Updated every year by DG GROW’s Chief Economist Team, this page provides the result of a matching performed between the account holders in the EU Transaction Log (EUTL) and Moody’s Orbis database. Thanks to the company identification codes, the user can easily retrieve additional data from Orbis, thus obtaining a firm-level dataset with both climate (e.g., yearly emissions, allocation of free allowances on the EU’s carbon market, etc.) and financial metrics (e.g., turnover, employment, etc.).
This matching is a follow-up to Simon Letout’s work under a joint JRC/DG GROW project. The relevant company identification codes are published in agreement with Moody’s.
Dataset
See the result of the matching (Excel file).
How to cite: European Commission, DG GROW Chief Economist Team (2024): EUTL-Orbis matching dataset [Dataset].
Matching procedure
The matching procedure relies on natural language processing (NLP) techniques, summarised below.
See the full matching procedure and code used (written in Python).
Step 1: Cleaning the variables
Step 2: NLP matching on firm names and legal identifiers
Step 3: Similarity measure on postcodes
Step 4: Filtering potential matches, resulting in the vast majority of firms having a single dominant match option
How to cite: Cameron, A. & Ho, V. (2024): Matching the EU Transaction Log and ORBIS: A Natural Language Processing approach.
Previous matchings
- 2021 matching (done with EUTL data from 2020) – this matching used this methodology under a joint JRC/DG GROW project.