1. Helsinki Q-20101 The impact of globalisation on the EU-system of statistical units ESSnet on profiling MNEs Helsinki, 5 May 2010 Jean Ritzen Statistics Netherlands

2. Helsinki Q-20102 Outline Introduction T he problem Purposes of the SU study GBR as starting point Direction of solution Some conclusions

3. Helsinki Q-20103 Preambulary principle Preambulary principle questions on what do we want to measure regarding MNEs: - Data on real economic processes of the groups? - Data on the national administrative organisations of the groups? (Which taxes in what stage: taxes are component of profit/loss  allocation variable)

4. Helsinki Q-20104 The problem The sum of the parts of a MNE differs from the total Reasons: - Each statistical agency collects information using own method, even if the used methods theoretically are harmonised. - Bottom up approaches do not lead to right totals - Inconsistencies in data collection and/or data processing - Insufficient recognition of the real context  ESSnet on profiling large and complex MNEs

5. Helsinki Q-20105 ESSnet on profiling MNEs Work packages: A. Feasibility study B. Methodological issues (e.g. statistical units) C. Examples and testing D. Communication and dissemination E Implementation

6. Helsinki Q-20106 Purposes of SU-study (WP-B) Purposes of the methodological study on statistical units - to provide the feasibility study with the methodological underpinning of the statistical units structure of enterprise groups to be used in business statistics and as object of 'profiling'. - to provide input for the development of the data model and the development of algorithms for delineation of statistical units within enterprise groups in the EGR and national statistical registers.. - to provide input for the process of adapting Council Regulation (EEC) No 696/93 of 15 March 1993 on the statistical units for the observation and analysis of the production system in the Community These purposes lead to the provision of an actualised system of well defined statistical units that meets and reflects the needs for adequate profiling of large and complex Multinational Enterprise Groups and thus meet the objectives of the ESSnet.

7. Helsinki Q-20107 Goal: Seeing the whole elephant Globalisation is an irreversible reality. Parts of the “elephant” must fit in the whole picture How to break down the puzzle and built up it again? Richard Barnabé, 2001; Roundtable MNE-project  report to UN-ECE

8. Helsinki Q-20108 Statistical units Statistical units are the units to which the statistical figures relate. Coherent system of statistical units developed, national and international (UN-ISIC, EU-SU-regulation 1993) EU-statistical units are defined in the Statistical units regulation (early nineties). Introduction of the aspect of autonomy for actors in the economy as the leading criterion (above homogeneity) Autonomy as criterion is important because of the need of availability of meaningfull relevant real economic information in bookkeeping or reports of units.

9. Helsinki Q-20109 EU-statistical units (1993 regulation) The main present statistical units are: – The Enterprise Group (EG) – The Enterprise (ENT) – The local unit (LU) Related to these units, other statistical units are defined, but these are more to be used for analytical purposes and are less appropriate for observation or publication purposes. These units are: –The Kind of Activity Unit (KAU), as a part of an enterprise –The Local Kind of Activity Unit (LKAU), as a part of a local unit; –The Unit of Homogeneous Production (as a part of an Enterprise or of a KAU); –The Local Unit of Homogeneous Production (as a part of a local unit or of a LKAU). –The Institutional unit (IU)

10. Helsinki Q-201010 EU Statistical units: relationships EG UHP IU EnterpriseLegal Unit KAU Local KAULocal UHP Local Unit Statistical World Administrative World Source: Peter Struijs

11. Helsinki Q-201011 Statistical units in the BR In the BR actors in the real economic world must be registered, according EU-BR-regulation. These are: 1. Enterprise group: unit contolling financing processes (Institutional sector code) 2. Enterprise: unit controlling the production processes (SIC-code) 3. Local unit (regional aspects of production processes, SIC-code) Operationalisation: translation of administrative or organisational units into statistical units, e.g. by profiling (national approach)

12. Helsinki Q-201012 (Domestic) Legal Entity (LeU) (Legal or natural person) Economic/statistical world Legal/administrative world (Domestic) Enterprise group Local (legal) entity Enterprise Local unit The relationships EG, ENT and LU, 1993

13. Helsinki Q-201013 (Domestic) Legal Entity (LeU) (Legal or natural person) Economic/statistical world Legal/administrative world (Domestic) Enterprise group Local (legal) person Enterprise Local unit The SBR model (national)

14. Helsinki Q-201014 Fundamental changes in interpretations of unit definitions - Definition or interpretation of the EG: Not longer combination of enterprises, but combination of legal entities which are under common control - Definition or interpretation of enterprise: Enterprise is result of top down analysis of EG. Enterprise as smallest combination of legal units can lead to problems, e.g. with ancillary activities Issue: Identification of the enterprise unit

15. Helsinki Q-201015 Introduction of the profiling method for large units Definition of profiling: Profiling is a method to analyse the legal, operational and accounting structure of an enterprise group at national and world level, in order to establish the statistical units within that group, their links, and the most efficient structures for the collection of statistical data.

16. Helsinki Q-201016 Reasons for international incomparabilities - the data collection method, including sampling (primary data collection/use of data in administrative registrations) - the nationally applied definitions of variables - differences of classification or in the use of classifications - errors in reporting data - use of different types of units (e.g. enterprise or local KAU) - deviating (definitions of) statistical units (e.g. different criteria like that of autonomy) - deviating methods used in the consolidation of data - decentralised (national) data compilation at MNEs

17. Helsinki Q-201017 An improved model (global EG --> truncated EG) Economic/statistical World (global) Global Enterprise group Legal entity Legal/administrative World (global) Local (legal) entity Economic/statistical World (sub-global) National part of Enterprise group (“truncated EG”) National enterprise Local unit Legal/administrative World (sub-global) Legal or operational unit (sub global) Local unit legal or operational

18. Helsinki Q-201018 An improved model (global EG --> truncated EG) Economic/statistical World (global) Global Enterprise group Legal entity Legal/administrative World (global) Local (legal) entity EGREGR Economic/statistical World (sub-global) National part of Enterprise group (“truncated EG”) National enterprise Local unit Legal/administrative World (sub-global) Legal or operational unit (sub global) Local unit legal or operational

19. Helsinki Q-201019 An improved model (global EG --> truncated EG), cont Advantage: -Co-ordination at EG-level: international tuning -Full coverage of MNE - National responsibilities remain Disadvantage: -Does not solve consistency problem Consequence: introduction additional unit, “truncated EG”

20. Helsinki Q-201020 A generalised SBR model (global) Legal Entity (LeU) (Legal or natural person) Economic/statistical worldLegal/administrative world Global Enterprise group Local (legal) entity Global Enterprise Local unit EGREGR

21. Helsinki Q-201021 A generalised SBR (EGR) model (global --> truncated) Economic/statistical World (global) Global Enterprise group Legal entity Legal/administrative World (global) Local (legal) entity Global Enterprise Local unit EGREGR Economic/statistical World (sub-global) Truncated Enterprise group Truncated Enterprise Local unit Legal/administrative World (sub-global) Legal or operational entity (sub global) Local unit legal or operational

22. Helsinki Q-201022 The SBR (EGR) model (global --> truncated) Legal/administrative World (global) Legal or operational unit (sub global) Economic/statistical World (global) Global Enterprise group Legal entity Local (legal) entity Global Enterprise Local unit EGREGR Economic/statistical World (sub-global) Truncated Enterprise group Truncated Enterprise Local unit Legal/administrative World (sub-global) Local unit legal or operational

23. Helsinki Q-201023 Requirements - Autonomy (still possible at sub-levels?) - Identifiability - Recognition (administrative, operational and statistical) - Accepted and acceptable (both MNE and statistics) - Data availability - Observable - Meaningful data at all levels (global and sub global) and for the specified uses Related to the available information systems

24. Helsinki Q-201024 Classifications - SIC (Standard Industrial Classification),  industries - Institutional classification (IC) - Classification of changes SIC and IC lead to homogeneous groups (by industry or institutional) Institutional classification applies to the Enterprise Group unit SIC relates to units related to production processes (Ent, KAU, Local Unit) Firstly the unit should be established, that has to be classified thereafter! Depending on purpose  dual or multiple classifications

25. Helsinki Q-201025 SU – special issues Special issues: –The subsidiarity principle –The response burden –The relationship with other unit systems (ISIC) Elaboration is dependent on the scope.

26. Helsinki Q-201026 How will subsidiarity be affected? From strict decentralised (national) to centralised 1. Strict subsidiarity: pure bottom up: existing practise 2. National authorities are responsible but based on harmonised rules and definitions 3. National authorities follow centralised group profile and are responsible for data collection accordingly nationally 4. Centralisation: Agency of country responsible for profile of the group collects data of the whole group and disseminates data to agencies of countries in which the group carries out activities

27. Helsinki Q-201027 Conclusions - Globalisation leads to the need of adaptation of systems (frames and processes) - More and more mutual interdependencies - Globalisation goes beyond European boundaries  need for tuning different statistical systems (e.g. EU and UN) - Profiling MNEs requires international communication and co-operation - Implementation using prototyping approach and gradually - Revision SU-regulation to be considered

28. Helsinki Q-201028 Thank you for your attention! Questions?/Discussion jhg.ritzen@cbs.nl