Report NEP-FOR-2020-11-30

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-FOR

The following items were announced in this report:

• Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," NBER Working Papers 28014, National Bureau of Economic Research, Inc.
• Capek, Jan & Crespo Cuaresma, Jesus & Hauzenberger, Niko & Reichel, Vlastimil, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Paper Series 305, WU Vienna University of Economics and Business.
• Jan Capek & Jesus Crespo Cuaresma & Niko Hauzenberger & Vlastimil Reichel, 2020. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," Department of Economics Working Papers wuwp305, Vienna University of Economics and Business, Department of Economics.
• John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2020. "Commodity Futures Return Predictability and Intertemporal Asset Pricing," Working Papers 202011, Geary Institute, University College Dublin.
• Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Ooft, Gavin, 2020. "Forecasting Monthly Inflation: An Application To Suriname," Studies in Applied Economics 144, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
• Bo Zhang & Jamie Cross & Na Guo, 2020. "Time-Varying Trend Models for Forecasting Inflation in Australia," Working Papers No 09/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Francisco Blasques & Meindert Heres Hoogerkamp & Siem Jan Koopman & Ilka van de Werve, 2020. "Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data," Tinbergen Institute Discussion Papers 20-078/III, Tinbergen Institute, revised 21 Jan 2021.
• Sidra Mehtab & Jaydip Sen & Subhasis Dasgupta, 2020. "Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models," Papers 2011.08011, arXiv.org, revised Jan 2021.
• Deepanshu Sharma & Kritika Phulli, 2020. "Forecasting and Analyzing the Military Expenditure of India Using Box-Jenkins ARIMA Model," Papers 2011.06060, arXiv.org.
• Shao, Yongtong & Xiong, Tao & Li, Minghao & Hayes, Dermot & Zhang, Wendong & Xie, Wei, 2020. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," ISU General Staff Papers 202001010800001619, Iowa State University, Department of Economics.
• Westler, Richard & Spacek, John, 2020. "A Disaggregate Air Fare and Cost Model for Forecasting Aviation Traffic," Papers 305955, Canadian Transportation Research Forum (CTRF).
• Hamidreza Arian & Seyed Mohammad Sina Seyfi & Azin Sharifi, 2020. "Forecasting Probability of Default for Consumer Loan Management with Gaussian Mixture Models," Papers 2011.07906, arXiv.org.