معرفی
Andrei Zeleneev is a Lecturer in Economics at University College London (UCL), Department of Economics, where he joined in 2020. He holds a PhD from Princeton University and is affiliated with CeMMAP (Centre for Microdata Methods and Practice). His research focuses on econometric methodologies, particularly addressing challenges in panel models, network models, and errors-in-variables. His work emphasizes nonparametric identification, robust estimation, and applied econometric techniques to handle unobserved heterogeneity and measurement errors.
Dr. Zeleneev’s academic background includes advanced training in econometrics, and his research spans both theoretical and applied domains. He has published extensively on topics such as treatment effects in large panels, latent variable modeling, and structural econometric approaches to network analysis.
His articles highlight innovations in handling complex data structures and improving the reliability of econometric inferences in settings with non-classical errors or latent factors. He maintains an active research agenda, with recent work addressing methodological advancements in semiparametric models and interactive fixed effects.
Dr. Zeleneev’s professional activities include teaching at UCL and contributing to the econometrics community through publications and affiliations with leading institutions.
