The use of administrative data in the production of business statistics has become more and more widespread. Statistical offices can obtain efficiency gains by the re-use of data from external sources, and counter the increase of non response in sample surveys with this strategy.

However, efforts are needed to ensure the quality of the data, because very often the administrative and other external data are not available in the form needed for statistics.

Since working with administrative data sets is still relatively new and the technology behind it changes over time, a systematic approach to qualifying the usefulness of administrative sources is only just emerging. Finding and resolving data quality issues with incoming data is in many cases performed on an ad hoc basis rather than by a repeatable set of processes.

One of the work packages of the European Statistical System Network (ESSnet) project on the use of administrative data in business statistics aims to assist statistical offices by collecting and presenting experiences with selecting and preparing administrative data for use in the production of statistical information.

The paper will present the first results achieved in elaborating a checklist for evaluating the usefulness of administrative data sources and on finding and resolving initial data quality issues in data sets before they are used further up in the chain.

Keywords: Administrative data; Data quality

Biography: Frank Verschaeren leads projects for the “databases and nomenclature” department of Statistics Belgium. Within the European ESSnet project on the use of administrative data in business statistics he is work package leader for package 2a: “Checklist to assist Member States when investigating the usefulness of Administrative Data” and package 2b: “Checklist for the quality of administrative data inputs”

He joined Statistics Belgium in 1997, contributed to the development of a harmonized methodology for Eurostat's Business Demography project and has built up experience in setting up new statistics and reengineering existing ones for his national statistical office.