Official Statistics

Background quality report: Venture Capital Trusts statistics

Published 20 January 2022

1. Contact

• Organisation unit - Knowledge, Analysis and Intelligence (KAI)
• Name - S Nath and G Dobson
• Function - Statistics Producers, Direct Business Taxes
• Mail address - HM Revenue and Customs (HMRC), Room 3/60, 100 Parliament Street, London SW1A 2BQ
• Email - venturecapital.statistics@hmrc.gov.uk

2. Statistical presentation

2.1 Data description

This is a National Statistics publication produced by HM Revenue and Customs (HMRC). It provides information on the number of Venture Capital Trusts (VCTs) raising funds, number of VCTs managing funds and the amount of funds raised by VCTs. It also includes the number of individuals claiming Income Tax (IT) relief on their Venture Capital Trust (VCT) investments and the amount of investment on which relief was claimed.

VCTs are one of the 4 tax-based venture capital schemes, introduced in 1995. See further information on VCTs and the policy background.

2.2 Classification system

For data on funds raised by VCTs (Table 1), the unique name of the VCT is used to aggregate the data.

For the VCT relief claimed through Self Assessment (SA) returns (Table 2a and 2b), a Unique Taxpayer Reference (UTR) number, assigned to each individual, is used to aggregate the data.

2.3 Sector coverage

The funds raised by VCTs are subsequently invested into companies from various sectors in the UK Standard Industrial Classification (SIC) 2007.

2.4 Statistical concepts and definitions

Tax year

The statistics are aggregated into tax years. A tax year stretches from 6 April until 5 April the following calendar year.

VCTs raising funds

VCTs which have issued shares to investors in the tax year.

VCTs managing funds

VCTs which were active at the end of the associated tax year (5 April). VCTs who have liquidated or merged with other VCTs are excluded from this figure.

2.5 Statistical unit

The units in the statistics are VCTs raising or managing funds, the amount of funds raised, individuals claiming IT relief on their VCT investments and the associated amounts invested by these individuals.

2.6 Statistical population

All VCTs listed on a UK recognised Stock Exchange and individuals who have invested into these VCTs.

2.7 Reference area

The geographic region covered by the data is the United Kingdom.

2.8 Time coverage

The statistics in each table of the publication cover different time periods:

• Table 1 covers the time periods from tax year 1995 to 1996 to tax year 2020 to 2021

• Table 2a and 2b cover the time periods from tax year 2017 to 2018 to tax year 2019 to 2020

Table 2a and 2b are reported with a one year time delay because the deadline for submitting SA returns for the tax year 2020 to 2021 has not yet passed and individuals can also submit late claims. Thus, the data for 2020 to 2021 is currently incomplete for publication.

3. Statistical processing

3.1 Source data

Investments in VCTs are notified to HMRC, but until recently not in a form suitable for data capture. Therefore, information on the number of VCTs and funds raised are obtained from publicly available internet sources, mainly FE Investegate VCTs information and news announcements. As a result, these figures are outside the managerial control of HMRC and are not considered National Statistics. However, they are published annually by HMRC as our current best indicators of the number of VCT funds and the amounts they raise in Table 1.

SA returns are used to collect data on VCT relief claimed by investors. This information will not cover investors making IT relief claims through other systems (eg PAYE) or not making any claims.

3.2 Frequency of data collection

The data is collected annually. This year’s statistics are based on data extracted in November 2021.

3.3 Data collection

The number of shares issued, corresponding issue price and date of issue are collected from commercial websites. The current status of the VCTs are also checked, for example, whether the VCT has liquidated or merged.

IT relief data is extracted from SA tax returns received by HMRC.

3.4 Data validation

Initial checks carried out on the data include:

• ensuring that the amount of funds raised has a realistic value
• checking that amounts invested on which relief was claimed is within the VCT investment limit (£200,000)
• checking that the VCT corresponds to the correct name to avoid the presence of duplicate VCTs
• flagging duplicate records, ie any individual VCT records with the same issue date and amount of investment are identified

Once the values are aggregated, any significant changes in figures from one statistical release to the next are investigated.

The total funds raised and amount raised by each individual VCT are compared with other data sources such as the Association of Investment Companies and Wealth Club. Small discrepancies between the figures arise due to differences in the methodology and assumptions used to compile the figures. In the case of large discrepancies, this is reported to VCT policy colleagues and further investigation takes place until the discrepancy is understood.

3.5 Data compilation

Dealing with missing data

For issue of share announcements with certain fields missing, for example issue price, the net asset value (NAV) is used as an approximation. The NAV is the value of the investment company’s assets, less any liabilities it has. This value is generally slightly different from the issue price, but it is a suitable estimate for when the issue price is not stated.

Where shares are issued at various prices, an average value is calculated.

Aggregating data

In Table 1, data are aggregated using the unique name assigned to each VCT. This unique name can change across tax years. A list is produced comparing the previous and current names of the VCTs - any duplicates are removed.

SA data are aggregated using a UTR assigned to each investor.

4. Quality Management

4.1 Quality assurance

All official statistics produced by KAI, must meet the standards in the Code of Practice for Statistics produced by the UK Statistics Authority (UKSA) and all analysts adhere to best practice as set out in the ‘Quality’ pillar.

Analytical Quality Assurance describes the arrangements and procedures put in place to ensure analytical outputs are error free and fit-for-purpose. It is an essential part of KAI’s way of working as the complexity of our work and the speed at which we are asked to provide advice means there is a high risk of error which can have serious consequences on KAI’s and HMRC’s reputation, decisions, and in turn on peoples’ lives.

Every piece of analysis is unique, and as a result there is no single quality assurance (QA) checklist that contains all the QA tasks needed for every project. Nonetheless, analysts in KAI use a checklist which summarises the key QA tasks, and is used as a starting point for teams when they are considering what QA actions to undertake.

Teams amend and adapt it as they see fit, to take account of the level of risk associated with their analysis, and the different QA tasks that are relevant to the work. At the start of a project, during the planning stage, analysts and managers make a risk-based decision on what level of QA is required.

Analysts and managers construct a plan for all the QA tasks that will need to be completed, along with documentation on how each of those tasks are to be carried out, and turn this list into a QA checklist specific to the project.

Analysts carry out the QA tasks, update the checklist, and pass onto the Senior Responsible Officer for review and eventual sign off.

4.2 Quality assessment

The QA for this project adhered to the framework described in ‘4.1 Quality assurance’ and the specific procedures undertaken were as follows:

Stage 1 – Specifying the question

Up to date documentation was agreed with stakeholders setting out:

• outputs needed and by when
• how the outputs will be used
• all parameters required for the analysis

Stage 2 – Developing the methodology

Methodology was agreed and developed in collaboration with stakeholders and others with relevant expertise, ensuring it was fit for purpose and would deliver the required outputs.

Stage 3 – Building and populating a model/piece of code

Stage 3 consists of the following steps:

• analysis was produced using the most appropriate software and in line with good practice guidance
• data inputs were checked to ensure they were fit-for-purpose by reviewing available documentation and, where possible, through direct contact with data suppliers
• QA of the input data was carried out
• the analysis was audited by someone other than the lead analyst – checking code and methodology

Stage 4 – Running and testing the model/code

Stage 4 consists of the following:

• results were compared with those produced in previous years and differences understood and determined to be genuine
• results were determined to be explainable and in line with expectations

Stage 5 – Drafting the final output

The final stage includes the following:

• checks were completed to ensure internal consistency (eg totals equal the sum of the components)
• the final outputs were independently proof read and checked

5. Relevance

5.1 User needs

This analysis is likely to be of interest to users under the following broad headings:

• policy makers in government
• academia and research bodies
• media
• venture capital associations
• companies receiving investments via VCTs
• investors investing in VCTs

5.2 User satisfaction

HMRC is committed to providing impartial quality statistics which meet our users’ needs. We encourage our users to engage with us so that we can improve our National and Official Statistics and identify gaps in our statistics.

If you would like to comment on these statistics or have any enquiries, please use the statistical contacts named at the beginning of the report.

5.3 Completeness

Tables 1 includes all shares issued by VCTs and all VCTs which were incorporated since 1995, as reported on commercial websites. There is a possibility of some share issues not being reported on the websites.

Table 2a and Table 2b include every case captured via SA returns. There may be VCT investors who claim relief outside SA and some may not submit any claims.

6. Accuracy and reliability

6.1 Overall accuracy

Table 1 is based on third party data. These figures are outside the managerial control of HM Revenue and Customs (HMRC) and are not considered National Statistics. To eliminate errors, we have performed checks with other data sources.

Table 2a and 2b are based on administrative data, and accuracy is addressed by eliminating non-sampling errors as much as possible through adherence to the quality assurance framework.

The potential sources of error include:

• errors in the reporting of share issues on commercial websites
• potential human error when manually collecting data from websites
• mistakes in the programming code used to analyse the data and produce the statistics

6.2 Sampling error

As no sampling is necessary, sampling error is not an issue.

6.3 Non-sampling error

Coverage error

Table 2a and 2b include every case captured via SA returns. Therefore, the data only includes investors who have claimed IT relief via SA forms.

Measurement error

Figures on the number of shares issued and issue prices could be incorrectly reported on commercial websites. The data are subsequently collected by analysts manually. This is another point at which data may be altered due to human error or software errors. There is a risk that errors involve very large investment amounts.

To mitigate this, checks are carried out and any incorrect large values which are detected are investigated (and potentially altered) in the analysis database before the statistics are produced.

Nonresponse error

Nonresponse errors may arise if a VCT does not announce an issue of its’ shares or if an investor does not make a claim for VCT relief.

Processing error

It is possible that errors exist in the programming code used to analyse the data and produce the statistics. This risk is reduced through developing a good understanding of the complexities of venture capital schemes, and thoroughly reviewing and testing the programs that are used.

6.4 Data revision

Data revision – policy

The UKSA Code of Practice for Official Statistics requires all producers of Official Statistics to publish transparent guidance on the policy for revisions.

News announcements for VCTs are published daily on commercial websites. There may be a few late annoucements or amended announcements being reported for the tax year 2020 to 2021, resulting in minor revisions to figures for 2020 to 2021 in Table 1 of next year’s release.

VCT investors can claim IT relief up to five years after the 31 January following the tax year in which the investment was made. Therefore, in next year’s publication, a small number of late claims may result in minor revisions to previously published figures, particularly to the provisional figures for 2019 to 2020.

Data revision – practice

This year, figures for 2019 to 2020 have been revised in Table 1 and figures prior to 2019 to 2020 have been revised in Table 2a and 2b.

6.5 Seasonal adjustment

Seasonal adjustment is not applicable for this analysis.

7. Timeliness and punctuality

7.1 Timeliness

All data including funds raised via VCTs and investors claiming IT relief were published in January 2022:

• Table 1 covers shares issued on or before 5 April 2021
• Table 2a and 2b cover returns relating to investments made on or before 5 April 2020

7.2 Punctuality

In accordance with the Code of Practice for official statistics, the exact date of publication will be given not less than one calendar month before publication on both the Schedule of updates for HMRC’s statistics and the Research and statistics calendar of GOV.UK.

Any delays to the publication date will be announced on the Schedule of updates and announcements for HMRC’s statistics webpage.

The full publication calendar can be found on both the Schedule of updates for HMRC’s statistics and the Research and statistics calendar of GOV.UK.

8. Coherence and comparability

8.1 Geographical comparability

This analysis is presented for a single region – the United Kingdom.

8.2 Comparability over time

There are no changes leading to comparability issues.

8.3 Coherence – cross domain

The value of funds raised in Table 1 could be different to figures produced by other commercial websites. This is due to differences in methodology and assumptions used to collect data.

Coherence – sub-annual and annual statistics

All statistics are presented as annual outputs. No coherence issues exist.

8.4 Coherence – internal

Rounding of numbers may cause some minor internal coherence issues as the figures within a table may not sum to the total displayed. Effort has been made to ensure totals between tables remain consistent where appropriate.

Total figures provided in Table 2a and 2b on the amount of investment on which Income Tax relief was claimed are not directly comparable with the figures on the amount of investment received by VCTs in a tax year shown in Table 1, as an amount of relief would be claimed outside Self Assessment, or not claimed at all.

9. Accessibility and clarity

9.1 News release

There were no press releases linked to this data over the past year.

9.2 Publication

The tables and associated commentary are published on the Venture Capital Trusts statistics webpage of GOV.UK.

The tables and associated commentary are published in HTML.

The document complies with the accessibility regulations set out in the Public Sector Bodies (Websites and Mobile Applications) (No. 2) Accessibility Regulations 2018.

Further information can be found in HMRC’s accessible documents policy.

9.3 Online databases

This analysis is not used in any online databases.

9.4 Micro-data access

Access to this data is not possible in micro-data form, due to HMRC’s responsibilities around maintaining confidentiality of taxpayer and VCT information.

9.5 Other

No other dissemination formats are available for this analysis.

9.6 Documentation on methodology

All up-to-date information on the methodology is found on this webpage.

9.7 Quality documentation

All official statistics produced by KAI, must meet the standards in the Code of Practice for Statistics produced by the UKSA and all analysts adhere to best practice as set out in the ‘Quality’ pillar.

Information about quality procedures for this analysis can be found in section 4 of this document.

10. Cost and burden

Funds raised by VCTs data is extracted manually from commercial websites and investor level data is obtained from an administrative data source. Thus, there is no additional burden on companies or HMRC tax inspectors to provide information.

This year, effort has been made to automate the production of statistics to some extent, increasing the efficiency of the process in forthcoming years.

It is estimated to take about 60 days full-time equivalent (FTE) to produce the annual analysis and publication.

11. Confidentiality

11.1 Confidentiality – policy

HMRC has a legal duty to maintain the confidentiality of taxpayer information.

Section 18(1) of the Commissioners for Revenue and Customs Act 2005 (CRCA) sets out our duty of confidentiality.

This analysis complies with this requirement.

11.2 Confidentiality – data treatment

The statistics in these tables are presented at an aggregate level so identification of individual companies is minimised, but potentially still possible.

Where potential risks exist, statistical disclosure control (SDC) is applied to cells within tables. SDC is the application of methods to ensure confidential data is not disclosed to parties who don’t have authority to access it.

SDC modifies data so that the risk of data subjects being identified is within acceptable limits while making the data as useful as possible.

Disclosure in this analysis is avoided by applying rules that prevent categories of data containing:

• small numbers of contributors
• small numbers of contributors which are very dominant

If a cell within a table is determined to be disclosive, its contents are suppressed either by removing the data or combining categories.

Further information on anonymisation and data confidentiality best practice can be found on the Government Statistical Service’s website.