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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, National Bureau of Economic Research, Inc, number 28014, Oct.
- 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, WU Vienna University of Economics and Business, number 305, Nov.
- 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, Vienna University of Economics and Business, Department of Economics, number wuwp305, Nov.
- John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2020, "Commodity Futures Return Predictability and Intertemporal Asset Pricing," Working Papers, Geary Institute, University College Dublin, number 202011, Nov.
- Behrens, Christoph, 2020, "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 26, DOI: 10.18452/22093.
- Gavin Ooft, 2020, "Forecasting Monthly Inflation: An Application To Suriname," Studies in Applied Economics, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise, number 144, Jan.
- Bo Zhang & Jamie Cross & Na Guo, 2020, "Time-Varying Trend Models for Forecasting Inflation in Australia," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 09/2020, Nov.
- 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, Tinbergen Institute, number 20-078/III, Nov, 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, arXiv.org, number 2011.08011, Nov, revised Jan 2021.
- Deepanshu Sharma & Kritika Phulli, 2020, "Forecasting and Analyzing the Military Expenditure of India Using Box-Jenkins ARIMA Model," Papers, arXiv.org, number 2011.06060, Nov.
- 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, Iowa State University, Department of Economics, number 202001010800001619, Jan.
- Item repec:ags:cantrf:305955 is not listed on IDEAS anymore
- Hamidreza Arian & Seyed Mohammad Sina Seyfi & Azin Sharifi, 2020, "Forecasting Probability of Default for Consumer Loan Management with Gaussian Mixture Models," Papers, arXiv.org, number 2011.07906, Nov.