A Proposal for a revisions policy of Principal European Economic Indicators (PEEIs) OECD STES WP 23...
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Transcript of A Proposal for a revisions policy of Principal European Economic Indicators (PEEIs) OECD STES WP 23...
A Proposal for a revisions policy of Principal European Economic Indicators (PEEIs)
OECD STES WP 23 - 24 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 Thank you for your attention!attention!