Report NEP-FOR-2019-06-17This 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.
The following items were announced in this report:
- Saulius Jokubaitis & Dmitrij Celov, 2019. "Forecasting the US GDP Components in the short run," Papers 1906.07992, arXiv.org.
- Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
- Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Oleksiy Kryvtsov & Luba Petersen, 2019. "Central Bank Communication That Works: Lessons from Lab Experiments," Staff Working Papers 19-21, Bank of Canada.
- Mueller, Hannes Felix & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
- Szabolcs Deák & Paul Levine & Afrasiab Mirza & Joseph Pearlman, 2019. "Designing Robust Monetary Policy Using Prediction Pools," School of Economics Discussion Papers 1219, School of Economics, University of Surrey.
- Earo Wang & Dianne Cook & Rob J Hyndman, 2019. "A New Tidy Data Structure to Support Exploration and Modeling of Temporal Data," Monash Econometrics and Business Statistics Working Papers 12/19, Monash University, Department of Econometrics and Business Statistics.