4 May 2010

Towards a common revision for European statisticsBy Gian Luigi Mazzi and Rosa Ruggeri Cannata

Q2010 European Conference onQuality in Official Statistics4-6 May 2010

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

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

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

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).

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

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

Eurostat – Unit D5 Key indicators for European policies

Revisions practices for PEEIsEuropean 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

Eurostat – Unit D5 Key indicators for European policies

General principles

1General 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.

2Consistency 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.

3 Communication 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.

Eurostat – Unit D5 Key indicators for European policies

Principles related to the data production process

4 Routine 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.

5 Major revisionsMajor revisions should only take place in larger intervals. They should be pre-announced, backwards implemented and coordinated across statistical domains and institutions.

6 Unexpected 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.

7Definition 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.

8Data 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.

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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

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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

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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

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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

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

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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

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Thank you for your

attention!