We develop a method to recover a granular, product-level input-output structure from firm-level customs transactions. Building on an association-rule mining algorithm, we exploit systematic co-occurrences between what firms import and what they export to infer input use in production.
- Speaker
- Date
- Tuesday 22 Sep 2026, 11:30 - 12:30
- Type
- Seminar
- Room
- 1.09
- Building
- Langeveld Building
with Antonio Vicencio Betanzo, Mingzhi Xu and Yawen Zheng
Applying the approach to data from several countries, we show that the inferred mappings closely resemble conventional input-output relationships and perform well in external validation exercises. We illustrate the value of these linkages in two applications. First, following China's WTO entry, export growth is accompanied by a pronounced rise in imports of the inputs our mapping associates with those exports. Second, in the 2018-2019 U.S.-China trade war, tariffed Chinese exports to the United States contract, and the shock propagates upstream: China's imports of exposed inputs fall, and third-country suppliers that specialize in those inputs experience the declines in their exports to China, especially if China is a key destination market.
Overall, simple pattern recognition tools and micro-level trade data can deliver high-resolution input–output linkages that improve exposure measures and empirical assessments of supply-chain propagation.
Registration for bilateral, lunch or dinner
Lunch will be provided. If you would like to meet the guest speaker for a bilateral, join for lunch or dinner, then please register by filling in the registration form.
