Report NEP-FOR-2021-10-04

This is the archive for NEP-FOR, a report on new working papers in the area of Forecasting. Rob J Hyndman issued this report. It is usually issued weekly.

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Other reports in NEP-FOR

The following items were announced in this report:

• Laura Coroneo, & Fabrizio Iacone, & Giancarlo Manzi, & Silvia Salini, 2021. "Predicting the COVID-19 epidemic: is a regional approach preferable?," Discussion Papers 21/06, Department of Economics, University of York.
• Item repec:rim:rimwps:21-20 is not listed on IDEAS anymore

• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
• Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
• Kadanga, Mayo Takémsi Norris & Togbenu, Fo-Kossi Edem, 2021. "Modélisation et prévision du nombre d’infections au coronavirus au Togo: une approche par un modèle ARIMA avec le logiciel R [Modeling and forecasting the number of coronavirus infections in Togo: ," MPRA Paper 109893, University Library of Munich, Germany.
• Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2021. "The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis," Working Paper 2021/1, Norges Bank.
• Sarun Kamolthip, 2021. "Macroeconomic forecasting with LSTM and mixed frequency time series data," Papers 2109.13777, arXiv.org.
• Xingzuo Zhou & Yiang Li, 2021. "Forecasting the COVID-19 vaccine uptake rate: An infodemiological study in the US," Papers 2109.13971, arXiv.org, revised Dec 2021.
• Eduardo Ramos-P'erez & Pablo J. Alonso-Gonz'alez & Jos'e Javier N'u~nez-Vel'azquez, 2021. "Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility," Papers 2109.12621, arXiv.org.
• Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
• Jinlong Ruan & Wei Wu & Jiebo Luo, 2021. "Stock Price Prediction Under Anomalous Circumstances," Papers 2109.15059, arXiv.org.
• Item repec:cdl:itsrrp:qt0v1906ts is not listed on IDEAS anymore