معرفی
Martin Mugnier is an Assistant Professor at the Paris School of Economics (PSE). He previously held postdoctoral positions at the University of Oxford (Nuffield College) as a Research Fellow. His research focuses on econometric methods, particularly nonlinear panel data models, high-dimensional statistics, and machine learning tools for estimation and identification. He earned his Ph.D. in Economics from Institut Polytechnique de Paris, completing his doctoral work at CREST and defending his thesis at ENSAE Paris in June 2023.
His research interests emphasize grouped fixed effects models, binary choice models, and computational methods for handling unobserved heterogeneity. Key contributions include developing estimators for nonlinear panel models and advancing techniques for discretizing time-varying effects. Mugnier collaborates actively with scholars like Laurent Davezies, Xavier D'Haultfœuille, and Ao Wang on foundational econometric problems.
His publications appear in leading journals such as the Journal of Econometrics and Quantitative Economics. He develops open-source implementations of his methods, including Python packages like nlmfe and BinLogitCMLE for conditional maximum likelihood estimation. His work bridges theoretical econometrics with practical computation, addressing challenges in modern high-dimensional data analysis.
