Report NEP-FOR-2024-11-11

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:

• Yang Liu & Ran Pan & Rui Xu, 2024. "Mending the Crystal Ball: Enhanced Inflation Forecasts with Machine Learning," IMF Working Papers 2024/206, International Monetary Fund.
• Zongwu Cai & Gunawan & Yuying Sun, 2024. "A New Nonparametric Combination Forecasting with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202412, University of Kansas, Department of Economics, revised Sep 2024.
• Ali Mehrabani, 2024. "Stein-Like Shrinkage Estimators for Coefficients of a Single-Equation in Simultaneous Equation Systems," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202414, University of Kansas, Department of Economics.
• Theophilus G. Baidoo & Ashley Obeng, 2024. "Navigating Inflation in Ghana: How Can Machine Learning Enhance Economic Stability and Growth Strategies," Papers 2410.05630, arXiv.org.
• Liu, Yirui & Qiao, Xinghao & Pei, Yulong & Wang, Liying, 2024. "Deep functional factor models: forecasting high-dimensional functional time series via Bayesian nonparametric factorization," LSE Research Online Documents on Economics 125587, London School of Economics and Political Science, LSE Library.
• Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).