We are pleased to announce the 6th Potsdam PhD Workshop in Empirical Economics. The aim of the workshop is to give talented young researchers the opportunity to present and discuss their research and to study new developments in Empirical Economics.
Lecturer and Topic
Guido W. Imbens, the Applied Econometrics Professor and Professor of Economics at Stanford Graduate School of Business, will give a series of lectures about Causal Inference and Machine Learning. Guido is well-known for his influential work on causal inference in econometrics and has published in the highest-ranking journals (inter alia Econometrica, American Economic Review, Review of Economic Studies, Journal of the American Statistical Association, Biometrika). He will introduce machine learning in the context of empirical economic research. Particular emphasis will be given on its use for estimating causal effects in economics and policy-related analyses, taking into account heterogeneous treatment effects, advances in experimental designs and synthetic control methods.
The 6th Potsdam PhD Workshop in Empirical Economics is open to around 20 doctoral students and post doctorates within two years after dissertation. Participants will be given the opportunity to present and discuss their own research in a poster session. We encourage all young researchers interested in Empirical Economics to apply.
Please submit your CV and a paper (or an extended abstract) by May 31, 2019 to workshopuempwifo.uni-potsdampde. There will be no workshop fees; travel and accommodation expenses have to be covered by the participants.
Thanks to all participants for an inspiring and interesting "6th Potsdam PhD Workshop in Empirical Economics".
A special thanks to the lecturer Guido W. Imbens for sharing his expertise and to the external discussants Rainald Borck, Nicolas Salamanca, Felix Weinhardt and Katharina Wrohlich for their helpful comments.
We are looking forward to the next event.
Professur für Empirische Wirtschaftsforschung
Universitätskomplex III (Griebnitzsee), Haus 1, Raum 3.07
Tel.: +49 331 977-3225
Fax: +49 331 977-3210