CSH Workshop: “Firm-level supply network data for policy making”

The ongoing digitalization of businesses and governments has generated new, fine-grained
administrative data that can be used to reconstruct the supply chain networks of entire
countries at the firm level. In this way, it is possible to model the world economy at a level of
detail never before seen, creating entirely new ways to manage supply chains that are relevant
to policymakers in central banking (for example, allowing one to better understand inflation
and assess financial stability), taxation (to stop VAT and customs fraud), national security (to
secure supply chains for critical goods and services), the green transition (to reconfigure
supply chains, and to improve carbon accounting), national statistics (to improve national
accounting), and industrial policy (to engineer future economic growth paths).

In tandem, recent scientific research has developed new tools and methods to better
understand and manage these highly complex supply chain systems. However, despite the
significant potential of these datasets, current scientific research and policy applications are
hindered by “data silos”. For example, country-level supply chain maps that are constructed
by VAT data could, in principle, be mapped onto imports and exports, allowing entire world
trade networks to be constructed, and global supply chain disruption scenarios to be
modeled. To overcome data silos and use the advantages across countries, national data
owners, policymakers, and scientists need to come together to map the extent of what is
possible, prioritize requirements and create roadmaps.

In this workshop we will bring together scientists and policymakers to discuss:

• the vision of mapping and real-time monitoring of the global supply network,
• how existing models can improve policymaking,
• current policy challenges that these new tools can help tackle,
• ways forward for collecting, standardizing, and sharing data, models, and results.

Agenda:

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Organizer:

Alexandra Brintrup (University of Cambridge)

Christian Diem (CSH)

François Lafond (INET/Oxford Martin School)

Anton Pichler (CSH)

Tobias Thomas (Statistik Austria)

Stefan Thurner (CSH)