dr. Sean Telg

Sean's research focuses on modeling highly non-linear data features such as speculative bubbles and asymmetric cycles, which are often disruptive to economic and financial markets. Therefore, he develops tools that are able to detect and forecast such events and these insights can be used from a risk management perspective.

His research is mainly relevant in the fields of macroeconomics and financial econometrics. The developed methodology can be used by central banks for policy decisions (public sector) and investors to mitigate risks (private sector). 

Sean's work mainly studies the mixed causal-noncausal autoregressive model, but extends beyond with topics on semiparametric panel approaches and observation-driven models. He also works on enriching existing econometric models with methods from data science and generative AI. This encompasses natural language processing, flow matching and diffusion models.

Sean teaches various courses on econometrics and data science on the bachelor and master level. Since September 2021, he is also Programme Coordinator of the BSc programmes in Econometrics and Operations Research as well as Econometrics and Data Science at the School of Business and Economics. Previously, he has also been Programme Coordinator of the MSc Econometrics and Operations Research (2021-2022) and Coordinator of the Minor Applied Econometrics: A Big Data Experience for All (2021-2024). As coordinator, Sean has developed preparation websites for both the BSc and the minor programmes, which can be accessed here and here, respectively.

Moreover, he is part of the SBE's Educators' Collective, which is a team of faculty members passionate about teaching and education innovation that provide advice to the Faculty Board.

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