1. The EU ESSnet project on ESSnet on « profiling large and complex MNEs »  State of the art / Crucial questions
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2. ESSnet on « profiling large and complex MNEs »
general context, related definition & the EU slides 3 & 8
approach, actions and operations slides 9 & 11
current state of operations slides 11 to 16
five options and operational proposals slide to 19
examples slide 20
future work slide
Annexes slide & 23
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3. Enterprise is presently defined as
ESSnet on « profiling large and complex MNEs » general context on « enterprises »: main issues (1)
Enterprise is presently defined as
- the smallest combination of legal units
- that is an organisational unit
- producing goods and services (for the market)
- … with a certain degree of autonomy in decision making
- especially for the allocation of its current resources
used at national level without international comparability:
- the sum of the parts usually differs from the total
- the required level is not specified (national, European or global?)
- no consistent standards for data collection
conceptually or in practice
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4. leading to an economic definition of “Profiling”
ESSnet on « profiling large and complex MNEs » general context on « enterprises »: main issues (2)
As a consequence of the increasing “globalisation”:
A growing gap between the managerial (economic) structure
and the legal composition and structure (in legal units)
Creating more and more significant, but usual, problems in statistics:
Turnover and intra group flows, complicated if multinational
Allocation of VA to countries
Inconsistencies of imports vs exports
And to new issues:
Ancillary activities
R& D
leading to an economic definition of “Profiling”
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5. legal - operational and – accounting structure of an enterprise group
ESSnet on « profiling large and complex MNEs » general context: economic definition of enterprise through profiling
Profiling is a method:
to analyse the
legal - operational and – accounting
structure of an enterprise group
in order to
establish the statistical units within that group and
their links and
the most efficient structures
for the collection of statistical data
Full Stop ?
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6. ESSnet on « profiling large and complex MNEs » the EU context (1)
In the EU the profiling necessity is:
related to two EU 1993 regulations (Statistical Business registers; Statistical units)
that did not allow “measuring the whole elephant” (Statistics Canada report to UNECE / CES 2005)
and lead to a new BR regulation (2008), including as well “enterprise groups” as “enterprises” .
But we still have to “translate” the definition and studies in operational processes.
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7. ESSnet on « profiling large and complex MNEs » the EU context (2)
The Profiling project is:
part of the MEETS programme (Modernisation of European Enterprise and Trade Statistics)
designed to achieve a streamlined framework of business-related statistics
Included in the system of the EGR (Euro Groups Registers)
in order to achieve coordinated and meaningful statistical unit structures for enterprise groups
(with maximum use of existing knowledge (EU and non EU))
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8. ESSnet on « profiling large and complex MNEs » the EU context (3)
An ESSnet, a new way for developing European Statistics:
bringing a number of NSIs into a partnership
to develop a common methodology
with the aim of largely disseminating the results
for use of the whole European Statistical System
with the strong support of Eurostat
The « profiling » partnership:
7 NSIs : CBS –NL, DESTATIS –DE, ISTAT –IT, ONS –GB,
SF –FI, OFS –CH , INSEE –FR coordinator

9. ESSnet on « profiling large and complex MNEs » the approach …
objectives & results structured into 3 steps:
: a positioning paper on feasibility of profiling;
an input on statistical units for an eventual change of EU regulation
: methodology, tools, guidelines …
2013 & on: full implementation of profiling inside EU
throughout the project: testing, iterations and early results
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10. ESSnet on « profiling large and complex MNEs » the planned actions,
WP A.   To define the feasibility and the scope of ‘profiling’ large and complex MNEs.
WP B.   To develop a common conceptual framework, methodology, rules and standards for profiling
WP C. To develop processes / workflows, tools,operational guidelines and quality control of profiling, organisational and financial models
WP D.   To test and implement 'profiling'
WP E.    To develop a model for sharing of 'profiles' (including legal framework)
WP Diss To disseminate and train
WP M To manage the ESSnet
WP = working package; managed by a leading partner (LP), 1 to 3 working partners (WP), all others being reviewing partners (RP)
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11. Framework Partnership Agreement: October 2009
ESSnet on « profiling large and complex MNEs » the operations worked out
Framework Partnership Agreement: October 2009
1st Specific Annual Agreement: December 2009
Kick-off meeting, 5 all-partners coordination meetings
Trilateral meetings: a way for Work Package leaders to cooperate
3 Workshops :
London Jan: the “why” and the “who”,with stakeholders views
Amsterdam Feb: Statistical Units
Paris 8-9 June: preferred options
Dissemination:
CIRCA BR (and a site in the future ?)
BR WG, EGR SG, SBS WG, etc
Q2010, Wiesbaden Group

12. SBS and FATS: first priority
ESSnet on « profiling large and complex MNEs » current state of operations (1)
Stakeholders still being consulted; priorities appear:
Structural Business Statistics (SBS)
as producers of specific data – eg on concentration
as basis for production statistics
as providers of information for National Accounts
National Accounts: to serve first EU needs or National needs?
Balance of Payments and Foreign Direct Investments (FDI)
FATS (I & O)
SBS and FATS: first priority
Strong links with the EGR project, as “Profiling” is:
directly in charge of the “enterprise” register
Also meant to check MNEs cluster, structure and principal activities
A question remains on data collection extension

13. Preferred Top-Down approach:
ESSnet on « profiling large and complex MNEs » current state of operations (2)
Large agreement on the necessity of confident relations with profiled MNEs
Preferred Top-Down approach:
accounting “Consolidation” Information System used as a starting point for analysis
IFRS in the EU for listed companies (stock & bonds)
use of operational segments or divisions (“GODS”): IFRS 8
need of extra data (eg intra-group inter-GODs flows)
Statistical units and profiling highly interlinked:
opportunity for creating the GEs (“global enterprises” being the statistical units usually derived from GODs)
TEs “truncated enterprises” as national parts of GEs

14. Statistical environment at global (GE) and national (TE) levels
ESSnet on « profiling large and complex MNEs » current state of operations (3) from the legal to the statistical world
Global
Group
TE1
TE2
TE3
TE4
GOD1
GOD2
GE1
GE3
GE2
Legal or operational
(non statistical)
environment
Statistical environment
at global (GE)
and national (TE) levels

15. not limited national boundaries are truncated parts of GEs
ESSnet on « profiling large and complex MNEs » current state of operations (4) main changes to the statistical units
autonomous entities: GEs
not limited national boundaries
national entities: TEs “truncated enterprises”
are truncated parts of GEs
often not “autonomous”
with a classification dilemma (example next slide)
GEs and TEs no more directly related to legal units:
(some) legal units may be split into more than one enterprise
Relations from (GEs & TEs) cluster to (LeU) cluster
questions the “rest of world” (outside EU) unit(s)
What about KAU and local LKAU?
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16. What should be the principal activity classification of GEs and TEs:
ESSnet on « profiling large and complex MNEs » current state of operations (5) unsolved territorial classification dilemma
What should be the principal activity classification of GEs and TEs:
The global one?
The national one?
Dual: keep both or choose?
Spain and France are manufacturers of goods conceived in France and sold in the whole of Europe through a unique French “trade” company
distributed in all EU countries through specialised affiliates
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17. Option A (the “no change” option): doing as present
ESSnet on « profiling large and complex MNEs » Five options for profiling, with a preferred one: option D « with further consideration to option E »
Option A (the “no change” option): doing as present
Option B: (the “minor change” option)
as option A
but applying standards (changes to documentation and use of it)
Option C: arrives at global (highest) level (of consolidation),
delivers country clusters; allowing each NSI to define its enterprises
What kind of checking?
Option D: profiling global groups
divide the global group in GEs, then in national TEs
enterprises list of LeU to NSIs for registers & data collection
Option E: manages the group cluster & the GEs
collects data centrally
apportions to national level
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18. a “model” of statistical units is essential for successful profiling
ESSnet on « profiling large and complex MNEs » … plus operational proposals (1):
1 Sharing the model:
a “model” of statistical units is essential for successful profiling
all countries need to use the same standards (for profiling both MNEs and large domestic groups)
2 Dealing with complexity:
deal with all cases is impossible (neither initially nor in the future)
a mechanism to develop rules for new cases rather than a complete set of new rules
managed by the BRWG or the EGR Steering Group
new rules and mechanism will progressively include treatment of: SE (European companies), holdings, SPEs, off-shoring, family closed companies, family groups, accountancy firms and other partnerships, etc
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19. ESSnet on « profiling large and complex MNEs » … plus operational proposals (2):
3 a process for profiling, first top-down, if necessary completed with bottom-up information:
delineating the global enterprise group by creating a cluster of all legal units belonging to the group
investigating the operational structure (as independently as possible from “legal” or administrative structure)
Identifying, from operating segments, all market-oriented entities (as GEs and basis of the future TEs) and allocating all other entities to these
link (at least try to) all legal units to enterprises (recognising that relationships can be: 1 to1; several to 1; many to many)
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20. ESSnet on « profiling large and complex MNEs » « examples » studied
testing, iterations and early results: permanent objectives throughout the project
restricted to “examples” until now
first “cases” studied in common:
3 groups within the motorcar industry (to check their similarities and differences)
a list of 18 differentiated MNEs (in industry, trade and services, all largely widespread in EU, some with SPEs), most of them being seen from at least two countries point of view
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21. ESSnet on « profiling large and complex MNEs » the future work
Next year program:
develop the common methodology
for EU and non EU groups
special cases
start and experiment the guidelines and tools
disseminate and involve (more) EU NSIs
set up a network of NSIs interested in developing profiling procedures
Needed discussion from EU statisticians
And cooperation with non-EU NSIs
Thank you for attention and comments
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22. ESSnet on « profiling large and complex MNEs » Annex (1): on IFRS
We propose to use (largely) the IFRS (the EU-GAAP):
knowing their pros and cons:
Pros:
Most widespread “administrative” “ EU” standards
Good standardisation of elementary flows and stocks
Compulsory for stock-traded and bond-traded groups
Include “operational segments” (with turn-over, operational results and employment figures)
Cons:
Consolidated data (no displayed national figure if intra-group flows)
Sometimes at levels lower than UCI
No standardised publication tables
Uncertain stability for the operational segments
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23. 1 Group-consistent classification
ESSnet on « profiling large and complex MNEs » Annex (2): classification
Which way use to restore consistency between EU and national statistics?
Is assignment of dual (plural) classifications to statistical units possible:
1 Group-consistent classification
2 Own-activity classification (solves ancillary activities problem and also commercial but not trade activities problems)
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