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13-Jul-07EGRv2: an improved way of sharing information on MNE Quality criteria in the EGR context Defined in the European statistics Code of Practice –1- Relevance –2- Accuracy and reliability –3- Timeliness and punctuality –4- Accessibility and clarity –5- Coherence and comparability
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The EGR version 2: an improved way of sharing informationon multinational enterprise groups
Introduction
The EGR the platform that supports the production of micro-based statistics on globalisation in Europe, both on country and European level.
settled down in 2009 (reference year 2008) 2013: EGR V2
– enabling statisticians and register staff of NSIs and NCBs to consult, to retrieve and to update EGR data
Quality issues: the role of the users
Quality criteria in the EGR context
Defined in the European statistics Code of Practice – 1- Relevance– 2- Accuracy and reliability– 3- Timeliness and punctuality – 4- Accessibility and clarity – 5- Coherence and comparability
Quality criteria in the EGR context Relevance
– the degree to which statistical outputs meet current and potential user needs. It depends on whether all the statistics that are needed are produced and the extent to which concepts used (definitions, classifications etc.,) reflect user needs.“
– EGR targeted to fulfil needs of users involved in statistics on globalisation:
• FATS statisticians• FDI statisticians• statisticians working on profiling multinational and complex
groups – Include in the EGR frame populations for these users– harmonise concepts used in globalisation statistics
• UCI• SPEs (to some extent)
Quality criteria in the EGR context Accuracy and reliability
– the degree of closeness of estimates to the true values – In the EGR context: information on the MNEs included in the
EGR should be close to the true situation • EGR should include the frame populations of the statistical
users • No under-coverage
– missing legal units in a given MNE, missing MNEs according to the target population
• No over-coverage– legal units registered several times under different
identification numbers• Classification variables should be reliable
– country of the UCI
Quality criteria in the EGR context Timeliness
– length of time between the event or phenomenon they describe and their availability
– crucial element for the EGR • Take into account users needs (delineate sample frame)• Take into account producers calendars
– EGR V2:• Reconcile users’ needs and producers’ constraints• Live process• Includes information from the users
Quality criteria in the EGR context Accessibility and clarity
– simplicity and ease with which users can access statistics, with the appropriate supporting information and assistance
– In the EGR;• Regulatory: exchanges of micro-data information have
been defined in several regulations• Pragmatically: access to the EGR for the users via a web
platform.• The clarity:
– use concepts and definitions common to the producers and the statistical users.
– recommendations manual and guidelines
Quality criteria in the EGR context Coherence and comparability
– degree to which the statistical processes by which statistical outputs were generated used the same concepts - classifications, definitions, and target populations – and harmonised methods
– in the EGR: • several countries may bring information on the same MNE
and on the same financial relationship in case of cross-border relationships.
• Priority rules have been settled down to treat potential conflicting cases.
• EGR V2, with the authentic source principle, intends to reduce the possibilities of incoherencies.
The EGR version 2 and its principles
Authentic source and authentic store concept – Authentic source: the source of which data are used as the
'truth' without additional investigation. • Source needs to meet certain quality requirements, e.g.
comprehensiveness, accuracy, reliability, timeliness, punctuality and comparability.
• Data defined/validated by an authentic source can not be overwritten by another source.
– Authentic store: the place where the original and latest version of a data element or a set of data elements is stored.
The EGR version 2 and its principles
Translation in the EGR– Authentic source:
• NSI for national legal units and enterprise units and national relationships
• EGR for non-EU units• NSI of the parent company or NSI of the subsidiary
company for cross border relationships– Authentic store: the place where the original and latest version
of a data element or a set of data elements is stored.• NSI for national legal units and enterprise units and national
relationships• EGR for non-EU units • EGR for cross-border relationships
The EGR version 2 and its principles
Translation in the EGR
– Availability of relationship data differs from country to country• the final solution applied in EGR should be defined in the
future
– Roles of central EGR and national registers precisely defined
– The enterprise group information stored in national business registers and in EGR will be identical at the time of the statistical outputs.
The EGR version 2 and its principles
Identification service for legal units– Critical factor to implement the principle of authenticity– Authentic source is responsible for the identification of units– Identification of foreign units is a major challenge
• Identification limited yet to the name and country of the legal unit
• Identification service should limit the duplications in the system• Identification service will provide a 'Legal Entity Identifier' for
legal units in and outside Europe. – This ID will be used as the primary identification number in the
workflows in the EGR network. – This ID should be unique and widely used. – For EU units the ID should be composed on the basis of a public
available national identification number associated with the country code
– For non EU units, the ID number of the commercial data providers sources may be use (Dun number or BvD ID)
The EGR version 2 and its principles
Platform for the users and producers– The main features of the platform are
• To consult 'live' EGR data • To update EGR data as far as allowed by the authenticity rules• To validate EGR data
– To be accessed by • Statisticians (FATS, FDI…)• Business register staff from NSIs and NCBs Profiling teams in the NSA should be responsible for the
validation of the pre-selected large MNEs in the target of profiling.
Eurostat central EGR will assess the quality of the information via macro-validation procedure and send information to the NSA for micro-validation.
The EGR version 2 and its principles Control of the quality: the evaluation/validation process
2010 2011 2012
Live register
I nitial Frame 2010
Updating 2010 Frame error correction
2010 VALI - DATION
2010
Initial frame 2011
Final frame 2010
The EGR version 2 and its principles Control of the quality: the evaluation/validation process
– macro evaluation : "monitoring/evaluating of significant changes in the EGR frame populations".
• should be applied to all the groups. • be undertaken several times until the frame is considered of enough
good quality to be released. • set of rules that allow detecting outliers • undertaken centrally by Eurostat.
– micro validation : "monitoring/evaluating of changes in a significant MNE “• result of output of the macro evaluation• independent process with separate request
– for part of the variables – for targeted populations (for example the largest MNEs).
• Some external information could be used as a reference to test the quality of EGR information.
• A list of groups that the NSIs should look at should be edited centrally by Eurostat.
The role of the users in the quality control in the EGR
Request for adding MNEs in the EGR– EGR 2008 and 2009: 5000 largest MNE operating in the EU.
2010 population has been enlarged to 10000 – EGR2013: full coverage of the target population of FATS and
FDI– Feedback from the users is expected
• Ask for adding or removing MNEs Intervention during the updating process
– Through the platform – Report events detected during their production process– Information included in the EGR according to the authenticity
principle
Profiling process
EGR LeUMNE and their LeU
constituents
Compare LeU from profiling and from the
EGR
Profiling LeU are in the EGR
EGR Identification process
Propose to introduce LeU in the EGR
NO
Proposal accepted by the authentic source
EGR staff in NSI sends the new information to
the EGR
LeU not introduced in the EGR
YES
NO
Updated MNE and their LeU
constituents
YES
Example of updating ofThe EGR by the users
The role of the users in the quality control in the EGR
Request for micro evaluation– micro evaluation/validation of a given MNE launched after
detection of suspicious figures during the macro evaluation– could be also made according to user information or on their
request• Example: users report information at the MNE level (global
figures on employment or turnover, place of the UCI,…) which is conflicting with the EGR information
Some limits to the users' intervention – Difficulty to fulfil contradictory needs– In case of contradictory information, need to introduce priority rules– Need to respect the single flow principle
• Requires an agreement between all the stakeholders at the national level
Thank you for your attention!