MNE-thing is possible: New OECD-UNSD data release strengthens open evidence on multinational enterprises
By Graham Pilgrim (graham.pilgrim@oecd.org) and Eugene Chang (eugene.chang@oecd.org), OECD Statistics and Data Directorate; Shirly Ang (angs@un.org) and Julian Chow (chowj@un.org), UN Statistics Division
Why do multinational enterprises matter?
Multinational enterprises (MNEs) play an increasingly central role in the global economy. They influence trade patterns, investment flows, and production across countries, yet their complex organisational structures can be difficult to map out using traditional statistical sources. The Multinational Enterprise Information Platform (MEIP) was developed to help address this challenge by offering a clearer view of large MNEs and the cross-border networks through which they operate.
Strengthening the evidence base on the structure and activities of multinational enterprises
MEIP consolidates publicly available data on MNEs in a single, structured environment. This includes data on subsidiaries, ownership links, digital presence, and major corporate events. By combining these, users can gain a more coherent understanding of how MNEs are organised and how they evolve over time. By making complex corporate relationships more transparent, MEIP supports analytical work in areas such as business dynamics and productivity, profit shifting and taxation or international trade and investment, and helps inform policymaking.
The platform gathers information on the 500 largest multinational enterprises and their geographic footprint with interactive tools to examine ownership structures and corporate networks in greater detail. MEIP also includes a digital register that documents companies’ online presence, and a monitoring tool that tracks significant structural events – including mergers, acquisitions, and reorganisations – helping users follow how multinational enterprises shift through time.
Introducing MNE Indicators in MEIP
For the first time, the 2024 release of MEIP incorporates information on companies’ employees, revenue, net profit and R&D. These data are collected through a methodology which compares and prioritises from hybrid sources, including company filings and data extracted from annual reports using AI tools. This addition strengthens the platform by offering context on MNE size, performance and investment in innovation.
In 2024, the global corporate landscape remained concentrated in the Americas, and the United States in particular, and Europe, which together host 74% of the top 500 MNE headquarters and their revenue, compared to 24% in Asia. By sector, technology and healthcare dominate research and development spending, making up about 80% of total R&D among the top 500 MNEs. At the same time, the technology and financial sectors generate around 55% of total net profit, highlighting their global corporate significance.
Across sectors, revenue per employee is highest for energy and utilities sectors, followed by healthcare and basic materials. R&D expenditure per employee is most concentrated in healthcare and technology sectors, whilst net profit per employee is greatest in utility and energy sectors.
MNEs in the news and the role of AI
Numerous elections, events, and megatrends made 2025 an eventful year. Our updated news database uses GDELT – a database of almost 50 million worldwide news articles using text analytics to extract information relating to companies, locations, individuals and topics – to map news articles to the top 500 MNEs. In total, almost 3 million articles mention one of our 500 MNEs explicitly in 2025, roughly 6% of the articles in GDELT. Combined, these MNEs receive more mentions than any individual country.
Artificial Intelligence was among the most prominent themes of 2025: around 1 in 20 articles mentioned AI, and 29% of these articles also referred to one of the top 500 MNEs, demonstrating their important roles in the development and deployment of AI. This represents a shift from 2024, when only 1 in 30 articles mentioned AI, but a third mentioned one of the top 500 MNEs. The change illustrates the growing global importance of AI and the broadening relevance of AI-related topics beyond the largest firms.
This news database also allows users to examine individual companies, including periods when media attention spikes in response to major corporate events such as mergers, acquisitions, or controversy. One such example is Abb Ltd, which announced it was going to sell its robotics division to Softbank in October 2025. This transaction represents a significant investment by a Japanese Headquartered company in a division which was previously held by a company headquartered in Switzerland.
What’s new in this MEIP release and what’s next
- New MNE Indicators add-in
The introduction of MNE Indicators – covering employees, revenue, net profit and R&D – represents a major expansion of the data available in MEIP. These indicators provide a more complete view of the size, performance and R&D spending of the largest multinational enterprises.
- New data sources
The Multinational Enterprise Information Platform (MEIP) is a robust foundation on which data can be linked and new insights built. The current MEIP release introduces several new data sources beyond the new MNE Indicators, that strengthen the platform’s content, usability and analytical potential.
This year we integrated a database of over 25 million company names from the S&P Data Unlocked Initiative. Matching companies to this business database unlocks new potential for MEIP as users are now able to use identifiers from S&P Capital IQ to complement the dataset or further analysis.
- New data pipeline for data extraction
Furthermore, we developed new methods to extract metadata from the millions of websites covered within the CommonCrawl to uncover more relationships. By analysing website scripts the platform now considers variables such as IDs for tools such as Google Analytics and website ownership identifiers to create more links than were previously available.
- Pilot use of AI-based tools
In addition, we have begun the pilot use of AI-based tools in selected stages of the project. These tools are being used to support tasks such as data integration and validation. While still experimental, these tools have helped improve consistency and efficiency in handling large volumes of public information.
Looking ahead, OECD and UNSD will continue to develop the platform and associated tools with a view to making them available. This will support national statistics offices and analysts in identifying parent-subsidiary information across borders and supplementing their national statistical business registers with additional data. These tools have the potential to support specialist Large Case Units in NSOs which are focused on ensuring global consistency with statistical standards and reducing data discrepancies at an international level.