Report NEP-ETS-2023-01-16

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Jaqueson K. Galimberti issued this report. It is usually issued weekly.

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Other reports in NEP-ETS

The following items were announced in this report:

• Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Cambridge Working Papers in Economics 2273, Faculty of Economics, University of Cambridge.
• Eva Biswas & Farzad Sabzikar & Peter C. B. Phillips, 2022. "Boosting the HP Filter for Trending Time Series with Long Range Dependence," Cowles Foundation Discussion Papers 2347, Cowles Foundation for Research in Economics, Yale University.
• Miguel Cabello, 2022. "Robust Estimation of the non-Gaussian Dimension in Structural Linear Models," Papers 2212.07263, arXiv.org, revised Sep 2023.
• Mboya, Mwasi & Sibbertsen, Philipp, 2022. "Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory," Hannover Economic Papers (HEP) dp-705, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Specification tests for non-Gaussian structural vector autoregressions," Working Papers wp2022_2212, CEMFI.
• Andrii Babii & Eric Ghysels & Junsu Pan, 2022. "Tensor Principal Component Analysis," Papers 2212.12981, arXiv.org, revised Aug 2023.
• Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.