معرفی
Prof. Damian Kozbur is an Associate Professor of Econometrics at the University of Zurich's Department of Economics, affiliated with the Digital Society Initiative. He holds a PhD from the University of Chicago (2014) and has been at UZH since 2016. His research focuses on integrating economic theory with machine learning tools, particularly in high-dimensional econometric models. Key areas include estimation techniques for weak instruments, panel data analysis, and clustering methods for statistical inference. He has contributed to journals like Econometrica and the Journal of Business and Economic Statistics. His work addresses applications such as market dynamics, causal inference in complex data, and policy analysis.
Education: PhD in Econometrics from the University of Chicago Booth School of Business (2014), BA in Mathematics (2008). Previous roles include ETH Zurich Fellow (2014–2016). Teaching includes advanced econometrics and machine learning courses for doctoral students.
Research Interests: High-dimensional econometrics, model selection, statistical inference, and applications of machine learning to economic problems. His recent articles tackle spatial dependence robustness, debiased machine learning, and forecast hedging with random forests.
Professional Service: Associate Editor of the Journal of Business and Economic Statistics since 2022. Active in reviewing for top econometric outlets like Journal of Econometrics and Econometric Theory.
