Deliverable 43 Riga Workshp Report - European Commission Workshp Report_0.pdfHe also explained the...

EUROPEAN COMMISSION - EUROSTAT ESSnet on consistency of concepts and methods of business-related statistics 2010 project on statistical units n° 30121.2010.005 - 2010.405

Deliverable 4.3

Riga Workshop: “ESSnet on Consistency–

Project on statistical units”

- Report -

Authors: Sarmite Prole, Svetlana Jesilevska

Final Version 1.2

ESSnet on Consistency of Concepts and Methods of Business and Trade-related Statistics

WP1: ESSnet on consistency – Project on statistical units, Riga, Latvia, June 2012 2

Content

Introduction ...................................... ................................................................ 3

Welcome and presentation of ESSnet on Consistency w orkshop .............. 4

ESSnet on consistency ............................................................................................ 4

Session 1: “What do we have?” and “What do we need? ” .......................... 4

1st part: What do we have? ..................................................................................... 4

Introduction and presentation of ESSnet on consistency – Project on statistical units .......................................................................................................................... 4

Results of the qualitative part of the Inquiry on identification of inconsistencies between Member States ........................................................................................ 6

Enterprise ....................................................................................................... 6

Kind-of-activity unit ....................................................................................... 10

Local unit ...................................................................................................... 12

Local kind-of-activity unit............................................................................... 18

National Accounts and Regional Accounts ................................................... 22

Results of the quantitative part of the Inquiry on identification of inconsistencies between Member States ...................................................................................... 22

Outline on identification and evaluation of inconsistencies in regulations for business related statistics ...................................................................................................... 26

Results of the vignettes on the test of a new definition of enterprises ...................... 28

2nd part: What do we need? .................................................................................. 30

Improved, new, operational, etc. definitions of the main statistical units for European business statistics ................................................................................................... 30

Session 2: Where do we go? ........................ ................................................. 33

Which statistical units lead to Business Statistics best fit for economic analysis? ... 33

Inconsistency problems from the point of view of National Accounts ...................... 35

Identify «enterprises»: the profiling procedure ......................................................... 37

Statistical units: Avoiding mistakes, identifying a consistent approach. From the statistical concept of autonomy to the statistical definition of enterprise ................... 38

Round up and conclusion ........................... .................................................. 42

Annex I – Workshop Agenda ......................... ................................................ 43

Annex II - List of participants ................... ..................................................... 45



Introduction

Character of ESSnet Consistency

The ESSnet on consistency of concepts and methods of business and trade-related statistics is divided into three activities:

• Statistical units (WP1) • Target population, frames, reference period, classifications and their

applications (WP2) • Characteristics and definitions (WP3)

The work on statistical units is the first task of the whole ESSnet. All activities refer to the consistency item. Objectives and organization of the workshop

ESSnet on Consistency - Project on statistical units workshop (workshop) is carried out within the framework of the “ESSnet on consistency of concepts and methods of business-related statistics” (WP1- 2010 project on statistical units). The workshop was successfully held on the 19th and 20th of June, 2012 at Hotel Avalon in Riga, Latvia. The goal of the workshop was to present the work done at the ESSnet project on consistency of Concepts and Methods of Business and Trade-related Statistics and to open discussion on the needs for revised statistical unit’s definitions.

Project on statistical units comprises the following five National Statistics Institutes (NSIs) of Austria (STAT), France (INSEE), Ireland (CSO), Italy (ISTAT) and Latvia (CSB). The co-ordinator of the WP1 is ISTAT. The workshop hosted by the Central Statistical Bureau (CSB) of Latvia with intensive support from the countries involved in WP1 and Eurostat.

The workshop was divided in two sessions (Annex I): • Session 1 was divided in two parts. The content of the 1st part was covered

under question “What do we have?” where was given overview of the results of the Inquiry on statistical units. There were presentations on the results of the Inquiry on identification of inconsistencies between Member States on Enterprise and Legal unit; Kind-of-activity unit, Local unit, Local kind-of-activity unit and on National Accounts/Regional Accounts. An outline on identification and evaluation of inconsistencies in regulations for business-related statistics was also presented. The identification and evaluation of inconsistencies in regulations is carried out within the ESSnet on Consistency Project on statistical units. The last presentation outlined the results of case studies on enterprise definitions on the test of a new definition of enterprise. The 2nd part was covered under Question “What do we need?” presenting improved, new, operational, etc. definitions of the main statistical units for European business statistics.

• Session 2 “Where do we go?” touched upon opinions of NSIs on which statistical units lead to Business Statistics best fit for economic and inconsistency problems from the point of view of National Accounts. The final presentations covered enterprise profiling procedure and definition of enterprise for statistical purposes.



Experts from Business statistics and National accounts from each Member State were invited to the workshop. Around 58 experts from 21 European countries and Eurostat joined the workshop. (See Annex II -List of participants).

Kaspars Misans, vice president of the CSB of Latvia, introduced the Agenda and emphasized the problem of consistency on statistical units where the statistical outputs of in different domains cannot be compared because the definitions, concepts and methodologies are partially or even completely different.

Welcome and presentation of ESSnet on Consistency workshop

Aija Zigure, president of the CSB of Latvia, welcomed everyone to the ESSnet on Consistency workshop. She underlined that it had been a pleasure for the CSB to host this workshop and also emphasized the meaning of ESSnet as it is a way to develop new projects, where Member States interested in a specific domain can actively collaborate on common tasks and then disseminate the results. She mentioned that the entire ESSnet on consistency operating within the MEETS Programme and ESSnet on consistency of concepts and methods of business-related statistics - 2010 project on statistical units fell under objective 2 of the MEETS programme aiming at the “achievement of a streamlined framework for business – related statistics”.

ESSnet on consistency (Hans-Eduard Hauser, EUROSTAT)

Hans-Eduard Hauser from Eurostat in his presentation showed the necessity to harmonise concepts and definitions across all business-related statistics and Member States. He also outlined expectations of Eurostat from the workshop on statistical units and ESSnet on consistency in general.

Session 1: “What do we have?” and “What do we need? ”

Chair: Sarmite Prole (CSB, Latvia)

Sarmite Prole outlined the content of the1st Session. She briefly explained that the session would be split in two parts. The content of the 1st part was covered under question “What do we have?” and the 2nd part was covered under question “What do we need?”

1st part: What do we have? Introduction and presentation of ESSnet on consiste ncy – Project on statistical units (Giuseppe Garofalo - Coordinator of the project on statistical units, ISTAT, Italy)

The presentation of Giuseppe Garofalo, Coordinator of the project on statistical units, covered the following:

• Identify and evaluate inconsistency regarding: o Inconsistency in statistical units applied in different statistical domains of

the system of business and trade-related statistics according to the European legislation



o Inconsistency in the application of the statistical units definition in different Member States

o Inconsistency of the existing statistical units for the development of new European statistical domains

• Make proposals for adjustment in EU regulations

He also explained the general aim of the questionnaire: • To identify and analyze the following typologies of inconsistencies:

o Inconsistency in statistical units applied in different statistical domains of the system of business and trade-related statistics according to the European legislation

o Inconsistency in the application of the statistical units definition in different Member States

• To take qualitative and quantitative measures

The inconsistencies were identified and evaluated in sections through qualitative and quantitative measures for the following units:

• Legal units/ Enterprises • Local units • Kind-of-activity units (KAU) • Local kind-of-activity units (LKAU)

and for the following domains: • Business register (BR) • Structural Business Statistics (SBS) • Short-term Statistics (STS) • National/Regional Accounts (NA/RA)

The structure of Inquiry on the Statistical units is described in Figure 1.

Figure 1: The structure of Inquiry on the Statistical Units

He mentioned that the response rate in the qualitative part of inquiry was very high (about 90% for all sections 1-6 regarding BR, SBS and STS domains) and for NA/RA the response rate was about 71%, shown in Table 1.



Table 1: Response rate by Sections

The compilation of inquiry was sent to 27 Member states of the European Union and to the EFTA Countries. Response was received from 29 countries.

Results of the qualitative part of the Inquiry on i dentification of inconsistencies between Member States

There were presented results of the Inquiry on identification of inconsistencies between MS on Enterprise; Kind-of-activity unit, Local unit, Local kind-of-activity unit and on National Accounts/Regional Accounts.

� Enterprise (Monica Consalvi - ISTAT, Italy)

Monica Consalvi explained in her presentation the main results of the qualitative part of the inquiry on the statistical unit “enterprise”.

Regarding results of inquiry she briefly described what kinds of administrative/ statistical sources were used in the respondent countries for the implementation of the enterprises in BR and for the detection of the main characteristics of this unit. She emphasised that the majority of the questions mainly referred to the definition of the enterprise as stated in Council Regulation (EEC) No 696/93 of March 1993 on the statistical units for the observation and analysis of the production system in the Community (Regulation 696/93 on the statistical units). The definition has been divided into three main parts and the application of each one has been investigated.



Enterprise is strictly dependent on how the legal unit is identified in view of the fact that the consistency of the BR with the definitions of statistical units in the regulation can depend on national legislation, especially in economic and fiscal area.

For Legal units, more than 61% of countries use more than one source and the average number is 2.7 per country. As regards enterprises, all countries use more than one source even to detect the characteristics of the unit. Exactly as expected, the fiscal sources are the most used for the variable “turnover” (71.4%) in the same way as the Social Security is for “employment” (75%). It is worthy of note that a considerable number of countries make use of surveys as a primary source to detect the values of the main characteristics and this is true above all to assess the economic activity code (42.9%), shown in Table 2.

Table 2: Respondent Countries by main administrativ e/statistical sources used to implement the enterprises in the BR and main det ected characteristics (% out of 28 respondent countries)

Within the presentation also mentioned that the application of each part of the definition has been researched using specific questions.

Table 3: Respondent Countries by methods to apply " Part 1" of the Enterprise definition

As regards “Part 1” of the definition, most of the countries perform some analyses to apply the concept of productivity; about 42% of countries say they use more than one



method to find out that a unit is an organizational unit producing goods or services. 13% of the countries consider each identified legal unit as a productive unit without further analysis, while more than 80% of countries say they perform further analyses to understand how the unit is actually productive, above all by using sources that could give this information (45%) or by using thresholds of certain variables (42%) or profiling methods (35%). Other methods are also relevant (19%) in this multiple choice. The most used variables for “threshold” are “employment” (61.5%), “turnover” (61.5%) and other sources like “income” and “wages” (53.8%).

Table 4: Respondent Countries by features of “auton omy” to apply "Part 2" of the Enterprise definition

As regards “Part 2” of the definition, more than 61% of countries say they consider more than one issue among the practical concepts stated on Eurostat BR Recommendation Manual 2010, in the Chapter 19D (Operational rules for the enterprise — Defining the enterprise), with an average number of 1.7 issues per country. It was assumed that the concept of “autonomy in decision-making” could be connected to the following issues: for about 68% of the countries it is relevant that the enterprise has accounts at its disposal and 42% consider if the operations of the enterprise are managed in an integrated manner. Not so many used the third concept, as only 39% of the countries consider the market orientation of an enterprise as an important issue. It should be noticed that 26% countries consider also some other issue as fundamental in the concept of autonomy.

As regards “Part 3” of the definition, half of the countries declare to follow only one approach and half of the countries follow precisely two of them.

Figure 2: Relationships between Legal Units and Ent erprises

Legal Unit Enterprise

Enterprise

Legal Unit

Legal Unit

Legal Unit...

Enterprise

Enterprise

Enterprise

...

1

m

m n

1 45.2 % (14)

38.7 % (12)

3.2 % (1)

6.5 % (2)Other relationships

Legal Unit

Legal Unit

Legal Unit...

1



In particular, 45.2% countries has a one-to-one relationship between legal units and enterprises, thus, unexpectedly, more than half countries perform some activities to combine together legal units for the identification of the enterprise. The majority combine more than one legal unit in the same enterprise (38.7%), while only one country consider it possible to split one legal unit in more than two enterprises. 6.5% declare to use some other methods to identify the enterprise as the smallest combination of legal units, for example in some cases the ancillary units that serve another unit are identified but the accounts are not consolidated.

To understand better which are the operations performed in case of combination/split of legal units and how far they are applied, some questions were asked to the subset of 15 countries where the link between Legal unit and Enterprise differs from a one-to-one relationship, explained in Table 5.

Table 5: Coverage of application of “Part 3” of the Enterprise definition

With regards to this subset of countries, there is a different coverage in the application of the operative criteria to combine/split Legal Units: only five countries broaden them to the whole population, while the other ones restrict the analysis to a relevant subset of units in the BR, having a large dimension (20%) or a particular legal form (30%), a specific economic activity (10%), or limiting the analysis just to the units involved in surveys or under manual investigations (40%).

Figure 3: Typologies of Legal units (LeUs) to be co mbined/ split to apply “Part 3” of the definition



As regards the typologies of Legal units (Figure 3) to which the rules to obtain an enterprise combining legal units could be applied, the discussed situations are the ones stated in Eurostat BR Recommendation Manual, Chapter 19E (Operational rules for the enterprise — Applying the definition). The most common situation is that the legal units carrying out vertically or horizontally integrated activities are combined to form a single enterprise (73.3%) but there are also 60% of the countries that take into consideration the legal units set up to hold the assets of two or more enterprises within an enterprise group.

Taking into account the information shown in the last three tables, together with the additional description of the activities performed by the Member States, it was possible to classify better the countries in terms of their treatment of legal units. According to the high/low coverage of the treated units in the BR and the number of typologies taken into consideration, about 52% of the countries perform some activities to combine legal units in the same enterprises when they considered them “not autonomous”, but actually only 30% of the countries carry out a complete analysis and apply in practice the procedure of the profiling approach in a “strict” sense. They represent 20% of the total enterprises in Europe and 18% of their employment.

Table 6: Treatment of Legal units (LeUs)

Summary of the results of the qualitative part of the inquiry on statistical unit “enterprise”:

• The use of threshold (turnover and/or employees) is the main criterion to identify enterprise from legal units

• The most often used criterion for “autonomy” is “an enterprise has accounts at its disposal” (68% of the NSIs)

• Profiling methods seem to be used by 11 (35.5 %) countries • Combination of LUs (using profiling or other methods) are performed by 15

countries • Regarding the inquiry results: 8 countries applied “strictly” for the

combination of LUs: 19.8 % in terms of total European enterprise, 18.0% in terms of total European employment

� Kind-of-activity unit (work was done by the CSO, Ireland)

Giuseppe Garofalo explained results made by the CSO. Highlighting the main points, he explained the KAU definition according to Regulation 696/93 on the statistical units: “The kind-of-activity unit groups all the parts of an enterprise contributing to the performance of an activity at class level (four digits) of NACE Rev.1 (2) and



corresponds to one or more operational subdivisions of the enterprise. The enterprise’s information system must be capable of indicating or calculating for each KAU at least the value of production, intermediate consumption, manpower costs, the operating surplus and employment and gross fixed capital formation”. He described the role of KAU in the ‘spine’ of Business Regulations. He also provided information on the countries which have KAU in each statistical domain.

In the Business Register (not required by Regulation) 11 countries implement this unit, 17 countries use KAU to produce SBS statistics (required by regulation), 13 countries use KAU to produce STS Industry statistics (required by regulation) and 2 countries use KAU to produce other STS statistics (not required by regulation), shown in Table 7.

Table 7: Respondent Countries by presence of KAU in the statistical domains

According to results of the inquiry 29 countries answered the questions on KAU (Iceland and Liechtenstein did not); 15 of these 29 countries do not have KAU or Local KAU on their Business Register.

The presenter mentioned that 17 countries can observe/estimate some or all variables for KAU in SBS, using information available in the BR or from other sources; 3 countries definitely cannot observe/estimate any variables for KAU in SBS; 9 countries – Do not identify KAU.

Figure 4: Which countries have KAU and/or Local KAU on Business Register?

Summary of the results of the quantitative part of the inquiry on statistical unit “KAU”: • The majority of the NSIs are not compliant with the KAU definition of

Regulation 696/93 on the statistical units that is mandatory for SBS and STS



• Only 8 NSIs (corresponding to 25.8% of the European Enterprises and to the 33.4% of the European Employment) observe/estimate the compulsory 6 variables

• Limiting the KAU definition to the observation of “value of production” and “employment” the coverage increased to 61.9% and 62.4%

� Local unit (Pierrette Schuhl, Sylvie Mabile - INSEE, France)

Sylvie Mabile offered analysis of the Local units concerning the questions of the qualitative part of the inquiry. She explained a local unit definition according to Regulation 696/93 on the statistical units where local unit is defined as “an enterprise or part thereof (e. g. a workshop, factory, warehouse, office, mine or depot) situated in a geographically identified place. At or from this place economic activity is carried out for which — save for certain exceptions — one or more persons work (even if only part-time) for one and the same enterprise”.

One can find questions about Local Units mainly in Module 3 in different sections of the inquiry. Module 5 was also reviewed, to look at relationships between LUs and LKAUs. Some information was also issued from filter questions in Short Term Statistics questionnaires, mainly in section C or D dealing with Turnover and Production in Industry. But the results of the second module on Regional Accounts will not be developed here, as only 3 countries answered ‘Mainly local units’ to the question “What is the «statistical unit» for which appropriate basic data are available to compile Regional Accounts in your country? (Single answer) Not any further indication was provided with these answers.

I. The Business Register experts point of view (Mod ule 3 section A)

In order to identify inconsistencies of the applied definition of Local Unit in different MSs and different statistical domains, the same third module was included in five sections of the web survey to NSIs (to be filled in by BR and STS experts, but not included in SBS section B, as Local Unit is not a statistical unit to be used in SBS regulation: see KAU or Enterprise)

I.1 Response Rates

Table 8 reports the global response rate of modules 3 in those five questionnaires. The information on Local units is mainly issued from BR experts (27 countries, section A). Only one country has submitted a module on Local Units in section D (STS in industry, Production) (see part III for further details on STS).

Table 8: Response rate to Module 3 (Local Units) in all sections (number of countries)

Number of modules 3

submitted

SECTION

A (BR) C (STS) D (STS) E (STS) F (STS)

No 2 28 28 28 27

Yes 27* 1

(empty) 2 3 2 3 4

Total 31 31 31 31 31

STS sections: C=Turnover (industry); D=Production (industry); E=Turnover (Retail trade & repair); F=Turnover (Other services)



The response rate is very high, above 90%, except for the requested description of “other geographical details” in the open question 3.4, where the response rate is only 50%.

The feedback area in the Local Unit module was filled-in by more than 32% of countries (10 countries).

Table 9: Response rate to Module 3 (Local Units) - in Section A (BR)

Qualitative questions in Module 3 - Local UnitsNumber of respondent

countries

Respondent rate (%)

3.1. List the main administrative/statistical sources used to implement the local units in the BR:Name of the source 29 93.5Fill in the administrative definition of the identified unit: 28 90.3

3.2. Reg. 696/93 states that "at or from" the place where the local unit is situated "economic activity is carried out for which one or more persons work for one and the same enterprise". How does NSI identify local units? 29 93.5

Methods of further analysis (multiple answer) 16 88.9Description of method used 16 88.9

3.3. Do you have local units without employment? 29 93.5List the main sectors/typologies for which you have local units without employment in your BR: 19 90.5

3.4. Which is the maximum geographical detail used to identify a local unit of an enterprise? 29 93.5Description of "Different geographical details" or "Other" 2 50.0

3.5. Is it possible in your NSI to georeference the local units? 29 93.53.6. Do you store more than one economic activity of the local units in your BR? 29 93.53.7. If 3.6=Yes, list the main administrative/statistical sources that permit to store more than one economic activity of the local unit: 18 90.03.8. If 3.6=Yes, does NSI identify these economic activities for the whole population of local units in the BR or just for a subset of them? 18 90.0

Description of the subset 10 83.33.9. Fill in your Local Unit "operative" definition: 28 90.3Please provide us your feedback: 10 32.3

I.2 Results

To implement the local units in the BR, 66% of countries use more than one source. Most countries use one or two sources, the average are 2.2 sources per country. Only one country indicates no source.

Table 10: ( Question 3.1) List the main administrative/statisti cal sources used to implement the local units in the BR (number of sour ces listed)

Number of sources Number of countries Percentage Total Number of sources

0 1 3% 0

1 9 31% 9

2 10 34% 20

3 4 14% 12

4 2 7% 8

5 3 10% 15

Total 29 100% 64

Mean = 2,2

The sources used may be administrative or statistical sources: 4 countries use only statistical sources; 11 countries, only administrative sources and 13 countries use the two types of sources (“mixed sources”).



The main administrative sources used are Social security sources (11 countries), Legal sources (10 countries) and Tax sources (7 countries). Statistical sources include Structural Business Surveys, Profiling sources and others business surveys. But some sources are not well defined.

Table 11: ( Question 3.2) Regulation 696/93 on statistical unit s states that “at or from” the place where the local unit is situated “e conomic activity is carried out for which one or more persons work for one and the same enterprise”. How does NSI identify local units?

No of countries %No Response 2 6.5

Each place is considered a local unit without furth er analysis 13 41.9

Further analysis (multiple answer): 16 51.6

1. By using sources that identify exactly a local u nit with employment 11 68.8

2. By using thresholds of one or more variables (e. g. persons employed, employees,...) 4 25.0

3. By using more complex methods (deterministic/pro babilistic models) 1 6.3

4. Other 3 18.8

‘Each place’ is considered a Local Unit without further analysis by 13 NSIs (42%), but the majority of countries (16 countries, 52%) use further analysis. The following question supported multiple answers, but 87% of these experts stated only one kind of analysis, mainly answering “by using only sources that identify exactly a local unit with employment” (11 countries). Besides, 5 countries use thresholds and/or more complex methods. Question 3.3: Do you have local units without emplo yment? This question investigates the existence of a minimum amount of employment in each unit. The answers suggest that there is, in practice, some confusion between the ‘employment’ concept and the ‘salaries’ (or wage earners) one. Regulation 696/93 on statistical units mentions “for which one or more persons work”: this criterion is probably not applied in the same way by all countries, depending on the available information. In fact, a majority of countries (19) do have LUs without employment in their BRs. But for 3 of them, there is probably confusion between employment and salaries, and for 6 of them, the answer underlines problems in BR quality or the absence of information about local employment. In practice, the employment criterion seems not to be a necessary condition to define a legal unit in the Business register. Question 3.4: Which is the maximum geographical det ail used to identify a local unit of an enterprise? Question 3.5: Is it possible in your NSI to georefe rence the local units? Almost all countries (25) use addresses to identify the LUs. But one mentions the registering of (X, Y) coordinates, one monitors Zip code, one monitors ‘Municipality’ and one does not register any geographical detail. A majority of countries is able to georeference the LUs (17 countries). Two more countries mention that they could be able to do it in the short term. Question 3.6: Do you store more than one economic a ctivity of the local units in your BR? If Yes:



Question 3.7: List the main administrative/statisti cal sources that permit to store more than one economic activity of the local unit Question 3.8: Does NSI identifies these economic ac tivities for the whole population of local units in the BR or just for a s ubset of them? A majority of countries (18) store more than one economic activity, but only 8 of them store it for all LUs and 10 of them store it only for a subset of their LUs. The subset is defined by surveys, sector (agriculture) or “If known by legal source”. Conversely, one country out of three (11 countries) store only one economic activity per LU in its BR. Sources used to store more than one activity of LUs in BR are:

• only statistical sources, for 3 countries • only administrative sources, for 5 countries • and ‘mixed’ sources, for 10 countries

Question 3.9: Fill in your Local Unit “operative” definition Most countries (15) give Eurostat’s definition or similar as their operative definition:

• 8 countries use administrative definitions • 3 countries use LKAU • 2 countries use “active locations” • and 1 country uses “LU=Enterprise”

Some of the countries that use administrative definitions may also use the results of survey(s) to define Local Units.

II. Relations between LUs and LKAUs (BR section- mo dules 3+5)

As regards the relation between Local Unit and Local KAU, some results could be obtained looking at the answers in Module 3 (concerning Local Unit) and Module 5 (concerning KAU). The following results are not directly issued from an explicit question in the web questionnaire, but from the confrontation of the different answers and more generally, from the qualitative answers in Module 1 (BR section).

Figure 5: Relations between LUs and LKAUs

For most countries (16), the questionnaire answers suggest that LUs are not explicitly different from Local KAUs. Moreover, some countries do not implement different statistical units for Local Units and for Legal units (or Enterprises). But in other



countries, the definition of LU is clearly derived from the LKAU, or the reverse: LUs are defined by aggregation of LKAUs in 5 countries, whereas LUs are surveyed to define LKAUs in 3 countries. One country implements more complex methods to define LUs and 4 countries did not give any information about LKAU.

III. Short Term Statistics (STS) sections

In the beginning of sections C, D, E, F1 of the survey sent to short term statistics experts, one and the same filter question was asked: “How does your NSI identify the population of statistical units observed in your Short-Term Statistics? (Single answer)

1. Enterprise 2. Local Unit 3. KAU 4. LKAU

For each item, 4 choices were prompted, and further modules were eventually required, depending on the answers of the following:

• Local Units are the ones identified in the Business Register without any further manipulation

• Local Units are identified by SBS • Local Units are identified by other sources • Units are identified using both the BR and other sources

Whatever unit, if the first choice is checked (without any further manipulation), no further module is asked. Notice that none of these domains have the Local Unit as a mandatory Unit: in STS, the mandatory unit is KAU in Industry, and the Enterprise in other activities. That explains why the information on local units is mainly issued from BR experts: no country was prompted to answer any module 3 in SBS sections. Table 12: Response rates of the filter questions in STS sections (and Local Unit answers); (“How does your NSI identify the population In Shor t Term Statistics?”)

STS Section Identification of Statistical Units

observed in STS

N° of countries %

C Industry (turnover) No response 3 9.7

2. Local Unit 4 12.9

Total (responses) 28 90.3

D Industry (production) No response 2 6.5

2. Local Unit 4 12.9


E Retail trade.(turnover) No response 3 9.7

2. Local Unit 0 0


F Other services (turnover) No response 4 12.9

2. Local Unit 0 0


1 Sections C and D relates to”Industry “(Turnover and Production), section E to “Retail trade and repair” (Turnover) and section F to “Other services” (Turnover).



Only 2 to 4 countries (over 31) did not answer the filter questions of the Short Term Statistics questions, depending on the section. But when they did, only 4 chose the Local Unit item in the industry sector (13% of countries, 14% of responses), and none in retail trade or other services. In services, the mandatory unit is the enterprise. So, it is not surprising that no country declares using the local unit in these activity sectors (sections E and F). Nevertheless, some countries do use LKAUs (4 countries in “retail trade and repair”, and 2 of them in “other services”). In manufacturing, the mandatory unit is the Kind of Activity Unit, but this unit is not mandatory in the statistical business register. Some NSIs may use proxies for KAUs, as local units. 4 countries report LUs for STS in industry, and they are the same in the Turnover (C) and the Production (D) sections. Note that in one country, the LKAU statistical unit was replaced in 2008 by the Local Unit, for administrative simplification reason. In the Turnover section, all 4 countries using Local Units for statistics in Industry didn’t mention ‘any further manipulation’ to define local units. But in the Production section, one country reported extra sources as SBS and Prodcom.

Figure 6: Statistical units observed for STS in Ind ustry (Production) and in Retail Trade (Turnover)

Conclusion: • Local Units are essentially evaluated by BR experts • Local unit is not relevant for statistical units for STS, except some cases for

industrial production, and if yes, information comes directly from BR • In practice: LUs always in BR, georeference is often available and possible for a

large majority of countries, but they are not always distinct from LKAUs (and in some cases, from Enterprises)

• Multiple administrative or statistical sources are used, but employment is sometimes missing at the local level, so it is not a compulsory criterion to define local units

• 2/3 countries monitor more than one activity (but usually not for all units), and the scope of the register may vary, including or not non market activities

The relevance with other domains within this inquiry was not tested (labour market, environment).



� Local kind-of-activity unit (Inga Oksentjuka, Liga Pranca – CSB, Latvia)

Inga Oksentjuka started her presentation with reference to definition of Local kind-of-activity unit stated in Regulation 696/93 on the statistical units: “Local Kind-of- activity unit is a part of kind-of-activity unit, which corresponds to local unit. Each KAU must have at least one Local KAU which corresponds to a local unit. Each enterprise should have at least one Local KAU”. She provided insight into inquiry questions on statistical units.

As regards the BR section of the questionnaire, 29 countries answered the questions on Local KAU, even though this unit is not mandatory in BR Regulation. 19 of them do not have Local KAU on their Business Register and in accordance with the information from the Inquiry, 10 countries have implemented Local KAU in the BR.

As regards the negative answers, when the NSIs were asked about the main reasons not to implement the Local KAU in their BR, the most frequently mentioned reason was in general the lack of information. Actually, out of 19 respondent countries who have not implemented Local KAU in their BR, five of them mentioned the lack of information to cover the population as the main reason, which is 26% of the total number of countries. Another 21% of countries affirm not to have enough information, due to the lack of input sources.

Another important reason is the lack of importance given to this unit, both from a legal point of view and in terms of users’ needs. Four countries (21%) mentioned as a reason the fact that identification of the LKAU is not mandatory in Regulation (EC) No 177/2008 of the European Parliament and of the Council of 20 February 2008 establishing a common framework for business registers for statistical purposes (Business register Regulation 177/2008) and thus it is not required in other provisions of law (either on the national or European level). Two countries (11%) have no internal and external users for Local KAUs and have no request for them. 5% of respondent countries mentioned that Local KAU was not a priority and another 5% said there are no strong needs for implementing Local KAUs in the BR. Results shown in Table 13.

Table 13: Implementation of the Local KAU in the BR

The presenter mentioned that in general the administrative information and the statistical sources have quite the same importance: they are used respectively in 90%



and 80% of the countries. In one country the units themselves inform the NSI about new Local KAU.

Figure 7: Administrative/statistical sources of the Local KAU (1)

Regarding Figure 8, the 40% of countries who implemented Local KAU use only information from Statistics as the main source, which includes Statistical surveys like Employment survey, SBS survey, BR survey and information from other statistics. 20% of the countries use only administrative sources, while the majority (40%) use both administrative and statistical sources at the same time.

Figure 8: Administrative/statistical sources of the Local KAU (2)

Figure 9 shows that 20% of the respondent countries use KAUs and local units for the identification of Local KAUs. The main source for this approach is the statistical surveys. The 10% of respondent countries mention that they identify Local KAUs directly from KAUs, using statistical surveys as the main source but also making use of administrative sources like the Tax register. Another 10% identifies Local KAUs from Local units, above all using branch approach. In most of the countries (60%) the identification of Local KAUs starts using other sources like surveys, different registers or legal units.



Figure 9: Starting point of Local KAU identificatio n

70% of the NSIs are capable of observing/estimating the variable “employment” and 40% observe and/or estimate the variable “value of production”. Another 40% use other variables and in most cases it is the turnover. Only one country has some information available on all the six variables, while at least 60% of the countries are not able to observe/estimate any other variable.

Figure 10: Available variables to identify the Loca l KAU

The countries who implement the Local KAU in the BR were also asked if the identification involves just a subset of units or if it takes into account the whole population of local units in the BR. As shown in Figure 11, 40% of respondent countries identify Local KAU for all local units, while 60% succeeds in act upon a subset of them.

Figure 11: Coverage of the implementation of the Lo cal KAU

The main criteria to choose the subset is by using the variable “persons employed” or performing some operations on certain specific NACE classes that are considered relevant by the NSIs.



The countries that have the Local KAU implemented in the BR were also asked to provide an “operational” definition of this unit, with the aim to obtain a precise description of the operational criteria used to define and identify this unit. According to the answers to this question, 10 countries were classified into three groups.

Figure 12: “Operational” definition of Local KAU

Summary of the results: • 19 countries do not have LKAU, because this unit is not mandatory in BR. • 10 countries have implemented LKAU in BR, out of them only 1 country has all

6 variables for KAU: o Value of Production o Intermediate consumption o Manpower costs o The operating surplus o Employment o Gross fixed capital information

• In STS and SBS the use of LKAU is not mandatory.

The discussions on results of the qualitative part of the Inquiry on identification of inconsistencies between Member States in BR, STS and SBS:

It was noted to draw attention to cases where one entrepreneur is involved in several enterprises.

Discussions:

Clarification regarding sole proprietors: • According to Regulation 696/93 on statistical units legal units include natural

persons who are engaged in an economic activity in their own right, so one can conclude that sole proprietorship is legal unit

• Regarding with inquiry results the majority of countries sole proprietors considered as enterprise. Only the NSI of the Netherlands uses the method of splitting the legal units for identifying of the enterprise



� National Accounts and Regional Accounts (Kerstin Gruber - STAT, Austria)

Kerstin Gruber explained the main results of the National Accounts (NA) and Regional Accounts (RA) questionnaire. She mentioned that the focus laid on the collection of the following information:

• Statistical units used in NA and RA • The most important data sources regarding statistical units • Quantitative effects of statistical units used in NA and STS and SBS the use of

LKAU is not mandatory

Regarding results of inquiry: • Core data on NA/RA base regarding KAU/LKAU units in the SBS • Implementation of the statistical unit KAU/LKAU differs widely from country to

country • Status quo of the implementation needs some further effort in NA/RA; • It has clearly turned out that detailed information below the enterprise level is

essential to produce harmonized and comparable macroeconomic data sets

No further discussion.

Results of the quantitative part of the Inquiry on identification of inconsistencies between Member States (Danila Filipponi – ISTAT, Italy)

Danila Filipponi presented the results on the quantitative part of the Inquiry on identification of inconsistencies between Member States. The aim in collecting quantitative information on the statistical units was to – measure – the inconsistency – if any – of the statistical units among Member States where the considered statistical units were Enterprises and KAU.

Concerning Enterprises, the idea was to evaluate the effect of the actions carried out by each country for the identification of the statistical unit as defined by the Regulation 696/93 on the statistical units. The impact of the applied treatments has been quantified considering, for each country, the dissimilarity between the distribution by NACE code of the legal units and the distribution of the enterprises. The measure used to assess the dissimilarity between the two distributions is the Index of Dissimilarity. It is a measure that vary between 0 and 1, where the higher is the number, the more unlike the two distributions are. The formula for computing the Index is:

∑=

−=K

i

ri

si ffD

12

1

Where k is the number of modality in the distributions and dif is the frequency of the

modality i in the distribution d, with ki ,,1 K= and srd ,= . The index D has been evaluated for three different dimensions: number, employed and turnover. Figure 13 shows the index by country and type of treatment.



Figure 13: Index of dissimilarity (of units, employ ed and turnover) by type of treatment and country

Figure 14 provides a means of summarising the data (Countries, class of dissimilarity for the units and treatments) in two-dimensional graphical form.

Figure 14: Correspondence analysis for Index of dis similarity of units, type of treatment and country

In order to explicate the index of dissimilarity of the distributions by NACE before and after the treatment as a function of the applied treatment of units and in relation with



the countries, it has been performed a Correspondence analysis. The applied treatments have been divided as:

Label in graphs Description of treatment

1. Part1 NO Part3 NO

No treatment of LeUs

2. Part1 YES Part3 NO

Thresholds or other methods to identify the productive units

3 Part1 YES Part2 YES

Both combination of LeUs and methods to identify the productive units

4 Part1 NO Part2 YES

Only combination of legal units

The conclusions for the enterprises are the following:

• The application of the PART 1 of the definition of Enterprise (identification of “productive activity” – threshold-) brings:

o big variation between legal units and Enterprises in terms of unit o small variation in terms of employment and turnover

• The application of the PART 3 of the definition of Enterprises (“combination of units”) brings variations in terms of employment and turnover

• The distribution of Legal units with respect to the distribution of Enterprises (in Units):

o decrease the incidence of NACE “L” and “S” (<-1) o high increase of “G”, “M” and “F” (>+1) o medium increase of “C”, “H” and “Q” (+0.5 to +1) o all the others are stable variation

Concerning KAU, the idea was to compare the distribution by NACE of the enterprise and KAU, considering as measure number, employed and turnover. Figure 15 shows the Index of dissimilarity of Number, Employed and Turnover by country and definition of KAU.

Figure 15: Index of dissimilarity of Number, Employ ed and Turnover by country

Table 16 show that out of the 29 countries that filled in the questionnaire, only 12 countries filled in the KAU quantitative section. Using a statistical model (GLMM) and



the information on secondary activity, it has been estimate the number of KAU for the missing country. Table 14 shows the number of KAU and enterprises in EU/EFTA by NACE.

Table 14: Number of KAU and enterprises in EU/EFTA by NACE

The conclusions for the KAU are the following:

• The results of the KAU analysis it is partial because of missing data for most of the biggest countries

• There are not evident differences between the Enterprise NACE distribution and KAU NACE distribution, even if the analysis carried out at section level could be partial

Discussions:

The delegates requested some clarification on the presentation, among statistical unit - enterprise and KAU, the availability of segment information and mentioned the national needs for collecting information. Relationships between legal unit and enterprise were also discussed.

It was emphasised that the use of combined legal units is of small importance to figures on employment and turnover but concentration of the production is higher. The delegates expressed opinions on the medium-size enterprises and their role in common statistics, especially on determination of complex enterprises.

In the field of the interpretation of KAU in the countries it was decided that it must be determined in which cases KAU is used and in which cases - the secondary activity.

Regarding data from Euro Groups Register only two countries (the United Kingdom and the Netherlands) have a significant number with more than one legal unit per enterprise.



Outline on identification and evaluation of inconsi stencies in regulations for business related statistics (Svetlana Jesilevska - CSB, Latvia)

Svetlana Jesilevska presented an outline on identification and evaluation of inconsistencies in regulations for business related statistics. She mentioned that the identification and evaluation of inconsistencies in regulations for business related statistics fell under objective of WP1 ’Statistical units’ of the Project ‘ESSnet on consistency of concepts and methods of business-related statistics’.

The presentation was focused to explain what kind of statistical units are used in different statistical domains and their compliance with Regulation 696/93 on the statistical units. Svetlana Jesilevska presented four types of statistical units:

• Units as defined in Regulation 696/93 on the statistical units, with clear reference to Regulation 696/93 on the statistical units (SBS; STS; Structure of Earnings Survey/Labour Cost Survey; Prodcom; Tourism; Waste Statistics; Vocational Training Statistics; Statistics on Information and Communication technology; Foreign-Affiliates Statistics; Environmental expenditure;

• Units according to Regulation 696/93 on the statistical units, but with exceptions and rather weak link to Regulation 696/93 on the statistical units (Research and Development; Innovation; Energy Statistics)

• Well defined specific units, without reference to Regulation 696/93 on the statistical units or with reference in a very indirect way (External Trade – Intrastat; Extrastat; Balance of Payments; Foreign Direct Investment Statistics; NA)

• Undefined units (Job Vacancy Statistics (the compilation of statistics shall be based on business units, but no definition is given and any reference to Regulation 696/93 on the statistical units is also missing); Labour Cost Index (Regulation 696/93 on the statistical units is quoted but there are no provisions which of the units have to be used); Labour Force Survey (the individual person is the central statistical unit, regardless of whether the sampling unit is an individual or a household. Information usually has to be collected for all individuals of the household).

Figure 16: Percentage of statistical domains accord ing to type of statistical unit

Only half of statistical domains according to requirements stated in regulations and manuals are based on statistical units as defined in Regulation 696/93 on the statistical



units and have clear reference to this Regulation. 15% of statistical domains are based on the units according to Regulation 696/93 on the statistical units, but with exceptions and rather weak link to Regulation 696/93 on the statistical units or refer to other undefined units. 20% of statistical domains are based on well-defined specific units, without reference to Regulation 696/93 on the statistical units or with reference in a very indirect way.

Examples of statistical units used in different statistical domains: • Enterprise is the statistical unit in BR; SBS; STS; Foreign-Affiliates Statistics;

Energy Statistics; Environmental expenditure; Prodcom; Statistics on Information and Communication technology; Research and Development; Innovation; Structure of Earnings Survey/ Labour Cost Survey; Vocational training.

• Local unit i s the statistical unit in BR; SBS; Tourism; Foreign-Affiliates Statistics; Structure of Earnings Survey/ Labour Cost Survey; Waste Statistics.

• Kind-of-activity unit is the statistical unit in SBS; Waste Statistics; STS. • Local kind-of-activity unit is the statistical unit in Tourism; NA.

She also mentioned examples of some special statistical units, shown in Table 15.

Table 15: Other statistical units

Statistical domain Statistical unit

Business Register ‘Enterprise Group’

Structural Business Statistics

‘business’ and ‘branch’ in Module V (Insurance); ‘credit institutions’ and ‘branches’ in Module VI (Credit institutions)

Statistics on External Trade

‘statistical unit’ means the basic observation unit, namely a natural person, a household, an economic operator and other undertakings referred to by the data (Regulation (EC) 223/2009)

Job Vacancy Statistics ‘business unit’

National Accounts ‘Institutional units’

Balance of Payments and Foreign Direct Investment

‘Institutional units’

Labour Force Statistics ‘individual’ or ‘household’

Labour Cost Index the LCI shall represent all the statistical units as defined in Council Regulation (EEC) 696/93; (Regulation (EC) 450/2003)

Svetlana Jesilevska presented clusters of survey-based statistics:

Cluster A: Economic Units/ Activity oriented Statistics The statistics usually address enterprises as respondents; the main variables primarily capture characteristics of the economic activities of these economic agents.

The following statistical domains belong to this group: SBS and Business Demography; STS; Some of the variables covered by STS such as prices are rather commodity oriented and do not fit well into the cluster of activity oriented statistics; FATS; Tourism; Environmental expenditure; Statistics on Information and Communication Technology – Enterprises and the information society); Research and Development; Structure of



Earnings Survey / Labour cost survey; Job Vacancy Statistics; Labour Cost Index; Vocational Training Statistics; FDI/International Trade in Services.

Cluster B: Person/ Household oriented Statistics These statistics focus on persons and households as respondents and units of observation.

The following statistical domains belong to this group: Tourism - Participation in tourism; Tourism – Data on trips; Statistics on Information and Communication Technology - Individuals, households and the information society; Labour Force Survey; Structure of Earnings Survey (to some extent, although also classified under Cluster A).

Cluster C: Commodity oriented Statistics The scope of these statistics is always defined with reference to certain commodities.

The following statistical domains belong to this group: Prodcom; Energy Statistics; Waste Statistics; External Trade.

General conclusions: • The legal acts and manuals governing the system of business-related statistics

themselves belong to very different age groups. • Great amount of legal acts and manuals have been reviewed. A comparison of

all these legal acts and manuals on a bilateral basis is almost impossible. • Lack of consistency with respect to the underlying statistical units will have

serious consequences. The use of administrative data based on different statistical units than the units as laid down in the legal act will constrain the comparability between statistical results from different statistical domains.

• The main inconsistency must be seen in the different statistical units on which the closely related projects are based.

• A number of statistical projects are not based on statistical units according to Regulation 696/93 on the statistical units.

• Business register Regulation 177/2008 does not require that all statistical units distinguished in Regulation 696/93 on the statistical units are included in the BR for statistical purposes.

• There is an additional need for revising the Regulation 696/93 on the statistical units and the statistical units used due to changes.

Discussions:

Several questions were raised on the need to use one statistical unit for all statistical domains. During the discussion it was emphasised that the focus should be on the statistical units and their consistency in different statistical domains. The problem that NSIs do not control the units that are used by the administrative organisations was stressed.

Results of the vignettes on the test of a new defin ition of enterprises (Dominique Francoz – Eurostat)

In her presentation Dominique Francoz explained results of a questionnaire on the test of new proposed definition of enterprise. The vignettes in this document have the same meaning as case studies on enterprise definition. The results are summarised from answers on 7 vignettes at the global level (global enterprises or GENs) defined



regardless of the geographic dimension and at the truncated enterprises (TENs): the national parts of the GENs.

Principles applied to build the vignettes • Stories must appear plausible and real to participants • Stories need to avoid depicting eccentric characters and disastrous events • Vignettes need to contain sufficient context for respondents to have an

understanding about the situation being depicted, but be vague enough to ‘force’ participants to provide additional factors which influence their decisions

• Vignettes must be presented in an appropriate format • The building of the vignettes • Describe current situations

o supposed to be encountered yet in the EU countries o difficult to tackle for the business statisticians o Solved with the new definition

• Cases presented according to a growing scale of complexity • Graphical illustration with a short text aside • To be tested in different domains of business statistics - SBS, STS, BR, NA

The purpose of the questionnaire was to test the situations identified by ESSnet profiling that occur frequently in the countries and to see the solutions applied. The results were shown by 7 vignettes:

• Treatment of a legal unit performing an ancillary activity for another legal unit or for 2 other legal units in the same group.

• Treatment of vertically integrated activities in one country and in two countries. • Treatment of international trading flows in the frame of a multinational

enterprise group. • Treatment of the headquarters. • Determination of the activity code in complex situation. • Treatment of a legal unit acting for 2 global enterprises in the group. • Organisational aspects of gathering statistics on newly defined statistical units.

General results of the vignettes: • 42 answers received from 25 EU countries • 7 countries sent a single coordinated answer for all the domains • 10 answers from BR respondents • A majority of respondents open to consider the enterprise as a set of legal units • NSIs promote the follow up of national activities against the global activity of the

group • The use of administrative data were not unanimously supported by the

respondents the NSIs prefer in majority to survey the new TEN • The split of legal units is not well accepted

The presenter also mentioned the role of ESSnet profiling and need to further explore how to build statistics on enterprises.

Preliminary conclusions: • A door is open for the change • Answers provided contradicted opinion expressed in working groups

o A majority of respondents open to consider the enterprise as a set of legal units

o Use of administrative data were not unanimously supported by the respondents: the NSIs prefer in majority to survey the new TEN



o Consolidated data are preferred • Distinguish the definition and the principles proposed by the ESSnet profiling

from their application o As results of the top down approach

� One GEN / one TEN � Split of legal units

o In practice � Double classification to adapt the NACE code of the TEN to the

activity performed in the country � Try to avoid the split of legal units as much as possible

(recommendation for profilers) • Need for pedagogy from the ESSnet profiling to the future users of the new

statistical units • Provide them with solutions on how to concretely proceed

o Aim of the documents: � Methodological document � Guidelines � Instructions

• Need to further explore how to use administrative data on legal units to build statistics on enterprises

Discussions:

The main discussion points regarding vignettes: • Clarifications of results regarding topics treated in seven vignettes. • Identifying legal units that belong to truncated enterprise and multinational

enterprise • Delineation information from legal units to enterprise from national and global

point of view • Need for common methodology how to profile the new statistical units

2nd part: What do we need?

Improved, new, operational, etc. definitions of the main statistical units for European business statistics (Norbert Rainer – STAT, Austria)

In his presentation Norbert Rainer described: • statistical units in current European business statistics • current definition of enterprise, KAU, LKAU, and Local unit • proposed definition of enterprise, KAU, LKAU and Local unit

Presenter characterized the current situation for the choice of the statistical units in the European business statistics as follows:

• Different statistical units are applied over the statistical domains. • Some units for which data are requested are not supported by the Business

register Regulation 177/2008. Some statistical domains refer to units which are not defined in the unit regulation.

• Data input relations between statistical domains are not always considered.



After the overview of the current situation he drew attention to the basic goals on consistent European business statistics:

• Achieve higher consistency between the various statistical domains of the European business statistics.

• Achieve higher consistency between the data of each domain of business statistics between the Member States.

and explained technical goals: • Propose improved/operational definitions for the main statistical units of the

European business statistics. • Make sure that the definitions are comprehensive. • Take into account the results of ESSnet Profiling. • Consider the requirements for Framework regulation to integrate business

statistics (FRIBS). He also explained the statistical units used in statistics and reasons for revision of Regulation 696/93 on the statistical units. Reasons for revision:

• Not specific in terms of certain economic branches: agricultural sector, public administration; non-profit sector

• Not up-to-date: e.g. enterprises groups; business accounting; • Ambiguous and not always operational • Specific units not considered, such as SPE, captive financial units, artificial

subsidiaries, head offices, • Split into observable and non-observable units

The presenter described current and proposed definitions on enterprise, KAU, Local unit and LKAU. Proposed definition of the enterprise of ESSnet Profiling: The enterprise is a single legal unit (including a natural person), an enterprise group as a set of legal units under common control, or a part of an enterprise group, producing goods or services. It benefits from a certain degree of autonomy in decision-making, especially for the allocation of its current resources. The enterprise will appear as an organisational unit that can provide meaningful data for statistics.

• The delineation process for the establishment of enterprises (Profiling) starts from the (global) enterprise group in a dialogue will the group head

• There are at least as many enterprises in a group as there are different sectors in the closed financial accounts (according to IFRS) of the group, but possibly more

• At the global group level, first “global enterprises” are being delineated. In a further step “truncated (national) enterprises” are delineated

• Within an all-resident enterprise group, the global enterprise and the truncated enterprise are one and the same unit

• The number of truncated enterprises in a specific country cannot be bigger than the number of global enterprises

• The new approach is a “top-down” approach as the delineation starts from the enterprise group / enterprise group head

• Also “top-down” as the delineation first aims to define the global enterprise, the national delineation is a result from the global profiling



Table 16: Comparison of current and proposed defini tion Criteria of autonomy:

• The group (head) has full autonomy at the highest level and exercises this mainly for strategic and long term decisions.

• Enterprises (within a group) are deemed to have only limited autonomy, especially related to the allocation of current recourses in the production process.

• The limited autonomy needs to be further specified by listing criteria, as the situation might be quite different between the groups.

Proposed definition: Kind-of activity unit The new definition is principally the same as the current definition. It only adds thresholds for the operational implementation. An enterprise should be split into KAUs, if:

• the enterprise has an annual production value of over... mio € and • at least one secondary activity accounts for more than 30% of total production

at class level of NACE Rev. 2 or • at least one secondary activity accounts for more than 20% of total production

at division level of NACE Rev. 2

Proposed definition: Local unit There is a change proposed with respect to the criteria of persons working. It should be more explicitly specified when a local unit where no person - not even temporarily - is working is still to be treated as a separate local unit. Proposed definition: Local kind-of-activity unit

• No change compared to the current definition. • For the operational implementation a LKAU needs only to be specified, if two or

more KAUs were established within an enterprise • Therefore, an enterprise for which no split into KAUs is requested - because

below the threshold - will only have one KAU (i.e. the enterprise itself) and each local unit corresponds to a LKAU

Resume and further procedure:



• Concerning enterprise definition: current and proposed definitions are only relevant for legal units under control of an all-resident or multinational enterprise group

• There should principally be no different treatment, whether an all-resident or multinational enterprise group

• Autonomy is the main criteria for enterprise definition • Exemptions of autonomy in case of national purpose

Discussions:

Several comments were made on statistical units definitions and their consistency. The participants mentioned that the current statistical units definitions were burdensome and not consistent from the point of view of an observation unit in different statistical domains. Particular attention was paid to the current KAU definition and proposals for a new definition were discussed.

Session 2: Where do we go?

Chair: Norbert Rainer (STAT, Austria)

Chairman Norbert Rainer opened the session reminding the goal of the ESSnet project on consistency of concepts and methods of business and trade-related statistics. He briefly explained the main points from Session 1 and gave a short introduction to Session 2 emphasising the crucial importance of consistent definitions and methodology for achieving consistency on the concept on the statistical units in business and trade-related statistics.

Which statistical units lead to Business Statistics best fit for economic analysis? (Olivier Haag, INSEE, France)

The presentation of Olivier Haag aimed at providing insight in statistical units which lead to Business statistics best fit for economic analysis. He described:

• French administrative units and their duties • The limits of the statistics based on legal units • The solution taking into account the group as equivalent to the enterprise • Necessity of the profiling • A new statistical register system for recording enterprises (profiled and stand-

alone legal units) Olivier Haag explained that until now, enterprises have been taken as equivalent to legal units. Enterprise equivalent to economic stakeholder: an economic unit, dealing with work and capital; producing goods or services; in order to sell them, with a certain degree of autonomy in decision making. The enterprise as defined above is not directly available in statistical sources: Legal unit = legal concept (legal person), directly available in statistical sources; no problem at all for the units outside groups (94 % of cases). These have a real autonomy in decision making; problem for the units controlled by groups: sometimes, they may have no autonomy at all, no stand-alone economic actors. The main difficulty:

• At which level is there autonomy in decision making • The group as a whole • The legal unit • An enterprise within the group



During the presentation the problem of legal reorganization impacts statistics was covered. The presenter proposed first solution: consider the group as equivalent to an enterprise; keep the legal unit as collection unit; aggregate the characteristics of its legal units to obtain the value of characteristics for the enterprise (« bottom-up method »). Some problems: this solution does not solve the problem of the intra group flows; this solution is not efficient for large groups (MNEs) because of the diversity of their activities. That’s why to obtain the best structural businesses statistics the French NSI decided:

• To begin a profiling process • To create a statistical register to record these enterprises

Three categories of groups are treated separately according to size and complexity: • Category 1: around 100 majors, annual individual interview

o 89 groups of 10 000 employees and more: 22 % of employees o 26 % of added value (private sectors, excluding finance and agriculture) o 223 « enterprises »: 27 % of employees, 34 % of value added

• Category 2: around 38 000 small groups, automatic processing o 33 651 groups’ less than 500 employees: 14 % of employees, 14 % of

VA o 5 285 groups with one or two legal units in France: 3 % of employees, 3

% of VA • Category 3: around 1 600 middle sized groups, semi-automatic processing

o 19 % of employees, 22 % of VA Category 1: Delineation of the enterprises in cooperation with the group Profiling a group means identifying the enterprises within this group, that is to say establishing their statistical structure, beyond the legal structure in legal units. Profiling a complex group has to be done in cooperation with it because:

• The group knows its own structure • The group knows how its accounts are produced • The group will have to reply to the statistical survey on the new structure • Possibility to have two enterprises with the same activity if they are autonomous

(example of SANOFI) They will be taken into account for the first time in 2013 for 2012 data. Category 2: Automatic process for the « small groups » A group = an enterprise Consolidation of accounts provided by the tax administration for legal units to obtain the data of the enterprise (bottom-up method), example, a group with a commercial and a product unit => the turnover of the commercial unit will not be taking into account. The statistical unit of collection could be the group or the legal units; it depends of the scope of the survey. There will be taken into account for the first time in 2015 for 2014 data. Category 3: A new statistical survey for the intermediate size groups The reporting unit of this new survey will be the group. This new survey has two main goals:

• To define the enterprise in the legal units : for this category the group could be divided into several enterprises

• To obtain individual consolidation ratios for tax data from the data of the legal units (bottom up)

For other surveys, the reporting unit could be the group or the legal unit. It will depend on the scope of the survey. They will be taken into account for the first time in 2016 for the 2015 data



The presenter explained solutions for delineation of enterprises and the main difficulties. Regarding solutions he looked through three categories of groups treated separately according to size and complexity:

• Delineation of the enterprises in cooperation with the group • Automatic process for the “small groups” • A new statistical survey for intermediate size groups

Within the presentation the presenter briefly explained a new register system for recording statistical units – SIRUS (for “Systeme d’Identification au Répertoire des Unités Statistiques”). A new register system to record all these units:

• Enterprises (profiled and stand-alone legal units) • Local units • Groups • Legal units and their “production units” • All the links between these units • Corporate networks”/ franchise

A large area to include as much “populations of interest” as possible

For More information: http://live.unece.org/stats/documents/2011.09.busreg.html

He also explained the necessity to take into account the needs of statistical operation and the needs of National Accountants:

• Implement a complete change to profiling: in order to treat all the enterprises in the same way; in a new base of National accounts (not before 2012).

• Steps in order to keep the continuity of the data: the total value added will not be changed but its sectorial breakdown will; make «Pro forma data» available for the year of the change.

• Implement new surveys on internal activities within enterprises: the information will be monitored at the level of enterprises, no more of legal units. As a consequence, a lot of vertically integrated activities would be lost. So, there will be new surveys on the internal functions of enterprises. (This will provide more complete, relevant information).

Discussions:

The French colleague highlights that in order to have more consistent data it is necessary to choose a set of main variables. There are necessities for three agreed set of variables which are the main ones and around which the others are gathered and compared. This set of variables include version of turnover, version of employment and probably version or proxy of variables (for example, value added).

Some participants were interested in clarifying information on data collection on Local units and delineation of ancillary units. Participants also touched upon the issue of double coding of enterprise.

Inconsistency problems from the point of view of Na tional Accounts (Eeva Hamunen, Statistics Finland)

The presentation of Eeva Hamunen was directed to inconsistency problems from the point of view of NA. She explained:

• Necessity to use different kind of units in NA



• Special requirements in Europe for NA • Difficulties in compiling NA • NA as a coordinating framework • Solutions to consistency problems

The presenter explained the need for different kinds of units in NA regarding ESA 2010. According to ESA 2010 2.03 a feature of the system is the use of types of unit corresponding to three ways of subdividing the economy:

• To analyse flows and positions, it is essential to select units which make it possible to study behavioural relationships among economic agents

• To analyse the process of production, it is essential to select units that bring out relationships of a techno-economic nature, or that reflect local activities

• To allow regional analyses, units that reflect local kinds of activity are needed

She also explained the necessity of the use of LKAU. According to ESA 2010 2.148 “ The institutional unit's information system must be capable of indicating or calculating for each local KAU at least the value of production, intermediate consumption, and compensation of employees, operating surplus, employment and gross fixed capital formation”. In fact, if NA use LKAU, it would be much easier to define the correct NACE category of the activity:

• R&D-activities of multinational enterprises could and should be classified to services

• Sales offices of MNEs could be classified to services? • ESA 2010 2.150 an industry consists of a group of local KAUs engaged in the

same, or similar, kind-of-activity. ESA 2010 2.152 the classification used for grouping local KAUs into industries is the NACE Rev. 2.

Within the presentation she provided a short overview of special requirements for NA in Europe and explained difficulties in compiling NA, briefly touching upon the significance of global productions. Special requirements in Europe:

• we need NATIONAL national accounts for o EU budgetary purposes: financing the budget by GNI resource and

VAT-resource o EU macroeconomic governance: EDP, ”six pack” o structural funds for supporting regions (regional accounts)

• own national needs: national budgets, national economic analysis

Difficulties in compiling national accounts: • how to define a national resident institutional unit, when enterprises are global

(not only European) • concepts in source statistics should follow SNA/ESA or it should be possible to

transform concepts to NA concepts • in practice, information on LKAUs is not easy to get ->

o have to be imputed o requirement: no consolidations between LKAUs

• inconsistency: foreign trade statistics record crossing the border – business statistics ownership

o global production o merchanting o goods sent abroad for processing o intellectual property products (IPP): R&D, software o special purpose entities (SPEs)



o quasi-transit trade (particularly in EU) • UNECE guide book: The Impact of Globalization on National Accounts

Regarding the point of view of NA she offered solutions to the consistency problems: • BR as a core of economic statistics • Evaluate whether the data collection is only possible from legal units • A special team for large enterprises • Data from different sources investigated at the same time • Co-operation with tax authorities • Use of EGR, data collection on enterprise groups • Necessity of FRIBS • In the conclusion the presenter noticed that NA should be a coordinating

framework for all economic statistics: • Conceptual framework: consistency of definitions and classifications • Accounting framework: numerical consistency of data from different sources

Discussions:

The participants mentioned that concepts, definitions and methodologies partially or even completely differ in different statistical domains. They mentioned that from the general point of view it was the reason for the lack of coherence and probably higher production costs and higher respondent burden.

Identify «enterprises»: the profiling procedure (Pierre Teillet, Coordinator of ESSnet Profiling, INSEE, France)

The presentation of Pierre Teillet, coordinator of ESSnet Profiling, explained the main objectives of the ESSnet Profiling project:

• Describe consistently the same MNEs in all EU+EFTA countries • Support efficient data collecting in SBS, FATS, FDI and if possible in STS • For direct dissemination and indirect use (National Accounts etc.)

An explanation for the meaning of profiling is provided: 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 most efficient structures for the collection of statistical data.

In his presentation he briefly explained that the proposals rely on moving from bottom-up/national to top-down/global analysis:

• Drop the previous “smallest combination of legal units” • Use “the autonomous part of an enterprise group” as “global enterprise” (GEN) • Complement it with “truncated enterprises” (TENs) as pure national parts of

GENs • Include both types of “enterprises” in a System of Statistical units

Profiling: • uses the MNEs information system for accounting consolidation • takes (organisational / management) operating segments as starting points for

delineation of economic “enterprises” (IFRS8), but they can differ at the end • with the result that an enterprise is (can be):

o a single legal unit (if independent)



o an enterprise group (i.e. a set of legal units under common control) o a part of an enterprise group with autonomous management.

• “enterprises” are organisational units => their autonomy (in decision making for allocation of their current resources) is an essential characteristic.

The move from bottom-up/national to top-down/global analysis supposes cooperation inside the ESS.

Profiling proposes to: • drop the previous “smallest combination of legal units” which is usually:

o national o bottom-up o often non autonomous

as basis of the enterprise • use “the autonomous part of an enterprise group” as “global enterprise (GEN)”

which is usually o top-down o multinational o compulsorily autonomous

• complement it by “truncated enterprises” as pure national parts of GENs. • and include “enterprises” in a System of Statistical Units

Pierre Teillet also explained an integrated process from “accounting” to enterprise structure, showed test results and proposed options for profiling.

No further discussion.

Statistical units: Avoiding mistakes, identifying a consistent approach. From the statistical concept of autonomy to the statistical definition of enterprise (Giuseppe Garofalo - Coordinator of the project on statistical units, ISTAT, Italy)

Giuseppe Garofalo explained the reasons for revision of Regulation 696/93 on the statistical units and drew attention to relationships with the existing EU regulations. He mentioned that the units defined in the Regulation have theoretical construction with a minor possibility to be applied in practice. He also explained the influence of the new FRIBS regulation on the following aspects:

• Best identification of the scope – the business sector • Unit of observation or unit for analysis • Definition of legal unit • From the legal to statistical definition • Simplified definition of enterprise

FRIBS Project: “Business statistics are, in the broad sense, the set of primary data compiled by national statistical authorities to measure the economic activities carried out by the business sector contributing to the GDP. The provision of harmonized statistical information of the economic activities of the business sector requires that the MSs use common statistical standards for the identification and definition of statistical units.

Interpretation: • Primary data means micro-data collection • They have to be collected at national level for national statistics



• They refer only to the Business sector (?) • Need of Statistical standards not only for statistical unit definitions but for the

“identification” of the units

Unit of observation or unit for analysis?

The unit of observation is the unit on which statistical data are collected. The unit of analysis is the entity that is being analyzed in the statistical study:

• Domains that use the enterprise as unit of analysis: Enterprise Demography and in general all statistics on the economic structure and its evolution (statistics based on BR)

• Domains for which the implementation of the definition of the statistical units is important for the quality of the domains: SBS, STS, (in general statistics by activities)

• Domains for which the implementation of the definition of the statistical units are not crucial: PRODCOM, Ex. Trade, etc. (in general statistics by products)

Definition of legal unit

Definition: All entities recognized by law, that exercise - wholly or partially - a productive activity. The legal entities are juridical persons, independently of the individuals or institutions which may own them or are member of them, and natural person who are engaged in an economic activity in their own right.

Interpretation: A legal entity has obligations and rights defined by laws. The law can define legal, administrative, fiscal, obligations and rights that govern the relationships between the legal entity and the State and between the natural or juridical persons that are the owners of the entity.

Obligations that define the relationship between the entity and the “stock exchange” market have to be taken in consideration. Accountable standards are “obligations”. It is possible to identify “single” legal entity or “group” of legal entities (Enterprise Group):

• a single legal entities are those not controlled by any other legal entity • a group of legal entities are those… (definition of EG/definition of control)

Definition of enterprise

Definition: An Enterprise is an autonomous market oriented unit. An enterprise carries out one or more activities at one or more locations. An enterprise will appear as an organizational unit that can provide meaningful data for statistics.

Autonomous means: It has the control of the use (may not be the owner from a legal point of view) of the whole productive means, of the whole productive process, of the whole productive outputs of the economic activities in which it is engaged.

Market means: It is a producer of goods and services sold, to independent buyers, on the basis of commercial consideration only, called “at arm’s length” (at economically significant prices.)

Organisational means: for the economic activities in which it is engaged, a planned and formal structure is identified. This structure is able to govern the whole business processes.



Meaningful data for statistics means: …

The enterprise can correspond to a single legal unit (not controlled by any other legal entity), an enterprise group as a set of legal units under common control, or a part of an enterprise group.

The operational criteria

To identify the enterprise some constrains have to be considered: • The reduction of cost and burden: massive use of administrative sources • The cluster vision of the economic operators

Operational criteria in case of a single legal enti ty

The “single” legal entities represent the great majority of the units for which business statistical data have to be collected. For these units the use of administrative data is a “must”

Operational criteria: In case of single legal unit the presence of turnover is considered as a proxy indicator to consider this unit as a statistical unit “enterprise”. Because the presence of different administrative and fiscal National laws, a threshold of turnover is identify to guarantee better comparisons and analysis at European level.

Operational criteria in case of group of legal enti ties

In the economic world the biggest enterprises have chosen to organize and conduct their business operations – at global or National level - in the cluster vision (set of various separate corporations) instead the atomistic one (single corporate entity). The new “short chain organisation”+ “new technology system” + “new standards” obligate and allow the top management to collect all needed information in short time to take its decisions. The global and general control is not limited to the “financial or strategic” aspects but focuses more on decisions of resources allocations, markets where produce and sell goods, price strategies, global communication and advertising strategies…

In the complex (global or national) organisations the short/medium/long time and strategic/current decision lose their meaning. In case of EG (national or global) the headquarter– or in same case the headquarters - may take all type of decisions – strategic and current - in own will and free from external influences, because it has the control of the whole productive means, of the whole productive process, of the whole productive outputs of the economic activities in which it is engaged.

The EGs can be organized in complex and different ways. To guarantee consistency between statistical data collected by NSIs, some well identified operational rules have to be defined. These rules have to be applicable in practices especially in collection of meaningful data for business statistics. The following criteria are connected with the needs to identify:

• Observable organizational unit • Units as homogeneous as possible in terms of economic activity. • Unit market oriented (consolidation of not market units)

The operational criteria in the case of group of legal entities:



• Mostly of the enterprise groups perform their activities in one single sectors or economic area (e.g. groups operating in transport, in retail sales, in financial sectors): Operational criterion 1: If one enterprise group (Multinational or National) performs its activities mainly in one single sectors or economic area it has to be identified as a single autonomous enterprise (global or truncated). These groups have to be classified on the basis of their main economic activity. If secondary activities exist they have to be treated as KAUs.

• Some groups have a complex structure: under a “financial holding” they can present more sub-groups that operate in different and distinct economical domains. These sub-groups identify more homogeneous activities or sometimes more homogeneous market area and often have sub-consolidated accounts: Operational criterion 2: In case of a conglomerate group each sub-group; if and only if it produces sub-consolidated accounts, have to be treated as an independent EG and the intra-flow transactions between the sub-groups are not taken in consideration.

• Some (Multinational or National) enterprise groups (or sub-groups) may decide to organise their activities in different “operating segments” or “business lines” or “GODs” or “profit centre”. Operational criterion 3: If the GODs are observable (their existence are proved in the reporting system of the Group), they are the starting point to identify and delineate the “autonomous enterprises”.

• Considering the market oriented criterion: Operational criterion 4: If one GOD inside a Group (or sub-group) represent a way on which the “group” itself performs a specific productive activity (it means that it contains all legal entities and their parts serving to this scope), it has sufficient homogeneity to be considered as single autonomous enterprise (global or truncated) and the previous criterion 1 is valid.

• Operational criterion 5: If inside a GOD there are legal entities market oriented, and carrying out activities not strictly linked with the disclosed segment, they have to be considered as autonomous enterprise units.

• Operational criterion 6: If one GOD perform support activities (as ancillary unit: administration, IT, wholesale, transport… or as artificially subsidiary corporation: owning land, building, equipment or being nominal employer) for other GODs and the main part (more than 50%) of its transactions is with other GODs it has to be considered as a serving GOD. In this case it is not considered an autonomous enterprise. The outputs of the serving GOD have to be considered as intermediate consumption for the other GODs and its accounting data have to be consolidated to identify the autonomous enterprise (global or truncated). Exceptions are the R&D and the holding activities.

Within the presentation he described operational criteria to identify the enterprise: • The case of a single legal entity • Threshold of a single legal entity • The case of group of legal entities

He also drew attention to the following questions: • In which market and for which market is it essential to identify the autonomous

enterprise? • For statistical purposes: are global and national the same markets? • What are the consequences for import/export or NA?



In the conclusion he explained definition of enterprise and pointed out that when defining an enterprise it is necessary to also articulate concepts related with it.

Discussions:

The discussion was mostly devoted to the expected results from ESSnet Profiling and ESSnet Consistency projects. The participants of the workshop asked for more precise provisions, in particular the impact on the national statistical needs. Some delegates mentioned that there might be problems with comparability between different statistical domains as the present regulations do not always clearly define statistical units.

The participants requested some clarification on the previous presentations, among others concerning enterprise and KAU.

Round up and conclusion

The work done within the workshop was summarised by Giuseppe Garofalo, coordinator of the project on statistical units. He mentioned that the results of inquiry on statistical units and proposals for definition of statistical unit “enterprise” are the starting point for a deeper analysis and for proposals on KAU and LKAU. Giuseppe Garofalo stressed that results presented during the workshop were strictly connected with the new proposals for FRIBS. He emphasised the importance of input by statistical experts from different statistical domains, including national accounts. He mentioned that some kind of network with experts should be created to disseminate proposals of ESSnet on Consistency not to limit the discussion with only members of ESSnet. Within the workshop clarification between national needs and global mission was done. He emphasizes that the collection of data for national purposes is extremely important as this data is input for administrative constraints, indicators etc.

Kaspars Misans, vice president of the CSB of Latvia, thanked the organisers, the participants of ESSnet on consistency – Project on statistical units for the work done within the project and participants of the workshop for collaboration.



Annex I – Workshop Agenda

ESSnet on consistency – Project on statistical unit s – Riga 2012 AVALON HOTEL

13th Janvara Str. 19, Riga, LV-1050, Latvia

Registration: 19th June 2012 from 9.00 Workshop starts at 9.30 on 19th June 2012 – ends at 13.00 on 20th June 2012 The goal of the workshop

The goal of the workshop is to present the work done at the ESSnet project on consistency of Concepts and Methods of Business and Trade-related Statistics and to open discussion on the needs for revised statistical unit’s definitions. Invitees to the Workshop

1. Two participants (one Business statistics expert and one National accounts expert) from each Member State

2. Specially Invited Experts 1st day - Tuesday, 19 th June 2012

Time Topic

9.00-9.30 Registration of the participants

9.30-9.40 Welcome and introduction (Aija Zigure – CSB, Latvia)

9.40-10.00 EU perspective (Hans-Eduard Hauser - Eurostat)

Session 1: What do we have?

Chair: Sarmite Prole - CSB, Latvia

10.00-11.20

Introduction and presentation of ESSnet on Consistency - Project on statistical units (Giuseppe Garofalo - Coordinator of the project on statistical units, ISTAT, Italy)

Results of the qualitative part of the Inquiry on identification of inconsistencies between Member States:

- Enterprise and Legal unit (Monica Consalvi - ISTAT, Italy) - Kind-of-activity unit (CSO, Ireland) - Local unit (Sylvie Mabile – INSEE, France) - Local kind-of-activity unit (Inga Oksentjuka – CSB, Latvia)

Questions and discussion 11.20-11.40 Coffee break

11.40-13.00

Results of the Inquiry on identification of inconsistencies on national and regional accounts between Member States (Kerstin Gruber – STAT, Austria)

Results of the quantitative part of the Inquiry on identification of inconsistencies between Member States (Danila Filipponi - ISTAT, Italy)



Questions and discussion 13.00-14.00 Lunch break

14.00-14.40 Outline on identification and evaluation of inconsistencies in regulations for business related statistics (Svetlana Jesilevska – CSB, Latvia)

Questions and discussion

14.40-15.50 Results of the vignettes on the test of a new definition of enterprises (Dominique Francoz - EUROSTAT)

Questions and discussion 15.50-16.10 Coffee break

16.10-17.20

What do we need?

Improved, new, operational, etc. definitions of the main statistical units for European business statistics (Norbert Rainer – STAT, Austria)

Questions and discussion 18.00 Social event

2nd day - Wednesday, 20 th June 2012

Time Topic

Where do we go?

Chair: Norbert Rainer – STAT, Austria

9.00-10.30 What statistical units do the Business Statistics need for their analysis? (Olivier Haag – INSEE, France) Inconsistences from the point of view of National Accounts. (Eeva Hamunen – Statistics Finland)

10.30-10.50 Coffee break

10.50-12.45 Define and identify statistical units: - Identify “enterprises”: the profiling procedure (Pierre Teillet -

Coordinator of the ESSnet Profiling, INSEE, France) - From the autonomy criterion to the statistical units definition

(Giuseppe Garofalo - Coordinator of the project on statistical units, ISTAT, Italy)

12.45-13.00 Round up and Closing



Annex II - List of participants

Name, Surname Organisation Email address Country

Kerstin Gruber Statistics Austria [email protected] Austria

Norbert Rainer Statistics Austria [email protected] Austria

Radek Smid Czech Statistical Office [email protected] Czech Republic

Vibeke Skov Møller Statistics Denmark [email protected] Denmark

Ingeborg Vind Statistics Denmark [email protected] Denmark

Katrin Aasmäe Statistics Estonia [email protected] Estonia

Dominique Francoz EUROSTAT [email protected] Eurostat

Hans-Eduard Hauser EUROSTAT [email protected] Eurostat

Eeva Hamunen Statistics Finland [email protected] Finland

Jukka Pakola Statistics Finland [email protected] Finland

Pierre Teillet INSEE [email protected] France

Pierrette Schuhl INSEE [email protected] France

Sylvie Mabile INSEE [email protected] France

Olivier Haag INSEE [email protected] France

Bernd Waldmüller Statistisches Bundesamt – Destatis [email protected] Germany

Stefan Hauf Statistisches Bundesamt – Destatis [email protected] Germany

Mária Forgon Hungarian Central Statistical Office [email protected] Hungary

Lilla Sarkadi Hungarian Central Statistical Office [email protected] Hungary

Aija Žīgure CSB of Latvia [email protected] Latvia

Kaspars Misāns CSB of Latvia [email protected] Latvia

Ilze Skujeniece CSB of Latvia [email protected] Latvia

Dzintra Bērziņa CSB of Latvia [email protected] Latvia

Evita Kupče CSB of Latvia [email protected] Latvia

Zane Bondare CSB of Latvia [email protected] Latvia

Sarmīte Prole CSB of Latvia [email protected] Latvia

Svetlana Jesiļevska CSB of Latvia [email protected] Latvia

Sandris Matīsiņš CSB of Latvia [email protected] Latvia

Arvīds Uibo CSB of Latvia [email protected] Latvia

Inga Malašenko CSB of Latvia [email protected] Latvia

Inga Oksentjuka CSB of Latvia [email protected] Latvia

Līga Pranča CSB of Latvia [email protected] Latvia



Laine Liepiņa CSB of Latvia [email protected] Latvia

Mārīte Baranova CSB of Latvia [email protected] Latvia

Dace Kravale CSB of Latvia [email protected] Latvia

Dana Zariņa CSB of Latvia [email protected] Latvia

Dace Baune CSB of Latvia [email protected] Latvia

Richard McMahon CSO Ireland [email protected] Ireland

Donal King CSO Ireland [email protected] Ireland

Carlo De Gregorio ISTAT [email protected] Italy

Giuseppe Garofalo ISTAT [email protected] Italy

Monica Consalvi ISTAT [email protected] Italy

Dario Ercolani ISTAT [email protected] Italy

Danila Filipponi ISTAT [email protected] Italy

Rob van der Holst Statistics Netherlands [email protected] Netherlands

Henk Verduin Statistics Netherlands [email protected] Netherlands

Mirosław Stępień Central Statistical Office [email protected] Poland

Julita Świętochowska Central Statistical Office [email protected] Poland

Maria Luisa Andrez Augusto

INE [email protected] Portugal

Gabriela Dusikova Statistical Office of the Slovak Republic [email protected] Slovak Republic

Marta Mravcova Statistical Office of the Slovak Republic

[email protected] Slovak Republic

Melita Matek Statistical Office of the Republic of Slovenia [email protected] Slovenia

Maria Teresa Garcia BANCO DE ESPAÑA [email protected] Spain

Ana Luisa Solera INSTITUTO NACIONAL DE ESTADÍSTICA [email protected] Spain

Ebba Hartzell Statistics Sweden [email protected] Sweden

Anders Jäder Statistics Sweden [email protected] Sweden

Stephen Curtis Office for National Statistics [email protected] United Kingdom

Alison Pritchard Office for National Statistics [email protected] United Kingdom

Andrew Allen Office for National Statistics [email protected] United Kingdom

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