New Data and Tools to Track and Analyse International Trade in a Changing World, 8 September 2026, online

Published on 4th of August 2026

International trade has undergone major disruptions to trade flows in recent years and significant shifts in policy, while trade continues to evolve as global value chains in response to changing demand and production patterns.

This conference aims to bring together a range of recent research using new sources of data and modelling tools to track, predict and analyse these developments.

14h - Opening remarks

14h05 – Keynote speech - [trade research, new data and tools]

Professor Simon Evenett, IMD Business School

Session 1 – Using new sources of data to track trade

14h40 Monitoring trade by commodity using big data
Graham Pilgrim, Yann Dorville & Annabelle Mourougane

15h00    Trade under Tensions: Insights from Media-Reported Bilateral Events"
CEPII Working Paper 2026- 02, Nathan Chevalier, Matthieu Crozet, Charlotte Emlinger & Daniel Mirza (2026 )
   Trade under Tensions: Insights from Media-Reported Bilateral Events

15h20   Automatic Product Classification in International Trade: Machine Learning and Large Language Models
Ignacio Marra de Artiñano, Franco Riottini Depetris & Christian Volpe Martincus (2025)
https://onlinelibrary.wiley.com/doi/10.1111/roie.70009

15h40 Bilateral Conflict Risk and Trade: Military Wars, Trade Wars, and Diplomatic Noise
Joshua Aizenman, Rodolphe Desbordes & Jamel Saadaoui (2026)
https://www.nber.org/papers/w35077

16h00 - Short break

Session 2 – Applying new modelling approaches to analyse and predict trade

16h10 New insights on services export competitiveness: drivers of comparative advantage and the granularity hypothesis across sectors and modes of supply
Matteo Fiorini and Andrew Green

16h30 The heterogeneous impact of the EU-Canada agreement with causal machine learning
Lionel Fontagné, Francesca Micocci & Armando Rung
The heterogeneous impact of the EU-Canada agreement with causal machine learning

16h50 Nowcasting World Trade with Machine Learning: A Three-Step Approach.
ECB Working Paper No. 2023/2836 – Menzie Chinn, Baptiste Meunier & Sebastian Stumpner
Nowcasting world trade with machine learning: a three-step approach

17h10 Machine learning and economic forecasting: The role of international trade networks
Thiago Christiano Silva, Paulo Victor Berri Wilhelm & Diego R. Amancio (2024)
https://www.sciencedirect.com/science/article/pii/S0378437124004862

17h30 - Closing remarks

Organizing and Scientific Committees:
Sebastian Barnes (OCDE), Jean-Charles Bricongne (Banque de France), Jean-Brieux Delbos (Banque de France), Jérôme Coffinet (Banque de France), Annabelle Mourougane (OCDE) and members of the GVE IA DS and OECD Innovation LAB.