The Office for National Statistics Administrative Data Methods Research Programme

The quantity of administrative data created, stored and processed in the world has grown exponentially over recent years, but the statistical theory to support its use in official statistics has not. That’s not to say that within the statistical community we are not using or investigating a wide var...

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Bibliographic Details
Main Authors: Claire Shenton, Lucy Tinklet, Hannah Finselbach
Format: Article
Language:English
Published: Swansea University 2019-11-01
Series:International Journal of Population Data Science
Online Access:https://ijpds.org/article/view/1239
Description
Summary:The quantity of administrative data created, stored and processed in the world has grown exponentially over recent years, but the statistical theory to support its use in official statistics has not. That’s not to say that within the statistical community we are not using or investigating a wide variety of statistical sources, but the methods used are not based on well-established theory like we have for surveys. As a National Statistical Institute (NSI), we are transforming to put administrative and alternative data sources at the core of our statistics. Combining new sources with surveys will allow us to meet the ever-increasing user demand for improved and more detailed statistics. However, using administrative data involves addressing a range of statistical challenges as identified in “Statistical challenges of administrative and transaction data” (Hand, 2018). The Administrative Data Methods Research Programme was set up to address these challenges by developing a statistical framework for using and integrating administrative and transactional data to produce official statistics and analysis. The key themes of the programme include quality, linkage, privacy, estimation, statistical design, analysis and innovative techniques. The programme will ensure the rigor and assurance of methods developed, allowing where possible wide-reaching application, and to create and share best practice and guidance. A key part of this programme will be engaging and working collaboratively with the statistical community in academia, government and private sector to help prioritise the challenges, shape the work programme and drive the work forward.
ISSN:2399-4908