New Chapter in the Upcoming Handbook of Econometrics Vol 7: Professor Alfred Galichon

Professor Alfred Galichon, a member of CRATE who holds joint positions in NYU Department of Economics and the Courant Institute, has been invited to contribute a chapter to the upcoming Handbook of Econometrics, Vol 7. The chapter is titled “Matching and Hedonic Models” and co-authored with Professor Bernard Salanie. Draft coming soon.

New Chapter in the Upcoming Handbook of Econometrics Vol 7: Professors Isabelle Perrigne and Quang Vuong

Professor Isabelle Perrigne, a research affiliate member of CRATE, and Professor Quang Vuong, Director of CRATE, have been invited to write the Chapter, titled Econometrics of Auctions, for the upcoming Handbook of Econometrics, Vol 7. The chapter presents a comprehensive review of the literature on the econometrics of auctions, detailing the empirical methods to-date. Draft coming soon.

National Science Foundation Grant: Professor Timothy Christensen 

Professor Timothy Christensen, a member of CRATE, has recently received a National Science Foundation Grant, for the title “Robust Inference on Counterfactuals”, SES-1919034, for years 2019-2022. 

NYU Paris: Under New Leadership of Professor Alfred Galichon

Professor Alfred Galichon, a member of CRATE who holds joint positions in NYU Department of Economics and the Courant Institute, has recently assumed the role of Director of NYU Paris. The academic center now offers a broad range of new courses in mathematics and computer science, and hopefully soon in other STEM fields including economics, with the objective of significantly expanding the number of students.

Newest CRATE Member: Professor Elena Manresa

NYU-CRATE welcomes the newest member of our research staff, Professor Elena Manresa.  Professor Manresa completed her PhD in Economics from CEMFI, Spain in 2014, and was previously a Visiting Assistant Professor at the University of Chicago. She has now joined the faculty of the NYU Economics Department.  She is an econometrician specializing in micro-econometrics, applied microeconomics and financial econometrics.  Her current research interests include exploring potential of machine learning techniques to explain economic phenomena, as well as statistical modeling based on the idea that economic data is different from any other kind of data (like medical or engineering data) because it shows us the decisions made by people, but not why. The why behind a data set is what Professor Manresa seeks to unveil.