1. 4 May 2010 Towards a common revision for European statistics By Gian Luigi Mazzi and Rosa Ruggeri Cannata Q2010 European Conference on Quality in Official Statistics 4-6 May 2010

2. Eurostat – Unit D5 Key indicators for European policies Outline Introduction Background: definitions and classifications Revisions practices for PEEIs European aggregates Principles for a common revisions policy for European statistics Issues related to common revisions policy at domain level Conclusions

3. Eurostat – Unit D5 Key indicators for European policies Revisions For the users: annoying phenomenon For the producers: normal phenomenon to increase progressively quality and precision Both: interested in gaining a better understanding of the revision process as well as in its analysis Informed decisions based on –transparency of the production process –Clear and publically available dissemination strategy

4. Eurostat – Unit D5 Key indicators for European policies European Statistics code of Practice Principle 8 Appropriate Statistical Procedures: revisions follow standard, well-established and transparent procedures Principle 12 Accuracy and Reliability: studies and analyses of revisions are carried out routinely and used internally to inform statistical processes Principle 15 Accessibility and Clarity: Statistics are presented in a form that facilitates proper interpretation and meaningful comparisons PEEIS: EFC Status Reports on information requirements in EMU

5. Eurostat – Unit D5 Key indicators for European policies Background definitions of revisions Definition 1: Any change in a value of a statistic released to the public by an official national or supranational statistical agency. When: Definition 2: For a given time series we define vintage the set of data that was the latest release at a particular moment in time. Definition 3: Historical data, catalogued and indexed by the date on which the data became available to the public, are referred to as “vintage” data (Anderson). Alternative definition for revisions: Changes from an earlier vintage of estimates to a later vintage (Fixler and Grimm).

6. Eurostat – Unit D5 Key indicators for European policies Classifications of revisions Revisions Classified by Reason – To incorporate better source data – To capture routine recalculation – To reflect improved methodology – To correct errors Revisions Classified by Scheduling Routine revisions Annual revisions Major revisions

7. Eurostat – Unit D5 Key indicators for European policies Effects of revisions Revision of existing interpretations of the course of the indicator Change of economic forecasts and policy implications Qualification of user interpretations of current and recent observations Information on the expected reliability of existing and future values Qualification of the degree of confidence Monitoring the quality of the data production process Improvement of the production process

8. Eurostat – Unit D5 Key indicators for European policies Revisions practices for PEEIs European aggregates HICP: follow Commission regulation heterogeneous practices: –the number of times a figure could get revised is varying –the extent of revisions back in time too: routine revisions could cover just few values, values up to one year or the entire series Trade-off: updated information towards less frequent revisions

9. Eurostat – Unit D5 Key indicators for European policies General principles 1 General and domain specific revisions policies Each statistical institution within the ESS defines, communicates and publicly releases well documented general revisions policies and domain specific ones applicable to European statistics under its responsibility. 2 Consistency and stability of domain specific revisions policies Domain specific revisions policies should be kept consistent across statistical domains and countries as far as possible and stable over a sufficiently long time period. 3Communication of revisions Statistical institutions within the ESS should define a common strategy for each statistical domain to communicate qualitative and quantitative information on data revisions of European statistics.

10. Eurostat – Unit D5 Key indicators for European policies Principles related to the data production process 4Routine and annual revisions Routine and annual revisions should be published in the framework of well defined, synchronised and regularly updated release/revision calendars at national and European level. Releases of European and national data aggregates should be synchronized as far as possible. 5Major revisions Major revisions should only take place in larger intervals. They should be pre-announced, backwards implemented and coordinated across statistical domains and institutions. 6Unexpected revisions Unexpected revisions should be reduced over time to the case of errors and unforeseeable accidents occurring in the production process. They should be released without waiting for scheduled revisions. Corrections should be accompanied by appropriate explanation. 7 Definition of domain specific revisions policies Domain specific revisions policies should rely on sound and homogenous methodological choices covering i.a. scheduling of revisions, possible use of thresholds, depth, and seasonal adjustment whenever applicable. 8 Data vintages and monitoring of revisions As far as appropriate, each statistical institution within the ESS carries out and disseminates regular revisions analysis at statistical domain level. For this purpose the adequate vintage databases consistent with release/revision calendars should be implemented, maintained and disseminated.

11. Eurostat – Unit D5 Key indicators for European policies Issues related to common revisions policy at domain level (1) Routine revisions –Concurrent adjustment –Current adjustment –Mixing the two strategies Choice based on: –Presence of a bias in the first data release –Randomness of the revisions process –Degree of volatility of the indicator

12. Eurostat – Unit D5 Key indicators for European policies Issues related to common revisions policy at domain level (2) Threshold + Avoid unnecessary revisions + Reduce the number of revisions - Small but significant revisions could be discarded -Affects aggregation constraints Threshold Level should depend on the characteristics of the generating process

13. Eurostat – Unit D5 Key indicators for European policies Issues related to common revisions policy at domain level (3) Extent back in time: largely varying, from few ones to the whole series –routine revisions should involve a limited number of periods –annual ones a larger number –Avoid inconsistencies over the time as well as breaks –Revise the whole series within a multi-annual benchmarking or rebasing exercise at regular intervals –Inform users on the extent of different kind of revisions

14. Eurostat – Unit D5 Key indicators for European policies Issues related to common revisions policy at domain level (4) Infra-annual time series: revisions policy of seasonally adjusted data Specific issues of the generating process to be considered at domain level ESS guidelines on seasonal adjustment –Revisions of raw data –Concurrent adjustment, partial concurrent adjustment, Current adjustment, controlled current adjustment

15. Eurostat – Unit D5 Key indicators for European policies Revisions Analysis OECD, member states, ECB vintage databases or data warehouses PEEIs vintage database Handbook on revisions analysis

16. Eurostat – Unit D5 Key indicators for European policies Conclusions Lack of harmonisation in current existing revisions practices for Europeans statistics (in particular PEEIs) Need for a general framework for a common revisions policy within the ESS To be complemented by domain revisions policies Will increase: –Transparency of the revision process –Data comparability –Harmonisation –Quality of European aggregates

17. Eurostat – Unit D5 Key indicators for European policies Thank you for your attention!