Report NEP-ETS-2021-07-12

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:

• Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
• Philipp Otto & Wolfgang Schmid, 2021. "Generalized Spatial and Spatiotemporal ARCH Models," Papers 2106.10477, arXiv.org.
• Søren Johansen & Anders Ryghn Swensen, 2021. "Adjustment coefficients and exact rational expectations in cointegrated vector autoregressive models," CREATES Research Papers 2021-10, Department of Economics and Business Economics, Aarhus University.
• Alexander Chudik & M. Hashem Pesaran & Ron P. Smith, 2021. "Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels," Globalization Institute Working Papers 409, Federal Reserve Bank of Dallas, revised 08 Nov 2023.
• Francesca Lilla, 2021. "Volatility Bursts: A discrete-time option model with multiple volatility components," Temi di discussione (Economic working papers) 1336, Bank of Italy, Economic Research and International Relations Area.
• Anastasiou, Andreas & Fryzlewicz, Piotr, 2022. "Detecting multiple generalized change-points by isolating single ones," LSE Research Online Documents on Economics 110258, London School of Economics and Political Science, LSE Library.
• Li, Y-N. & Chen, J. & Linton, O., 2021. "Estimation of Common Factors for Microstructure Noise and Efficient Price in a High-frequency Dual Factor Model," Cambridge Working Papers in Economics 2150, Faculty of Economics, University of Cambridge.