1. Eurostat-ECE Seminar on Business Registers June 21-22, 2005
The MNE project
Eurostat-ECE Seminar on Business Registers
June 21-22, 2005

2. Background
The Multinational Enterprise Project (MNE) arose from the session on globalization at the June 10-12, 2003 Conference of European Statisticians in Geneva
Objective: to identify areas where the measurement of the activities of multinational enterprises could be improved
Assess feasibility of having MNEs report in an integrated fashion to several national statistical offices (NSOs), taking into account the confidentiality legislation governing the respective NSOs

3. Project structure and governance
Five participating countries
Canada, France, Italy, The Netherlands, United Kingdom
Bureau of the Conference of European Statisticians (CES) acted as the steering committee
Roundtable on Business Survey Frames has served as a sounding board

4. Study hypotheses Areas where improvements might be identified
the description of the structure of the MNE in the registers and other files of the NSOs
the measurement of important economic and financial variables relevant to national accounting
the coordination of measurement activities between NSOs

5. Study design Common questionnaire Integrated collection
Four variables: Sales, operating profits/loss, capital expenditures, number of employees
List of legal entities covered by data supplied
Integrated collection
Home country NSO collects from MNE on behalf of all NSOs and shares data with them
Starting point is data from public annual report for global entity, split by MNE, by country

12. Analysis
Compare data received from MNEs as part of study (directly or by data sharing from other NSO) to data obtained in regular statistical program
Provide measures of “nearness” of both sources

13. Reactions of MNEs
Each participating country contacted a minimum of 3 MNEs
MNE had to have at least one production facility in each of the five countries
11 MNEs agreed to participate
8 had operations in all 5 countries
3 had operations in 4 of the 5 countries
All agreed to data sharing waiver
Coordinated approach operationally feasible

14. Analysis results Structure Variables
Counts of legal entities by MNE, by NSO, common
Variables
Measure of nearness
Difference= ((MNE response – Internal results)/MNE response)*100
If difference < % then the code was set to “-2”
If %<= difference < -5 % then the code was set to “-1”
If % <= difference <= 5 % then the code was set to “0”
If % < difference <= 10 % then the code was set to “1”
If % < difference then the code was set to “2”

15. Legal structure of MNEs

16. Legal structure of MNEs
In all, there are 50 data points for which comparisons were possible
22 exactly the same count of legal entities
28 differences
20 small differences (1 or 2 legal entities)
8 large differences
For 6 of these 8, problem lies with the structure of MNEs in their home countries
Legal structures in home countries are larger
Errors are therefore potentially larger
Getting the home country structure right is therefore key to the overall measurement of the MNE

17. Sales
Of the 45 measurements that are available, 20 are within 10% of each other and 25 are more that 10% apart.
Reasons
differences in the structure of the MNE reported in the previous section
MNEs were not able, or willing, to provide intra-enterprise sales between geographic segments

18. Operating profits or losses
Only 19 measurements for which it is possible to make comparisons, out of a possible 52
Only variable that was considered confidential by the MNEs
Of the 19 measurements, 5 are within 10% of each other and 14 are more that 10% apart

19. Capitalized expenditures
32 observations for which comparisons are possible
13 are within 10% of each other and 19 that are more than 10% apart
Often, no data against which to compare in regular statistical program because units are too small, or surveyed at establishment level

20. Total number of employees
46 observations for which comparisons can be made
23 within 10% of each other and 23 that are more than 10% apart
Most accurately measured variable

21. Resident vs foreign affiliates
Overall, the data obtained for resident MNEs directly by NSOs tend to be more comparable to internal sources than the data obtained for foreign affiliates of MNEs through data sharing with other NSOs

22. Conclusions
Data collected in a coordinated fashion from the MNEs for this study provided results that were different from the data collected by survey or administrative instruments in the regular programs of the National Statistics Offices
28% within 10%
36% more than 10% divergent
36% cannot be compared for a variety of reasons

23. Conclusions Employment variable most accurately measured
Followed closely by the sales variable
Capitalized expenditures were less well measured than either
Operating earnings variable was the most poorly reported and the least accurately measured

24. Conclusions
A centrally coordinated collection approach, such as used for this study, might elicit a defensive reaction by MNEs that is not encountered when each national component is approached individually
The centrally coordinated approach to collection may in fact result in less data being collected from the MNEs overall than independent approaches to each national component

25. Recommendations Terminate study in its present form at this point
Work be continued under the auspices of the Eurostat project on the creation of a European register of enterprise groups, taking into account specific learnings and experiences from the project