General Description
We are pleased to announce the latest EABCN Training School; a three-day course entitled “The Bootstrap and its Applications to Panel and Factor Models” taught by Professor Silvia Gonçalves (McGill University) that will take place via Zoom on 3, 4, 5 June 2025. It is primarily aimed at participants in the Euro Area Business Cycle Network, but applications will also be considered from doctoral students, post-doctoral researchers and economists working in central banks and government institutions outside of the network, as well as commercial organisations (fees are applicable for non-network non-academic organisations).
The main goal of this class is to provide students with an overview of the bootstrap and its applications in different contexts in economics allowing for both cross sectional and serial dependence. We will cover pure time series applications as well as panel data models and factor models. The emphasis will be on discussing the conditions that the bootstrap needs to meet to be valid in each application.
The deadline to submit an application has now passed.
About the Instructor:
Sílvia Gonçalves is a Professor of Economics at McGill University. She received her Ph.D. in 2000 from the University of California, San Diego. Before joining the Department of Economics at McGill University in 2017, she was a Professor of Economics at the University of Western Ontario (2015-2017) and at the Université de Montréal (2000-2015). Her work in econometric theory has focused on developing bootstrap methods that apply computing power to allow accurate inference for a range of statistical problems in economics, with a focus on dependent data, including financial data, panel data, and spatial data. This work has been cited extensively and published in Econometrica, JASA as well as in the top field journals in econometrics.
She received the first CWEN prize for research by a young woman researcher in a Canadian University in 2010 and currently serves as an Associate Editor of the Journal of Econometrics, Journal of Business Economic & Statistics, and Journal of Applied Econometrics.
