Official Statistics

Quality Report: Plastic Packaging Tax (PPT) statistics

Published 17 August 2023

1. Contact

Organisation unit: Knowledge, Analysis and Intelligence (KAI)
Name: Environmental Taxes, Indirect Taxes, Customs & Co-ordination
Mail address: HMRC, Knowledge, Analysis and Intelligence (KAI), 3 New Bailey, Salford, M3 5JL
Email: revenuemonitoring@hmrc.gov.uk

2. Data description

This publication provides a breakdown of historical receipts, registered businesses and tonnages for the Plastic Packaging Tax (PPT).

The publication includes revenue statistics which are up to the latest full financial year of operation before the statistics release. Tonnages that are included in the statistics represent the tonnages declared in the relevant financial year. Tonnage statistics are based on the tonnages of plastic packaging that are manufactured in and imported into to the UK.

This publication only includes figures for previous years. Forecasts of future PPT receipts are produced and published by the Office for Budget Responsibility (OBR), and can be found on their website.

2.1 Classification system

The data used to compile the PPT statistics come from several sources:

• cash receipts and returns data are taken from the Enterprise Tax Management Platform (ETMP)

• tonnage declaration and liabilities data is taken from information provided by traders on the PPT return form

• standard industrial classification (SIC) codes information is currently not available due to insufficient data quality, however this will be re-assessed in the future if there is a user interest

These forms and returns help classify the data within the PPT statistics and provide the main breakdowns into the different tax heads.

A unique taxpayer reference (UTR) number is assigned to each registered UK trader. These UTRs are used during the data aggregation process.

2.2 Tax coverage

PPT is an indirect tax charged following the manufacturing or importing of plastic packaging that contains less than 30% recycled content.

Businesses must register for PPT if they manufacture or import more than 10 tonnes of plastic packaging in the UK. The analysis in this statistical publication focuses on the registered businesses.

2.3 Variable definitions

PPT receipts

The amount of PPT tax liability that is owed to HM Revenue and Customs (HMRC). This is revenue reported in the statistics.

Tax liability

The total amount of tax debt owed to HMRC by a business or entity.

Financial year

The statistics are aggregated into financial years. A financial year stretches from 1 April until 31 March the following calendar year.

Financial quarters

A quarter is a three-month period within the financial year. Each financial year contains four quarters. The first quarter of a financial year starts in April and ends in June.

Registered population

The number of businesses that have signed up to the PPT including businesses that have registered outside of the UK.

2.4 Unit

The PPT returns data is reported to HMRC in killograms. Within the statistics, the plastic packaging declared amounts are aggregated into thousands of tonnes. The units used to display the plastic packaging tax revenue is million pounds.

2.5 Time coverage

The statistics cover the financial year time period.

2.6 Reference area

The statistics cover businesses who manufacture in the UK including Northern Ireland and foreign businesses whose packaging is imported into the UK.

3. Statistical processing

3.1 Source data

The data used to compile the PPT statistics come from two sources:

• cash receipts and returns data are taken from the Enterprise Tax Management Platform (ETMP)

• tonnage declaration and liabilities data is taken from information provided by traders on the PPT return form

3.2 Frequency of data collection

The data for PPT receipts are updated daily into databases for analysis as new returns can be made daily by businesses.

3.3 Data collection

Data on PPT receipts are sourced from ETMP. Collection is part of the team’s normal administrative procedures.

Data on PPT revenue collected and tonnages are sourced from PPT tax returns via ETMP. This is downloaded using the software package SAS. Any code is thoroughly checked and quality assured.

Data is sense checked and checked against previous months. Any unexpected trends are thoroughly investigated and explained.

3.4 Data validation

Statistics are sense checked after compilation to ensure there are no mistakes or unexplained outliers.

Data may be compared to external or public sources to validate that trends are consistent.

3.5 Data compilation

Data for PPT revenue, registered population and tonnages are sourced from ETMP which are downloaded using the software package SAS. The data is then aggregated in the software package R. The aggregated data is analysed during the data compilation and sense checked to ensure accuracy.

3.6 Adjustment

No significant adjustment currently takes place within the PPT statistics.

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 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 people’s 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.

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; 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 and populating a model/piece of code

The statistics were quality assessed as follows:

• 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

The statistics were quality assessed to be explainable and in line with expectations.

Stage 5 – Drafting the final output

The final outputs were quality assessed as follows:

• checks were completed to ensure internal consistency (for example, 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:

• national government – policy makers and MPs

• academia and research bodies

• media

• industry stakeholders

• general public

5.2 User satisfaction

The demand for the PPT statistics is demonstrated by the number of Freedom of Information (FOI) requests made by the general public since it came into operation.

The PPT statistics have not been evaluated in a survey or consultation as of July 2023.

5.3 Completeness

It is a legal requirement that all businesses are regulated and submit the relevant returns required. Penalties exist for non-compliance. The statistics contained in this report can therefore be considered as complete despite the possibility of revisions.

6. Accuracy and reliability

6.1 Overall accuracy

The statistics 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 nature of the administrative data used may mean some errors exist in the recorded figures which would impact the accuracy of production estimates.

The potential sources of error include:

• companies entering incorrect information onto return forms

• human or software error when entering the data into systems

• companies not completing their returns by the required date

• mistakes in the programming code used to analyse the data and produce the statistics

6.2 Sampling error

No sampling takes place within the PPT statistics.

6.3 Non-sampling error

Coverage error

The data used to produce these publications is exhaustive, and covers all plastic packaging sold under UK jurisdiction which is subject to excise duty that is over the 10 tonne threshold where businesses must declare their plastic packaging. This means that data on volumes and receipts refers to all plastic packaging placed declared to HMRC on the market legally. Coverage error is therefore not relevant.

Measurement error

The main sources of measurement error could be categorised as respondent errors and include the following:

• companies may make errors entering their information onto return forms, whether this is done on paper or electronically

• company tax return data is subsequently entered onto HMRC systems either manually or by electronic transmission, which is another point at which data may be altered due to human or software error

Nonresponse error

The PPT statistics are routine administrative data based on receipts and clearances that must be submitted, therefore nonresponse error is not relevant.

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 code and thoroughly reviewing and testing the programs that are used.

6.4 Data revision

Late returns can influence the data used for the publications. For that reason, the last financial year of data is labelled as ‘provisional’, although revisions tend to be minor. Where there are revisions they are clearly marked as ‘revised’, and information is given as to the reasons and scale of the revisions if appropriate.

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.

6.5 Seasonal adjustment

No seasonal adjustment occurs within the PPT statistics (as the time series are not yet long enough) and is therefore not relevant to the publication.

7. Timeliness and punctuality

7.1 Timeliness

The statistics are published one month after a full financial year’s worth of data has been collected. The statistics take around one week to produce once the data has been collected. The remaining time is spent quality assuring the information in the statistics.

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.

There have been no incidents of late publication of the statistics and this is the first quality report produced for the PPT publications.

8. Coherence and comparability

8.1 Comparability over time

There are no known comparability issues with the PPT Statistics.

8.2 Coherence – cross domain

No known issues regarding coherence between domains.

Coherence – sub-annual and annual statistics

No known issues regarding coherence between sub-annual and annual statistics.

Coherence – national accounts

The statistics are coherent with the national accounts framework, but users should note that PPT revenue is reported on a cash basis by HM Revenue and Customs (HMRC), such as when cash payments are received, but within some national accounts publications, such as the Office of National Statistics Public Sector Finances publication, PPT revenue is published on an accrued basis, for example when tax liability was accrued by taxpayers.

8.3 Coherence – internal

No known issues regarding coherence between internal datasets.

9. Accessibility and clarity

9.1 News release

We will link press notices here once we are aware of them.

9.2 Publication

The data is publicly available within the PPT statistics and is published at 9.30 am on the pre-announced date of release.

The PPT statistics commentary is published in Hypertext Markup Language (HTML) format, as generated within internal UK government HTML Markdown software. The PPT statistics data tables which accompany the commentary are published in Open Document Spreadsheet (ODS) format.

Accompanying the statistics are a background and references document which include:

• definitions of PPT rates

• details on how PPT duties are levied and paid

• methodology for producing PPT duties statistics

• statistical quality information, including HMRC’s rounding policy

• hyperlinks to relevant pages where users can find more information

• both historic duty rates and background and references are published in HTML format

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 information.

9.5 Other

There aren’t any other dissemination formats available for this analysis.

9.6 Documentation on methodology

Background and references to the PPT statistics are publicly available to users within the PPT statistics.

9.7 Quality documentation

All official statistics produced by KAI, 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.

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

10. Cost and burden

The annual update to the statistics takes up to 2 weeks in total for the main analyst to complete and receive QA from other analysts, the team leader, and the person signing off the release. The annual cost, therefore, is around days a year (2 weeks per publication completed 1 time a year).

There is no respondent burden since the data is taken from administrative sources which are used by taxpayers to make their usual returns to HMRC.

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

Before going live, the statistics are classified as pre-released experimental official statistics, and are therefore subject to a restricted protective marking when referred to in email correspondence and are subject to the Code of Practice for Official Statistics, which is strictly enforced.