On June 13-14, 2022, the second Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series will be organized in Maastricht.

This two-day workshop aims to provide a platform for exchanging and discussing the latest developments in econometrics and statistics on topics related to dimensionality reduction and inference in high-dimensional time series, including (but not limited to) issues related to post-selection inference, statistical learning, penalized regression methods, factor models and common features.

Invited talks will be given by Matteo Barigozzi (University of Bologna), Sumanta Basu (Cornell University), Anders Bredahl Kock (University of Oxford), Siem Jan Koopman (VU Amsterdam), Marcelo Medeiros (Pontifical Catholic University of Rio de Janeiro), Weining Wang (University of York) and Takashi Yamagata (University of York).

The provisional programme is available here.