Call for Papers
About the Economic Data Science Society (EDSS)
The rapid development of artificial intelligence (including generative AI) and the availability of machine learning techniques have combined to create opportunities and challenges in the economy. Concurrently, the availability of alternative and non-traditional data has made it possible for economists to deepen their analysis and understanding of economic activity. Taken together, these represent a broad set of topics at the intersection of data science and economics that are being actively explored by economists, researchers, and business leaders.
In October 2025, experts from public, private and academic entities convened to officially create the Economic Data Science Society (EDSS). The goal of the Society is to promote the development of data science techniques to understand and solve economic problems, catalyzing fruitful projects at the crossroads of data science and economics and enabling cooperation across entities.
This Society, structured under a non-profit association statute, will have a dedicated website, storage capacities for sharing data, code and papers, and will also organize events, propose tools to help economists and data-scientists (for example to search economic conferences, such as ConfWatcher (https://confwatcher.b2ideas.eu), which has already received more than 4000 unique visits worldwide, and will be extended to other domains).
There are already members from renowned institutions (IMF, European Commission, OECD, the Fed, the ECB, Banque de France, Bank of England, University College London, CREST/Polytechnique, NYU Abu Dhabi, Kayrros, Quantcube Technology…) and new members from public, academic (including students) and private institutions willing to cooperate are welcome to join.
The Inaugural EDSS Conference
The EDSS Conference will take place at the Banque de France (31 rue Croix des Petits Champs, 75001 Paris, France) on July 9th and 10th, 2026.
The conference will have parallel sessions that are open to members from public, private and academic institutions, including students. This event aims to drive interdisciplinary discussions and work that fosters innovative research and informs better decision-making in both academic and policy environments.
Call for Papers
We invite you to submit empirical or theoretical work focused on (but not limited to):
1) Methods for macroeconomic & policy analysis (forecasting, inference, simulation)
- Intersections of econometrics and AI/ML, including forecasting applications
- Machine learning for central banking / monetary policy and policy evaluation
- Machine learning, agent-based models, possibly with reinforcement learning, and complex-systems approaches for economic dynamics and simulation, scenario design and stress testing
2) LLMs & generative / agentic / multimodal AI for economic analysis
- LLM methodology and applications, including forecasting/nowcasting
- Explainability, robustness, and decisions/behaviours of LLMs
- Applications of generative, agentic, and multimodal AI in economic analysis
3) Measuring and tracking the economy with novel / alternative data
- Web-scraping applied to economics (e.g., housing, labour markets, prices of goods and services)
- Tracking economic activity with satellite data
- Use of large-scale or novel datasets for economic measurement and monitoring
4) Text-as-data: narratives, institutions, and law
- Narrative extractions in economics
- Law, economics, and text analysis
5) Cross-cutting (relevant to all categories):
- Synthetic data generation and its implications for research and policy
- Risks and governance questions around AI adoption in the economy
- Bridges between econometrics and machine learning/Deep-Learning/AI, especially to balance accuracy vs. overfitting & epistemic risk
- Advanced learning unusually applied to economics, like self-supervised/transfer learning/foundation models
Hands-on training sessions are also planned for students and professionals, covering themes such as, but not limited to, satellite data or web-scraping used for the tracking of economic evolutions.
Submissions for presentation at this workshop should be sent to edss@banque-france.fr no later than 30 April 2026. Full papers are preferred but extended abstracts may also be considered.
Authors of accepted papers will be contacted by mid-May. The conference will be in-person only. The fees will be 200€ for the two days, except for students for which the fees will be 30€ for the two days.
For members of the EDSS, the fees will be reduced to 150€ for the two days for non-students and 20€ for students.
A separate social event will be organized on 9th July evening in a restaurant in Paris (location and tariff to be confirmed)
For any enquiry, please contact edss@banque-france.fr. We look forward to your contributions!
Confirmed Keynote Speakers: Jesús Fernández-Villaverde (Professor of Economics at University of Pennsylvania), Stephen Hansen (Professor of Economics at University College London), Isaiah Hull (Co-Founder & CTO at FirstQFM, & Research Fellow at Rethinc Labs (UNC Chapel Hill)).
Organizing and Scientific Committees: Silvia Albrizio (IMF), Douglas Araujo (Central Bank of Brazil), Erik Balodis (Bank of Canada), Thomas Berthelot (Banque de France), Jean-Charles Bricongne (Banque de France), Marcos Centurion (University of Grenoble), Jérôme Coffinet (Banque de France), Maximilian Freier (ECB), Andreas Joseph (Bank of England), Rabab Khatib (Banque de France), Roland Lubrano (Banque de France), Marwan Menaa (Banque de France), Juan Mora Sanguinetti (Bank of Spain), Anna Simoni (CREST/Polytechnique), Leif Anders Thorsrud (BI Norwegian Business School) and Pablo Winant (ESCP).
