A Proposal for a revisions policy of Principal European Economic Indicators (PEEIs) OECD STES WP June 2008

PEEIs Revisions Policy 2 This paper expresses the authors' personal opinion and does not necessarily reflect the view of Eurostat. The paper has been drafted as contribution to the OECD/Eurostat Task Force on "Performing Revisions Analysis for Sub-Annual Economic Statistics" The proposals contained in this paper are currently under discussion in Eurostat and they cannot be yet considered as an Eurostat official revisions policy At this stage, comments form OECD members will be welcomed

PEEIs Revisions Policy 3 Background 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 EFC Status Report

PEEIs Revisions Policy 4 Background definitions Definition 1: Any change in a value of a statistic released to the public by an official national or supranational statistical agency –new observations become available and some past values are modified –the current and some previous values are modified 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

Eurostat - Unit D1 Key indicators forf the European policies PEEIs Revisions Policy Background definitions 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 of revisions: Changes from an earlier vintage of estimates to a later vintage (Fixler and Grimm).

PEEIs Revisions Policy 6 Classification 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 Timing Unexpected Routine revisions Expected Annual revisions Major revisions

PEEIs Revisions Policy 7 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

PEEIs Revisions Policy 8 Main pillars of the PEEIs Revisions Policy Principle 1 General policy on data revisions Principle 2 Specific revisions policies for each statistical domain Principle 3 Documentation and communication of revisions Principle 4 Consistency and stability over time of domain specific revision policies

PEEIs Revisions Policy 9 Principle 5 Release/revision calendars and revisions Principle 6 Accessibility of data vintages Principle 7 Regular monitoring of revisions Principle 8 Major revisions Principle 9 Unexpected revisions Principles related to the revisions process

PEEIs Revisions Policy 10 Domain revisions policies How often to revise? When a revision can be considered “significant”? –Advantages and drawbacks of thresholds How far back to revise? Revisions of European aggregates –Consistent revisions policies –Synchronisation of releases

PEEIs Revisions Policy 11 Revisions and seasonal adjustment Released according to the same calendar of unadjusted ones Appropriate revisions policy for each PEEI Assessed according to the ESS SA guidelines

PEEIs Revisions Policy 12 Conclusions General principles applicable to all kind of statistics To be complemented by domain policies Will increase: –Transparency of the revision process –Data comparability –Harmonisation

PEEIs Revisions Policy 13 Thank you for your attention!