statistik.atSeite 1 Norbert Rainer Quality aspects and quality criteria of a classification revision and its implementation European Conference on Quality in Official Statistics May, Helsinki Session 13: Reengineering of statistics production

statistik.atSeite 2  Background and motivation  Character of statistical classifications  Quality report of statistical classifications  Quality of implementation of statistical classifications  Resume Overview

statistik.atSeite 3  No EU legal requirements to elaborate quality reports for statistical classifications  No EU legal requirements to produce implementation reports of the newly revised classifications  Rarely, no mentioring of classification issues/aspects in the ESS Standards for Quality reports Background and motivation (1)

statistik.atSeite 4  Statistical classifications are indispensible instruments for nearly all statistical domains  There is a remarkable high number of statistical classifications  The application of statistical classification affects all parts of the statistical production process  The revision of the central statistical classifications has thus great influence on the data production Background and motivation (2)

statistik.atSeite 5 ? Is the concept of quality reports applicable to statistical classifications? ?Do we need to differentiate between the classification and its implementation? ? Where do we document quality issues of classification implementation? ?Do we have an answer to the question whether the currently implemented revised system of economic classifications has contributed to the quality of economic and business statistics, and if yes, to what extent and in which aspects? Background and motivation (3)

statistik.atSeite 6  Statistical classifications as instruments  model of reality  language  tool for producing and presenting of statistical data  Statistical classifications as statistical products Quality report Character of a statistical classifications

statistik.atSeite 7 Quality reporting criteria/issues of statistical classification Quality dimensions Issues/criteria RelevanceStructure and hierarchical level of the classification with respect to user needs AccuracyConceptual basis and theoretical model Timeliness and punctuality Revision / update policy Accessibility and clarity Comparability and coherence Access to the classification and its metadata Clarity of classification devices Harmonisation of classification: internationally, between the various classifications, over time

statistik.at Seite 8 Six statistical processes ESS Standard for Quality Reports (Eurostat, 2009): With respect to quality indicators and quality reports a distinction is made between the following six categories of statistics (statistical processes): 1.Sample surveys 2.Census 3.Statistical process using administrative sources 4.Statistical process involving data from multiple data sources 5.Price and other economic index process 6.Statistical compilations Statistical registers Statistical classifications

statistik.atSeite 9 Easy access to the classification and its concepts and content; clarity of classification instruments Extent of achieved harmonisation How the user needs have been considered Adequate and improved conceptual basis and model of reality Quality of classification and implementation feedback Quality report of a (revised) statistical classification Implementation feedback Timeliness of changed reality and user needs considered; prunctuality of the revision process

statistik.atSeite 10 Quality of implementation Example of NACE Rev. 2 implementation Transformation of the European classification into a national one (translation issues, etc.) Recoding of all units in the business register (and in administrative registers) Double coding of the units in the business register Adaptations of the statistical survey concepts Construction of time-series (Double reporting, Back casting) Quality reports of the business register Quality reports of the various statistical domains

statistik.atSeite 11 Quality of implementation NACE Rev. 2 Coding and recoding Business register Double coding Backwards coding Surveys / data production Statistical data Double reporting Backcasting

statistik.atSeite 12  Contrary to the importance of classifications for the production of statistical data, less attention is given to the classifications in the context of quality reports  An updated/revised classification will certainly improve the quality of the statistical data, however, the extent of the improvement depends also on implementation issues outside the classification domain  Especially in the case of the revision of a central statistical classification to be implemented in a lot of statistical domains, on overall assessment of the quality issues related seems advisable, in addition to the single quality reports Resume

statistik.atSeite 13 Thank you for your attention ! Norbert RAINER mailto: Tel.: