Report NEP-FOR-2025-01-20

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:

• McCloskey, PJ & Malheiros Remor, Rodrigo, 2024. "Comparative Analysis of ARIMA, VAR, and Linear Regression Models for UAE GDP Forecasting," MPRA Paper 122860, University Library of Munich, Germany, revised 01 Dec 2024.
• Xiaoqian Wang & Rob J Hyndman & Shanika Wickramasuriya, 2024. "Optimal Forecast Reconciliation with Time Series Selection," Monash Econometrics and Business Statistics Working Papers 5/24, Monash University, Department of Econometrics and Business Statistics.
• Xiaoqian Wang & Rob J Hyndman, 2024. "Online Conformal Inference for Multi-Step Time Series Forecasting," Monash Econometrics and Business Statistics Working Papers 20/24, Monash University, Department of Econometrics and Business Statistics.
• Paul Ghelasi & Florian Ziel, 2025. "A data-driven merit order: Learning a fundamental electricity price model," Papers 2501.02963, arXiv.org.
• Yangzhuoran Fin Yang & Rob J Hyndman & George Athanasopoulos & Anastasios Panagiotelis, 2024. "Forecast Linear AugmentedProjection (FLAP): A Free Lunch to Reduce Forecast Error Variance," Monash Econometrics and Business Statistics Working Papers 13/24, Monash University, Department of Econometrics and Business Statistics.
• Meg Tulloch, "undated". "Nowcasting and Forecasting Average Weekly Earnings in the United Kingdom," National Institute of Economic and Social Research (NIESR) Discussion Papers 565, National Institute of Economic and Social Research.
• Nuwani K Palihawadana & Rob J Hyndman & Xiaoqian Wang, 2024. "Sparse Multiple Index Modelsfor High-dimensional Nonparametric Forecasting," Monash Econometrics and Business Statistics Working Papers 16/24, Monash University, Department of Econometrics and Business Statistics.
• Chang, Jinyuan & Fang, Qin & Qiao, Xinghao & Yao, Qiwei, 2024. "On the Modeling and Prediction of High-Dimensional Functional Time Series," LSE Research Online Documents on Economics 125599, London School of Economics and Political Science, LSE Library.
• Guhan Sivakumar, 2025. "HMM-LSTM Fusion Model for Economic Forecasting," Papers 2501.02002, arXiv.org.
• Jairo Flores & Bruno Gonzaga & Walter Ruelas-Huanca & Juan Tang, 2024. "Nowcasting Peruvian GDP with Machine Learning Methods," Working Papers 2024-019, Banco Central de Reserva del Perú.
• Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024. "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper 122899, University Library of Munich, Germany.
• Ignacio Garr'on & Andrey Ramos, 2025. "High-frequency Density Nowcasts of U.S. State-Level Carbon Dioxide Emissions," Papers 2501.03380, arXiv.org.