18/07/2008
Special UPF Seminar Features Harvard Professors Donald Rubin and Guido Imbens
On Monday, July 7, Harvard professors Don Rubin and Guido Imbens held a joint seminar in the auditorium of the Ciutadella Campus. The topic discussed was “Can an economist and a statistician agree on statistical methods?”
The seminar took place in the form of an open conversation between the two experts, moderated by GSE Affiliated Professor and UPF Professor José García-Montalvo. The interchange was followed by an open question session and discussion with the audience.
The event offered a unique opportunity for GSE summer school students, particularly those in the Microeconometrics program, to take part in the vibrant economics community in Barcelona. The two distinguished professors are widely considered among the most productive and influential econometricians in recent history, with some of their papers ranking among the most cited economics and statistics research of the 1990s. Professor García-Montalvo, organizer of the seminar, extolled the influential contributions of the two researchers, saying “if Nobel Prizes were awarded to a statistician, [Don Rubin] would be the strongest candidate.”
Donald Rubin is the John L. Loeb Professor of Statistics at Harvard University, where he has taught since 1984. He received his PhD from Harvard in 1970 and has held positions at Princeton, the University of Wisconsin-Madison, and the University of Chicago.
Professor Rubin is perhaps best known for the Rubin Causal Model, a set of methods designed for causal inference with observational data, and for his methods for dealing with missing data. He published his major papers on the Rubin Causal Model in 1974-1980, and is currently writing a book on the subject with Professor Imbens.
Guido Imbens is Professor of Economics at Harvard University. A native of the Netherlands, he received his PhD from Brown in 1991, and held positions at UC Berkeley and UCLA before joining the Harvard faculty in 2006.
Professor Imbens' contributions to the field of econometrics have had an enormous influence on assessing the effects of interventions from both field and experimental data. He is widely known for his pioneering work on the local average treatment effect (LATE), which allows researchers to better compare outcomes for individuals receiving experimental intervention versus those receiving no added treatment.
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