Developing Quality Indicators for Business Statistics Involving Administrative Data: Work of the ESSnet on Administrative Data
John-MarkĀ Frost
Quality Centre, Methodology Directorate, Office for National Statistics, Newport, United Kingdom

With the increasing use of administrative data in the production of business statistics comes the challenge for statistical producers of how to assess quality. Although the European Statistical System (ESS) dimensions of quality apply to all statistics, not all elements of these dimensions are appropriate for statistics that are fully or partly based on administrative data. This is particularly the case for indicators of accuracy but also applies to other quality dimensions.

One of the work packages of the European Statistical System Network (ESSnet) project on the use of administrative data in business statistics aims to address this issue. In particular, the aim is to develop quality indicators for business statistics involving administrative data. To achieve this, work has been done to review existing practices across more than 30 NSIs and, based on this, a list of basic quantitative quality indicators has been drawn up. Work is ongoing to develop composite and more complex quality indicators and qualitative indicators.

This paper will outline the work of the AdminData ESSnet in this area, the results of the research into quality indicators, and will introduce and review the list of basic quantitative quality indicators developed thus far. Progress on the work to develop more complex and composite indicators will also be provided.

Keywords: Administrative data; Quality indicators; Business statistics; ESSnet

Biography: John-Mark Frost is a member of the Quality Centre in the UK Office for National Statistics. He has been a member of the European Statistical System network (ESSnet) project on the use of administrative data in business statistics since it start in 2009 and he leads the work package that aims to develop quality indicators for business statistics involving administrative data.