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Session 32

Innovative Practices in Economic Statistics

5 June 2026
09:00 – 10:15
ŠIBENIK III

Presentation title
Multiregional models and Trade in Value Added: developing essential tools for a complex global economy
Globalization has radically transformed how goods and services are produced and exchanged, giving rise to increasingly fragmented and interconnected global value chains (GVCs).

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This complexity challenges traditional trade statistics, which often fail to capture the full economic impact of international production networks and geopolitical changes. To address this gap, INE-Spain has launched the Panel of International Trade in Value Added (TiVA) Indicators, primarily designed as a visualization tool to present these methodologically complex indicators clearly and accessibly for the Spanish economy.

These indicators quantify Spain’s integration into global production systems by tracing how value added is created, distributed, and exchanged across countries and sectors. They provide a powerful tool for analyzing economic, social, and environmental interdependencies, allowing for more accurate assessments of supply chain vulnerabilities, geopolitical risks, and economic shock transmission. Built using national accounts data and based on FIGARO, the multi-regional input-output model developed by Eurostat and the European Commission’s Joint Research Center, the panel exemplifies international cooperation and optimal use of European statistical infrastructure.

The TiVA framework also enables simulation of the macroeconomic effects of tariffs or other geopolitical shocks on domestic GDP. By applying targeted tariff scenarios to specific products, sectors, or trade partners, the model captures both the direct impact on affected industries and indirect ripple effects across upstream and downstream chains. The results demonstrate how disturbances propagate through GVCs, reshaping value-added generation across national economies. These findings highlight the importance for policymakers of considering complex interdependencies when designing trade strategies—fostering more resilient, competitive, and strategically autonomous economies in an uncertain global environment.

Main author / Presenter
Juan Cervigón, David Calvete
National Statistics Institute

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Juan Cervigón is Head of Unit in the Large Cases Unit Division at the National Statistics Institute of Spain (INE), where he has led work on data dissemination and globalization statistics. He has extensive experience in official statistics, representing Spain in international task forces and expert groups related to international trade and globalization. Juan holds a Degree in Mathematics from the University of Valencia and a PhD in Economics from Universidad Autónoma de Madrid. Alongside his public-sector role, he brings over 25 years of private-sector experience, including senior executive positions in banking, real estate, and renewable energy, and has served as Vice President of the Spanish Wind Association. He is also an experienced academic lecturer, teaching statistics, machine learning, and sampling methods in English at Universidad Carlos III de Madrid and previously at Instituto de Empresa. His recent research focuses on globalization, multinational enterprises, and intangible assets in economic statistics.

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Presentation title
Keeping the systems of National Accounts relevant: quality considerations
As economies and business models evolve and new features appear, the systems of National Accounts – the measurement frameworks of the size and dynamics of national economies – need to be updated to keep the pace and remain relevant.

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In March 2025, the UN Statistical Commission endorsed the 2025 System of National Accounts (2025 SNA) as the new global standard for the compilation of national accounts statistics worldwide. Compared to the previous 2008 SNA, the revised standard includes elements of the digital economy, considers the effects of economic globalisation and gives prominence to the impact of economic activities on the depletion of natural resources.

Following the SNA, Eurostat is coordinating the update of the 2010 European System of National and Regional Accounts (ESA 2010), to align it to the 2025 SNA. This update is needed to enhance the relevance of the European national accounts standard and to preserve the international comparability with non-EU economies that will follow the 2025 SNA. As usual methodological improvements will be associated with a review of compulsory transmissions requirements to better serve EU policy uses. Therefore, further improvements of national accounts with respect to different quality dimensions, such as notably relevance, timeliness, comparability, and coherence will be considered.

Implementing the changes in the national accounts systems is not straightforward, thus concerns about the quality of the “new” estimates inevitably emerge. In the context of the update of ESA 2010, the European Statistical System is addressing these practical implementation issues, in particular regarding the recording of Data as an asset and Natural resources.

This presentation will illustrate the identified issues and possible solutions that Eurostat and NSIs are considering.

Main author / Presenter
Nicola Massarelli
Eurostat

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Nicola Massarelli works for Eurostat, where he leads the team on National Accounts methodology. He has been closely involved in the preparation of the 2025 System of National Accounts and coordinates the ongoing update of the European System of Accounts (ESA 2010).

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Presentation title
The Role of Large Cases Units in Assuring Data Quality
The rise of Global Value Chains (GVCs), primarily driven by large and complex Multinational Enterprises (MNEs), has introduced signi!cant challenges for o"cial statistics.

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The fragmentation of production across multiple countries and continents makes it increasingly di"cult to measure national economic activity accurately. Large and complex MNEs account for a substantial share of most national economies. In Denmark, for example, the !ve largest MNEs alone contribute 15% of total value added, 30% of total exports, and nearly 80% of global production. Consequently, inaccurate reporting from such large MNEs can severely compromise the quality of business and trade statistics and, by extension, National Accounts.To address these challenges, many National Statistical Institutes (NSIs) have established Large Cases Units (LCUs) - specialized teams dedicated to understanding the complex structures and operations of large MNEs and ensuring data quality and consistency across relevant statistical domains. In recent years, the creation of LCUs has been actively encouraged and supported by international entities such as the United Nations and Eurostat.This paper examines the role of LCUs in ensuring high-quality o"cial statistics through the case of the Danish LCU, established by Statistics Denmark in 2018. It explores key questions: (1) How is the LCU organized and integrated into existing production processes? (2) What innovative practices have been introduced? (3) How does it create value for internal and external stakeholders? (4) How does it enhance the quality of involved statistical domains? (5) What were – and remain – the main challenges for success? While the organization and functioning of LCUs vary considerably across countries, the Danish LCU encompasses several typical LCU functions: pro!ling, data consistency analysis, data compilation and consolidation, as well as communication with large MNEs. The paper thus concludes by discussing lessons learned by the Danish LCU team since its establishment and how these insights may be applied to LCUs in other countries performing similar tasks.

Main author / Presenter
Jon Mortensen
Statistics Denmark

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Mr. Jon Mortensen is Chief Advisor in Statistics Denmark’s Large Cases Unit. With over a decade of experience analyzing the impact of large and complex enterprises on official statistics, he serves as Denmark’s National Coordinator in Eurostat’s Expert Network on Multinational Enterprises (MNEnet). Jon’s expertise spans international trade statistics, balance of payments, and structural and short term business statistics. Before joining Statistics Denmark, he worked with the United Nations Development Programme in Thailand, the Danish Institute for International Studies, Copenhagen Business School, and the Danish Energy Agency. He holds a PhD in Global Health and Trade.

Presentation title
A proof of concept for reengineering data collection systems for multinational enterprises through a Large Cases Unit (LCU) approach
In an increasingly interconnected global economy, national statistical systems face mounting challenges in accurately measuring value added within domestic borders, especially amid complex global production arrangements.

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The growing intricacy of global value chains, the prominence of intangible assets, and the evolving structures of multinational enterprises (MNEs) have exposed significant limitations in traditional statistical frameworks. Conventional data sources — such as customs records and trade-in-services surveys — are no longer sufficient to capture modern production models like factoryless manufacturing, merchanting, processing abroad, and transactions involving intellectual property products.

In response, INE-Spain established a Large Cases Unit (LCU) in 2022 to address these gaps through an integrated, enterprise-centered approach. The LCU combines multiple administrative and statistical sources with direct engagement with large enterprise groups. Its work has uncovered structural inconsistencies in the current statistical system, highlighting the urgent need for a shift in data collection strategies.

Building on these insights, INE-Spain is pioneering an innovative data collection model centered on large enterprise groups operating in the national economy. At the heart of this initiative is a centralized reporting framework through which entire corporate groups submit harmonized data for all their subsidiaries via a single access point. As part of this effort, a proof of concept is carried out with selected multinational enterprises, implementing a fully digital, API REST–based reporting system using standardized JSON data structures for the automated transmission of firm-level information. This prototype illustrates the feasibility of secure, machine-readable exchanges between enterprises and statistical authorities, reinforcing the potential of a modernized, technology-driven approach.

The process leverages advanced technologies and standards for direct access to business information and is reinforced by structured, high-level dialogue between LCU experts and corporate leadership. This approach also opens the door to a new relationship with businesses, where official statistics can offer tailored services linked to companies’ own data, enhancing mutual value and trust.

Main author / Presenter
Sixto Muriel, Jorge Novalbos
National Statistics Institute

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Sixto Muriel is Director of the Large Cases Unit at the INE-Spain, leading strategic engagement with major multinational enterprises to improve the statistical recording of globalization. His work focuses on enhancing data quality in National Accounts, Balance of Payments, and globalization indicators. He has over 20 years of experience in official statistics and has held senior positions at INE, including Deputy Director of National Accounts and Deputy Director of Population Statistics. He has also worked in labour statistics, social statistics, and survey methodology. Sixto contributes to international statistical cooperation through expert groups at OECD, Eurostat, United Nations and IMF. He is an Adjunct Professor of Statistics at Universidad Carlos III de Madrid. He holds degrees in Mathematics and Economics and a Master’s in Public Management and Leadership. Jorge Novalbos is a Senior Statistician of the State and works in the “Large Cases Unit” Division at the INE. He holds a degree in Electrical Industrial Engineering and a Master’s in Industrial Engineering, both obtained from the Universidad de Castilla-La Mancha. His main responsibilities include the development and implementation of new indicators for measuring global trade, as well as the supervision and monitoring of the statistical register of globalization.

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