On January 31, 2025, the SCOR-Foundation held a workshop on machine learning methods for econometrics at SCOR’s offices in Paris, with the support of the Toulouse School of Economics and the SCOR-TSE “Risk Markets & Value Creation” Chair.
Aimed at actuaries and data scientists, the workshop was led by Stéphane Villeneuve and Nouri Meddahi from the Toulouse School of Economics (TSE), with contributions from Da Cheng Xiu (University of Chicago Booth School of Business), René Garcia (TSE and Université de Montréal), and Christian Gouriereux (TSE & University of Toronto).
The workshop provided a unique introduction to the primary machine learning techniques that are increasingly being employed in econometrics. It explored how these methods can be applied to concrete risk-sharing problems and discussed their advantages over conventional econometric methods. It also addressed the potential pitfalls associated with using these methods, such as overfitting, interpretability, and the risk of spurious correlations.
This event gave participants a deeper understanding of the strengths and limitations of machine learning in econometrics, equipping them to critically assess machine learning models and effectively apply these to their own research.
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Go to the SCOR-TSE Chair page
