Quality evaluation of statistical processes based on administrative data

Over the last decade, National Statistical Institutes (NSIs) have progressively moved from single- to multi-source statistics. By combining different data sources (direct survey, administrative and big data) NSIs can increase the detail of information, save data production costs and reduce burden on respondents. The Italian NSI (Istat) has strongly increased the use of administrative archives as primary source for statistical production purposes. To this aim, a system of statistical registers based on the integrated use of administrative sources is under development, and many statistical processes have being accordingly re-designed. Such a change calls for a tailoring of the current approaches for quality measurement and assessment. While in Istat a total quality framework based on the Total Survey Error (TSE) is well developed for surveys, a quality framework supporting the design of the new required statistical processes, based on the use of several types of sources, their evaluation and monitoring is still missing. To this extent, the adaptation of the TSE lately proposed in literature for statistical processes using administrative data sources has been taken as reference. We illustrate as the proposed quality framework has been tested on a new process - the statistical register Frame-SBS - that supports the estimation of structural statistics on businesses. As a major result, a proposal for an additional quality assessment phase is described.