professionals	100.0%
5113	Gardeners/ landscape gardeners	1.9%

Source: Cebr for Historic England

Recognising that the Historic England definition of the heritage sector had remained largely unchanged since 2018, as with SIC codes, this study similarly reevaluates SOC classifications using 2 primary approaches:

1. Conversion of SOC 2010 to SOC 2020 classifications: All SOC 2010 codes were mapped onto SOC 2020 equivalents to reflect updated occupational classifications. Seven out of the 9 SOC codes included in the Historic England report were validated by this approach.

2. Review of new evidence on heritage occupations, including:

analysis of heritage job boards and university career guidance materials
examination of broader literature, such as Historic England’s Conservation Basics report (2013). This resulted in the addition of SOC code not previously considered: SOC 2453 Quantity Surveyors
review of heritage academia employment data using Higher Education Statistics Agency (HESA) and Russell Group university data

These refinement exercises informed the finalised list of SOC codes used in this study. The updated list, along with the proportion of each occupation attributed to the heritage sector, is provided in Table 4.

Table 4: SOC codes included and their heritage proportions

SOC 2020 code	Proportion included
2115: Social and humanities scientists^{[footnote 4]}	16.9%
2151: Conservation professionals	100.0%
2451: Architects	20.5%
2453: Quantity Surveyors	20.5%
2454: Chartered Surveyors	20.5%
2472: Archivists and curators	100.0%
3114: Building and civil engineering technicians	20.5%
5113: Gardeners and landscape gardeners	17.4%^{[footnote 5]}

1.3 Economic impact calculations and results

The economic contribution of the heritage sector was estimated in alignment with the DCMS Sector Economic Estimates methodology, as closely as possible, ensuring consistency and comparability with official statistics.

Employment estimation

Heritage employment is measured as the number of filled jobs (both first and second jobs) and calculated using SIC-SOC matrices derived from the ONS’s Annual Population Survey (APS) microdata. Weighted variables were applied to ensure nationally representative estimates. Subsequently, the proportion of employment within each SIC attributable to heritage was calculated, enabling detailed analysis at the 4- and 5-digit SIC level. Regional estimates were also derived using APS variables.

Gross Value Added (GVA)

GVA was estimated using DCMS’s standard multi-step approach, which incorporates the ONS’s Annual Business Survey data (ABS), National Accounts, and Balanced Regional GVA data. Due to the heritage sector’s span across both SIC and SOC codes, additional steps were required to apportion GVA for partially heritage SICs based on heritage employment proportions.

Where negative approximate GVA (aGVA) values were reported in the ABS, due to high public subsidies or data limitations stemming from a lack of survey responses, turnover data were used as a proxy, as currently done by DCMS for SIC 91 (encompassing libraries, archives, museums and other cultural activities). For SICs not covered by the ABS, GVA was apportioned using heritage employment shares within each two-digit SIC division.

The results of this research may overlap with other DCMS Sector Economic Estimates, as heritage occupations can appear in any SIC. However, data are provided at the four- or five-digit SIC level, allowing straightforward removal of any double-counting. This enables users to adjust totals by excluding SICs already attributed to other DCMS sectors, ensuring consistency across estimates.

In addition, GVA and employment estimates from this research are not directly comparable with those from the Historic England methodology. Differences are due to varying geographic coverage (UK vs. England), project scope (direct vs. aggregate impacts), and how the heritage sector is defined. Neither approach will consistently produce higher or lower direct estimates than the other.

Consideration of wage-based adjustments

An alternative approach using wage data was explored when calculating heritage GVA, to account for potential differences in productivity between heritage and non-heritage employees within a particular SIC. However, limited sample sizes - especially for heritage SOCs - hindered robust conclusions at the SIC-SOC level.

Overall, while some limitations persist, particularly in data granularity and coverage, the methodology ensures a rigorous and representative estimation of the heritage sector’s economic footprint.

Results

The methodology was applied to the years 2011-2022. GVA results for 2022, presented in Table 5 below, show that the sector contributed £15.2 billion to the economy. A combined 48% of this GVA was contributed by two SICs: 43.3, Building Completion and Finishing, and 43.9, Other Specialised Construction Activities. Overall, core heritage SICs, including the aforementioned two, contributed 58.8% of heritage GVA in 2022, with the remaining 41.2% contributed by secondary heritage SICs.

Table 5: Heritage GVA by industry (£m), 2022

Type	SIC	GVA contribution, £m	% of total GVA
Core Heritage Industries	43.3 Building completion and finishing	4,390	28.9%
	43.9 Other specialised construction activities	2,892	19.1%
	91.02 Museum activities	868	5.7%
	91.03 Operation of historical sites and buildings	695	4.6%
	91.012 Archive activities	74	0.5%
	Total Core heritage industries	8,918	58.8%
Secondary Heritage Industries		6,256	41.2%
Total		15,174	100%

Source: ONS data, Cebr analysis

Figure 1 presents chained volume measures (inflation-adjusted estimates) of UK heritage sector GVA between 2011 and 2022. A general upwards trend is apparent between 2011 and 2016, followed by a period of no growth from 2016 to 2018. Around the pandemic, heritage GVA declined moderately to £12.5bn (at 2022 price levels), but by 2022 had recovered well beyond pre-pandemic levels and indeed beyond the prior peak between 2016 and 2018, to £15.2bn.

Figure 1: Heritage Sector GVA (£bn at 2022 price levels), CVM, 2011–2022/Source: ONS data, Cebr analysis

Similarly to GVA, employment estimates were produced for every year between 2011 and 2022. A breakdown of employment by SIC code is presented in Table 6. From this table, we see that total employment in the heritage sector in 2022 was 297,000 with the heritage construction industry making up 43% of this employment. Overall, core heritage SICs, including the aforementioned two, contributed 64.2% of heritage employment in 2022, with the remaining 35.8% contributed by secondary heritage SICs.

Table 6: Distribution of heritage employment across SIC codes (000s) in 2022

Type	SIC	Number of heritage filled jobs (000s)	% of total employment
Core Heritage Industries	43.3 Building completion and finishing	91	30.6%
	91.02 Museum activities	43	14.6%
	43.9 Other specialised construction activities	37	12.5%
	91.03 Operation of historical sites and buildings	10	3.5%
	91.012 Archive activities	9	2.9%
	Total Core heritage industries	191	64.2%
Secondary Heritage Industries		106	35.8%
Total		297	100%

Source: ONS data, Cebr analysis

Figure 2 presents heritage employment levels in the UK between 2011 and 2022. A generally steady trend is apparent with strong growth in the early 2010’s followed by a sharp fall during the COVID-19 period, then strong growth of 9.0% in 2022. By 2022, heritage employment was still slightly below pre-pandemic levels.

Figure 2: Heritage employment in the UK (000's) between 2011 and 2022/Source: ONS data, Cebr analysis

1.4 Business demography and trade

A secondary objective of this study was to assess the feasibility of producing trade and business demography statistics for the heritage sector, using the SIC-SOC methodology. While DCMS typically includes trade and business data in its sectoral economic estimates, such outputs are not currently available for the heritage sector either within this report, or prior research for Historic England, due to methodological limitations. SIC-SOC mapping is well-suited for estimating GVA and employment but is not directly applicable to trade and business statistics, creating potential issues in the generation of consistent statistics across DCMS Sectors.

The study explored whether trade and business data could be estimated by linking SIC-based statistics to the share of employment or GVA identified as heritage-related. While this is feasible for wholly heritage SIC codes (e.g. museums, archives), it is less reliable for partially heritage SICs. Assumptions about trade or business activity based on employment shares may not hold - for example, heritage construction cannot be exported, unlike general construction services.

For trade, 2 potential approaches were considered: a resource-intensive survey-based method to estimate import/export propensities across heritage occupations, and a simplified method based on thresholds for including full SIC codes in the heritage definition. Both have limitations, but the latter may offer a pragmatic solution aligned with precedent in other DCMS sectors.

Similar challenges apply to business demography, particularly for identifying the number and size of businesses undertaking heritage-related work within partially heritage SIC codes. There are further conceptual challenges associated with classifying organisations as heritage or non-heritage in a binary manner, for organisations who undertake some heritage and some non-heritage work. Here, a simplified approach - classifying SICs as heritage if their principal activity is heritage-related - could offer a practical interim solution. Further research and consultation would be required to refine this approach.

1.5 Limitations of this research

This research has produced and tested a new methodology for measuring the scale of the heritage sector. Due to the experimental nature of the methodology developed, there are analytical limitations worth discussing.

Firstly, the SIC-SOC mapping process used to reconcile heritage-occupation employment with SIC codes relies on data from the APS. In recent years, the ONS has identified increasing volatility in APS estimates due to ongoing challenges with declining response rates and response levels, and sample weighting. The high degree of sensitivity of the heritage employment and GVA calculations in this methodology to APS results mean that the estimates produced are highly dependent on the quality of APS data, particularly at the five-digit SIC code level.

Furthermore, the SIC codes of the organisations with which APS respondents are assigned by the ONS, per information provided by the survey respondent on the nature of their organisation’s activity. Accurate identification of heritage sector activity therefore depends on accurate identification of heritage SIC codes, per this process. A resulting limitation of our analysis is that it will not capture organisations which undertake some heritage-related work, but for which this does not result in their principal SIC code being identified as heritage-related, and where employees do not principally work in heritage-related occupations.

Secondly, the ABS data on approximate Gross Value Added (aGVA), used to determine a SIC code’s portion of divisional activity in the National Accounts, frequently reports negative figures for several SIC codes. In addition to this, a number of SIC codes are not captured by the ABS. These issues require the use of 2 different alternative estimation processes for all SIC codes in affected divisions, introducing 2 separate sources of inconsistency into the analysis.^{[footnote 6]} This inconsistency is mitigated to the greatest extent possible by clearly defining the conditions for the use and consistent application of the alternative methodology.

Question 2

2. Introduction

Accepted Answer

The Centre for Economic and Business Research (Cebr) is pleased to present this report to the Department for Culture, Media and Sport (DCMS) and Historic England, which sets out the methodology developed to estimate the economic contribution of the UK’s heritage sector. The aim of the research was to produce a data-driven methodology for DCMS to own, with the potential in the future to consider using this to produce official statistics for the heritage sector, as part of DCMS’s Sector Economic Estimates.

In this report we also present the results of applying the outlined methodology for the years 2011 to 2022. To provide the possibility for heritage sector estimates to be presented alongside other DCMS Sector Economic Estimates in the future, it was necessary that the methodology not only be technically and conceptually accurate in identifying heritage sector activity, but also be as consistent as possible with DCMS’s current Economic Estimates methodology and to meet the standards of official statistics.^{[footnote 7]} The methodology developed here meets this goal.

Section 3 explains the methodology developed. Section 4 subsequently presents the results of our analysis. We first focus on 2022, the most recent year for which complete data is available, including a deep dive on the sector’s composition within this year. We then present time series for 2011 to 2022, for employment (as number of filled jobs) and for inflation-adjusted chained volume measures of GVA, considering trends over that period. Section 5 discusses further one of the limitations of the approach: the inability of the current methodology to produce business demography and trade statistics. Section 6 provides a conclusion to the report.

Further technical detail is subsequently presented in Appendix I. Appendix II includes a discussion of how the findings of this research fit alongside other similar research, including other DCMS Sector Economic Estimates and previous methodologically similar research conducted by Cebr for Historic England. Appendix III includes additional methodological detail and further supplementary data.

Question 3

3. Scope and methodology

Accepted Answer

3.1 Background and scope of the study

Quantifying the economic impact of the heritage sector is challenging, due to the lack of a consistently agreed upon definition and the diverse nature of the sector, which spans a wide range of industries from the repair of historic buildings to the preservation of National Landscapes. This fragmentation complicates its classification within the ONS’s Standard Industrial Classification (SIC) system. Furthermore, activity within the heritage sector spans a wide range of government departments including DCMS, the Department for Environment, Food and Rural Affairs (DEFRA) as well as the Ministry of Housing, Communities and Local Government (MHCLG). This creates further challenges from a government and policy perspective.

Although some SIC codes, like 91.03 - Operation of historical sites and buildings (as discussed further below), clearly exclusively relate to heritage, solely relying on these codes would result in an underestimation of the size of the heritage sector. This is because other SIC codes partially undertake heritage-related work, at times due to having employees working within them performing heritage activities, even if the overall SIC is not focused on heritage-related activity. A clear example of this is construction-related SIC codes, such as SIC code 43.91 – Roofing activities, which while not exclusively undertaking heritage work, do employ people who work on heritage buildings utilising specific heritage-related skills, and therefore should rightly be included in the heritage sector.

A proxy for the heritage sector is currently captured in DCMS Sector Economic Estimates using a single four-digit SIC code, 91.03 - Operation of historical sites and buildings and similar visitor attractions. It is widely agreed both by DCMS and within the sector, that the single SIC code currently used by DCMS underestimates it’s true contribution.^{[footnote 8]} The underestimation of the heritage sector results in a lack of recognition of its contribution to the economy, with potential connotations including access to government funding.

To address similar issues for the creative industries, DCMS introduced the concept of creative intensities, which seeks to establish the proportion of a given SIC sector that involves creative occupations.^{[footnote 9]} DCMS does this using Standard Occupational Classification (SOC) codes. These function similarly to SIC codes; however, they provide a system for classifying employment by the occupation, rather than industry of an employee. In this context, SOC codes are used to define creative occupations and calculate the subsequent employment in each industry from these creative occupations. To calculate the ‘creative intensity’ of an industry, the total ‘creative employment’ within a SIC code is divided by the total employment within the SIC code.^{[footnote 10]} If this resulting proportion is above the threshold of 30%, the entirety of the SIC is considered a candidate for inclusion within the definition of creative industries.

Applying the creative intensities methodology to the heritage sector poses challenges, as it risks producing unreliable estimates. The method includes entire industries exceeding the 30% threshold, regardless of their specific focus. Therefore, as an example, it could theoretically attribute the total economic value of building repair and retrofit to the heritage sector, even if not all work within this SIC code is related to heritage buildings. This would result in an overestimation of the heritage sector’s size. Equally SICs in which only a small proportion of activity is heritage-related would be fully excluded, this time understating the economic value supported by heritage.

Despite the various challenges hindering the calculation of the economic impact of the heritage sector, in recent years, progress has been made in applying innovative ways to explore and measure the contribution of the heritage sector to the UK economy. This includes the research titled “The heritage sector in England and its impact on the economy”, commissioned by Historic England and undertaken by Cebr. This employed a ‘SIC-SOC methodology’ (evaluating employment in both relevant SIC and SOC codes), to estimate the economic footprint of the heritage industry within England, with research utilising this methodology frequently conducted between 2018 and 2024.^{[footnote 11]}

It is worth noting that the Historic England research above was produced to capture the total economic footprint of the heritage sector. That included: i) the direct impacts - gross value added (GVA) and employment generated by the heritage sector itself, utilising the SIC-SOC approach; ii) the indirect impacts – GVA and employment that arises through the activities stimulated in the supply chains of the heritage sector; and, iii) the induced impacts - GVA and employment that arises through the activities supported in the wider economy when the employees associated with the direct and indirect heritage activities spend their earnings on domestic goods and services. However, the current project aims to create a new methodology to estimate only the direct GVA and employment impacts of the heritage sector for DCMS (in line with Official Statistics included in the DCMS Economic Estimates).

Prior to this research, DCMS commissioned Alma Economics to evaluate potential approaches to analysing the heritage industry, including the Historic England and Cebr SIC-SOC approach. The evaluation culminated in a report entitled “A feasibility study and preliminary framework for an alternative heritage sector statistics methodology”. The report evaluated different approaches to estimating the economic impact of the heritage sector, ultimately concluding that the SIC-SOC approach was the most robust. This was for various reasons, including the ability to cover both heritage industries and occupations, resulting in a more holistic view of the sector, the alignment of the methodology with classifications used in Official Statistics (i.e. SICs)^{[footnote 12]}, and the provision of a methodology to develop comparable estimates of the heritage sector over time.

Following the above report, DCMS has commissioned the present study which aims to estimate the economic impact of the heritage sector in the UK utilising a SIC-SOC approach, in a methodologically consistent manner with other DCMS Sector Economic Estimates and the UK’s National Accounting Framework. The scope of this report is limited to tangible heritage for the reasons set out in Alma Economics’ report. This is primarily the fact that tangible heritage can be more effectively mapped to industries, while this is more difficult for intangible heritage assets. Within this, the present study also aims to refine the selection of the SIC and SOC codes that comprise the heritage sector, from those included in the Historic England reports. This process is highlighted in detail in the methodology below. It was underpinned by extensive discussion with DCMS, Historic England and a steering group of key stakeholders in the heritage industry, supported by complementary research and data.

3.2 Introduction to SIC-SOC mapping

The SIC-SOC methodology involves integrating data from multiple sources to account for both industrial (SIC) and occupational (SOC) contributions to the heritage sector. This allows us to consider industries that undertake heritage work (such as the operation of historical sites and buildings) as well as people employed in non-heritage industries who carry out heritage work (such as archivists who work in non-heritage sectors, for example, universities).

How this methodology functions:

1. The SIC and SOC codes which are considered part of the heritage sector are selected, using the Historic England research as a starting point. The list of SIC and SOC codes included in the Historic England research was developed by Ortus Economic consultancy and Historic England through desk research and consultation with key heritage sector stakeholders when this research was first commissioned in 2016. From this starting point, several data-driven approaches are used to either validate the list of SIC codes included from the Historic England report or alter the selection of SIC and SOC codes considered part of the heritage sector.

2. For some SIC and SOC codes, a portion rather than the entirety of the activity within the SIC or SOC is heritage related. For these SICs and SOCs, further specific methodological approaches are used to evaluate, where available data permits, the share of the SIC or SOC that should be included within the heritage sector. These specific approaches are discussed further later within this report.

3. Employment data from the Annual Population Survey (APS), which classifies first and second jobs by both SIC and SOC, is used to create 2 matrices of employment across the economy (one for first and one for second jobs), by both SIC and SOC. These also demonstrate the overlap between all possible SIC and SOC pairings. A simplified example of the matrices created, utilising illustrative data, is displayed below in Figure 3.

4. For both first and second jobs, we cannot simply sum the employment of heritage SIC codes and heritage SOC codes. This would result in double counting, since employees in heritage SOC codes also employed in heritage SIC codes would be counted twice.

5. Therefore, all heritage SOC employment is mapped to SIC codes in both matrices, so that final heritage employment numbers are presented in terms of SIC codes only. Employment (as number of filled jobs) is subsequently summed across all SIC codes in which heritage employment is observed. Within this report, we refer to SIC codes which we have defined as being part of the heritage sector as ‘core’ heritage SIC codes. SIC codes which are identified as having workers in heritage occupations working within them, are referred to as ‘secondary’ heritage SICs.

An illustrative example of this methodology and how double counting is avoided, is presented below.

Figure 3: A simplified example of a SIC-SOC matrix

Blue-highlighted SIC and SOC codes are considered part of the heritage sector, while grey-highlighted codes are not.^{[footnote 13]} Below, we lay out the correct way to interpret this matrix to calculate total heritage employment.

For core heritage SIC codes, such as SIC 91.02: Museums Activities, employment from all SOC codes is considered part of the heritage sector, leading to the heritage employment total for SIC 91.02 being 5.

For secondary heritage SIC codes, such as SIC 90.04: Operation of arts facilities, only employment in heritage SOC codes (24.72: Archivists and Curators) is included, leading to SIC 90.04 having a total heritage count of 4.

This approach results in a total heritage employment of 9. No double counting is ensured, as all employment is classified by SIC code, avoiding the duplication that could arise if employment in heritage SIC and SOC codes were simply added together.^{[footnote 14]}

Overall, by integrating both SIC and SOC classifications, this methodology offers a more inclusive representation of heritage sector activities than traditional SIC-based approaches. In doing so, it lays the groundwork for a comprehensive, official estimate of the heritage sector’s economic contribution, examining employment and GVA while remaining consistent with DCMS’s established statistical frameworks.

3.3 SIC code selection

This section details the process used to determine which SIC codes should be considered part of the heritage sector’s definition. Where appropriate, we also consider the share of these SIC codes that are undertaking heritage-related activity and, therefore, the share of the industry which should be included.

A share of an industry (or later in the report, occupation) is included when only some activity within the industry (or occupation) is heritage-related. In these instances, it would be inappropriate to consider the whole industry part of the heritage sector. Therefore, we use wider data, often considering different ‘proxies’ for the share of an industry’s activity that should be considered heritage-related. For these SICs (or SOCs) which are partially heritage and partially non-heritage, we are dependent on wider data and the availability of sensible proxies, to estimate the share of activity which is indeed heritage-related.

A limitation of this approach is that for SICs or SOCs which are partially heritage-related, only industries or occupations for which robust proxies can be identified or applied can be included. Our approach within this project has been to develop as extensive a definition as possible, within the constraints of current data availability. However, there are likely to be other SICs or SOCs which could conceptually be considered partially heritage, but for which current data does not facilitate an accurate estimation of this share, and thus their partial inclusion (for example the heritage transport industry). For a more detailed explanation of how we applied this approach when considering potential heritage SIC codes, please see Appendix I.

3.3.1 SIC codes previously considered part of the heritage sector

Since Alma Economics’ report concluded that the SIC-SOC approach used in the Historic England reports produced between 2018 and 2024 is the most appropriate way to estimate the heritage sector’s economic impact, the starting point for this research was the set of SIC and SOC codes included in the 2024 Historic England report. These industries are displayed in Table 7, along with the proportion of these industries that were considered part of the heritage sector, providing the ‘starting point’ for the classification of heritage SIC codes.^{[footnote 15]}

Table 7: The SIC codes and proportions thereof included in research for Historic England

SIC codes	Code description	Proportion included
43.3	Building completion and finishing	31%
43.9	Other specialised construction activity	31%
91.012	Archive activities	100%
91.020	Museum activities	100%
91.030	Historical sites and buildings	100%

Source: Cebr for Historic England

SIC codes are classified as fully heritage (i.e. where 100% of the SIC is included as heritage, as for Archives, Museums, and Historical Sites) where all work (and thus employment) in the industry is related to the preservation and display of heritage assets such as heritage artifacts. Construction-related SIC codes (43.3 and 43.9)^{[footnote 16]} were included in the Historic England methodology to account for construction activities specific to heritage buildings.

The 2013 Skills Needs Analysis report,^{[footnote 17]} produced for Historic Scotland, English Heritage and the Construction Industry Training Board (CITB), estimates heritage-related construction employment by identifying relevant roles within the construction sector and the number of people in those roles undertaking heritage work. On this basis, heritage-related construction activity is included within the definition of the heritage sector. SIC codes were selected over SOC codes to map heritage construction employment, as SIC codes more effectively identify known businesses that are specifically and consistently engaged in heritage construction work. In contrast, relying on SOC codes could have resulted in the inclusion of activity in other construction SIC codes which conceptually could not undertake heritage-related work. A more detailed explanation of this methodological choice is provided in Appendix I.

3.3.2 Review of evidence and potential alterations to the list of SIC codes included in the heritage sector

The SIC codes discussed above only act as a ‘starting point’ for this research. As part of this project, we re-examined the evidence, to explore potential alterations, including those driven by new research released since 2018 (given that the Historic England reports’ definition had remained largely unchanged since this point). This includes both exploring new SICs and evaluating the arguments for including previously incorporated SIC codes.

As part of this, we undertook 3 primary approaches, as described below and subsequently discussed further within this section of the report:

1. An analysis of National Lottery Heritage Fund (NLHF) grant data^{[footnote 18]} to validate the inclusion of initial heritage SICs, and as a starting point for shortlisting other SICs that could be considered. Further consideration was then given to these shortlisted SIC codes, as to whether it would be appropriate to include some or all activity within the definition of the heritage sector.

2. A review of new resources relating to the heritage sector, including the 2024 Historic England report, produced by Harlow Consulting in September 2024, titled “Skills Needs Analysis: For the Repair, Maintenance and Retrofit of Traditional (pre-1919) Buildings in England.” This allowed us to specifically re-examine the heritage construction industry, utilising updated data to estimate the share of relevant SIC codes attributable to heritage. This directly addresses an area for improvement identified by Alma Economics, as they correctly identify that the Historic England report produced by Cebr between 2018 and 2024 relied on employment data from 2012, to calculate the proportion of construction SICs, related to heritage construction.^{[footnote 19]}

3. Examination of ‘supported’ SIC codes. When evaluating the economic impact of ‘material cultural heritage’ within the EU, ESPON, a European funded programme for Territorial Development and Cohesion, suggests the use of proxy indicators – “keys” – to estimate the share of specific industries which should be defined as part of the heritage sector.^{[footnote 20]} This includes analysis of heritage sector spending on ancillary sectors, which are in some proportion conducting heritage work. For example, ESPON’s report estimates 1.9% of spending on the ICT sector within the EU in 2015 was by heritage organisations, thus arguing that 1.9% of economic activity within the ICT industry should be considered part of the heritage sector. We conducted a similar analysis here, considering the expenditure of identified ‘core’ heritage SICs (the SIC codes identified in Table 1) on other industries. We refer to these other SIC codes which have levels of heritage expenditure above 0.5% of total expenditure by core heritage SICs, as ‘supported SICs’.

The following descriptions are a summary of the 3 approaches highlighted above. A more detailed description of the NLHF grant analysis and of supported SIC codes, is provided in Appendix I.

National Lottery Heritage Fund grant data

The following description is a summary of the process undertaken to analyse the National Lottery Heritage Fund grants awarded between 2013 and 2024.

The National Lottery Heritage Fund grant analysis relies on data published by the NLHF, which details the grants received by organisations to undertake heritage projects, between April 1^st 2013 and December 19^th 2024. This data set lists the name of the organisation, the company number and the grants awarded to the organisation. ^{[footnote 21]} To determine the SIC codes of organisations receiving National Lottery Heritage Fund grants, Companies House mapping files are used to convert company numbers listed by the NLHF grants into SIC codes, allowing us to aggregate the grants received per SIC code. The top 50 SIC codes by grants received were then sorted by the sum of grants received (Tables A and B in Appendix I).

Table 8, presented below, is the result of the mapping exercise detailed above, and only includes SIC codes which received grant funding between 2013 and 2024, approximately equalling or exceeding 0.5% of their market turnover in 2022 (per Annual Business Survey data). The table is sorted by the ratio of grants received to market turnover (used as a metric to standardise for overall size of each sector receiving grants), and identifies that SIC codes 91.012, 91.020 and 91.030 (which are ‘core’ heritage SICs) are the codes with the highest grant to turnover ratio. These findings reinforce the notion that these sectors engage extensively in heritage-related work.

Table 8: SIC codes from NLHF grant data, sorted by the percentage of market turnover in 2022 that grants between 2013 and 2024 are equivalent to. ^{[footnote 22]}

Top 15 List	SIC Code	Total Award (£000’s)	Market Turnover (£000’s)	Ratio
1	91.020 - Museums activities	166172	779269	21.32%
2	91.030 - Operation of historical sites and buildings and similar visitor attractions	113953	623551	18.27%
3	91.012 - Archives activities	9791	66647	14.69%
4	85.520 - Cultural education	37829	416949	9.07%
5	91.011 - Library activities	9775	110525	8.84%
6	91.040 - Botanical and zoological gardens and nature reserves activities	42453	721892	5.88%
7	90.040 - Operation of arts facilities	27922	734162	3.80%
8	94.990 - Activities of other membership organizations n.e.c.	49635	5361224	0.93%
9	94.910 - Activities of religious organizations	10683	1303951	0.82%
10	85.600 - Educational support services	11322	2051041	0.55%
11	90.030 - Artistic creation	21229	4124430	0.51%
12	90.010 - Performing arts	21417	4379588	0.49%

Source: NLHF data, ONS data, Cebr analysis

When examining the non-core heritage SIC codes above, 4 have a notably higher grant to turnover ratio than others: 85.520 - Cultural Education; 90.040 - Operation of Arts Facilities; 91.040 - Botanical and zoological gardens and nature reserve activities; and 91.011 - Library activities. The most promising SIC code for potential inclusion was cultural education, which had the highest grant to turnover ratio outside of ‘core’ heritage SIC codes. However, it was ultimately not included due to a lack of evidence to apportion the data to heritage. These 4 potential candidates are all discussed further, in Appendix I.

Revisiting the construction industry skills data

As discussed, the Historic England reports produced by Cebr between 2018 and 2024, relied on the 2013 Historic England report titled “Skills Needs Analysis 2013 Repair, Maintenance and Energy Efficiency Retrofit of Traditional (pre-1919^{[footnote 23]}) Buildings in England and Scotland”, to estimate the share of construction-related SIC codes undertaking heritage-related work. Specifically, this report had data from 2012 on the FTE (full time equivalent) employment of the construction heritage sector which was used in conjunction with Business Register and Employment Survey (BRES) data to determine the proportion of 2 three-digit SIC codes, SIC 43.3 and 43.9, identified by Cebr as being the SIC codes related to building repair and maintenance. This resulted in the proportion of 31% seen in Table 1, with a more detailed explanation of this calculation available in Footnote 23.

New evidence allows us to update this proportion. Specifically, this data is made available through the 2024 Historic England report titled “Skills Needs Analysis: For the Repair, Maintenance and Retrofit of Traditional (pre-1919) Buildings in England”, produced by Harlow Consulting and published in September 2024. The 2024 Skills Needs Analysis provides fresh insights into the number of construction workers actively engaged in heritage projects. This updated report not only estimates figures comparable to the 2013 Skills Needs Analysis, but also distinguishes between the number of workers solely employed on heritage buildings, and those using heritage specific skills in their work.^{[footnote 24]} Crucially, the roles it examines are wood trades, bricklaying, painting, decorating, plastering, roofing, flooring, glazing, and scaffolding, which are all activities that are accounted for by SIC 43.3 and SIC 43.9, reinforcing the rationale for using these SIC codes to represent heritage construction activity.^{[footnote 25]}

Per the 2024 Skills Needs Analysis, the number of construction workers using heritage specific skills in England in 2023 is equal to 97,224 FTE workers. As conducted in the Historic England reports on the economic impact of the heritage sector, we divide heritage-related employment per the Skills Needs Analysis by total number of jobs (counting both first and second jobs) in the SIC codes related to the repair and maintenance of the heritage sector, specifically SIC 43.3 and 43.9, per APS data.^{[footnote 26]} This results in an estimate that 24.8% of employment in these SIC codes is heritage activity, replacing the 31.0% previously used in the Historic England analysis. This ensures that calculations regarding the heritage construction industry remain both current and closely aligned with actual sector activity.

Broader heritage activity and the ESPON “keys” framework

The ESPON heritage framework highlighted in Alma Economics’ report, presents a further method for identifying industries related to the heritage sector. Amongst other approaches, the ESPON framework aims to use the spending of the heritage sector on other industries, to determine the proportion of other industries’ revenue that is generated from heritage sector spending. This implicitly assumes that spending in other sectors by heritage organisations supports heritage-related economic activity (i.e. if X% of spending on insurance was for heritage purposes, X% of the insurance sector’s own economic contribution is heritage-related). We refer to these SIC codes identified through this approach, as ‘supported SICs’.

As part of this project we explored this approach, using Office for National Statistics’ (ONS) Supply and Use Tables for the UK to estimate the expenditure from primary heritage SIC codes (i.e. those already identified in Table 1) on all other SIC codes in the UK economy. More detail on this process and the results is outlined in Appendix I, however after compiling the list of ‘supported’ SICs, we ultimately decided against introducing them into the definition of the heritage sector. This was predominantly due to a desire to maintain consistency with other DCMS Sector Economic Estimates, which do not include similarly ‘supported activity’ within their definition. However, further research with broader purposes regarding the wider economic footprint of heritage – if it is not bounded by definitional consistency with other DCMS Sector Economic Estimates – may want to consider the inclusion of shares of these supported SICs.

Ultimately, the list of SIC codes considered part of the heritage sector in this research remains unchanged from the Historic England study. This is due to a lack of evidence to support the inclusion of additional SIC codes, and a data-driven corroboration of the existing list. This results in the finalised list of SIC codes for our analysis, displayed in Table 9, looking very similar to the list of SIC codes analysed in the Historic England report displayed in Table 7.

While the SIC codes themselves have not changed, the share of the 2 construction-related SIC codes have been adjusted. This adjustment, detailed above, reflects updated data on the number of workers engaged in heritage construction using heritage-specific skills, ensuring the analysis is using up to date estimates of the size of the construction heritage sector.

Table 9: The list of SIC codes and proportions thereof included in this research

SIC codes	Code description	% SIC code included
43.3	Building completion and finishing	24.8%
43.9	Other specialised construction activity	24.8%
91.012	Archive activities	100%
91.020	Museums activities	100%
91.030	Historical sites and buildings	100%

Source: Historic England, ONS data, Cebr analysis

3.4 SOC code selection

3.4.1 Review of SOC codes previously considered part of the heritage sector

In addition to some heritage activity being identified through SIC codes, other parts of the sector are best identified through SOC codes. This is particularly the case where individuals work in heritage-related occupations, which are present in industries across the economy (such as archivists who may work in both heritage industries like museums and non-heritage organisations such as universities).

This section details the process used to determine which SOC codes should be considered part of the heritage sector. Where appropriate, we also consider the share of these SOC codes that are undertaking heritage-related activity, and therefore, the share which should be included within our definition of the heritage sector. As discussed in Section 3.2, for employees who are both within a heritage SIC and heritage SOC, we use SIC-SOC mapping to prevent double counting of their employment.

As with SIC codes, the starting point for this research was again the set of SOC codes included in the 2024 Historic England report. These initial occupations are displayed in Table 10 which include the following:

Specialised construction activities, as captured through SOC code 2431, 2432, 2434, 3114, which will have part of their workforce undertaking construction projects on heritage buildings
Occupations which undertake work related to the discovery and preservation of other physical heritage assets, such as SOC code 2452: Archivists and curators (preserving heritage documents and manuscripts) and archaeologists within SOC code 2115: social and humanities scientists
SOC codes 3550 and 5113, accounting for the preservation of natural heritage^{[footnote 27]}

Table 10: List of SOC codes deemed to be part of heritage sector in research for Historic England

SOC 2010 codes	Code description	Proportion Included
2114	Social and humanities scientists^{[footnote 28]}	21.7%
2141	Conservation professionals	100.0%
2431	Architects	20.5%
2432	Town planning officers	20.5%
2434	Chartered surveyors	20.5%
2453	Archivist and curators	100.0%
3114	Building / civil engineers	20.5%
3550	Conservation and environmental associate professionals	100.0%
5113	Gardeners/ landscape gardeners	1.9%

Source: Cebr for Historic England

As for SICs, we again reevaluate this list considering new evidence, recommendations proposed by Alma Economics’ report and wider changes in occupation-based statistical classification systems, as described further in the following section.

3.4.2 Review of evidence and potential alterations to the list of SOC codes included in the heritage sector

To build on the foundation established by Historic England’s identification of heritage-relevant SOC codes, we revisited and refined the list of occupations included in our analysis of the heritage sector. This review was prompted by 2 key developments: recommendations from the Alma Economics report, which suggested further exploration of heritage-related roles, and structural updates to the ONS’s Standard Occupational Classification (SOC) system introduced in 2021.^{[footnote 29]} To refine the selection of SOC codes, we therefore took 2 approaches.

Firstly, we reclassified the previous SOC 2010-based heritage occupations in Table 10 above, to SOC 2020 codes utilising a conversion matrix produced by the ONS.^{[footnote 30]} After converting the previous SOC 2010 codes into SOC 2020 codes,^{[footnote 31]} we reviewed their updated descriptions to assess their continued relevance to the heritage sector. As a part of this process, we also revisited methodologies used to determine the share of respective occupations which are considered heritage-related, where appropriate.

Secondly, we explored the potential inclusion of occupations not previously considered by the Historic England research. This involved gathering evidence from a range of sources, including:

Mapping between SOC 2010 and SOC 2020

In 2018, Historic England and Cebr began their analysis of the heritage sector, with the occupation-based component of the heritage sector’s definition based upon the SOC 2010 classification system. At the time, this was the most up to date classification system used by the ONS. However, in 2021, the SOC 2020 classification system was introduced, to enhance accuracy and better reflect changes in job roles and classifications.

At this point in time, the Historic England research chose to retain the SOC 2010 classification system for comparability across years. However, this research adopts SOC 2020, to take advantage of the improved classification of job activities within SOC 2020 codes. To bridge the systems, we use an ONS-provided conversion matrix, mapping SOC 2010 codes included in the Historic England research to their SOC 2020 counterparts, as shown in Table 11. SOC codes with major changes to their definition and classification, are shared red.

Table 11: SOC 2010 to SOC 2020 conversion

SOC 2010 code	SOC 2020 code
2114: Social and humanities scientist	2115: Social and humanities scientist
2141: Conservation professionals	2151: Conservation professionals
2431: Architects	2451: Architects
2432: Town planning officers	2452: Chartered architectural technologists and planning officers and consultants
2434: Chartered Surveyors	2454: Chartered surveyors
3114: Building and civil engineering technicians	3114: Building and civil engineering technicians
2453: Archivists and curators	2472: Archivists and curators
3550: Conservation and environmental associate professionals	5119: Agricultural and fishing trades
5113: Gardeners and landscape gardeners	5113: Gardeners and landscape gardeners

Source: ONS

From the above, we can see that most SOC 2010 codes were reclassified under SOC 2020 with minimal change to their occupational labels. For example, Archivists and Curators were reclassified from 2453 to 2472 with no change to their occupational title. For these SOCs, due to the consistency in definition between SOC 2010 and SOC 2020, our starting point, subject to further scrutiny, was including the new SOC 2020 code within our updated heritage definition. However, a minority - specifically Town Planning Officers and Conservation and Environmental Associate Professionals - were reclassified into broader SOC 2020 categories.

Conservation and environmental associate professionals were reclassified into 2 broader SOC 2020 codes: 94% of employment maps to 5119 Agricultural and Fishing Trades, and 6% to 2152 Environmental Professionals. A review of the updated task descriptions (Appendix I, Table B) showed that no heritage related work was captured by these new SOC 2020 codes.^{[footnote 32]} As such, we do not include either of the new SOC 2020 codes in our updated list of heritage SOC codes.

Similarly, the SOC 2010 occupation, Town Planning Officers, is now part of the broader SOC 2452 (Chartered Architectural Technologists and Planning Officers). This combines multiple planning-related roles, without the ability to isolate heritage-specific tasks due to the broad set of activities going on within the occupation code. Therefore, we again do not include the new SOC 2020 code, within our updated heritage definition.^{[footnote 33]}

With the exclusion of these 2 SOCs, we therefore proceed with the following SOC 2020 codes, as our starting point for this project’s definition, before we subsequently consider evidence to extend this list. Further details on the approach for calculating the share of SOC codes which are only partially included, is given below the table.

Table 12: Summary table of SOC 2020 codes included in the current analysis

SOC 2020 code	Proportion included	Reason for proportion	Inclusion type
2472: Archivist and Curators	100%	All work in the SOC code is related to heritage preservation through conservation of books and other collections.	Full
2151: Conservation professionals	100%	All work in the SOC code is related to the preservation of natural heritage, specifically National Landscapes.	Full
2115: Social and Humanities Scientists	16.9%	Proportion is equal to the number of Archaeologists in the UK in 2022 from the Federation of Archaeological Managers and Employers, divided by the total number of first and second jobs in the SOC code from the APS.	Partial
2451: Architects	20.5%	Proportion equal to the share of pre-1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings built before and after 1919.	Partial
2454: Chartered Surveyors	20.5%	Proportion equal to the share of pre 1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings build before and after 1919.	Partial
3114: Building and Civil Engineering Technicians	20.5%	Proportion equal to the share of pre 1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings built before and after 1919.	Partial
5113: Gardeners and Landscape Gardeners	17.4%	Proportion equal to the number of landscape gardeners working on heritage gardens and parks and heritage buildings with gardens.	Partial

Apportionment of heritage construction workers

Three construction SOC 2020 codes - 2451 (Architects), 2454 (Chartered Surveyors), and 3114 (Building and Civil Engineering Technicians) - were validated using Historic England’s Practical Building Conservation: Conservation Basics (2013) which identified these 3 SOC codes as occupation which are necessary to the repair and maintenance of heritage buildings.

The ideal approach to apportion the share of these SOCs undertaking heritage-related work, would be utilising the proportion of construction projects worked on by architects, chartered surveyors and building and civil engineers, that involve buildings built before 1919.^{[footnote 34]} However, due to this precise data being unavailable, the total share of the UK’s building stock built pre-1919, is used as a proxy. This proportion is equal to 20.5% and is calculated by taking the total building stock of pre-1919 buildings in the UK and dividing this by the total building stock in the UK.^{[footnote 35]} It is therefore assumed that 20.5% of architects, chartered surveyors and building and civil engineers’ employment, belongs to the heritage sector.

Within SOC 2115 (Social and Humanities Scientists), only archaeologists are relevant to heritage. This occupation is grouped with wider social scientists, such as economists, so we again estimated the proportion within the wider SOC, who are archaeologists and thus heritage sector workers.

To determine this proportion, data from the State of the Archaeology Market 2022, produced by FAME (Federation of Archaeological Managers and Employers) was used. This report detailed the total number of archaeologists employed in the UK in 2022 (6,703 total employees). This figure was then divided by the total number of first and second jobs within SOC 2115 in the UK in 2022 from the Annual Population Survey yielding a proportion of 16.9%.^{[footnote 36]} This percentage is subsequently used to apportion total employment within SOC 2115, ensuring only archaeologists within this SOC are included.

Apportionment of gardeners and landscape gardeners

To estimate the heritage-relevant share of employment, we used Annual Population Survey data to analyse the distribution of gardeners across industries, focusing on employment in 6 SIC codes with potential links to heritage:

81.300 – Landscaping activities
55.100 – Hotels and similar accommodation
68.201 – Housing associations
84.110 – Public administration
94.990 – Membership organisations
97.000 – Domestic workers employed by households

For SIC 81.300, we compared the area of registered historic parks and gardens to the total landscaped area in England, estimating that 19.3% of gardeners in this SIC are heritage-related.^{[footnote 37]} For the remaining SIC codes, we applied a 20.5% proxy based on the share of UK buildings constructed before 1919, assuming that the prevalence of gardeners is proportional to the distribution of buildings by age.

Weighting these proportions by the employment distribution across industries, we estimate that 17.4% of gardeners and landscape gardeners work in a heritage capacity. A more detailed breakdown of this methodology is provided in Appendix I.

The 17.4% of SOC code 5113 included in this analysis is notably higher than the 1.9% used in the Historic England research. This increase reflects the broader range of SIC codes considered here, which capture a wider set of heritage-related gardening activities across different sectors.^{[footnote 38]}

3.4.3 Review of evidence for occupations not considered in the Historic England reports

Analysis of heritage job boards and university heritage career guidance

In their report, Alma Economics suggest examining heritage job boards and university career guidance pertaining to the heritage sector, to explore heritage jobs listed in these documents that were not included in the Historic England reports. To do this, we started by analysing the University of Edinburgh Centre for Research Collections, Herriot Watts University, Heritage alliance and Museum Association, as prescribed by Alma Economics. This was followed by an extensive review of larger job boards including Indeed and LinkedIn, filtering for terms related to heritage organisations (such as museum, archive, heritage and preservation).

This exercise was valuable in validating many of the inclusion of occupations already included in our analysis, specifically archivist, curators and architects, which were all mentioned multiple times in relation to heritage occupations. However, it did not lead to the identification of new SOC codes to include in our analysis of the heritage sector.

This is because most jobs listed on these websites were either already considered heritage occupations (as discussed above), or they were general roles within heritage organisations which are not as an occupation inherently heritage-related, such as secretaries or financial planners. These jobs would be included within our SIC code analysis through their employer’s inclusion as a heritage organisation within a heritage industry, rather than being appropriate for specific inclusion through SOC codes.

Analysis of Historic England’s report titled Conservation Basics published in 2013, focusing on built heritage

As mentioned in the analysis of SOC codes included in the Historic England reports, the Historic England report titled the ‘Practical Building Conservation: Conservation Basics’, sheds light onto the specialised construction occupations that work within the heritage sector, including Architects, Chartered surveyors and Civil engineering technicians. In addition to these occupations, which were included in the Historic England analysis of the heritage sector, the report specifically mentions the importance of quantity surveyors (SOC 2020: 2453) in the repair and maintenance of heritage buildings. The report indicates that quantity surveyors and chartered surveyors work alongside each other on most construction projects, including those which are heritage related. When working together, chartered surveyors assess the quality of the buildings ensuring they meet sector standards, while quantity surveyors estimate the volume and cost of materials required for construction and maintenance projects. Specific examples of this are provided, including Tonedale Mill in Somerset, where quantity surveyors worked alongside chartered surveyors.

On balance, we have included quantity surveyors (SOC 2453) in our analysis of the heritage industry. Due to the close alignment with the other specialised construction SOC codes discussed before, we have used the same apportionment method to determine the proportion of workers in this SOC code that work in the heritage industry, resulting in 20.5% of SOC code 2453: quantity surveyors, being included in the heritage sector.

Analysis of evidence relating to heritage academics

The Alma Economics report discusses including heritage academics in further analysis. This possibility was explored as part of our research; however, several challenges arise, primarily the absence of consistent data (for example, the existence of centralised databases of heritage academics).

To evaluate the feasibility of this approach, we employed 2 methods:

1. Higher Education Statistics Agency (HESA) Data: Using data from the HESA database, we examined the number of academics in related disciplines - History, Classics, and Archaeology - as a proxy for heritage, as there is no specific heritage discipline listed in HESA’s classifications. HESA data indicates 5,145 academics in these fields, representing 2.14% of the UK’s 240,420 academics. However, this proxy likely overstates the actual number of heritage-focused academics due to the inclusion of 3 broader disciplines.

2. Russell Group universities: As an additional exercise with a manageable sample, we manually reviewed the websites of the 24 Russell Group Universities to count academics affiliated with heritage departments. Of the 24 Russell Group Universities, only 8 have a heritage department, while another 9 employ some academics that have the term ‘heritage’ in their job title. From these 17 Universities we counted the number of academics employed that worked with heritage. The remaining 7 Universities did not have easily identifiable heritage academics or departments; therefore, we counted their heritage academics as zero. Overall, this analysis found that less than 1% of the Russell Group’s roughly 103,000^{[footnote 39]} academics are working in heritage departments, with the caveat that academics undertaking heritage-related work outside of heritage-specific departments, who did not contain the term heritage in their job title, would not be included.

These findings suggest that including heritage academics in the analysis would require substantial effort for a limited return. Heritage academics constitute a very small proportion of the UK’s academic workforce and determining which disciplines to include would be difficult to do consistently with accuracy and in a fully-data driven manner. Moreover, it would not be possible to conduct this analysis retrospectively (given that universities often have lists of current academics but not public retrospective records), and therefore assumptions would have to be made that the share of academics in heritage roles was historically stable. Replicating this analysis in the future would also be time-intensive for future researchers. In addition, academics undertaking work related to other DCMS sectors are not included within Economic Estimates for these sectors, creating a potential inconsistency if specifically, heritage academics were included within the analysis.

Given these challenges and the limited impact on the overall estimate, on balance we have not included heritage academics, however further research, particularly for bespoke projects that do not require annual updates, would be of value.

After this extensive investigation of the SOC codes included in the Historic England analysis of the heritage sector, combined with the investigation of new evidence aimed at identifying any SOC codes not considered by the Historic England reports, the finalised list of SOC codes in our analysis is detailed in Table 13. We also include the proportion of these SOC codes that are considered part of the heritage sector, along with whether the SOC (in prior SOC 2010 form) was previously included within the equivalent Historic England estimates.

Table 13: SOC codes included and their heritage proportions

SOC 2020 code	Proportion included	Included in Historic England research
2115: Social and humanities scientists	16.9%	Yes
2151: Conservation professionals	100%	Yes
2451: Architects	20.5%	Yes
2453: Quantity Surveyors	20.5%	No
2454: Chartered Surveyors	20.5%	Yes
2472: Archivists and curators	100%	Yes
3114: Building and civil engineering technicians	20.5%	Yes
5113: Gardeners and landscape gardeners	17.4%	Yes

3.5 Economic impact calculations

Once the heritage sector has been defined by relevant SICs and SOCs (as outlined in the section above), its economic contribution is estimated using a methodology aligned as closely as possible with DCMS’s Sector Economic Estimates.^{[footnote 40]}

Heritage employment figures (as number of filled jobs) are derived from the Annual Population Survey. Based on the previously identified heritage SICs and SOCs, we calculate the number of filled jobs (including both first and second jobs) in heritage-related industries and occupations. These figures are then used to estimate the proportion of each industry’s workforce engaged in heritage activity.

Gross Value Added is estimated by assuming that the proportion of an industry’s GVA attributable to heritage activity corresponds to its proportion of heritage-related employment. These employment-based shares are then applied to industry-level GVA figures from the ONS’s Quarterly National Accounts. This approach produces heritage GVA estimates that are consistent with both DCMS Sector Economic Estimates and the UK National Accounts.

Further detail on the precise methodology for both employment and GVA estimates can be found in Appendix III. This appendix also includes a discussion of the feasibility of using the proportion of total industry wages that are paid to heritage workers, as a potentially better proxy for the share of an industry’s GVA that is attributable to heritage activity.

Question 4

4. Economic contribution of the heritage sector

Accepted Answer

This section presents the economic contribution of the heritage sector in terms of GVA and employment. These estimates are derived by applying the methodology described in Section 3.5, to the definition of the heritage sector developed in Sections 3.3 and 3.4. We first present the heritage sector’s economic contributions in 2022, before presenting the entire time series from 2011–2022. For both, we present results first at the UK level, and then at the regional level.

All monetary estimates for 2022 are presented at current price levels in Section 4.1.1. A chained volume measure GVA series, which adjusts for inflation, is presented in Section 4.2.1. Chained Volume Measures remove the effect of price changes so that only the actual movement in quantities is measured. Rather than fixing all figures to a single base year, each year’s data is linked – or ‘chained’ – to the preceding year. This approach maintains accuracy over time by preventing distortions that can arise when prices change.

4.1 Economic impact of the heritage sector in 2022

4.1.1 Gross Value Added

National impact of the heritage sector

Gross value added to the UK economy by the heritage sector reached £15.2 billion in 2022. Table 14 presents a breakdown of UK GVA by core and secondary heritage industries, as defined by the SIC codes discussed in Section 3.3 of this report. This compares to DCMS’s latest Operation of historical sites and buildings (the closest proxy for heritage in DCMS Sector Economic Estimates) GVA estimate for 2022 of £0.7 billion. ^{[footnote 41]}

Table 14: Heritage GVA by industry (£m), 2022^{[footnote 42]}

Type	SIC	GVA contribution, £m	% of total GVA
Core Heritage Industries	43.3 Building completion and finishing	4,390	28.9%
	43.9 Other specialised construction activities	2,892	19.1%
	91.02 Museum activities	868	5.7%
	91.03 Operation of historical sites and buildings	695	4.6%
	91.012 Archive activities	74	0.5%
	Total Core heritage industries	8,918	58.8%
Secondary Heritage Industries		6,256	41.2%
Total		15,174	100%

Source: ONS data, Cebr analysis

The heritage industries with the largest GVA contributions are ‘43.3 Building completion and finishing’, contributing £4.4 billion, and ‘43.9 - Other specialised construction activities’, contributing £2.9 billion. Of the 3 industries in division 91, ‘91.012 - Archive activities’ contributed £74 million, ’91.02 - Museum activities’ contributed £868 million, and ‘91.03 - Operation of historical sites and buildings’ contributed £695 million. The total gross value added by core heritage industries amounts to £8.9 billion, while heritage-related economic activity in secondary heritage industries contributed £6.3 billion in GVA.

Heritage activity was recorded in 53 of the 88 different 2-digit SIC divisions in 2022.^{[footnote 43]} Table 15 presents the 10 of these divisions with the largest heritage GVA contributions in 2022. Heritage activity in divisions not included in the SIC-based definition of the heritage sector is generated by employees in heritage-focused occupations, as discussed in Section 3.4.

Table 15: The 10 largest SIC divisions by GVA contribution (£bn), 2022

Top 10 SIC divisions	GVA, £bn	% of total
43 Specialised construction	7.3	48.1%
68 Real estate	1.8	12.1%
91 Libraries, archives, museums and other cultural activities	1.8	11.6%
71 Architectural and engineering activities	0.6	3.6%
41 Construction of buildings	0.5	3.2%
42 Civil engineering	0.4	2.6%
81 Services to buildings and landscape activities	0.4	2.5%
84 Public administration and defence	0.3	1.8%
74 Other professional, scientific and technical activities	0.2	1.6%
72 Scientific research and development	0.2	1.5%
All other divisions	1.7	11.4%
Total	15.2	100%

Source: ONS data, Cebr analysis

Division 43, Specialised construction, contributed £7.3 billion in GVA to the heritage sector, constituting 48% of 2022’s total heritage activity. In 2022, total construction sector GVA in the UK’s National Accounts experienced a bumper year, particularly relative to the other divisions in the top 10 above. This partially explains the large share contributed by division 43. However, the main reason that the division’s contribution is so large is that the 2 major construction-related heritage SICs (43.3 - Building completion and finishing, and 43.9 - Other specialised construction activities) fall within this division. The heritage shares of activity in all divisions other than 43 and 91 are limited, and only identified by employment in heritage-related occupations. The 78 divisions outside of the top 10 contributed a combined £1.7 billion in GVA, slightly below that contributed by division 91 alone.

Six of the top 10 divisions (43, 68, 71, 41, 42 and 81) revolve principally around the design, construction and maintenance of buildings, infrastructure and the environments thereof. These divisions constitute £11.0 billion of the £15.2 billion in total heritage GVA, or 72%. This is also apparent at the 5-digit SIC code level, at which most of the top 15 SIC codes by heritage GVA are related to sites and structures. See further detail in Appendix III.

Regional impact of the heritage sector

Figure 4 shows the distribution of heritage GVA across the UK nations and the English regions.

Figure 4: GVA by nation and region (£bn), 2022/Source: ONS data, Cebr analysis

English heritage GVA constituted £13.1 billion of the £15.2 billion UK total in 2022, or 86%. Scotland’s GVA totalled £1.1 billion (7.5% of UK total), while Welsh and Northern Irish heritage sector GVA totalled £0.5 billion (3.3%) and £0.4 billion (2.3%), respectively.

Of the English regions, London and the South East dominated, contributing a combined £5.5 billion in GVA, 42% of England’s total and 36% of the UK’s total. The East of England and the North West made a similar contribution to each other, at £1.4 billion.

4.1.2 Employment

National impact of the heritage sector

In 2022, the heritage sector accounted for 297,400 jobs across the UK. Approximately 0.8% of all UK filled jobs, or equivalently one in every 122 jobs that year were in the heritage sector.

Heritage employment was widespread, present in the same 53 2-digit SIC codes as GVA (equivalent to 124 4- or 5-digit SIC codes), the vast majority of which were secondary SICs. Table 16 presents the distribution of heritage employment across industries at the 4 and 5-digit level.

Table 16: Distribution of heritage employment across SIC codes (000s) in 2022^{[footnote 44]}

Type	SIC	Number of heritage filled jobs (000s)	% of total employment
Core Heritage Industries	43.3 Building completion and finishing	91	30.6%
	91.02 Museum activities	43	14.6%
	43.9 Other specialised construction activities	37	12.5%
	91.03 Operation of historical sites and buildings	10	3.5%
	91.012 Archive activities	9	2.9%
	Total Core heritage industries	191	64.2%
Secondary Heritage Industries		106	35.8%
Total		297	100%

Source: ONS data, Cebr analysis

Within core heritage SICs, the construction SIC code 43.3 - Building completion and finishing accounted for the highest number of jobs (30.6% of total heritage jobs), followed by SIC code 91.02 - Museum activities (14.6%) and 43.9 - Other specialised construction activities (12.5%). Employment within core heritage SICs constituted 64.2% of total heritage employment, while secondary SICs constituted above a third of heritage employment, at 35.8%.

Figure 5 further breaks down the secondary SICs category and presents the 5 SIC codes which accounted for most heritage employment in 2022, within this category^{[footnote 45]}.

Figure 5: Distribution of heritage employment among the top secondary SIC codes (000s) in 2022/Source: ONS data, Cebr analysis

Heritage employment in these SIC codes reflects the presence of heritage occupations in said industries. This is reflected in Figure 5, where the top contributions to heritage employment were made in SIC codes closely associated with heritage SOCs, such as 5513 - Gardeners and Landscape Gardeners and 2431 - Architects. For instance, out of the total 106,400 heritage jobs in these part-heritage SICs, approximately 26,700 (25%) were employed in landscape and service activities.

Regional impact of the heritage sector

We provide below the regional distribution of heritage employment in 2022^{[footnote 46]}.

Figure 6: Distribution of heritage employment across English regions and UK nations (000s) in 2022/Source: ONS data, Cebr analysis

London and the South East were the regions where heritage employment was most concentrated in 2022, accounting for 18.1% and 14.6% of the total, respectively. Scotland and the rest of the English regions, except for the North East, made contributions to heritage employment of a broadly similar magnitude to each other (between 7.1% and 9.8% of total heritage employment).

4.2 Economic impact of the heritage sector over time

4.2.1 Gross Value Added

National impacts over time

Figure 7 presents chained volume measures of heritage sector GVA for the entire time series, from 2011–2022. All estimates included in this section are adjusted for inflation and in 2022 prices.

Figure 7: Heritage Sector GVA (£bn at 2022 price levels), CVM, 2011–2022 /Source: ONS data, Cebr analysis

From 2011 to 2022, the UK heritage sector GVA overall increased in real terms, from £12.4 billion in 2011 to £15.2 billion in 2022 (23%), despite moderate but brief dips in activity seen in 2012, 2017, 2019 and around the time of the COVID-19 pandemic. The £15.2 billion in heritage sector activity in 2022 is an increase of £1.7 billion (13%) on 2021, demonstrating not only a recovery from the impact of the pandemic, but also a new high point for value added by the sector. Prior to 2022, 2016 and 2018 were the years in which the heritage sector GVA was largest, at £14.3 bn.

The significant increase seen in 2022 was largely due to an increase in general construction activity beginning in 2021 and picking up pace in 2022 (as shown in Figure 8 below), which did not see a commensurate increase in construction-related heritage employment.

Figure 8: Heritage GVA by Industry, (£bn at 2022 price levels), CVM, 2011–2022/Source: ONS data, Cebr analysis

Figure 8 presents heritage GVA by the two-digit SICs in which the core heritage industries are grouped, and all other secondary heritage industries. While heritage activity in SIC 43 increased moderately by 12% between 2011 and 2022 in real terms, activity in SIC 91 was lower in 2022, at £1.8bn, than it was in 2011, at £1.9bn. Heritage GVA added by all other industries grew 54% over the same period, and the share of total heritage sector GVA added by secondary heritage industries grew from 32% in 2011 to 40% in 2022. This demonstrates that heritage-related work is increasingly being conducted outside of heritage-focussed organisations and traditionally heritage-associated industries, and is thus only possible to detect through SIC-SOC mapping of heritage-related occupations.

Regional impacts over time

Table 17 presents select data derived from chained volume measures of national and regional heritage sector GVA from 2011–2022. A full national and regional CVM series can be found in Appendix III.

Table 17: Change in the Heritage Sector’s GVA in real terms (£bn at 2022 price levels, and %)

Nation / Region	GVA, 2022 (£bn)	Change since 2021 (%)	Change since 2011 (%)
North East	0.4	16.1%	-2.6%
North West	1.4	16.9%	35.1%
Yorkshire and The Humber	1.0	14.5%	15.8%
East Midlands	0.9	15.8%	25.0%
West Midlands	1.1	19.5%	37.1%
East of England	1.4	10.8%	20.1%
London	3.0	6.2%	11.9%
South East	2.5	13.5%	33.1%
South West	1.3	15.5%	36.7%
England	13.1	12.8%	23.8%
Wales	0.5	16.2%	21.8%
Scotland	1.1	5.3%	5.8%
Northern Ireland	0.4	14.8%	16.4%
United Kingdom	15.2	13.0%	22.6%

Source: ONS data, Cebr analysis

London, the South East, and the East of England are consistently the 3 largest regions by heritage GVA, constituting an average of 20%, 16%, and 10% of UK GVA, respectively. The smallest regions by heritage GVA are consistently the North East (averaging 3% of UK total), East Midlands (6%), and Yorkshire and the Humber (7%).

Total heritage GVA attributable to the English regions grew from £10.6 billion in 2011 to £13.1 billion in 2022, a total growth of 24%. Among the nations, Scotland contributes the next largest share to the UK’s heritage sector, averaging 8% of the UK total. Wales contributes an average of 3%, and Northern Ireland 2%.

The regions which saw the largest real changes in heritage GVA between 2011 and 2022 were the South West (37%), West Midlands (37%), and North West (35%), whereas the regions which saw the smallest real GVA changes were the North East (-2.6%), Scotland (6%), and London (12%).

4.2.2 Employment

National impacts over time

Figure 9 presents heritage employment between the years 2011 and 2022.

Figure 9: Heritage employment in the UK (000s) between 2011 and 2022 / Source: ONS data, Cebr analysis

Between 2011 and 2022, heritage employment in the UK grew by 10.1%, from approximately 270,000 to 297,000 jobs, with the highest year-on-year growth (of 9.0% and approximately 25,000 jobs) achieved between 2021 and 2022. In absolute terms, sector employment peaked in 2017, when approximately 305,000 people were working heritage jobs.

Our analysis reveals a somewhat volatile trend in heritage employment over the sample period, with the years between 2015 and 2019 seeing larger contrasts year to year. This trend was primarily driven by the construction sector, as employment in the rest of heritage and part-heritage SIC codes remained broadly stable (as demonstrated further in Figure 11, in this section).

As the pandemic struck in 2020, heritage employment decreased by 4.6%, with heritage employment declining further in 2021, to approximately 273,000. The period between 2021 and 2022 saw considerable growth in heritage employment, although still leaving 2022 absolute heritage employment levels slightly below pre-pandemic levels.

Figure 10 presents heritage employment as a share of total UK employment between 2011 and 2022, and similarly reflects the trends described in Figure 9.

Figure 10: Heritage employment as a share of total UK employment (%) between 2011 and 2022 / Source: ONS data, Cebr analysis

As previously described, heritage employment as a share of the UK labour force did not follow a constant trend between 2015 and 2019, later followed by a decrease in 2020 and 2021, and subsequent post-pandemic moderate recovery. This could suggest that heritage sector employment was, on average, impacted more by the COVID-19 pandemic than the rest of the UK labour force.

Figure 11 provides further insight into the time series presented above, as we disaggregate heritage employment and present trends in each of the heritage and partially heritage SIC codes that make up the bulk of employment in the sector.

Figure 11: Heritage employment disaggregated by SIC code (000s) between 2011 and 2022/Source: ONS data, Cebr analysis

Figure 11 confirms the significant impact of construction industry trends on wider heritage employment. Specifically, jobs in the SIC codes included within 43.3 - Building completion and finishing experienced some volatility in the years between 2015 and 2019. Given that this SIC code accounts for the largest share of heritage employment up to 2019, these trends made a noticeable impact on the employment estimates in the sector.

As to the effect of the pandemic on heritage employment, the trough reached in 2021 is explained by falling employment in most of the primary and secondary SIC codes between 2020 and 2021, with Museum activities seeing the largest drop..^{[footnote 47]} Secondary SICs, further, considerably contributed to the post-pandemic heritage employment recovery, being the largest contributor to heritage employment by 2022. In particular, upticks in employment in SIC division 81 - Services to buildings and landscape activities and division 74 - Other professional, scientific and technical activities were main drivers of recovery for the employment of the sector after COVID-19.

Regional impacts over time

Table 18 presents select data of national and regional heritage sector employment from 2011–2022. A full national and regional employment series can be found in Appendix III.

Table 18: Change in the Heritage Sector’s employment (000s, or %)

Nation / Region	Employment, 2022 (000s)	Change since 2021 (%)	Change since 2011 (%)
North East	8	-8.1%	-21.2%
North West	29	0.5%	3.4%
Yorkshire and The Humber	23	1.7%	8.8%
East Midlands	22	17.9%	25.1%
West Midlands	21	-1.4%	12.4%
East of England	27	-0.3%	21.4%
London	53	43.5%	6.7%
South East	43	5.0%	18.7%
South West	28	12.9%	9.2%
England	253	10.5%	10.7%
Wales	13	10.4%	19.3%
Scotland	21	-9.9%	-12.3%
Northern Ireland	6	-5.5%	43.4%
United Kingdom^{[footnote 48]}	297	9.0%	10.1%

Source: ONS data, Cebr analysis

Between 2011 and 2022, London has most consistently made the largest absolute contributions to heritage employment in the UK, accounting for approximately 53,000 heritage jobs in 2022. The large growth seen in the capital between 2021 and 2022 (up by 43.5%) captures the post-Covid recovery period after a particularly stark decline of the regional construction industry during the pandemic (causing a fall in the region’s heritage employment of 30.4% in 2021). By 2022, heritage employment in London had fully recovered, up by 1.6% relative to 2019.

Northern Ireland and the East Midlands saw the largest relative increase to their heritage employment between 2011 and 2022, of 43.4% and 25.1%, respectively. On the other hand, the North East and Scotland were the only 2 regions to decrease their total number of heritage jobs between 2011 and 2022, down by -21.2% and -12.3%, respectively.

Question 5

5. Evaluating the feasibility of producing trade and business statistics

Accepted Answer

A secondary objective of this project was assessing the feasibility of addressing one of the SIC-SOC methodology’s current limitations: the lack of production of trade and business demography statistics for the heritage sector. Estimates for trade and the number and size of businesses are typically included within DCMS Sector Economic Estimates for DCMS Sectors, with only minor exceptions.^{[footnote 49]} Therefore, the lack of these estimates for the heritage sector under a SIC-SOC methodology would create issues in the generation of consistent data sets, were heritage estimates following this bespoke methodology to be added to other DCMS sectors within official data releases in the future. Equally the lack of data pertaining to heritage trade and business demography constraints understanding of specific business or trade-related activity or understanding of demographics and detail within this. For example, currently under a SIC-SOC methodology, data cannot be provided to assess whether heritage organisations are larger or smaller than the average UK business, or whether the heritage sector has a net positive or negative effect on the UK’s balance of trade.

Their omission arises from the inherent features of a SIC-SOC methodology, which has been identified as the optimal approach for the calculation of GVA and employment estimates. This is also the reason why similar prior research conducted by Cebr for Historic England has focused on GVA and employment as variables, rather than trade or business statistics. This is noted by Alma Economics within their feasibility study that preceded this report:

‘One notable limitation of this [SIC-SOC] methodology is its inability to generate trade statistics, or other metrics that rely solely on industrial codes, such as number and size of businesses in the sector. The SIC-SOC mapping enables the attribution of a share of a given industry employment or GVA to the heritage sector. However, this mechanism cannot be directly applied to other statistics. In other terms, the share of an industry attributed to the heritage sector for employment or GVA purposes may not reflect its proportion in trade statistics, also considering that heritage goods and services are often not tradable, and when they are, they are most likely captured by trade figures of other sectors, such as arts, craft, and museums.’

By contrast, solely SIC-based sectoral estimates, such as those produced for many other DCMS sectors, better facilitate estimating business demography and trade figures than any SIC-SOC approach can. Other sectors, when mapped at the four- or five-digit SIC level, can be cross-referenced with wider business demography and trade data, with data for constituent SIC codes aggregated to produce estimates for DCMS sectors.^{[footnote 50]} This is the approach typically taken for other DCMS sectors. Challenges related to this arise for a SIC-SOC approach when estimating the economic activity identified through heritage occupations rather than industries, as wider business or trade statistics do not typically consider occupation as a variable within data collection. This makes it problematic to directly link trade or business demography statistics to employment identified through occupations.

This challenge at face value is partially overcome within this project, as we estimate the distribution across all four- and five-digit SIC codes of employment in heritage SOCs. By mapping employment and GVA exclusively to SIC codes, it may be assumed that the subsequent SIC-based steps for other DCMS sectors can be followed. This would entail compiling and then aggregating business demography and trade estimates for heritage SIC codes, with impacts potentially prorated where only a share of a SIC code is considered part of the heritage sector. For example, for SIC codes for which a percentage of employment is part of the heritage sector, you could theoretically assume that an equal percentage of imports and exports for that SIC code are attributable to the heritage-related component of the sector.

However, the validity of this assumption, both for trade and business demography, is questionable. We explore this further separately for trade and business statistics, before discussing options and ultimately making recommendations, within the next subsections.

Trade

For 3 SIC codes – archive activities, museum activities and the operation of historical sites, buildings and similar visitor attractions - the entirety of the SIC is included within the heritage definition. Given the nature of these SIC codes, extensive trade in either goods or services is unlikely;^{[footnote 51]} however, to the extent that this does occur, it could still be identified through the typical DCMS methodology for trade statistics.

For other SIC codes, in which a share of activity is considered a part of the heritage sector, the optimal means for estimating imports and exports would be to calculate heritage-specific import and export propensities by sector. In economics, these propensities refer to the percentage of goods and services imported or exported: for example, a heritage sectoral export propensity would be calculated by dividing the value of the sector’s heritage exports by total heritage production within the SIC.

For specific heritage activity within a SIC code, it is likely that these propensities vary relative to the import or export propensity for all activity within the SIC. If this were the case, it would mean that the assumption that the share of imports and exports for a SIC code attributable to the heritage-related component of the sector is equal to the share of employment attributable to heritage is unlikely to be robust.

To best demonstrate this, consider heritage-related construction, which is a significant component of both total heritage employment and total heritage GVA. By definition, within this report heritage-related construction is estimated by considering the construction and maintenance occurring on UK buildings that were built pre-1919. It is therefore not possible for this construction activity on UK buildings to represent an export, yet the UK is a significant exporter of construction services (per UK Pink Book data).The heritage export propensity in construction-related SIC codes should therefore be zero (or very low)^{[footnote 52]} while the overall export propensity across UK construction is clearly higher.

Undertaking survey-based work of heritage institutions and occupation workers to understand the share of goods and services that are imported and exported, would be an optimal approach to address this issue. If a sufficient sample size of heritage workers within each SIC known to include heritage employment could be accessed, import and export propensities could be calculated, for specific heritage work within each SIC. These propensities, relative to the average propensity across the entirety of each SIC code, could then be used to apportion total imports and exports by SIC, to estimate solely the heritage-related component. Aggregating across all SIC codes would give a robust estimate for total heritage-related trade.

This of course would be a significant endeavour, given the high number of SIC codes with a small share of heritage employment within them. An alternative, simpler approach would be the following:

1. Include all trade identified within the archives, museums, and operation of historical sites, buildings and similar visitor attractions SIC codes. As the entirety of each SIC is included, this can be done in a manner consistent with wider DCMS Economic Estimates.

2. For construction-related SIC codes, assume that no trade occurs, for the conceptual reasons set out above.^{[footnote 53]}

3. For all other SIC codes, include the entirety of the trade if a certain significant threshold for the importance of heritage within the SIC code is reached. For example, if more than 50% of the industry is part of the heritage sector (per employment shares), the SIC could be considered one in which principal activity is heritage-related, and thus the entirety of the SIC’s trade could be included, utilising existing DCMS approaches. While something of a simplification, this follows the precedent of the approach for both the selection of creative industries SIC codes (a SIC is fully included if a certain proportion of occupations in the industry are considered creative) and tourism industries business demography statistics (all businesses within a SIC are considered part of the tourism industries, if the SIC is one in which the principal activity is a ‘tourism characteristic activity’).

Both approaches have weaknesses: the survey-based analysis would be very resource intensive and the required employees tricky to sample, while the simpler approach would likely slightly underestimate trade in the heritage sector, due to exclusion of SICs with a positive but low level of heritage activity. However, the lack of a perfect approach is a function of utilising a SIC-SOC methodology and the fundamental incompatibility of this with existing wider trade data.

Business demography

Heritage business demography estimates are challenging from both a conceptual and data-related perspective. Conceptually, the classification of an organisation with some but not all heritage workers within it is tricky. For example, if a building maintenance firm undertakes some projects on heritage buildings and some work on non-heritage buildings, subsequently employing some heritage specialists and some non-specialists, should this be classified as a heritage organisation? Should it make a difference if the share of heritage-related work is 10%, 40% or 90% of all work?

Even withstanding these conceptual considerations, from a data-related perspective it is challenging to estimate the number of organisations undertaking heritage-related work. For SIC codes which are entirely part of the heritage sector (archives, museums, and operation of historical sites, buildings and similar visitor attractions), all organisations within the SIC can be considered heritage organisations. Estimates for the number and size of businesses can be sourced utilising the methodology for other DCMS sectors, primarily utilising Inter-Departmental Business Register (IDBR) data, as provided by the ONS. However for SICs which are partially heritage, either of the following could theoretically be true:

1. Heritage-related projects are split equally between all businesses within the SIC. Therefore, all businesses undertake some heritage work.

2. Heritage-related projects are concentrated within a small number of specialised businesses. Therefore, the share of businesses within the SIC undertaking heritage work is low; potentially even lower than the total share of employment within the SIC that is heritage-related.

From existing data sets, it is not possible to evaluate which of these is true, or where in the middle the answer lies for each SIC. Optimally, this could be ascertained through surveys of heritage organisations across all SIC codes defined as part of the heritage sector (asking questions on the share of heritage-related work), through surveys of all organisations within the SIC (asking questions on if they undertook heritage-related work and the share of this), or potentially through exploration of the capabilities of ‘big data’ approaches.^{[footnote 54]}

With this data, it would then be possible to estimate the proportion of businesses within a SIC, undertaking differing levels of heritage-related work. From this point a decision, perhaps in tandem with wider industry consultation, could be made for a ‘cut-off’ value, denoting the minimum share of work within a business that needs to be heritage-related for that business to be classified as a heritage business. Combining these findings, an estimate could be produced within each SIC, for the share of businesses above this ‘cut-off’ percentage that are therefore classified as heritage businesses.

Extrapolating as needed to IDBR data (in line with the wider DCMS demography methodology), the number of heritage businesses within each SIC could be identified. Aggregating these would yield estimates for the whole heritage sector.

Question 6

6. Conclusion

Accepted Answer

The aim of this research was to develop a bespoke methodology to estimate the economic contribution of the heritage sector within the UK, which could in the future be used to produce official DCMS Economic Estimates for the Heritage sector. This report develops a methodology which more comprehensively captures the true scale of the heritage sector’s contribution to the economy, relative to the current narrower DCMS proxy – Operation of historical sites and buildings. It does this by implementing the SIC-SOC mapping approach, as used in research for Historic England between 2018-2024, and as recommended by Alma Economics’ feasibility assessment.

Therefore, this new methodology builds upon the research conducted for Historic England, refining the selection of industries and occupations included as part of the heritage sector using official data, evidence produced by the heritage sector, and relevant organisations. Additionally, unlike the Historic England reports, the new methodology maintains consistency, as closely as possible, with DCMS Economic Estimates methods, allowing this methodology to be used to produce official sector economic estimates, if DCMS so wished. Furthermore, the estimates calculated in this report cover the heritage sector throughout the UK (with breakdowns by region), while the Historic England reports only consider the heritage sector within England.

When comparing the contribution of the heritage sector in 2022 as calculated in this report with the current DCMS proxy, we find a significant difference in the magnitude of the figures. Specifically, the new methodology finds a total GVA contribution of £15.2bn and a total employment of 297,000, while the DCMS finds a GVA contribution of £0.7bn and a total employment of 10,000.

The discrepancy in economic impact between this report and the current DCMS proxy, is of course driven by the broader definition implemented in this report. Specifically, by examining the breakdown of GVA in the heritage sector and constituent SIC codes, we find that the largest contributors to the heritage sector are the SIC codes related to the construction sector. This is due to the high level of related employment identified and the highly skilled nature of the work performed. Additionally, when considering the total employment in the heritage sector, the ‘secondary’ SIC codes, which are those that are not heritage industries but that employ heritage occupations (SOCs) make up nearly a third of the total employment within the heritage sector. This is employment which would otherwise be excluded if we followed a simple SIC code-based approach.

These findings not only highlight the economic importance of the heritage sector in the UK for the value of those in the sector but also have potential policy-related connotations. This could manifest in terms of recognition, funding, and wider support from government, particularly if DCMS does adopt a broader definition for the heritage sector in the reporting of economic statistics, as proposed within this report.

Although this report proposes a methodology that allows for a broader and more accurate estimate of the true size of the heritage sector, this is still not necessarily exhaustive. As touched upon earlier in the report, one of the advantages of the SIC-SOC methodology proposed, is that it facilitates the identification of employment (and subsequently also GVA) through both heritage SICs and heritage SOCs. However by extension, this employment still needs to be identifiable through the utilisation of these existing classification systems, as this is a prerequisite for consistent reporting within DCMS Sector Economic Estimates, and the UK’s reporting of official economic statistics. In instances where heritage activity occurs outside of these frameworks, or it still cannot be robustly identified within these frameworks, our methodology is unlikely to fully capture the associated economic impact.

While working through the development of this project’s methodology, several instances of this occurring were identified. These include the following:

1. Activity dependent on heritage assets, but which does not map well to identified heritage SIC or SOC codes. This includes the operation of heritage properties as commercial assets, such as accommodation, event spaces or sports venues. In instances in which these organisations report as a SIC code the activity that they facilitate, rather than their operation of a historical building, the current methodology is unlikely to identify this activity.^{[footnote 55]}

2. In SICs or SOCs, in which a proportion but not all activity is heritage-related, and a reliable proxy is not available to quantify this proportion, we are unable to include this activity. A good example of this is heritage-related transport. The operation and maintenance of heritage transport (for example heritage railways and rolling stock) could theoretically be included, as we include similar activity for the maintenance of heritage buildings. Unfortunately, while we were able to estimate the share of maintenance associated with heritage buildings (by considering the share of all buildings constructed pre-1919, per VOA data), similarly robust data was not accessible for transport. Given the level of robustness required for further DCMS purposes, some known activity is therefore not currently able to be captured within this methodology.^{[footnote 56]}

3. As prescribed by the scoping report that preceded this report, the focus of this research is only tangible heritage, due to their relatively greater ease of being mapped to SICs and SOCs. Further research could look to include this, although challenges associated with comprehensively mapping to SICs and SOCs are likely to remain.

4. The key data source for the estimation of employment figures was the Annual Population Survey. This has notable strengths in its coverage, such as inclusion of the self-employed (including sole traders) and individuals working for small organisations who are not large enough to be VAT registered. Both segments can at times be excluded from other business statistics, but their employment and GVA is reflected within this analysis. However, volunteers are not currently included, as voluntary work is not included within the APS variable used in this research, to identify the industry and employment of individuals. Therefore voluntary employment is not included within our headline employment estimates, while GVA generated by volunteers is likely to be imperfectly measured.^{[footnote 57]}

These limitations reflect the ongoing challenges measuring a sector that is so diverse, and for which significant work is needed to map even components of the sector to official frameworks of reporting economic statistics. While this report and the associated methodology capture a significantly broader range of the heritage sector, with benefits regarding both recognition and policy, clearly the current definition is not necessarily exhaustive.

However, as with all fragmented or complex sectors, there is a trade-off between increasing methodological complexity in an iterative manner in the pursuit of exhaustive figures, and balancing requirements with economic statistics for the approach to be both replicable in an efficient manner and consistent with existing reporting frameworks. The current proposed methodology and associated findings are an attempt to balance these competing needs, facilitating an approach that is both valuable for the sector and for DCMS to use in the future.

Question 7

Appendix I: Further technical material related to SIC-SOC mapping

Accepted Answer

This appendix consolidates additional detail on the SIC-SOC mapping process, and addresses the varied technical challenges and conceptual questions that arose during the research.

Rationale for only including proportions of construction SIC codes

Presenting the initial list of SIC codes to this research project’s steering group, made up of heritage sector professionals, resulted in several questions being raised about the ‘core’ SIC codes included and those that are potentially missed. Specifically, questions were raised around why construction industries had a proportion of their activity attributed to the heritage sector, and no other industries received the same treatment. Some of the industries mentioned by the heritage professionals were heritage transport, including heritage trains and ships, as well as heritage buildings being used as event spaces such as wedding venues.

The reason these other industries which do undertake some heritage work are not included in the list of ‘core’ SIC codes is because there is no evidence base to quantify the share of these industries that belong to the heritage sector. We are only able to estimate the heritage construction industry because of the 2024 Skills Needs Analysis which provides an estimate of the number of construction workers who use heritage skills on heritage construction sites. This allows us to create an estimate of the repair and maintenance construction SIC codes (43.3 and 43.9), that belong to the heritage sector. However, when considering the heritage buildings that act as wedding venues, an equivalent resource to the 2024 Skills Needs analysis does not exist, making it difficult to accurately determine the share of this industry that belongs to the heritage sector, which we could theoretically do if a resource detailed the share of wedding venues that are heritage buildings. Therefore, the lack of evidence related to the heritage sector share of these other industries makes it unfeasible to include them as part of the heritage sector in the current research. However, if a heritage building is used as a wedding venue but self identifies as a heritage SIC code like ‘Operation of historical sites and buildings’, it will be captured in our analysis. Overall, we agree that the true size of the heritage sector is larger than the list of SIC and SOC codes we consider ‘core’, and therefore, we join the steering committee of this project in calling for more research to be done on the heritage share of industries not directly considered in our analysis, such as heritage wedding venues and heritage transport. This research will help in future refinement of the size of the heritage sector, as we hope it will help quantify the share of these industries that belong to the heritage sector.

Despite the explicit inclusion of some SIC codes which undertake heritage activities, the use of our SIC-SOC methodology does allow us to capture heritage employment in non ‘core’ heritage industries. Therefore, if an industry does employ people who undertake a heritage job, they are included through the ‘secondary’ SIC mechanism detailed in Section 3. This means that we do partially capture some industries through their employment of heritage occupations, making our estimate of the heritage sector wider and more comprehensive than a simple SIC based approach, which only considers the ‘core’ heritage industries.

Rationale for SIC based approach instead of SOC base approach for the construction industry

As discussed in Section 3.3, Historic England’s report, produced by Harlow Consulting in 2024 and entitled “Skills Needs Analysis: For the Repair, Maintenance and Retrofit of Traditional (pre-1919) Buildings in England”, estimates the employment of construction workers utilising heritage-related skills. It does this through considering the broad construction-related roles undertaking these tasks (through data provided by the Construction Industry Training Board), and further the share of individuals within these roles, undertaking specifically heritage-related work. When evaluating the utilisation of Harlow Consulting’s research for the development of this project’s methodology, consideration was given as to whether mapping this employment to wider SIC codes or wider SOC codes, was more appropriate.^{[footnote 58]}

On balance, our view was that utilising SIC codes would be more accurate, for several key reasons:

1. SIC codes allow us to capture construction businesses that solely work on heritage buildings. Using SIC codes enables the inclusion of construction businesses that exclusively work on heritage sites (for example Donald Insall Associates and Carrek Limited). For these businesses, the entirety of their workforce should be considered as part of the heritage sector, which our utilisation of SIC codes allows us to do.

2. Utilising SOC codes and apportioning across SIC in which these occupations work, would risk including heritage employment in SIC codes that do not undertake heritage-related work. If we used SOC codes to account for the activities listed in the 2024 Skills Needs Analysis, which includes painters, plasters, floorers and more, we would likely find employment in SIC codes we know are unrelated to heritage. This is because these occupations are employed across a multitude of SIC codes, some of which, for example SIC 41: Construction of buildings, only relate to the construction of new (i.e. non-heritage) buildings. Utilising SIC codes allows us to more accurately identify heritage employment specifically in industries which logically undertake heritage-related work.

By applying this refined methodology, heritage construction employment estimates remain robust, data-driven, and aligned with real-world sector activity.

Detailed description of NLHF funding analysis

The starting point for this analysis was the National Lottery Heritage Fund grants data set, which details the organisations that received grant funding between April 1^st 2013 and December 19^th 2024. This data set lists the name of the organisation, the company number^{[footnote 59]} (if applicable), and the grants awarded to the organisation.

However, this data set does not provide SIC codes. Since Companies House requires each organisation with a company number to declare a SIC code based on the main activity of the organisation, it is separately possible to map each recipient’s company number to the declared SIC code(s), allowing us to identify which SIC codes received NLHF grants.

To do this, Companies House mapping files were used to link grant recipients to their SIC codes. This approach was taken for all organisations with a company number, and all organisations from the same SIC code were aggregated to estimate the total grants received per SIC. The results from this analysis are presented in Table A.

Table A: Top 50 SIC codes, sorted by NLHF-grants sum and with % of market turnover that 2013 – 2024 grants are equivalent to.^{[footnote 60]}

Top 50 List	SIC Code	Total Award (£000’s)	Market Turnover (£000’s)	Ratio
1	91.020 - Museums activities	166172.08	779269	21.32%
2	91.030 - Operation of historical sites and buildings and similar visitor attractions	113952.538	623551	18.27%
3	94.990 - Activities of other membership organizations n.e.c.	49634.892	5361224	0.93%
4	91.040 - Botanical and zoological gardens and nature reserves activities	42453.086	721892	5.88%
5	85.520 - Cultural education	37828.63	416949	9.07%
6	88.990 - Other social work activities without accommodation n.e.c.	29099.51	9509728	0.31%
7	74.909 - Other professional, scientific and technical activities n.e.c.	28275.835	11444364	0.25%
8	90.040 - Operation of arts facilities	27921.829	734162	3.80%
9	36.000 - Water collection, treatment and supply	22539.29	16012803	0.14%
10	85.590 - Other education n.e.c.	22454.628	9522579	0.24%
11	90.010 - Performing arts	21416.73	4379588	0.49%
12	90.030 - Artistic creation	21228.548	4124430	0.51%
13	93.290 - Other amusement and recreation activities n.e.c.	20171.686	2599559	0.78%
14	96.090 - Other personal service activities n.e.c.	20106.586	8660662	0.23%
15	82.990 - Other business support service activities n.e.c.	18289.12	58287510	0.03%
16	74.990 - Non-trading company	12259.346	-	n/a
17	85.600 - Educational support services	11322.404	2051041	0.55%
18	94.910 - Activities of religious organizations	10683.241	1303951	0.82%
19	91.012 - Archives activities	9790.968	66647	14.69%
20	91.011 - Library activities	9774.942	110525	8.84%
21	02.100 - Silviculture and other forestry activities	9517.422	1510256	0.63%
22	68.320 - Management of real estate on a fee or contract basis	9469.468	13580507	0.07%
23	68.209 - Other letting and operating of own or leased real estate	8367.174	28780388	0.03%
24	74.901 - Environmental consulting activities	7083.762	2254208	0.31%
25	90.020 - Support activities to performing arts	7029.983	1828718	0.38%
26	81.300 - Landscape service activities	4820.561	6366441	0.08%
27	85.320 - Technical and vocational secondary education	4607.876	3195362	0.14%
28	70.229 - Management consultancy activities other than financial management	4373.905	71934657	0.01%
29	88.910 - Child day-care activities	4344.2	5263390	0.08%
30	86.900 - Other human health activities	3636.524	13227054	0.03%
31	49.100 - Passenger rail transport, interurban	3361.1	11798639	0.03%
32	02.400 - Support services to forestry	3285.228	350730	0.94%
33	88.100 - Social work activities without accommodation for the elderly and disabled	3231.599	7574314	0.04%
34	41.100 - Development of building projects	3115.861	35729646	0.01%
35	79.909 - Other reservation service activities n.e.c.	2989	1013589	0.29%
36	43.999 - Other specialised construction activities n.e.c.	2914.826	13264165	0.02%
37	85.200 - Primary education	2648.096	5415073	0.05%
38	59.111 - Motion picture production activities	2270.342	3973502	0.06%
39	13.200 - Weaving of textiles	2070.886	732543	0.28%
40	96.040 - Physical well-being activities	1950.319	472693	0.41%
41	72.200 - Research and experimental development on social sciences and humanities	1864.702	420117	0.44%
42	03.220 - Freshwater aquaculture	1799.5	276913	0.65%
43	82.110 - Combined office administrative service activities	1633.026	4441418	0.04%
44	72.190 - Other research and experimental development on natural sciences and engineering	1628.511	41517146	0.00%
45	55.900 - Other accommodation	1595.413	1399498	0.11%
46	01.450 - Raising of sheep and goats	1534.6	-	n/a
47	47.190 - Other retail sale in non-specialised stores	1488.618	34457680	0.00%
48	93.199 - Other sports activities	1356.882	5292777	0.03%
49	85.310 - General secondary education	1297.339	4566922	0.03%
50	63.990 - Other information service activities n.e.c.	1296.537	1992584	0.07%

Source: NLHF

While 91.020, 91.030 and 91.040 all feature in the top 4, of the 2 heritage-related construction ‘core’ SIC codes, (43.3 and 43.9) only one constituent five-digit SIC code, 43.999,^{[footnote 61]} is featured in Table A. All other five-digit SIC codes that make up SIC codes 43.3 and 43.9,^{[footnote 62]} do not feature in Table A, as these five–digit SIC codes did not receive any grants from the NLHF between 2013 and 2024.

We hypothesise that this may be due to construction firms typically being contracted by heritage-focused organisations in other SIC codes, rather than applying for grants directly. Consequently, they appear less frequently as lead recipients in the NLHF data. Further research, as discussed in Section 3.3, corroborates the inclusion of these 2 SIC codes, beyond simply this hypothesis.^{[footnote 63]}

When examining the SIC codes not included in the Historic England report (or non-core Heritage SIC codes), as discussed in Section 3.3, 4 have a notably higher grant to turnover ratio than others. These are 85.520 - Cultural Education; 90.040 - Operation of Arts Facilities; 91.040 - Botanical and zoological gardens and nature reserve activities; and 91.011 - Library activities. Despite the evidence that these SIC codes do receive a substantial amount of grants, including these SIC codes within the heritage sector comes with few conceptual challenges. Each of these are explored below:

Cultural education

Cultural education registers the highest grant-to-turnover ratio among non-core^{[footnote 64]} heritage SIC codes. Although a portion of its activities may relate to heritage, determining exactly how much is heritage-focused remains challenging. This is because there is no evidence base that allows us to distinguish between the heritage and non-heritage part of the cultural education sector. Therefore, there is no clear method we can use to accurately determine the share of this SIC code which belongs to the heritage sector.

Additionally, culture education comes with conceptual challenges that arise due to its status as an intangible heritage asset.^{[footnote 65]} Therefore, on balance, we do not include cultural education within the heritage sector.

Operation of arts facilities

The operation of arts facilities primarily encompasses roles related to facilitating, managing, and hosting artistic events. Although some of the grants in this category may finance heritage exhibitions or performances, much of the wider activity associated with operating the facilities are not exclusively heritage-focused, while many activities within these facilities often extend into broader cultural realms. Hence, on balance, this industry was not incorporated into the heritage sector.

Botanical and zoological gardens and nature reserve activities

Botanical and zoological gardens and nature reserve activities focus on the operation of the aforementioned gardens and reserves, along with wildlife preservation. Much of the activity within this SIC code, such as the preservation of wildlife from around the world in zoos, is unrelated to the UK’s heritage sector. This SIC code is therefore not included within our analysis.

Library activities

Library activities revolve around the services provided by libraries including book lending, storage and the preservation of collections. Although some of this work will include the preservation of heritage assets, in the form of heritage documents and manuscripts, overall, there is no objective data that allows discernment of the proportion of the work in libraries that is heritage related. Therefore, on balance, we do not include libraries within the heritage sector as they face similar issues to the cultural education sector.

Description of activities that occur in reclassified SOC 2020 codes

Table B: Description of activities that occur in the reclassified SOC 2020 codes

SOC 2020 code	Proportion included	Reason for proportion	Inclusion type
2472: Archivist and Curators	100%	All work in the SOC code is related to heritage preservation through conservation of books and other collections.	Full
2151: Conservation professionals	100%	All work in the SOC code is related to the preservation of natural heritage, specifically National Landscapes.	Full
2115: Social and Humanities Scientists	16.9%	Proportion is equal to the number of Archaeologists in the UK in 2022 from the Federation of Archaeological Managers and Employers, divided by the total number of first and second jobs in the SOC code from the APS.	Partial
2451: Architects	20.5%	Proportion equal to the share of pre-1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings built before and after 1919.	Partial
2454: Chartered Surveyors	20.5%	Proportion equal to the share of pre 1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings build before and after 1919.	Partial
3114: Building and Civil Engineering Technicians	20.5%	Proportion equal to the share of pre 1919 buildings out of the total UK building stock. This assumes that construction work is evenly distributed between buildings built before and after 1919.	Partial
5113: Gardeners and Landscape Gardeners	17.4%	Proportion equal to the number of landscape gardeners working on heritage gardens and parks and heritage buildings with gardens.	Partial

Source: ONS

Detailed description of ESPON framework

The ESPON heritage framework highlighted in Alma Economics’ report presents a new perspective for identifying the industries related to the heritage sector. Section 4.3 of the ESPON paper discusses the notion that in further sectors (architecture, tourism, ICT, insurance and real estate),^{[footnote 66]}a portion but not the entirety of the sector is associated with heritage activity. For these sectors, proxy indicators – referred to as “keys” – can be used to estimate the proportion of activity attributable to heritage. For example, in tourism the proportion of tourists’ spend for travelling for heritage-related leisure purposes are proposed as an indicator, whilst in ICT and insurance, expenditure in the respective sectors by ‘material cultural heritage’^{[footnote 67]} agents are suggested.

To identify sectors related to heritage, we used input-output table modelling, applying the share of expenditure from “core” heritage to identify broader heritage sectors, the same proxy that ESPON applied to ICT and insurance. This approach implicitly assumes that spending in these sectors by heritage organisations supports heritage-related economic activity (i.e. if X% of spending on insurance was for heritage purposes, X% of the insurance sector’s own economic contribution is assumed to be heritage-related).

This exercise began by defining our “core” heritage SIC codes to be used as the basis for locating broader heritage activity, i.e. the SIC codes in Table 1. Leveraging a similar conceptual approach to ESPON, we then used Office for National Statistics’ (ONS) Supply and Use Tables for the UK to estimate the expenditure from ‘core’ heritage SIC codes on all other SIC codes in the UK economy, rather than limiting consideration to a select pre-chosen few. As our core heritage SIC codes did not perfectly align with those in the supply and use tables (which are often published at a two-digit SIC level), we also had to apply relevant SICs within the supply and use tables with appropriate weights. To estimate these weights, we used ONS data from the Annual Business Survey to ascertain the proportion of total turnover attributable to the relevant SIC codes for 2022 (the most recent year for which data was available), to proxy the share of expenditure attributable specifically to the heritage component of each SIC.

Using this approach, we estimated the expenditure from core heritage industries on all other sectors. For sectors experiencing a high share of expenditure from core heritage (above 0.5%), a shortlist was developed both based upon the data, and judgement as to whether the SIC had an appropriate conceptual link to heritage.^{[footnote 68]} As part of this process, we also breakdown the SIC codes listed in the supply use tables into the ‘core’ SIC codes, where appropriate, to determine the proportion of spending coming from ‘core’ heritage industries. For example, the supply and use tables classify the whole construction sector as one group (i.e. SIC codes 41, 42 and 43 are grouped together). However, we are only interested in expenditure from 43.3 – Building completion and finishing and 43.9 – Other specialised construction activity. To deal with this, because 43.3 accounted for 4.0% of the total turnover for construction, and 43.9 accounted for 2.4% of the total, we can assume that 6.4% of the expenditure from construction is heritage related. This allows us to capture the spending attributable to only ‘core’ heritage SIC codes.

As an example of a ‘supported’ SIC for inclusion, 0.9% of total demand for services to buildings and landscapes stems from ‘core’ heritage SIC codes. This is intuitively important for heritage as it provides direct support services for physical heritage assets (i.e. cleaning and landscaping for heritage properties) and thus was deemed suitable for inclusion. The final shortlisted set of SIC codes, which we refer to as ‘supported SICs’, is presented below.

Table C: The SIC codes and proportions for “supported” SICs’

SIC codes	Name	Share of SIC code that could potentially be included
16	Manufacture of wood and products of wood and cork, except furniture; manufacture of articles of straw	2.6%
231 - 234, 237 - 239	Glass, refractory, clay, porcelain, ceramic, stone, and abrasive products	2.0%
7732	Renting and leasing of construction and civil engineering machinery and equipment	1.8%
203	Manufacture of paints, varnishes and similar coatings, printing ink, and mastics	1.6%
80	Security and investigation activities	1.2%
81	Services to buildings and landscape activities	0.9%
932	Amusement and recreation activities	0.7%
1812	In descriptive terms, printing other than for newspapers.Other printing ^{[footnote 69]}	0.6%

Having compiled the list of ‘supported SICS’, we ultimately decided against introducing them into our heritage definition. This was done to maintain consistency with other DCMS sectors, which do not include supported activity in their estimates, analysing the direct contribution of the sector. However, further research with broader purposes – for example if not bounded by definitional consistency with other DCMS sectors – may want to consider the inclusion of shares of these supported SICs.

Addressing Alma Economics’ suggestion to reclassify the heritage cutoff date

Alma Economics’ feasibility assessment suggests that the date of construction for a building to be considered a heritage building could potentially be revised from pre-1919 (excluding 1919) to pre-1945 (excluding 1945). They state that there could be merit in reconsidering the cutoff date for heritage construction, as it would allow important interwar architecture to be considered as part of the heritage sector (including the Piccadilly tube line and Art Deco architecture).

In assessing the rationale for using 1919 as the cutoff for heritage classification, we examined the underlying reasoning behind this distinction. The year 1919 is significant due to the construction techniques and materials commonly used before this period, which changed notably around this point.

This is referenced across multiple sources, including Historic England’s report on understanding listed buildings in Wales, which sets out that pre-1919 buildings were constructed without cavity walls and relied heavily on materials such as stone and wood. This classification is further supported by the Construction Industry Training Board (CITB), which concurs with Historic England in defining heritage buildings as those utilising solid wall construction; a technique that largely ceased in 1919.

Given this widely accepted definition, this report maintains the classification of heritage buildings as those constructed before 1919. This ensures consistency with leading authorities in the heritage construction sector, while also recognising the evolution of construction techniques after 1919, which replaced traditional heritage methods.

Calculation of the proportion of SOC code 5113: Gardeners and Landscape Gardeners, that belong to the heritage sector

As outlined in Section 3.4.2, SOC code 5113 includes individuals working on both heritage and non-heritage assets. Without a singular clear proxy for the share of gardeners working on heritage gardens across the UK, we evaluate this on a SIC-by-SIC basis.

SIC Code 81300: Landscape Service Activities

The SIC code with the highest level of employment amongst gardeners, is landscape service activities. Employment within this SIC/SOC pairing, covers gardeners maintaining parks, gardens, and green spaces.

Historic England reports that England has over 1,700 listed parks and gardens covering 176,325 hectares.^{[footnote 70]} These sites are considered part of the natural heritage sector and are therefore included in our analysis. To estimate the proportion of gardeners working on these heritage sites, we compare the total area of listed parks and gardens (176,325 hectares) with total relevant land managed (913,220 hectares),^{[footnote 71]} as estimated per the Land Use Statistics: England 2022 data set. This yields a heritage proportion of 19.3%, which is applied to the total employment in SIC 81.300 (130,143 gardeners). As a result, we estimate that 25,118 gardeners work on heritage-related parks and gardens.

This methodology assumes that listed gardens and parks in England as a share of all gardens and parks in England, is representative of the UK as a whole. Due to data availability, England-level data is used to estimate the share of heritage gardeners in SIC 81.300 across the UK.

Other Relevant SIC Codes

Additional SIC codes employing heritage gardeners include:

Hotels (SIC 55.100)
Real estate rental (SIC 68.201)
Public administration (SIC 84.110)
Membership organizations (SIC 94.990)
Households employing staff (SIC 97.000)

Data on the distribution of gardeners working on gardens attached to heritage buildings relative to non-heritage buildings is limited. As a proxy, equivalent to arguments around some construction and building maintenance-related SOC codes, we use the percentage of buildings in the UK which were built before 1919 (20.5%). This method does not account for differences in average garden size, maintenance needs, or likelihood of professional gardening services, and further research would be ideal in this area.

The estimated figure of 20.5% is then used as a proxy for the share of total employment within these SIC/SOC pairings, that is likely to be undertaking heritage work.

Combining these estimates, total heritage gardener employment is estimated to be 30,018 in 2022, or 17.4% of total employment in SOC code 5113 (172,519). This estimate of 17.4% is used across all years.

Table summarising the key assumptions for the partial SIC and SOC codes included in our analysis of the heritage sector

Table D: Key assumptions used to determine the share of SIC and SOC codes included in our analysis

SIC code	Proportion included	Rationale behind this proportion
91.012: Archive activities	100%	Included in its entirety as archives aim to maintain and preserve collections of heritage assets.
91.020: Museum activities	100%	Included in its entirety as museums aim to maintain and display collections of heritage assets.
91.030: Operation of Historical buildings and sites	100%	Included in its entirety as historical buildings and sites are directly related to built heritage, and thus the operation of these heritage sites is a heritage activity.
Construction SIC codes (43.3: Building completion and finishing and 43.9: other specialised construction activities)	24.8%	This proportion is derived from the 2024 Skills Needs Analysis commissioned by Historic England. The report estimates that 97,224 FTE construction workers used heritage construction skills in 2023. This figure was divided by total FTE jobs in SIC codes 43.3 and 43.9 to determine the share of these codes to be included in the heritage analysis.
SOC 2020 code	Proportion included	Assumption and source leading to this proportion being included
2472: Archivist and Curators	100%	Included in its entirety because all work going on within this SOC code is related to the conservation of heritage assets.
2151: Conservation professionals	100%	Included in its entirety because all work going on within this SOC code is related to the conservation of natural heritage, including the preservation of National Landscapes.
2115: Social and Humanities Scientists	16.9%	Based on FAME’s State of the Archaeological Market 2022, this proportion reflects the share of archaeologists within this SOC code. It was calculated by dividing the number of archaeologists by total jobs in SOC 2115 (from APS).
Construction SOC codes (2451: Architects, 2452: Chartered Surveyors, 2453: Quantity Surveyors, and 3114: Building and Civil Engineering Technicians)	20.5%	These roles are identified as essential to heritage construction in Historic England’s Practical Building Conservation: Conservation Basics (2013). Due to their project-based and specialised nature, and in the absence of granular data, it is assumed they work on heritage buildings in proportion to the share of UK buildings constructed pre-1919 (20.5%). This building age distribution is used as a proxy for heritage construction work.
5113: Gardeners and Landscape Gardeners	17.4%	The underlying calculation for this 19.3% can be found in the proceeding section, where data on the total landmass of listed parks and gardens in England, provided by Historic England, is divided by the total landscape area of England provided by Land Use Statistics. This proportion reflects the estimated share of gardeners working in heritage contexts. It was calculated by analysing industry (SIC) data where this occupation is employed. For SIC 81300 (landscaping), the share of registered historic parks and gardens over total landscaped area was used (19.3%).^{[footnote 72]} For other relevant SIC codes, a 20.5% proxy based on pre-1919 building stock was applied. The industry-weighted average yields a 17.4% heritage share.

Question 8

Appendix II: Comparability of estimates

Accepted Answer

Comparison with and presentation alongside other DCMS Sector Economic Estimates

The raw results of this methodology do not account for overlap with other DCMS Sector Economic Estimates. Since the SIC-SOC mapping process can uncover heritage-related activity in any SIC in the economy (through the presence of heritage occupations), there is significant potential for overlap with all other DCMS Sectors.

However, the methodology developed here produces National Accounts-consistent and DCMS-consistent GVA estimates and DCMS-consistent employment estimates at the four- or five-digit SIC level. This means if removal of any double-counting with other DCMS Sectors is desired, any four-digit or five-digit SICs that are already counted in another DCMS sector can simply be subtracted from the heritage sector total.

Comparison with Historic England’s heritage sector reports

The methodology employed by Cebr to estimate the size of the heritage sector for Historic England, used up until our latest report in August 2024, was fundamentally different to that designed during this research. A brief summary of the method used in that research, is as follows:

1. For constituent heritage industries fully captured by the relevant SIC codes, employment figures are obtained from the Office for National Statistics’ Business Register and Employment Survey (BRES).^{[footnote 73]}

2. For some constituent industries, occupations rather than the industries are well defined, based on SOC codes. For these industries, employment estimates are derived by combining the APS data with the BRES data. These data sets are used to triangulate an estimate for heritage activities with no apparent industry SIC codes but with defined occupations, via the construction of bespoke SIC-SOC matrices. This is known as SIC-SOC mapping.

3. For heritage activities neither captured by SIC nor SOC codes, secondary data sources are used to estimate heritage employment figures or the employment share that could be applied to the relevant SIC or SOC codes.^{[footnote 74]}

4. Then average wages in each SIC/SOC and region combination are found from ASHE data.

5. These average wages are multiplied by the number of heritage employees in each SIC/SOC and region combination, giving total heritage compensation by SIC/SOC/region combination.

6. These figures are used to find regional heritage employee compensation as a proportion of total regional employee compensation.

7. These proportions are used to apportion total regional GVA to estimate regional heritage GVA.

8. Regional heritage GVA is further apportioned by each SIC/SOC’s heritage proportion of total regional SIC/SOC compensation from (2) to get heritage GVA by SIC/SOC and region.

9. Employment shares from the SIC-SOC mapping are then used to distribute SOC GVA across the SICs, to produce a regional GVA estimate by heritage SICs only.

While conceptually similar, care must be taken when comparing the 2 sources of GVA and employment estimates for the heritage sector. It is not possible to determine whether this new proposed methodology will consistently overestimate or underestimate the size of the heritage sector relative to the old Historic England methodology. The differences in GVA and employment estimates between the 2 methodologies are due to 3 key factors:

1. Geographic Scope: This research for DCMS covers the whole of the UK, while Historic England focuses on England.

2. Definitional Scope: The Historic England research examined both the direct and indirect impacts of the heritage sector, while this research for DCMS only examines the direct impact of the heritage sector. Additionally, an updated SIC and SOC code selection has led to differences between the defined scope of the heritage sector. Finally in this research, employment is measured as the number of filled jobs to retain consistency with DCMS reporting, whereas employment in the Historic England research was measured as the number of people employed. In practice, for this research this involves explicitly counting second jobs in employment estimates.

3. GVA calculations: For both projects, GVA is estimated by first estimating employment in the heritage sector, then utilising this as a key input to estimate GVA on a SIC-by-SIC basis. However in this research, the GVA methodology developed aligns with DCMS’s Sector Economic Estimates GVA methodology, which was not a requirement of the Historic England project. This entailed minor technical adjustments, including around the key data sources used, as described further in Appendix III.

Question 9

Appendix III: Detailed methodology and additional estimates

Accepted Answer

Employment

For the estimation of heritage employment, we used SIC-SOC matrices for both first and second jobs constructed with Annual Population Survey microdata. In order to ensure our results were nationally representative, we populated the SIC-SOC matrices with weights included in the APS (specifically the personal weight variable, ‘PWTA’), rather than with the number of respondents that fell within each SIC-SOC pairing.

As well as estimating absolute heritage employment levels for every year between 2011 and 2022, we also aimed to find the share of every SIC’s employment attributable to the heritage sector at the 4 or 5-digit level, for every year in the time series. We did so by calculating total employment (in terms of both first and second jobs) in each SIC code using the personal weights included in the APS, and dividing our heritage estimates by these figures.

For the regional apportionment of the employment estimates, we used the ‘Region of first job (GORWKR)’ variable in the APS, in line with DCMS Sector Economic Estimates Methodology. More detailed information on DCMS’s standard methodologies can be found in the technical and quality assurance reports.^{[footnote 75]}

For the analysis of heritage employment before 2021, we used the respective APS SOC variables for each year, coded according to the SOC 2010 classification, in line with the structure of this data.^{[footnote 76]} This, however, poses minimal inconsistency with post-2021 analysis, since the relevant SOC 2010 codes were in these cases selected according to the ONS translation tables between SOC 2010 and 2020. For the relevant SOC 2020 codes for which we were required to map back to SOC 2010, mapping was possible on a very close to one-to-one basis. For instance, while in post-2021 analysis the SOC ‘2215 Social and humanities scientists’ was used, in pre-2021 analysis it was the SOC ‘2114 Social and humanities scientists’ that was included. Estimates for the number of heritage workers employed by this and other SOC codes, therefore, are comparable between 2020 and 2021.

Gross Value Added

The standard DCMS Sector Economic Estimates method for estimating current-prices GVA is briefly summarised below.

1. Extract approximate Gross Value Added (aGVA) from the Annual Business Survey (ABS) at industry level (three-to-four-digit SIC), for each SIC of interest in each region.

2. Sum these to calculate the division-level (two-digit SIC) aGVA for the divisions relevant to the sector to be defined.

3. Calculate the proportion of industry-level to division-level aGVA for each region and industry.

4. Apply the UK-level proportions to division-level GVA in the National Accounts, for the divisions relevant to the sector being defined.

5. Apply the regional and national proportions to the National Accounts Balanced Regional GVA tables. Constrain the division–region estimates to the division–UK level estimates.

Using balanced GVA makes comparison with the wider UK economy more straightforward and ensures that non-market production is included in the DCMS estimates. To apply this method to the heritage sector, which is not well defined solely by SICs, we also need to apportion the aGVA of each partially heritage four- or five-digit SIC-region combination by the proportion of employment in that four- or five-digit SIC which is heritage-related, as defined by the heritage SOC codes discussed in Section 3.4.3. We then multiply the resulting proportions by the National Accounts UK-level and regional GVA.

DCMS’s above methodology produces estimates in current prices (CP) which are then used to construct chained volume measures (CVM). The methodology designed in this research similarly produces estimates in current prices that are then used to construct chained volume measures, which are presented in Section 4.2.1.

Adaptations to DCMS’s standard GVA methodology

In ABS data, aGVA may be negative for some four- or five-digit SIC codes due to factors such as high levels of public subsidy or poor survey coverage. To address this, and following discussions with DCMS’s Economic Statistics team, National Accounts GVA was apportioned using a proxy measure.

1. First, we estimate the proportion of employment in each five-digit SIC code that is heritage-related, based on SOC data.

2. Then, we calculate the share of total turnover in a two-digit SIC division that each five-digit SIC code contributes. The use of turnover in place of aGVA is the key adaptation to the approach.

3. These 2 proportions are multiplied to estimate the share of divisional economic activity attributable to heritage workers in each five-digit SIC code.

4. Finally, the division’s GVA in the National Accounts was multiplied by this proportion to allocate an appropriate share of divisional GVA to each five-digit SIC code.

This method was used for all five-digit SIC codes within a two-digit division where negative aGVA occurred at any point between 2011 and 2022. This affects 16 of the 53 two-digit divisions in which heritage activity was recorded in 2022, but only £2.7bn (15.0%) of the UK’s heritage sector GVA that year. Of this £2.7bn, 66% was value added by division 91, for which this method is already used in DCMS’s current methodology. The figures below provide further quality assurance information.

Table A: ABS quality assurance

No. of years affected	No. of 5-digit SICs
1 Year	19
2 Years	12
3 Years	1
4 Years	6
5 Years	0
6 Years	2
7 Years	1
8 Years	1
9 Years	0
10 Years	1
11 Years	0
12 Years	0
Year	No. of 5-digit SICs with negative aGVA
2011	11
2012	13
2013	19
2014	13
2015	8
2016	10
2017	6
2018	8
2019	4
2020	9
2021	3
2022	4

Notably, 19 five-digit SIC codes reported negative aGVA in only one of the 12 years covered. As a result, the GVA of all other five-digit SIC codes in the affected SIC codes’ two-digit divisions is estimated using the turnover approach for all 12 years, even though aGVA may be positive for these SIC codes in each of the 12 years. Such an approach is necessary because the National Accounts GVA data being apportioned are provided at the two-digit divisional level. If both turnover and aGVA shares were used varyingly to apportion the GVA of the same division, the GVA attributable to a particular five-digit SIC code could vary within and across years solely depending on the number of other five-digit SIC codes in the division estimated using each approach. This would produce inconsistent and potentially misleading estimates of five-digit SIC code GVA.

Using the same approach across all years and SIC codes in an affected division therefore trades off lower accuracy (from using turnover data in years for which aGVA data are positive) against consistency of methodology and thus comparability of estimates for a given SIC code over the time series.

Step 2 in the adapted approach above is a method already employed by DCMS to estimate the GVA of SIC 91 Libraries, archives, museums and other cultural activities (where negative aGVA figures are reasonably common), but not currently any other SICs. This is because, to the best of our knowledge, this issue has not been encountered in SIC codes in any other DCMS sectors, beyond SIC 91.

A further challenge in applying DCMS’s standard methodology arises due to the fact that some four- and five-digit SICs in which we find heritage employment are not covered by the ABS, such as 84.11 General public administration activities.^{[footnote 77]}. This means it is not possible to find these SICs’ share of divisional (two-digit SIC) aGVA, which DCMS usually employs to apportion GVA in the National Accounts, as described above.

After discussion with DCMS’s Economic Statistics team, it was decided that, for any SICs not covered by the ABS, heritage employment shares were to be used to apportion National Accounts GVA. These heritage employment shares are estimated as the number of heritage-related employees in a given four- or five-digit SIC as a proportion of the total number of employees in the 2-digit division, to which the four- or five-digit SIC belongs. These shares are then multiplied by the division’s GVA in the National Accounts Supply Use Tables.

Consideration of wages as a proxy for heritage activity

Cebr examined the feasibility of using the proportion of total wages paid to heritage-related employees within a four- or five-digit SIC code to improve upon using heritage employment shares to estimate the share of activity in a SIC attributable to heritage activity. The motivation for this was that using heritage-related employment (defined by SIC and SOC codes) as a proxy for heritage GVA requires an assumption that a heritage worker within a given SIC generates the same average GVA as all workers in that SIC. However, if heritage employees are more (or less) highly skilled and earn higher (or lower) wages than others in the same SIC, this assumption is likely not to hold. Using heritage wage shares (as a proxy for productivity) rather than heritage employment shares was explored as a potential means of controlling for this, when estimating the share of GVA attributable specifically to heritage workers.

Our initial approach was to assess weighted average wages across each SIC, both for heritage SOCs specifically and across all SOCs, using 2022 microdata from the Annual Survey of Hours and Earnings (ASHE). However, we found significant sample size issues, particularly for heritage SOCs, where all but one SIC had fewer than 20 observations for total heritage employment. This limited how granular we could be in our analysis, specifically with regard to calculating compensation for specific SIC-SOC pairings. In these pairings, the sample size was often less than 5 observations. This meant that it was difficult to say with confidence whether heritage workers within a SIC were truly paid on average more or less than non-heritage workers within each SIC code, or if this was simply an artifact of specific wages for a small number of respondents.

To assess the significance of this sample size issue we then took a broader approach, calculating the weighted average salary across all SICs in which heritage employment was present, while incorporating our earlier findings on heritage employment distributions across SIC codes. This was with the overall aim of estimating the average wage of heritage workers, relative to the average wage of all workers across SIC codes in which heritage activity is present. This allowed testing the hypothesis of whether heritage workers were disproportionately paid more or less than all employees, across SICs in which heritage workers are employed. Looking at the results, the weighted average salary was approximately £33,100 for heritage employment and £30,300 for all employment – a difference of roughly 9%. This suggests that while our initial hypothesis – that heritage employees might earn more than the average worker in relevant SICs (and accordingly should be reflected in our estimates) – holds some merit, the discrepancy, while notable, is not particularly large.

Based on this finding and the challenges of drawing firm conclusions about heritage average wages versus overall average wages within specific SIC codes due to sample size limitations, the decision was made – after discussions with DCMS’s Economic Statistics team – to use heritage employment shares instead of heritage wage shares to estimate the proportion of GVA attributable to heritage within each SIC.

From the supplementary analysis conducted across all SIC codes for heritage relative to non-heritage wages, this likely will slightly underestimate heritage GVA. But given the sample size challenges, on a SIC code-by-SIC code basis, the risks of losing accuracy through more granular analysis of heritage wages, outweigh the potential advantages.

Table E: 15 largest 4 or 5-digit SIC codes by employment contribution, 2022^{[footnote 78]}

SIC code	Employment, 000s
91.02 Museum activities	43,474
43.32 Joinery installation	38,992
81.30 Landscape service activities	26,685
43.999 Specialised construction activities n.e.c.	21,805
43.341 Painting	20,034
43.33 Floor and wall covering	11,603
43.91 Roofing activities	10,607
91.03 Operation of historical sites and buildings	10,432
43.31 Plastering	10,169
43.39 Other building completion and finishing	8,727
91.012 Archive activities	8,698
71.111 Architectural activities	4,923
43.991 Scaffold erection	4,902
71.122 Engineering related scientific and technical consulting activities	4,854
41.202 Construction of domestic buildings	4,057
All other SIC codes	67,481
Total	297,443

Table F: 15 largest 4- or 5-digit SIC codes by GVA contribution (£m), 2022

SIC code	GVA, £m
43.32 Joinery installation	1,529
43.39 Other building completion and finishing	1,463
43.999 Specialised construction activities n.e.c.	1,367
91.02 Museum activities	868
43.991 Scaffold erection	833
91.03 Operation of historical sites and buildings	695
43.91 Roofing activities	692
68.31 Real estate agencies	585
68.201 Renting and operating of Housing Association real estate	517
43.341 Painting	485
68.32 Management of real estate on fee or contract basis	397
43.33 Floor and wall covering	388
81.30 Landscape service activities	373
68.209 Other letting and operating of own or leased real estate, n.e.c.	344
43.31 Plastering	318
All other SIC codes	4,320
Total	15,174

Table G: National and regional heritage sector employment (000s), 2011–2022

Nation / Region	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
North East	10	9	9	8	10	11	9	9	11	10	9	8
North West	28	26	27	29	27	28	27	29	28	28	29	29
Yorkshire and The Humber	21	20	20	21	23	22	24	23	23	24	22	23
East Midlands	17	18	17	19	18	16	21	22	20	17	18	22
West Midlands	19	20	18	22	22	21	21	23	24	21	21	21
East of England	22	23	25	28	27	29	32	28	26	28	27	27
London	50	44	47	48	52	47	50	50	52	53	37	53
South East	36	35	41	37	43	44	50	40	44	39	41	43
South West	25	27	29	28	28	27	26	26	25	24	24	28
England	229	224	233	241	250	245	260	249	254	244	229	253
Wales	11	13	13	13	14	12	13	12	13	13	12	13
Scotland	24	25	22	23	27	26	25	26	25	22	23	21
Northern Ireland	4	6	6	6	6	5	5	4	6	6	7	6
United Kingdom^{[footnote 79]}	270	270	276	285	299	290	305	295	300	287	273	297

Table H: National and regional heritage sector GVA (£bn at 2022 price levels), CVM 2011–2022

Nation / Region	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
North East	0.4	0.4	0.4	0.4	0.4	0.4	0.4	0.4	0.4	0.3	0.3	0.4
North West	1.0	0.9	1.0	1.0	1.1	1.1	1.1	1.2	1.1	1.0	1.2	1.4
Yorkshire and The Humber	0.9	0.8	0.8	0.9	0.9	0.9	0.9	0.9	0.9	0.8	0.9	1.0
East Midlands	0.7	0.6	0.6	0.7	0.7	0.7	0.7	0.8	0.8	0.7	0.7	0.9
West Midlands	0.8	0.8	0.8	0.9	0.9	1.0	1.0	1.0	0.9	0.8	0.9	1.1
East of England	1.1	1.1	1.1	1.2	1.3	1.4	1.4	1.4	1.4	1.2	1.2	1.4
London	2.6	2.1	2.4	2.4	2.7	2.9	2.9	2.9	2.9	2.2	2.7	3.0
South East	1.8	1.7	1.7	1.9	2.0	2.2	2.1	2.1	2.1	2.2	2.1	2.5
South West	0.9	0.9	0.9	1.0	1.0	1.1	1.2	1.2	1.2	1.1	1.1	1.3
England	10.2	9.3	9.7	10.4	11.1	11.8	11.6	11.9	11.7	10.4	11.2	13.1
Wales	0.4	0.4	0.4	0.4	0.4	0.4	0.4	0.5	0.4	0.4	0.4	0.5
Scotland	1.0	1.0	1.0	1.1	1.2	1.2	1.1	1.1	1.1	0.9	1.0	1.1
Northern Ireland	0.3	0.2	0.2	0.3	0.3	0.3	0.3	0.3	0.3	0.3	0.3	0.4
United Kingdom	12.0	11.0	11.4	12.2	13.0	13.8	13.5	13.8	13.5	12.1	13.0	15.2

This report was produced by Alma Economics in August of 2024. ↩
This framework was developed by ESPON to try and estimate the size of the cultural heritage sector in Europe, in their 2019 report. ↩
This SOC code includes all social and humanities scientists, however, in this context we are particularly interested in Archaeologists. ↩
The share of Social and Humanities Scientists included in the heritage sector has decreased from that used in the Historic England work. This is a consequence of adjustments related to including second jobs within the scope of our analysis. ↩
It is clear that between Table 3 and Table 4, the proportion of Gardeners and Landscape gardeners considered part of the heritage sector has increased substantially. This is due to a methodological difference between this research and the Historic England research because our research identified a wider range of SIC codes that employ heritage gardeners than the Historic England research, as detailed later in the report. ↩
For SIC codes which report negative aGVA in the ABS, the SIC code’s share of divisional turnover is used instead to apportion divisional GVA. For SIC codes not captured by the ABS, divisional heritage employment shares are used. This process is discussed in detail in Appendix III. ↩
The methodology for DCMS Sector Economic Estimates is available in the technical reports published alongside each statistical release. ↩
Within the DCMS Sector Economic Estimates methodology (for a link, see Footnote 9), it is stated that ‘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’. To demonstrate this further, the 2022 DCMS Sector Economic Estimates found that the 91.03 - Operation of historical sites and buildings directly generated a gross value added (GVA) of £0.7bn to the UK economy. As a comparative example, the 2024 Historic England report titled “The heritage sector in England and its impact on the economy” found that in 2022, the heritage sector generated a GVA of £15.3bn. GVA for DCMS Sectors is available here. ↩
The methodology for the creative intensities approach is detailed by DCMS in a methodological note, available here. ↩
This is possible because SIC code employment is possible to map to SOC codes, using data from the UK’s Annual Population survey, which asks respondents questions on both their industry and occupation of work. ↩
This research covers England only due to the scope of Historic England’s activity, although a methodologically consistent approach could be undertaken for analysis covering the entirety of the UK. ↩
One of the weaknesses of a ‘big data’ driven approach that was considered within Alma Economics’ report, is further work needed to map to SIC codes. ↩
Although this figure does feature SIC and SOC codes which are later classified as part of the heritage sector, this figure is strictly for illustrative purposes. An explanation of why these SIC and SOC codes are classified as belonging to the heritage sector is set out in Sections 3.3 and 3.4. ↩
If we were to simply add the employment in heritage SIC and SOC codes, we would get a total employment of 11; 5 from the heritage SIC code 9102 and 6 from summing all heritage SOC code employment from SOC 2472. This would lead to the 2 heritage employees who work as archivists or curators within the museums sector, being included twice. ↩
This report was produced by Cebr, on behalf of Historic England and was completed in August 2024. It is available here. ↩
These SIC codes were selected as their activity most closely matches the repair and maintenance work conducted by people working in the heritage construction industry. SIC code 433 is described as building completion and finishing, indicating that the work done in this SIC code, is related to activities that go on once construction of the building is mostly finished, including painting, captured by SIC code 4334: painting and glazing. SIC code 439 is described as other specialised construction activity, which includes scaffold erecting, captured by SIC 43991: scaffold erection, which is required for all building renovation and maintenance. Therefore, conceptually the three-digit SIC codes 433 and 439 are the SIC codes which capture the repair and maintenance of buildings, acting as a base to analyse the size of the heritage construction industry which is only related to the repair and maintenance of heritage buildings. ↩
This report is the predecessor for the updated 2024 report of the same naming format, discussed above. ↩
NLHF grant funding is given out by the National Lottery to support heritage projects within the UK. Although the aim of this fund is to support heritage within the UK making the data set a good signal for heritage activity, the National Lottery does not itself have a prescriptive definition of the heritage industry that it uses to decide who is eligible to receive grants. ↩
The heritage construction industry was included in the Historic England reports titled “The heritage sector in England and its impact on the economy”, produced between 2018 to 2024, using the previously mentioned 2013 Historic England “Skills Needs Analysis 2013 Repair, Maintenance and Energy Efficiency Retrofit of Traditional (pre-1919) Buildings in England and Scotland.” This report estimated that 86,880 FTE construction workers in England, were undertaking work on traditional (built pre-1919) buildings, in 2012. Cebr subsequently used this figure to calculate the share of the construction industry related to heritage. We did this by finding the SIC codes that related to the repair, maintenance and retrofit of buildings in general, which was narrowed down to SIC codes 433 and 439. After identifying these SIC codes, this heritage-specific construction was divided by total FTE employment in these SIC codes in England in 2012, per Business Register Employment Survey (BRES) data. The proportion reported in Table 1 (31.0%), is the result of this calculation. In subsequent years, we then assume that this share of the SIC codes attributable to heritage is stable. ↩
This framework was developed by ESPON to try and estimate the size of the cultural heritage sector in Europe, in their 2019 report available here. ↩
The company numbers are a unique code given to organisations to make them identifiable on the Companies House website. Companies House is the executive agency of the British Government that maintains the register of companies, employs the company registrars and is responsible for incorporating all forms of companies in the United Kingdom. However, some organisations will not have company codes, for example most charities. ↩
All SIC codes which have a proportion lower than 0.10% of NLHF grants to market turnover were excluded, however as mentioned above, the full list of SIC codes can be found in Appendix I. ↩
The distinction of heritage buildings as those created pre-1919 stems from the report titled “Understanding Traditional (pre-1919) and Historic Buildings for Construction and Built Environment Courses” produced by Historic England and Cadw in 2019. In this report, Historic England classifies heritage construction as construction using solid walls instead of walls with cavities, and buildings that make use of stone and wood as key construction materials. This designation allows for the capture of traditional building materials and techniques used in and before 1919, which were replaced by modern construction techniques including walls with cavities and a fall in the use of traditional materials like wood and stone. ↩
To calculate this, they use the share of pre-1919 buildings, the intensity of the work required and the average square meterage of heritage repair and maintenance sites. ↩
See Appendix I for a detailed reasoning as to why SIC codes were used to account for the heritage construction industry instead of SOC codes. ↩
Further detail on the rationale for mapping this employment to appropriate SIC codes rather than SOC codes, is given in Appendix I. ↩
In this context, natural heritage refers to the sites that are protected by Historic England and the UK government which includes listed parks, and National Landscapes. ↩
This SOC code includes all social and humanities scientists, however, in this context we are particularly interested in Archaeologists. ↩
This is to ensure the analysis within this reconsidered definition, is using the ONS’s most recent classification system. Although the classification systems function very similarly, the SOC 2020 classification was created in 2021 to update and provide a more accurate description of the activities undertaken in each occupation. ↩
This reclassification was not considered in the Historic England reports to maintain definitional consistency between years, and so SOC codes were analysed using the previous SOC 2010 classification rather than changing to the SOC 2020 classification in 2021. ↩
This is to ensure the analysis within this reconsidered definition, is using the ONS’s most recent classification system. Although the classification systems function very similarly, the SOC 2020 classification was created in 2021 to update and provide a more accurate description of the activities undertaken in each occupation. ↩
SOC 5119 relates to the conservation of forest and fish populations while SOC 2152 relates to the development of wider environmental policy. ↩
To facilitate the continued inclusion of town planning officers, we considered the viability of estimating the share within the new SOC 2020 code of workers who were previously classified as Town Planning Officers, per the SOC 2010 definition. This would have been theoretically feasible utilising the discussed ONS-produced mapping files, between the definitions. However, these mapping files are based upon data from 2014-16. Without the continued production of new files, which to the best of our knowledge is not anticipated, the reliability of this approach would therefore decline over time. Therefore, given DCMS’s aim of developing a methodology with long-term applicability, we ultimately did not proceed with this approach. ↩
Alma Economics suggests that there could be some merit for reclassifying the heritage construction cut -off date to 1945, to capture the important interwar year construction activity. However, after reviewing reports from Historic England and CITB, we decided against this approach, as detailed in Appendix I. ↩
Data available here ^. Worth noting that our figure is to 3 significant figures rather than rounded, and is very close to the pre-1919 share of heritage buildings within England, available here. ↩
Data from the State of the Archaeology market 2022 report was reported in terms of FTE employment and Annual Population Survey data was similarly reported in terms of FTE employment. ↩
The data referring to the total land mass of England which is comprised of listed parks and gardens can be found here^. Which can then be divided by the total landscape land mass found at Land Use Statistics to calculate the 19.3% referred to above. ↩
Specifically, the inclusion of gardeners working in the landscaping activities resulted in a substantial increase in the share of all gardeners who are in the heritage sector. This is because this is the SIC with the highest number of gardeners employed, but in prior research this SIC had not been included as a potential SIC in which heritage gardeners may be employed. This was due to difficulties isolating the share of gardeners within this SIC who undertake heritage-related work, with the approach for isolating this, as described further in Appendix I, only developed as part of this project. ↩
Academic staff reported by Russel group in the financial year 2022/23. The source for this figure is available here. ↩
Due to some unique characteristics, particularly in SIC codes not currently part of other DCMS sectors, some specific adaptations to the methodology were required in order to apply it to the heritage sector. These are individually discussed within Appendix III. ↩
See DCMS Sector Economic Estimates. ↩
Figures may not sum due to rounding. ↩
The 88 SIC divisions are numbered between 01 and 99, with several numbers omitted. To see the full SIC hierarchy, visit UK SIC 2007 - Office for National Statistics. ↩
Figures may not sum due to rounding. ↩
SIC codes are here presented at the 4 and 5-digit level, as opposed to aggregated into divisions as in the GVA discussion. ↩
Totals do not exactly sum to the national heritage employment estimate because of the inclusion of people who live in the UK but work outside of it (possibly in Crown dependencies like Jersey, Guernsey, or the Isle of Man) within our national estimate. ↩
While we have ensured the robustness of the data analysis, it remains possible that certain trends in the report, such as this one in the Museum sector, could be driven by measurement error in underlying APS data. In this survey, respondents self-select into their respective SIC codes, introducing some degree of measurement error which is not necessarily of the same magnitude or in the same direction from year to year. ↩
Values for the United Kingdom include filled jobs where the workplace is reported as outside of the UK. Due to this, and the inclusion of jobs where the location is not given, the values for England, Wales, Scotland, and Northern Ireland do not sum to the UK total. ↩
For example, estimates for the Civil Society sector are not included within either business demography or trade statistics, due to differences in definition relative to other DCMS sectors and thus methodological incompatibility. ↩
A further step for trade in goods is the mapping between international commodity codes (specifically, CN08) and 4-digit SICs. This is explained further in wider DCMS methodological guidance with standardised lookup files setting out the link between CN08 codes and SICs within DCMS sectors, as accessed here ↩
To this point, all 3 of these SIC codes are included within other DCMS sectors. For goods, only museums has identified commodity codes mapped to it. For services, within recent DCMS Trade in Services releases, relevant other DCMS subsectors containing the 3 heritage SIC codes typically either have very low level of services trade, no trade recorded, or data is suppressed to prevent the release of disclosive information (itself a likely indication that trade is conducted by only a small number of organisations). ↩
This caveat acknowledges the potential for some heritage occupation workers within heritage SIC codes to work on overseas projects. ↩
Note that this assumption is slightly stronger for exports than imports. It is theoretically possible that specialist advice on heritage-related construction is considered a services import. The extent of this is not likely to be significant, but difficult to evaluate precisely. ↩
For example, it may be possible to establish the share of employment within specific organisations that is undertaking heritage-related work, with this used as a proxy for the share of work at the organisation level that is heritage-related. ↩
An example of this is Camden Place in Chislehurst, Kent. This is a listed building built in 1717 (therefore classified as a heritage building) and where Emperor Napolean III died in exile. This also now operates as a golf club, and the main SIC codes listed on Companies House are SIC 93110 (Operation of sports facilities) and 93120 (Activities of sport clubs). This means that employees of Camden Place would not automatically be captured within this project’s methodology, unless their occupation happened to be within a heritage SOC. Economic activity associated with expenditure on the maintenance of the building would still be included through the building maintenance SIC codes. ↩
An alternative approach could have been only including SICs or SOCs which are exclusively heritage-related. This would have had advantages associated with consistency (i.e. the building maintenance vs transport maintenance inconsistency above), but would have ultimately led to a narrower definition of the sector. As increasing the breadth of heritage’s definition was the key priority for this research, ultimately the decision was taken to prioritise including as much activity as was feasible, given data availability. ↩
We frame this measurement as imperfect rather than non-existent, as overall GVA estimates are ‘anchored’ to national accounts consistent estimates of GVA, as discussed further in Section 3. The specific contribution of individual SIC codes to GVA is estimated by considering the share of employment attributable to heritage employees, within a two-digit SIC. Therefore if heritage employees disproportionately rely on voluntary employment, it is likely that our GVA estimates within this report are underestimated, as the GVA generated by voluntary workers will not be reflected in the employment-based distributions (excluding voluntary workers) that underpin GVA calculations. ↩
Specifically, the approach taken was dividing heritage employment as estimated in the Skills Needs Report, by total employment within appropriate SIC codes to estimate the share of activity within these SICs attributable to heritage. The same logic could theoretically have been applied by dividing total employment per the Skills Needs Report by total employment within appropriate SOC codes, to estimate the share of activity within the SOC codes attributable to heritage. The Construction Industry Training Board’s employment categories do not map perfectly to either SIC or SOC codes, and therefore this additional methodological step is required. ↩
The company numbers are a unique code given to organisations to make them identifiable on the Companies House website. Companies House is the executive agency of the British Government that maintains the register of companies, employs the company registrars and is responsible for incorporating all forms of companies in the United Kingdom. However, some organisations will not have company codes, for example most charities. ↩
Note that for 2 SICs, this comparative exercise of grants and market turnover is not possible. These are 74.990 – Non-trading companies and 01.450 – Raising of sheep and goats. This is because turnover estimates for neither are provided, within the Annual Business Survey. For 74.990 – Non-trading companies, this is because the SIC is intended to refer to companies with transactions (i.e. bank activity), but which are not actively trading. We suspect that businesses classifying within this SIC do so erroneously, as the act of receiving a grant should disqualify an organisation from being within this SIC. For 01.450 – Raising of sheep and goats, the Annual Business Survey only has partial coverage of the agricultural sector, with this SIC not included. ↩
Under the SIC code classification, broader SIC codes such as the 3 digit SIC code 43.9, can be broken down into more granular SIC codes at the four- and five-digit level, such as SIC code 43.999. ↩
At the three-digit level, this SIC code is 43.3, however, similarly, to SIC code 43.9, this SIC code can be broken down into more granular four- and five-digit SIC codes, none of which feature in the NLHF analysis. ↩
The reason for using these SIC codes to capture the heritage construction industry in the Historic England reports between 2018 and 2024 is detailed in Appendix I. ↩
Where core refers to those SIC codes considered in the Historic England reports between 2018 and 2024. ↩
Within the scope of this project, only tangible heritage is included. ↩
The framework also lists specialised construction activities, but this is omitted as it is a sector we have already identified to be part of our heritage definition. ↩
ESPON defines material cultural heritage as ‘objects of immovable (e.g. archaeological sites, cultural landscapes) and movable (e.g. paintings, books) nature recognised as having heritage value in each country/region according to 3 types of recognition: listed as having heritage value and legally protected; listed as having heritage value but not legally protected; historical building stock. This also includes places that are publicly accessible and where movable material cultural heritage objects are stored/exhibited, namely archives, libraries and museums.’ ↩
This was important as it is possible that a two-digit SIC in the supply and use tables containing some heritage activity, could spend on another SIC, with that expenditure exclusively being made by the non-heritage related share of the SIC code. We therefore further considered the definition of included activity within each SIC code, to sense check the likelihood that the expenditure could have come from the heritage-related share of the SIC. ↩
In descriptive terms, printing other than for newspapers. ↩
This data comes directly from Historic England and can be found here. ↩
This figure is calculated by summing outdoor recreation and residential gardens from the Land Use Statistics These 2 segments of land use capture parks, gardens, sports facilities, outdoor areas of schools and commercial building. ↩
The underlying calculation for this 19.3% can be found in the proceeding section, where data on the total landmass of listed parks and gardens in England, provided by Historic England, is divided by the total landscape area of England provided by Land Use Statistics. ↩
Business Register and Employment Survey - Office for National Statistics ↩
For example, data on archaeologists were supplemented with research from FAME Archaeology’s ^{State of the Archaeological Market} reports. ↩
See also the National GVA methodology and Regional GVA methodology. ↩
The ONS only publishes employment statistics utilising the SOC 2020 classification from 2021 onwards. Therefore analysis before this point is conducted per the older classification. ↩
A full list of the ABS’s coverage can be found here. ↩
SIC codes are here presented at their most granular level. That is, for SIC codes such as 43.99 which can be disaggregated further, into 43.999 and 43.991, these are presented at the 5-digit level. For SIC codes such as 91.03, which contain no further subdivisions, we present them at the 4-digit level. ↩
Values for the United Kingdom include filled jobs where the workplace is reported as outside of the UK. Due to this, and the inclusion of jobs where the location is not given, the values for England, Wales, Scotland, and Northern Ireland do not sum to the UK total. ↩

SOC 2020 code	Description of activities of SOC 2020 code
2115: Social and humanities scientists	Social and humanities scientists study and analyse human behaviour, and the origin, structure and characteristics of language undertake research in areas such as sociology, economics, politics, archaeology, history, philosophy, literature, the arts organise the collection of qualitative and quantitative information and perform subsequent analyses.
2151: Conservation professionals	Conservation professionals are responsible for ensuring that landscapes, habitats and species are protected via appropriate management and conservation. They promote public understanding and awareness of the natural environment and help develop and implement appropriate policies to achieve these objectives.
2152: Environmental professionals	Environment professionals investigate, address, and advise on a variety of terrestrial and marine environment and resource management issues, including the development and implementation of environmental policies and remedies that address the impacts of human activities and industrial processes on the environment.
2451: Architects	Architects plan and design the construction and development of buildings and land areas with regard to functional and aesthetic requirements.
2452: Chartered architectural technologists and planning officers	Chartered architectural technologists, planning officers and consultants direct or undertake the planning of the layout and the co-ordination of plans for the development of urban and rural areas, provide architectural design services, and negotiate and manage the development from conception to completion of construction projects and lead on a variety of technical functions and solutions in the design of buildings and the layout of urban and rural areas.
2454: Chartered surveyors	Chartered surveyors conduct surveys related to the measurement, management, valuation and development of land, natural resources, buildings, other types of property, and infrastructure such as harbours, roads and railway lines.
2472: Archivists and curators	Archivists, conservators and curators collect, appraise and preserve collections of recorded and other material of historical interest.
3114: Building and civil engineering technicians	Building and civil engineering technicians perform a variety of technical support functions to assist civil and building engineers.
5119: Agricultural and fishing trades	Job holders in this unit group perform a variety of agricultural, practical conservation activities, and fishing tasks not elsewhere classified.
5113: Gardeners and landscape gardeners	Gardeners and landscape gardeners cultivate flowers, trees, shrubs and other plants in public and private gardens, construct features to improve the appearance of existing terrain, and cut and lay turf.

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About the authors

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1. Executive summary

1.1 Scope

1.2 Methodology overview

SIC code selection and refinement

Refinement of SIC Codes:

SOC code selection and refinement

1.3 Economic impact calculations and results

Employment estimation

Gross Value Added (GVA)

Consideration of wage-based adjustments

Results

1.4 Business demography and trade

1.5 Limitations of this research

2. Introduction

3. Scope and methodology

3.1 Background and scope of the study

3.2 Introduction to SIC-SOC mapping

3.3 SIC code selection

3.3.1 SIC codes previously considered part of the heritage sector

3.3.2 Review of evidence and potential alterations to the list of SIC codes included in the heritage sector

National Lottery Heritage Fund grant data

Revisiting the construction industry skills data

Broader heritage activity and the ESPON “keys” framework

3.3.3 Final list of SIC codes included with the proportion of these SIC codes related to heritage

3.4 SOC code selection

3.4.1 Review of SOC codes previously considered part of the heritage sector

3.4.2 Review of evidence and potential alterations to the list of SOC codes included in the heritage sector

Mapping between SOC 2010 and SOC 2020

Apportionment of heritage construction workers

Apportionment of archaeologists within social and humanities scientists

Apportionment of gardeners and landscape gardeners

3.4.3 Review of evidence for occupations not considered in the Historic England reports

Analysis of heritage job boards and university heritage career guidance

Analysis of Historic England’s report titled Conservation Basics published in 2013, focusing on built heritage

Analysis of evidence relating to heritage academics

3.4.4 Final list of SOC codes included with the proportion of these SOC codes related to heritage

3.5 Economic impact calculations

4. Economic contribution of the heritage sector

4.1 Economic impact of the heritage sector in 2022

4.1.1 Gross Value Added

National impact of the heritage sector

Regional impact of the heritage sector

4.1.2 Employment

National impact of the heritage sector

Regional impact of the heritage sector

4.2 Economic impact of the heritage sector over time

4.2.1 Gross Value Added

National impacts over time

Regional impacts over time

4.2.2 Employment

National impacts over time

Regional impacts over time

5. Evaluating the feasibility of producing trade and business statistics

Business demography

6. Conclusion

Appendix I: Further technical material related to SIC-SOC mapping

Rationale for only including proportions of construction SIC codes

Rationale for SIC based approach instead of SOC base approach for the construction industry

Detailed description of NLHF funding analysis

Cultural education

Operation of arts facilities

Botanical and zoological gardens and nature reserve activities

Library activities

Description of activities that occur in reclassified SOC 2020 codes

Detailed description of ESPON framework

Addressing Alma Economics’ suggestion to reclassify the heritage cutoff date

Calculation of the proportion of SOC code 5113: Gardeners and Landscape Gardeners, that belong to the heritage sector

SIC Code 81300: Landscape Service Activities

Other Relevant SIC Codes

Table summarising the key assumptions for the partial SIC and SOC codes included in our analysis of the heritage sector

Appendix II: Comparability of estimates

Comparison with and presentation alongside other DCMS Sector Economic Estimates

Comparison with Historic England’s heritage sector reports

Appendix III: Detailed methodology and additional estimates

Employment

Gross Value Added

Adaptations to DCMS’s standard GVA methodology