The latest Data Explained summarises experiences and learning from working with the Annual Survey of Hours and Earnings (ASHE) linked to Pay-As-You-Earn (PAYE) and Self-Assessment Data – England, Scotland, and Wales.
The data in this collection comes from HMRC’s administrative system for personal tax records. The data includes payments made to employees (PAYE), some additional information on employment and end-of-year summaries, and submissions for self-assessment (SA) required from most people who receive non-employment income. These PAYE and SA files can be linked to the ONS Annual Survey of Hours and Earnings (ASHE), a survey aimed at 1% of employees collected by ONS for Great Britain.
The collection comprises seven research-ready datasets compiled from this data:
- weekly_clean: PAYE data for those paid weekly
- monthly_clean: PAYE data for those paid monthly
- weekly_panel: PAYE data for all employees, with monthly pay split across weeks
- monthly_panel: PAYE data for all employees, with weekly pay added up to months
- ASHE_supplement: a summary of the PAYE data for an employee for a year, intended to be
used in collaboration with ASHE data - SA: all the data from the self-assessment records collected into one file
- SA_summary: a subset of the SA data intended to contain the most useful variables
To explore these data, this Data Explained provides an overview of the following elements:
- How is the data collected?
- Key variables
- What can the data be used for?
- Data limitations encountered
- Suggested improvements
- Suggested future data linkages
- Recommendations to data owners
You can find the full Data Explained here.
If you want to find out more about the data, you can find the following information in the Data Documentation tab:
- HMRC quick user guide
- PAYE variables list
- SA variables list
- Creating the PAYE panel
- Understanding ASHE and HMRC reference numbers.
If you use the ASHE in your research, don’t forget to sign up to the WED Knowledge Hub, a platform for researchers to ask questions of each other regarding ASHE datasets or analysis using ASHE data.