Mapping the Structure of Global Production and Trade

Global trade is structured by production networks — intricate webs of input-output relationships that determine how economic shocks propagate across products and countries. Traditional trade statistics capture bilateral flows but miss the underlying network structure. We map it.

Our flagship AIPNET dataset uses generative AI to construct a production network over 5,000+ product nodes, where directed edges represent input-output relationships. The network reveals which products are critical intermediates, which countries occupy central network positions, and how these positions have shifted during the 21st century.

We have used this network to study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar, demonstrating how trade disruptions propagate through the network in predictable ways. This research informs governments designing on-shoring and industrial policy, investors assessing supply chain risk, and international organisations tracking structural change in the global economy.