about me
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About me
I am an Econometrician who works on Economics and Forecasting, and more recently on their interaction with AI. I am (full) Professor at ESSEC Business School, in the greater Paris area and codirector of the ESSEC Metalab for Data, Technology & Society.
I am also a member of the OECD network of AI experts and of the Executive Committee of the Society for Nonlinear Dynamics and Econometrics (SNDE), I am a former Head of the Department of Information Systems, Decision Sciences & Statistics at ESSEC (2020-22).
On the research side, as Economics cannot be a proper experimental science (contrary to Physics and Natural Sciences, economists cannot and will not conduct large scale experiments on economies), if we have any hope for it ever to become a proper "science" rather than a set of opinions, we need to be able to refute and reject wrong theories.
This is the purpose of econometricians: we develop tools to judge economic theories by their empirical relevance. The lack of experimentation implies that we have to resort to historical data and see what laws and principles are permanent and hidden. This is in fact a form of data sciences developed specifically with social sciences in mind.
In this context my interests have also been recently about the interplay between Data Sciences and Social Sciences since both are ultimately about understanding human behavior and how we can have a progressive modeling strategy, i.e. truly moving towards science. My specific focus of interest lies in dynamic phenomena, their models and the principles of dependence over time and forecasting.
Official short bio
Guillaume CHEVILLON is Professor at ESSEC Business School, and Academic CoDirector of the ESSEC Metalab for Data, Technology & Society. He has also been, since its creation in 2015, codirector of the ESSEC|CentraleSupélec Master in Data Sciences & Business Analytics, among the top ranked such programs in Europe (#1 on average in Europe in QS rankings since their inception, #3 worldwide). He is a member of the OECD network of experts on AI and former Head of the Department of Information Systems, Decision Sciences & Statistics at ESSEC.
His field of research is econometric theory with applications to forecasting and statistical learning in economics and finance. His interests range from dynamic spillovers in large scale networks to dependence in unstable environments and the reinforcement between agents’ behaviors and policies that aim to influence them. Applications include monetary policy, business cycles, financial bubbles, energy forecasting, social networks, global warming and pandemic dynamics.
Guillaume obtained an MPhil and a DPhil in Economics from the University of Oxford, and a Master in Engineering from Ecole des Mines de Paris. He has been a visiting scholar or professor at, inter alia, Brown, Oxford, NYU, Keio, UNSW Sydney and the NY Federal Reserve. He regularly publishes or is interviewed in mainstream media.