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Using Administrative Data to Improve Social Statistics – An Example of Collaborative Work. Minda Phillips, Office for National Statistics. Paul Sinclair, Department for Children, Schools and Families. Outline of Presentation. Introduction New data sharing opportunities Statistical Drivers
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Using Administrative Data to Improve Social Statistics – An Example of Collaborative Work Minda Phillips, Office for National Statistics. Paul Sinclair, Department for Children, Schools and Families.
Outline of Presentation • Introduction • New data sharing opportunities • Statistical Drivers • Feasibility Research • Next Steps • Lessons Learned
Introduction Access to, and use of, administrative data will contribute to:- • the development of new and improved statistics; • maintaining survey and census response rates; • reducing compliance costs; and • minimising respondent burden.
Data Sharing The passage of the Statistics and Registration Service Act 2007 will:- • facilitate the sharing of data for statistical purposes; • provide a mechanism for removing existing legal barriers or create new legal gateways. Subject to secondary legislation in each case and • ministerial consent; • parliamentary approval.
Migration Statistics Improvement Programme This programme set up in 2007 is designed to:- • provide better migration statistics; • improve the mid-year population estimates and population projections; • develop new demographic indicators; • co-ordinate the publication of key outputs.
Migration Statistics Improvement Programme Special attention is being given to:- • producing better information on local populations; • pinpointing areas with high turnover; • understanding internal migration moves; • identifying the characteristics of migrants; • developing/integrating administrative and survey sources to improve monitoring of population change.
Feasibility Research Pilot or feasibility studies must be undertaken to:- • understand the scope, content and quality of specific sources; • develop appropriate methods of data cleaning, linkage and matching; • test data handling and processing arrangements.
School Census - Scope The School Census covers those attending:- • nurseries; • primary schools; • middle schools; • secondary schools; • city technology colleges; and • academies.
School Census – Information Collected Information on pupils includes:- • identifiers; • characteristics; • attendance; • Exclusions; • post -16 learning aims; • special needs.
School Census - Quality Research has facilitated understanding of:- • data collection and processing; • quality assurance and validation; • coverage; • completeness; • accuracy; and • data definitions and classifications.
Business Case Feasibility research facilitated the:- • development of the statistical business case; • identification of a sub-set of variables; • aggregate analyses.
Next Steps Feasibility research on linkage and matching:- • sample of birth records; • data on educational attainment.
Linking Birth Data and the School Census The second part of our work will help us to:- • investigate the feasibility of linking and matching birth records with information for children in the first year of primary education; • understand the factors affecting match rates and associated methodological issues; • consider variations between information on births and the number of 5 year olds recorded in the School Census and establish whether or not there are differences for those whose birth records can, and cannot, be successfully linked.
Lessons Learned Our work has underlined the importance of:- • good will; • effective working relationships; • trust; • effective communication; • availability of resources; • shared understanding of roles and responsibilities.
