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The impact of globalisation on the EU-system of statistical units. ESSnet on profiling MNEs Helsinki, 5 May 2010. Jean Ritzen Statistics Netherlands. Outline. Introduction T he problem Purposes of the SU study GBR as starting point Direction of solution Some conclusions.
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The impact of globalisation on the EU-system of statistical units ESSnet on profiling MNEs Helsinki, 5 May 2010 Jean Ritzen Statistics Netherlands Helsinki Q-2010
Outline • Introduction • The problem • Purposes of the SU study • GBR as starting point • Direction of solution • Some conclusions Helsinki Q-2010
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) Helsinki Q-2010
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 Helsinki Q-2010
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 Helsinki Q-2010
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. Helsinki Q-2010
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 Helsinki Q-2010
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. Helsinki Q-2010
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) Helsinki Q-2010
Statistical World Administrative World EG Enterprise Legal Unit IU KAU Local Unit UHP Local KAU Local UHP EU Statistical units: relationships Source: Peter Struijs Helsinki Q-2010
Statistical units in the BR In the BR actors in the real economic world must be registered, according EU-BR-regulation. These are: Enterprise group: unit contolling financing processes (Institutional sector code) Enterprise: unit controlling the production processes (SIC-code) 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) Helsinki Q-2010
Economic/statistical world Legal/administrative world (Domestic) Enterprise group (Domestic) Legal Entity (LeU) (Legal or natural person) Enterprise Local (legal) entity Local unit The relationships EG, ENT and LU, 1993 Helsinki Q-2010
The SBR model (national) Economic/statistical world Legal/administrative world (Domestic) Enterprise group (Domestic) Legal Entity (LeU) (Legal or natural person) Enterprise Local (legal) person Local unit Helsinki Q-2010
Fundamental changes in interpretations of unit definitions - Definition or interpretation of the EG: Not longer combination of enterprises, but combinationof 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 Helsinki Q-2010
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. Helsinki Q-2010
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 Helsinki Q-2010
Economic/statistical World (global) Economic/statistical World (sub-global) Legal/administrative World (global) Legal/administrative World (sub-global) Legal or operational unit (sub global) National part of Enterprise group(“truncated EG”) Legal entity Global Enterprise group National enterprise Local unit legal or operational Local (legal) entity Local unit An improved model (global EG --> truncated EG) Helsinki Q-2010
Economic/statistical World (global) Economic/statistical World (sub-global) Legal/administrative World (global) Legal/administrative World (sub-global) Legal or operational unit (sub global) EGR National part of Enterprise group(“truncated EG”) Legal entity Global Enterprise group National enterprise Local unit legal or operational Local (legal) entity Local unit An improved model (global EG --> truncated EG) Helsinki Q-2010
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” Helsinki Q-2010
A generalised SBR model (global) Legal/administrative world Economic/statisticalworld Legal Entity (LeU) (Legal or natural person) Global Enterprise group EGR Global Enterprise Local (legal) entity Local unit Helsinki Q-2010
A generalised SBR (EGR) model (global --> truncated) Legal/administrative World (global) Economic/statistical World (global) Economic/statistical World (sub-global) Legal/administrative World (sub-global) EGR Legal or operational entity (sub global) Global Enterprise group Truncated Enterprise group Legal entity Global Enterprise Truncated Enterprise Local unit legal or operational Local (legal) entity Local unit Local unit Helsinki Q-2010
Legal/administrative World (global) Economic/statistical World (global) Economic/statistical World (sub-global) Legal/administrative World (sub-global) Legal or operational unit (sub global) EGR Global Enterprise group Truncated Enterprise group Legal entity Global Enterprise Truncated Enterprise Local unit legal or operational Local (legal) entity Local unit Local unit The SBR (EGR) model (global --> truncated) Helsinki Q-2010
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 Helsinki Q-2010
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 Helsinki Q-2010
SU – special issues Special issues: • The subsidiarity principle • The response burden • The relationship with other unit systems (ISIC) Elaboration is dependent on the scope. Helsinki Q-2010
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 Helsinki Q-2010
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 Helsinki Q-2010
Thank you for your attention! • Questions?/Discussion • jhg.ritzen@cbs.nl Helsinki Q-2010