Quality and methods for administrative data in official statictics
In this article, Charlie Wroth-Smith, Head of Methodological Research Hub at the Methodology & Quality Directorate, shares insights on the quality and methods of utilizing administrative data in official statistics. The discussion covers key aspects such as data collection, validation, and analysis, highlighting the significance of accurate data for robust statistical outcomes.
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Presentation Transcript
Quality and methods for administrative data in official statistics Charlie Wroth-Smith Head of Methodological Research Hub, Methodology & Quality Directorate 29 June 2022
Administrative data Why? The data revolution - opportunities for analysis and public policy, and for increased efficiency Transformation putting administrative data at the core of our statistical systems Be collaborative adopt creative solutions such as outsourcing and developing partnerships across the private and public sectors. Develop our capability to integrate administrative and commercial data sources, supported by appropriate methods. Keep pace with advances in technology [and techniques]
But there are challenges. Definitional differences Coverage issues Missingness Lack of metadata Linkability e.g. no unique identifier Changes to systems, variables etc
UK Administrative Data Methods Research programme Aims: To make effective use of non-survey sources To develop a statistical framework for using administrative data in official statistics To ensure rigor, transparency and assurance of methods developed to produce official statistics using new and integrated data sources To create and share best practice and guidance Collaborative approach:these are shared challenges!
Administrative data research themes Quality framework, indicators and uncertainty measures Linkage linkage error, multiple sources, new techniques Privacy confidentiality methods to deal with linked data, more granular outputs and new ways of disseminating data Estimation handling definitional or conceptual differences, under/over coverage Statistical design guidance or case studies for integrating survey and admin data for official statistics Innovative techniques e.g. synthetic data
Quality for administrative data Developed administrative data quality framework for use across UK government Covers entire administrative data journey Includes question bank to guide discussions with data suppliers to understand quality Includes quality dimensions
European Statistical System Quality Dimensions Relevance Accuracy and Reliability Timeliness and Punctuality Accessibility and Clarity Coherence and Comparability
Quality Quality indicators and measures that are understood by users Open source code for measuring quality Guidance on how to communicate quality to users Guidance on how to engage with data suppliers to improve data quality
Questions Contact details: Charlie.wroth-smith@ons.gov.uk - Head of Methodological Research Hub international.development@ons.gov.uk UK International Development Team
