Registers and MNEs in business statistics
Sector: Government • Location: Sweden
Source: EU Funding & Tenders Portal
Area 1 of the action on “European profiling on the structure of the Top tier MNE groups” The intention with this project is to further increase our knowledge and understanding of the European Profiling Methodology. We plan to take further steps in this area of work by doing European profiling on the structure of the Top tier MNEs focusing on updating the legal unit (LEU), the control relationships
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Area 1 of the action on “European profiling on the structure of the Top tier MNE groups” The intention with this project is to further increase our knowledge and understanding of the European Profiling Methodology. We plan to take further steps in this area of work by doing European profiling on the structure of the Top tier MNEs focusing on updating the legal unit (LEU), the control relationships (REL) and the global enterprise groups (GEG) data. We will use the Profiling forum on Wiki to exchange information about the MNEs (like mergers and splits, change of GDC etc.). The seminar and webinars will give us and the other participating countries opportunities to discuss issues raised and thus improve harmonisation of methods and procedures. Area 3 of the action on “Implementation of the NACE Rev.2.1 in the Business Registers” The intention with this project is to create and implement an automatic re-coding algorithm for the transition to NACE Rev.2.1. This will be performed through an ensemble of previous state of the art methods and new methods, e.g., machine learning, to create a well-performing algorithm. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
