Official Statistics

Background Quality Report: Employee Share Schemes statistics

Updated 18 January 2023

1. Contact

Organisation Unit - Knowledge, Analysis, and Intelligence

Contact Names - J Webb, R Waite

Contact Function – Specialist Personal Tax Statistics

Contact Email Address – [email protected]

Contact Mail Address – Liverpool, India Buildings, 4th Floor

2. Statistical presentation

2.1 Data Description

The Employee Share Scheme (ESS) statistics contain data relating to four tax-advantaged employee share scheme types. These include Company Share Option Plans (CSOP), Enterprise Management Incentives (EMI), Save as You Earn Share Option Schemes (SAYE) and Share Incentive Plans (SIP). They contain data including the numbers of companies using schemes, numbers of employees receiving awards or numbers of awards, values awarded, numbers of employees exercising options and estimates of the value of the Income Tax and National Insurance relief received.

The statistics are compiled from HMRC’s administrative data, which is based off annual returns for employment related securities.

The individual tables produced each year are as follows:

• Table 1 – Estimated cost of Income Tax and National Insurance relieved,

• Table 2 – Number of companies with tax advantaged Employee Share Schemes,

• Table 3 – Save As You Earn Option Plans,

• Table 4 – Company Share Option Plans,

• Tables 5.1 to 5.4 – Share Incentive Plans,

• Table 6 – Enterprise Management Incentives,

• Table 7 – Company Scheme Types,

• Table 8 – Number of live schemes

2.2 Classification System

The ESS statistics contain breakdowns of data on a company and individual level.

2.3 Sector Coverage

Employee share schemes allow employees to acquire options over shares or receive shares directly in their company as part of their remuneration. This allows employees and employers to benefit from income tax and National Insurance contribution reliefs. This publication covers the four tax advantaged shared schemes listed in section 2.1 only and does not cover other, non-tax advantaged share schemes that companies may also operate.

2.4 Statistical concepts and definitions

Scheme

As per section 2.1 there are four tax advantaged share schemes and companies may operate more than one share scheme at a time. Table 8 provides information on the number of live schemes under operation.

Grant

Employees may be “granted” share options by their employers which give them the right, but not the obligation, to purchase shares at a certain price at some point in the future. Tables 3 (SAYE), 4 (CSOP) and 6 (EMI) provide estimates of the number of companies that grant options and the number of employees that receive share options.

Exercise

Employees can acquire shares by exercising their share options. The conditions under which this can be done vary across share schemes. Tables 3 (SAYE), 4 (CSOP) and 6 (EMI) provide estimates of the number of companies where employees exercise options and the number of employees exercising options.

Gain

The value of shares acquired when employees exercise share options may be higher than the price they pay under their share option. This difference is the “gain” made by an employee. Tables 3 (SAYE), 4 (CSOP) and 6 (EMI) provide estimates of the financial value of gains made by employees on their options.

Awards

Under SIP, employees are directly awarded shares rather than being granted share options. Tables 5.1 to 5.4 provide information on the number of employees awarded shares and the value of shares awarded.

2.5 Statistical unit

The statistics relate to individuals and companies, the financial value of their share options / awards, and the gains made through their participation in tax advantaged share schemes.

2.6 Statistical population

The target population for which information is sought to compile the statistics are individuals or companies participating in tax advantaged employee share schemes.

2.7 Reference area

The ESS statistics cover the United Kingdom as a whole.

2.8 Time coverage

The time coverage is different for each of the different types of employee share schemes. SAYE statistics are based on data from tax year ending 1980 to present. CSOP statistics are based on data from tax year ending 1985 to present. EMI and SIP statistics are based on data from tax year ending 2000 to present.

3. Statistical processing

3.1 Source data

The data used for the ESS statistics for tax year ending 2016 onwards is taken from the return templates submitted online. These templates can be found online at Employment related securities return templates and forms under the heading ‘End of year return templates and guidance notes’ along with the EMI1 form for notifying HMRC of the grant of options in an EMI scheme.

The data used for the National Statistics for years up to tax year ending 2014 comes from the annual paper return forms (found at Employment related securities return templates and forms under the heading ‘Forms and templates for previous years’) along with the EMI1 form notifying the grant of options.

No national statistics were produced for tax year ending 2015. See section 8.2 ‘Comparability over time’.

3.2 Frequency of data collection

Data on employee share schemes is collected annually.

3.3 Data collection

As above, all employers who operate employment related securities schemes must submit an online return each year for all schemes. These must be submitted by 6 July following the end of the tax year, or 30 days after the form was issued if later.

3.4 Data validation

Analysts with knowledge of employee share schemes undertake checks of the data by evaluating changes in the aggregate, maximum, minimum, and average values for all data fields. If there are any unexpected changes in these aggregate values they investigate return forms on a company or individual level. Any records deemed to be incorrect may be adjusted or excluded from the dataset used for the statistics publication.

3.5 Data compilation

HMRC’s analysts aggregate data from information provided on the employment related securities return forms. Statistical software is used to extract, sort, filter and aggregate the data in order to produce the tables for the national statistics publication. However, due to the potential for late filing by some companies or individuals, some returns may be missing from the tables. See section 6.3.3 ‘Nonresponse error’.

4. Quality management

4.1 Quality assurance

All official statistics produced by HMRC’s Knowledge, Analysis, and Intelligence (KAI) organisation unit must meet the standards in the Code of Practice for Statistics produced by the UK Statistics Authority 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 that summarises the key QA tasks, and is used as a starting point for teams when they are considering what QA actions to undertake.

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 then 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. The quality assurance review checklist used for the production of these statistics was last reviewed in June 2022.

4.2 Quality assessment

The QA for this project adhered to the framework described in section 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, and all the 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 a piece of code

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.

Quality Assurance of the of the input data was carried out as described in the data validation sections in section 3 ‘Statistical processing’.

The analysis was audited by someone other than the lead analysts, who also has expertise in employee share schemes and data analysis.

Stage 4 – Running and testing the code

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

Checks were completed to ensure internal consistency. For example, checking that the totals equalled the sum of components, both within and across tables.

The final outputs were independently proof-read and checked by senior expert data analysts outside of the employee share schemes team.

5. Relevance

5.1 User needs

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

• national government – policy makers and Members of Parliament (MPs),

• regional and local governments,

• academia and research bodies,

• media,

• business community,

• the general public

5.2 User satisfaction

The most recent survey carried out to establish user satisfaction was in 2012. Within government, the main users of the ESS statistics are HMRC and HM Treasury, as well as smaller interest from other government departments. The survey also indicated that there are also some users of the statistics outside of the government. The majority of respondents identified themselves as “Legal/Tax advisory”. In addition, the data was also used by representative trade unions or professional bodies, lobby groups (or similar), publishers and share schemes administrators. There may also be interest in this publication from academics conducting research on this topic.

In response to the feedback, we produced a new table detailing scheme combinations on Table 7 and new columns for companies with employees granted shares or options, or exercising options. The value of the total gains and those eligible for Income Tax and National Insurance contributions relief have been added for Company Share Option Plans (CSOP), Enterprise Management Incentives (EMI) and Save As You Earn (SAYE) schemes. This has not been done for Share Incentive Plans (SIP) schemes as employees receive awards of shares rather than options. We introduced a new table in 2015 that shows the costs to the Exchequer for each of the schemes which can be found in Table 1. This table makes it easier for the user to view and compare costs for Income Tax and National Insurance Contribution reliefs associated with the four tax advantaged share schemes.

5.3 User completeness

It is a legal requirement that all companies operating the tax advantaged share schemes submit an employment related securities return by the required deadlines. Penalties exist for non-compliance.

6. Accuracy and reliability

6.1 Overall accuracy

There are a number of potential sources of error in the data, including sampling (for tax year ending 2014 and earlier), non-sampling error and assumptions and estimates used in the statistics production. The main source of error is where data has been entered incorrectly by the company. The data is therefore quality assured to identify these errors and if necessary, other available data is used to estimate correct values such as historical share prices and companies house records. There should not be any sampling error in the statistics for years following tax year ending 2014 as the online filing system for employment related securities replaced paper forms in tax year ending 2015, making all data available for analysis without the need for manual data capture with sampling within HMRC. Data is now submitted by companies online through templates provided by HMRC.

6.2 Sampling error

Since data for tax year ending 2016 onwards is taken from electronic templates submitted online, employees no longer need to be sampled for data capture so there should not be any sampling error for tax year ending 2015 onwards. For years prior to tax year ending 2014 the statistics were based on a sample of the paper forms returned. This means that there will be some sampling variability around the data for those years.

6.3 Non-sampling error

Coverage error

As stated in section 6.1 ‘Overall accuracy’ since tax year ending 2016 the national statistics are based on all data submitted by companies to the Employment Related Securities system.

Measurement error

One source of error in the data is where data has been entered incorrectly, either by the company sending the form or as part of the data entry process. Common mistakes made by companies include incorrect currencies being used on the form, the price being entered in pence instead of pounds or the total value of shares being entered instead of the value for individual shares. Prior to tax year ending 2015, when the online submissions began, an error might also be made in keying in the values from the form at the data entry stage. To identify these errors, we check the data for outlying values, against the share schemes limits and check the data in the electronic databases against data from the paper tax return form itself. We also use other available data to estimate the correct value such as historical share prices that are publicly available, data from other parts of the form, or data for the same company for another year. Where it appears erroneous data has been submitted it is either adjusted or omitted from the national statistics.

Nonresponse error

Some data fields are defined as “optional” on the return forms and therefore a high level of non-response is prevalent. We believe this has a small impact on the national statistics. Furthermore, the figures produced in the statistics typically do not represent 100 percent of individuals. This is due to late filing - companies who do not submit their online returns by the required date. We do not make any adjustments to the aggregate statistics for late filers, however, because the statistics are produced nearly a year after the filing deadline we believe that late filers would not significantly affect the statistics.

Processing error

From tax year ending 2015, companies submit their completed returns or notifications online using the Employment Related Securities returns system. This removes the chance of manual input error within HMRC processing but does not remove the chance of manual input error by companies when completing templates. Templates that are submitted through the Employment Related Securities returns system are subject to an electronic validation check that includes assessing the type and format of data entered and checks for any missing mandatory information. Only data from templates that pass this initial validation will be included in this publication.

6.4 Data revision

Data revision – policy

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

Data revision – practice

Each year we update the national statistics to reflect the latest full year data only. This is based on data submitted for a given tax year that ended one year prior to the publication to allow for late filing and data processing. For example, in June 2021 the national statistics were updated for data from tax year ending 2020. Historical time series will only change if it is necessary due to a significant methodological change.

7. Timeliness and punctuality

7.1 Timeliness

The statistics are aggregated into tax years, which run from 6 April until 5 April. Since April 2015, companies have been required to submit their annual returns using the online Employment Related Securities system. Returns templates should be submitted by companies no later than midnight on the 6 July after the end of the tax year. For EMI schemes, companies also need to complete a separate template to notify of any options granted within 92 days of the grant. Updates to the tables are expected to be published in June the following year to allow time for data received from Employment Related Securities to be checked and corrected where necessary.

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 HMRC National Statistics website.

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

Not applicable.

8.2 Comparability over time

There have been some issues with comparing the data overtime. In the move from paper returns to online returns, the Employment Related Securities service encountered some technical difficulties in the first year, affecting the supply of data for tax year ending 2015. It was therefore not possible to update these ESS statistics for tax year ending 2015 leading to a gap in the series.

Furthermore, various policy changes may have led to the figures being incomparable over time, and caution would need to be taken when comparing them.

In 1996, CSOP replaced Discretionary Share Option schemes. In 2000, new schemes were not approved for approved profit-sharing schemes. In 2003, no further shares were appropriated to employees by existing schemes.

In 2008, the limit of the value of EMI shares that can be granted to an employee increased from £100,000 to £120,000. In 2012, the limit of the value of EMI shares that can be granted to an employee increased further from £120,000 to £250,000.

In 2014, the employee contribution limit for SAYE schemes increased from £250 per month to £500 per month. In 2014, the annual limits for awards or purchase of SIP shares increased from £3,000 to £3,600 for free shares, and from £1,500 to £1,800 for partnership shares.

8.3 Coherence – cross domain

Not applicable.

8.4 Coherence – internal

In general, if figures used in the national statistics are rounded, they are rounded to thousands (for number of employees/companies data), and millions (for share value data). However, when calculating totals, averages and doing internal consistency checks, unrounded figures are used. As a result, the totals may not add in the tables.

9. Accessibility and clarity

9.1 News release

There have been no press releases linked to this publication over the past year.

9.2 Publication

The publications are made annually. They are available on the Employee Share Schemes website. The tables and background are produced in an OpenDocument format. The commentary is produced in a HTML format. All documents comply 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

The analysis is not used in any online databases.

9.4 Micro-data access

Access to the data used in this publication is available through HMRC’s Datalab, which allows approved researchers to access de-identified HMRC data in a government accredited secure environment.

9.5 Other

Not applicable.

9.6 Documentation on methodology

Documentation on the methodology is available in a separate background document, which is produced alongside the statistical tables. It is available on the website for Employee Share Scheme statistics page.

9.7 Quality documentation

All Official Statistics produced by HMRC must meet the standards set out 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.

10. Cost and burden

There is no respondent burden since the data is sourced from information on tax returns that companies or their agents are required to complete. The annual operational cost (staff time) of producing the statistical tables and accompanying documents is approximately 25 days FTE.

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 the identification of individuals is not possible.

To ensure that no individual taxpayers or customers can be identified, statistical disclosure control (SDC) is applied to the cells within the tables. SDC is the application of method to ensure confidential data is not disclosed to parties who do not have the authority to access it.

SDC modifies published 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:

• a small numbers of contributors,

• a small numbers of contributors that are very dominant,

• or if a cell within a table is determined to be disclosive, its contents are suppressed either by removing the data or—as done in this publication—combining categories

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