Econometrics Seminar Series. Spurious factors in data with local-to-unit roots
Published: 6 February 2024
16 February. Professor Alexey Onatski, University of Cambridge
Dr Alexey Onatski, University of Cambridge
"Spurious factors in data with local-to-unit roots"
Friday, 16 February. 3pm
Room 355 Gilbert Scott Building
Abstract
This paper extends the spurious factor analysis of Onatski and Wang (2021) to high-dimensional data with heterogeneous local-to-unit roots. We find a spurious factor phenomenon similar to that observed in the data with unit roots. Namely, estimated “factors” reflect the structure of the strong temporal correlation of the data and do not correspond to any cross-sectional commonalities, that genuine factors are usually associated with.
We conjecture that the spurious factor phenomenon holds, more generally, for data obtained from high frequency sampling of heterogeneous continuous time (or spacial) processes, and provide an illustration.
Bio
Received PhD from Harvard University in 2001. Took up his first academic position at Columbia University, NY. Joined the Economics Faculty at Cambridge in 2010. Associate editor of Journal of Econometrics, Journal of Business and Economic Statistics and Random Matrices: Theory and Applications. Works in the intersection of Random Matrix theory and high-dimensional Econometrics.
For further information, please contact business-school-research@glasgow.ac.uk
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First published: 6 February 2024
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