CHEVILLON Guillaume

Actuellement

Depuis 2020

Chair, Département des Systèmes d'Information, Sciences de la Décision & Statistiques, ESSEC

CoDirecteur Académique ESSEC METALAB for Data, Technology & Society

Depuis 2015

Professeur (Full), ESSEC Business School

CoDirecteur Académique (pour l'ESSEC) du Master ESSEC|CentraleSupélec Data Sciences & Business Analytics

Précédemment

2020 Visiting Professor, Keio University, Tokyo & UNSW, Sydney

A partir de 2007 Membre associé Laboratoire de Macroéconomie, CREST-INSEE

2012-13 Chercheur Visitant, Département d'Economie, New York University

2012 - Chercheur Visitant, Federal Reserve Bank of New York

2011 - Professeur Visitant, Département d'Economie, Université d'Oxford

2010-15 Professeur Associé, ESSEC Business School

2006-9 Professeur Assistant, ESSEC Business School

2003-6 Economiste à l'OFCE (SciencesPo)

1999-2006 Chargé de cours et maître de conférences à SciencesPo, HEC, ENA, Université Paris-Dauphine, University of Oxford (Econometrics, Time Series, Forecasting, Statistics, Macroeconomics)

• 2004 : Ph.D. en Economie (University of Oxford, Royaume-Uni)
• 2004 : Ph.D. en Economie (University of Oxford, Royaume-Uni)
• 2000 : M.Phil. en Economie (Brasenose College, University of Oxford, Royaume-Uni)
• 2000 : M.Phil. en Economie (Brasenose College, University of Oxford, Royaume-Uni)
• 1998 : M.Sc. en Ingénierie d'Execution (Diplôme d’Ingénieur) (Mines ParisTech, France)
• 1998 : M.Sc. en Ingénierie d'Execution (Diplôme d’Ingénieur) (Mines ParisTech, France)

Positions académiques principales

• 2015 - présent : Professeur (ESSEC Business School, France)
• 2015 - présent : Professeur (ESSEC Business School, France)
• 2010 - 2015 : Professeur associé (ESSEC Business School, France)
• 2010 - 2015 : Professeur associé (ESSEC Business School, France)
• 2006 - 2010 : Professeur assistant (ESSEC Business School, France)
• 2006 - 2010 : Professeur assistant (ESSEC Business School, France)

Autres positions académiques

• 2015 - 2023 : CoDirecteur du MSc in Data Sciences & Business Analytics (ESSEC-CentraleSupélec) (ESSEC Business School, France)
• 2015 - 2023 : CoDirecteur du MSc in Data Sciences & Business Analytics (ESSEC-CentraleSupélec) (ESSEC Business School, France)
• 2020 - 2023 : Directeur Académique Intelligence Artificielle pour le Business & Economie Digital (ESSEC Business School, France)
• 2020 - 2023 : Directeur Académique Intelligence Artificielle pour le Business & Economie Digital (ESSEC Business School, France)
• 2020 - 2022 : Responsable de département IDS (ESSEC Business School, France)
• 2020 - 2022 : Responsable de département IDS (ESSEC Business School, France)
• 2008 - présent : Chercheur Associé (Centre de recherche en économie et statistique (CREST), France)
• 2008 - présent : Chercheur Associé (Centre de recherche en économie et statistique (CREST), France)
• 2020 : Professeur visitant (Fukuoka University, Japon)
• 2020 : Professeur visitant (Fukuoka University, Japon)
• 2020 : Professeur visitant (Keio University, Japon)
• 2020 : Professeur visitant (Keio University, Japon)
• 2020 : Professeur visitant (UNSW Business School, Australie)
• 2020 : Professeur visitant (UNSW Business School, Australie)
• 2012 - 2013 : Chercheur Visitant (9 mois), Département Economie (New York University, États-Unis)
• 2012 - 2013 : Chercheur Visitant (9 mois), Département Economie (New York University, États-Unis)
• 2012 : Chercheur Visitant (3 mois), Fonction Monnaie et Macro (Federal Reserve Bank of New York, États-Unis)
• 2012 : Chercheur Visitant (3 mois), Fonction Monnaie et Macro (Federal Reserve Bank of New York, États-Unis)
• 2011 : Professeur Visitant (un demi semestre), Département Economie (University of Oxford, Royaume-Uni)
• 2011 : Professeur Visitant (un demi semestre), Département Economie (University of Oxford, Royaume-Uni)
• 2007 - 2010 : Chercheur Visitant (séjours régulier plusieurs fois par an), Département Economie (Brown Université, États-Unis)
• 2007 - 2010 : Chercheur Visitant (séjours régulier plusieurs fois par an), Département Economie (Brown Université, États-Unis)
• 2003 - 2006 : Research Fellow (Economie) à OFCE (Institut d'Etudes Politiques, France)
• 2003 - 2006 : Research Fellow (Economie) à OFCE (Institut d'Etudes Politiques, France)
• 2000 - 2002 : Assistant de Recherche pour le Prof D. F. Hendry, Département Economie (University of Oxford, Royaume-Uni)
• 2000 - 2002 : Assistant de Recherche pour le Prof D. F. Hendry, Département Economie (University of Oxford, Royaume-Uni)

• 2023 - 2027 : Research grant on AI driven oncological treatments (France)
• 2023 - 2027 : Research grant on AI driven oncological treatments (France)
• 2021 - 2024 : CY Projet Emergence (France)
• 2021 - 2024 : CY Projet Emergence (France)
• 2016 - 2018 : Project Blanc (Fondation ESSEC, France)
• 2016 - 2018 : Project Blanc (Fondation ESSEC, France)
• 2014 - 2020 : Divers financements du Labex MME-DII (Labex MME-DII, France)
• 2014 - 2020 : Divers financements du Labex MME-DII (Labex MME-DII, France)
• 2007 - 2019 : Bourses de recherche, Europlace Institute of Finance (en collaboration) (Institut Europlace de Finance (IEF), France)
• 2007 - 2019 : Bourses de recherche, Europlace Institute of Finance (en collaboration) (Institut Europlace de Finance (IEF), France)
• 2007 - 2020 : Financement régulier du Centre de Recherche de l'ESSEC depuis 2007 (ESSEC Business School, France)
• 2007 - 2020 : Financement régulier du Centre de Recherche de l'ESSEC depuis 2007 (ESSEC Business School, France)

• BAUWENS, L., CHEVILLON, G. and LAURENT, S. (2023). We modeled long memory with just one lag! Journal of Econometrics, 236(1), pp. 105467.
• CHEVILLON, G., MAVROEIDIS, S. and ZHAN, Z. (2020). Robust Inference in Structural Vector Autoregressions with Long-Run Restrictions. Econometric Theory, 36(1), pp. 86-121.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2020). Probabilistic Forecasting of Bubbles and Flash Crashes. Econometrics Journal, 23(2).
• CHEVILLON, G., HECQ, A. and LAURENT, G. (2018). Generating Univariate Fractional Integration within a Large VAR(1), Journal of Econometrics, 1(204), pp. 54-65.
• CHEVILLON, G. and MAVROEIDIS, S. (2018). Perpetual Learning and Apparent Long Memory. Journal of Economic Dynamics and Control, 90, pp. 343-365.
• CHEVILLON, G. and MAVROEIDIS, S. (2017). Learning can generate long memory. Journal of Econometrics, 198(1), pp. 1-9.
• CHEVILLON, G. (2017). Robust Cointegration Testing in the Presence of Weak Trends, with an Application to the Human Origin of Global Warming. Econometric Reviews, 36(5), pp. 514-545.
• CHEVILLON, G. (2016). Multistep Forecasting in the Presence of Location Shifts. International Journal of Forecasting, 32(1), pp. 121-137.
• CHEVILLON, G. (2014). Multi-step Forecast Error Corrections: A Comment on “Evaluating Predictive Densities of US Output Growth and Inflation in a Large Macroeconomic Data Set” by Barbara Rossi and Tatevik Sekhposyan. International Journal of Forecasting, 30(3), pp. 683-687.
• CHEVILLON, G., MASSMANN, M. and MAVROEIDIS, S. (2010). Inference in Models with Adaptive Learning. Journal of Monetary Economics, 57(3), pp. 341-351.
• CHEVILLON, G. (2009). Multi-Step Forecasting in Emerging Economies: An Investigation of the South African GDP. International Journal of Forecasting, 25(3), pp. 602-628.
• CHEVILLON, G. and RIFFLART, C. (2009). Physical Market Determinants of the Price of Crude Oil and the Market Premium. Energy Economics, 31(4), pp. 537-549.
• CHARLETY-LEPERS, P., CHEVILLON, G. and MESSAOUDI, M. (2009). Stratégies de vote en AG face aux résolutions externes. Revue Française de Gestion, 198(8-9), pp. 277-296.
• CHEVILLON, G. (2007). Direct Multi-step Estimation and Forecasting. Journal of Economic Surveys, 21(4), pp. 746-785.
• CHEVILLON, G. (2005). Analyse Econométrique et Compréhension des Erreurs de Prévision. Revue de l’OFCE, 95, pp. 327-356.
• CHEVILLON, G. and HENDRY, D. (2005). Non-parametric Direct Multi-Step Estimation for Forecasting Economic Processes. International Journal of Forecasting, 21, pp. 201-218.
• CHEVILLON, G. and RIFFLART, C. (2004). Brouillard autour des puits de pétrole. Revue de l’OFCE, (253), pp. 1-4.
• CHEVILLON, G. and DAP (2004). Les tribulations de la parité euro/dollar, Revue de l’OFCE, (252), pp. 1-4.

• CHEVILLON, G. and TIMBEAU, X. (2006). Impact du taux de change sur le tourisme en France. In: Evolution Recente du commerce extérieur Français. 1st ed. Paris: La Documentation Française, pp. 99-108.
• CHEVILLON, G., HEYER, E. and LEMOINE, M. (2004). Perspectives de l'économie Française à l'horizon 2009. In: Rapport d'information du Sénat n° 70. 1st ed. Paris: pp. 138-203.
• CHAUVIN, V., CHEVILLON, G. and HEYER, E. (2003). Perspectives de l'économie Française à l'horizon 2008. In: Rapport d'information du Sénat n° 69. 1st ed. Paris: pp. 132-188.

• CHEVILLON, G. and KURITA, T. (2023). What Does It Take to Control Global Temperatures? Prospective and Counterfactual Carbon Abatement Policies in a Cointegrated VAR Model. In: 2023 Symposium of the Society for Nonlinear Dynamics & Econometrics. Orlando.
• BAUWENS, L., CHEVILLON, G. and LAURENT, S. (2022). We modeled long-memory with one lag! In: 2022 Aarhus Workshop in Econometrics. Aarhus.
• CHEVILLON, G. and KURITA, T. (2022). What Does It Take to Control Global Temperatures? Prospective and Counterfactual Carbon Abatement Policies in a Cointegrated Vector Autoregressive Model. In: 2022 International Symposium on Forecasting (IFS). Oxford.
• CHEVILLON, G. (2022). The Bias-Variance Trade-off in (Un)Conditional Multistep Forecasting, Predictive Regressions and Local Projections. In: 2022 Society for Financial Econometrics (SoFiE) Annual Meeting. Cambridge.
• CHEVILLON, G. and KURITA, T. (2022). What Does It Take to Control Global Temperatures? Prospective and Counterfactual Carbon Abatement Policies in a Cointegrated Vector Autoregressive Model. In: 2022 International Association for Applied Econometrics (IAAE) Conference. London.
• BAUWENS, L., CHEVILLON, G. and LAURENT, S. (2022). We Modeled Long Memory with One Lag! In: 2022 Quantitative Finance & Financial Econometrics. Marseille.
• CHEVILLON, G. and KURITA, T. (2022). Counterfactual Policy Analysis in a Cointegrated Vector Autoregressive Model, with an Application to Monetary Policy near the Zero Lower Bound. In: 2022 Society for Nonlinear Dynamics and Econometrics (SNDE) Symposium. Online.
• BAUWENS, L. and CHEVILLON, G. (2021). We Modelled Long Memory with Just One Lag! In: 15th International Conference on Computational and Financial Econometrics (CFE). London.
• BAUWENS, L., CHEVILLON, G. and LAURENT, S. (2019). Forecasting Long Memory through a VAR Model. In: 4th Vienna Workshop on High-Dimensional Time Series in Macroeconomics and Finance 2019.
• CHEVILLON, G. (2019). The Bias-Variance Trade-off in Multistep Forecasting and Predictive Regressions at Intermediate and Long Horizons. In: 27th annual symposium of the Society for Nonlinear Dynamics and Econometrics 2019.
• CHEVILLON, G. (2019). The Bias-Variance Trade-off in Multistep Forecasting and Predictive Regressions at Intermediate and Long Horizons. In: 2019 Quantitative Finance and Financial Econometrics (QFFE).
• CHEVILLON, G. and MAVROEIDIS, S. (2019). The Shadow of a Doubt. In: 2019 Workshop Annuel de l'ANR MultiRisk.
• CHEVILLON, G. (2018). Exuberance: Sentiments Driven Buoyancy. In: 2018 Econometric Theory and Time Series Analysis (ETTSA) Workshop.
• BAUWENS, L., CHEVILLON, G. and LAURENT, S. (2018). Forecast Comparisons for Long Memory. In: Quantitative Finance and Financial Econometrics (QFFE 2018).
• CHEVILLON, G., BAUWENS, L. and LAURENT, S. (2018). Forecasting Long Memory via a VAR Model. In: 12th International Conference on Computational and Financial Econometrics (CE) 2018.
• CHEVILLON, G., BAUWENS, L. and LAURENT, S. (2018). Forecasting Long Memory via a VAR Model. In: 1st Applied Financial Econometrics Workshop.
• CHEVILLON, G., BAUWENS, L. and LAURENT, S. (2018). Forecasting Long Memory via a VAR Model. In: Workshop on Long Memory.
• CHEVILLON, G. and MAVROEIDIS, S. (2018). Perpetual Learning and Apparent Long Memory. In: 26th Annual Symposium of the Society for Nonlinear Dynamics & Econometrics.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2018). Probabilistic Forecasting of Bubbles and Flash Crashes. In: 2018 Asian Meeting of the Econometric Society.
• CHEVILLON, G., HECQ, A. and LAURENT, S. (2016). Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence. In: 2016 Asian Meeting of the Econometric Society (AMES2016).
• CHEVILLON, G., HECQ, A. and LAURENT, S. (2016). Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence. In: 2016 Summer Forum of the Barcelona School of Economics.
• CHEVILLON, G., MAVROEIDIS, S. and ZANG, Z. (2016). Robust Inference in Structural VARs with Long-Run Restrictions. In: 24th Symposium of the Society for Nonlinear Dynamics and Econometrics.
• CHEVILLON, G., MAVROEIDIS, S. and ZHAN, Z. (2016). Robust Inference in Structural VARs with Long-Run Restrictions. In: 10th International Conference on Computational and Financial Econometrics.
• CHEVILLON, G. and SOPHOCLES, M. (2015). Learning Can Generate Long Memory. In: 2nd Annual Conference of the International Association for Applied Econometrics (IAAE).
• CHEVILLON, G., HECQ, A. and LAURENT, S. (2015). Long Memory through Cross-Section Dependence and Marginalization. In: 23rd Annual Symposium of the Society for Nonlinear Dynamics and Econometrics.
• CHEVILLON, G., LAURENT, S. and HECQ, A. (2015). Long Memory Through Margnialization of Large Systems and Hidden Cross Section Dependence. In: 4th Long-Memory Symposium.
• CHEVILLON, G., SOPHOCLES, M. and ZHAOGUO, Z. (2015). Robust inference in Structural VARs with Long-Run Restrictions. In: 38th Annual National Bureau of Economic Research (NBER) Summer Institute.
• CHEVILLON, G., NAVROEIDIS, S. and ZHAN, Z. (2015). Robust Inference in Structural VARS within Long Run Restrictions. In: 16th OxMetrics User Conference.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coefficient Model. In: 68th European Meeting of the Econometric Society.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2014). Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Co-efficient Model. In: Summer Institute 2014 of the National Bureau of Economic Research.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Forecasting Bubbles in a Near Explosive Random Coefficient Model. In: 25th EC2 Conference on "Advances in Forecasting".
• CHEVILLON, G., HECQ, A. and LAURENT, S. (2014). Persistence Through Correlation. In: 15th OxMetrics User Conference.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Sentiment Driven Buoyancy. In: 8th International Conference on Computational and Financial Econometrics (CFE 2014).
• CHEVILLON, G. and MAVROEIDIS, S. (2014). The Shadow of a Doubt: The Dynamic Impact of Exceptional Uncertainty. In: 2014 Society for Nonlinear Dynamics and Econometrics (SNDE) Conference.
• CHEVILLON, G. (2013). Detecting and Forecasting Large Deviations and Bubbles in a near Explosive Random Coefficient Model. In: 2013 NBER-NSF Time Series Conference.
• CHEVILLON, G. (2013). Long Memory through Correlation. In: 7th Annual Methods in International Finance Network Workshop.
• CHEVILLON, G., HECQ, A. and LAURENT, S. (2013). Long Memory Through Correlation. In: 7th International Conference on Computational and Financial Econometrics (CFE).
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2012). Detecting and Predicting Rational Asset Price Bubbles in a Near Explosive Random Coefficient Autoregressive Model. In: SMU-ESSEC Symposium on Empirical Finance and Financial Econometrics 2012.
• CHEVILLON, G. (2012). Learning Can Generate Long Memory. In: 2012 NBER-NSF Time Series Conference.
• CHEVILLON, G. and MAVROEIDIS, S. (2012). Learning Generates Long Memory. In: 20th Symposium of the Society for Nonlinear Dynamics and Econometrics.

• CHEVILLON, G. (2022). L'algorithme est in influenceur comme les autres. Le Monde.
• CHEVILLON, G. (2021). The power of persuading: Can and should we regulate AI algorithms? OECD Publications.
• CHEVILLON, G. (2020). Laisser-faire or Policing social networks. ESSEC Knowledge & Reflets Magazine.
• CHEVILLON, G. (2020). Laisser-faire or Policing social networks. ESSEC Knowledge.
• CHEVILLON, G. (2019). Il semble illusoire de contrôler a priori les outils d’intelligence artificielle car leurs conséquences sont quasi imprévisibles. Le Monde.
• CHEVILLON, G. (2018). Et si on réinitialisait les réseaux sociaux en 2019 ? La Libre Belgique.
• CHEVILLON, G. (2018). Les employeurs sont à la recherche d’ingénieurs-manageurs, interview by M. de Amorim. Le Monde.
• CHEVILLON, G. (2018). Et si on réinitialisait les réseaux sociaux ? Libération.
• CHEVILLON, G. (2016). Des algorithmes dangereux pour le débat démocratique. Libération.
• CHEVILLON, G. (2016). L'étudiant co-créateur de sa formation. Le Monde des Grandes Ecoles.
• CHEVILLON, G. (2016). La nécessité de l’alliance data sciences et business analytics dans la création de valeur. Journal des Grandes Écoles.
• CHEVILLON, G. (2015). La Banque centrale européenne agit-elle trop tard ? La Tribune.
• CHEVILLON, G. (2014). How econometrics helps us explain Climate Change. ESSEC Knowledge.
• CHEVILLON, G. (2014). Three Big Questions Preoccupying Economists. ESSEC Knowledge.
• CHEVILLON, G. (2013). Homo-oeconomicus : un comportement modèle ou un modèle de comportement ? La Tribune.
• CHEVILLON, G. (2012). Tous les électeurs sont-ils égaux ? Les Echos.
• CHEVILLON, G. (2004). Buts et Abus d'une Constitution. Libération, pp. 40-40.
• CHEVILLON, G. (2004). Commerce Extérieur: les Raisons du Déficit. Interview by Sophie Fay. Le Monde.

• CHEVILLON, G. 2017. Data Scientist: Think Big! Short interview by Mireille Weinber. October.
• CHEVILLON, G. 2017. Managing the robots. Short interview. September.
• CHEVILLON, G. 2016. Stop à l'anarchie sur les médias sociaux ? Interview by Thierry Boutte. November.