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Report NEP-FOR-2019-06-17
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:
- Saulius Jokubaitis & Dmitrij Celov & Remigijus Leipus, 2019, "Sparse structures with LASSO through Principal Components: forecasting GDP components in the short-run," Papers, arXiv.org, number 1906.07992, Jun, revised Oct 2020.
- Timmermann, Allan & Zhu, Yinchu, 2019, "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13746, May.
- 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, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2019-24.
- Oleksiy Kryvtsov & Luba Petersen, 2019, "Central Bank Communication That Works: Lessons from Lab Experiments," Staff Working Papers, Bank of Canada, number 19-21, Jun, DOI: 10.34989/swp-2019-21.
- Mueller, Hannes & Rauh, Christopher, 2019, "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13748, May.
- Szabolcs Deák & Paul Levine & Afrasiab Mirza & Joseph Pearlman, 2019, "Designing Robust Monetary Policy Using Prediction Pools," School of Economics Discussion Papers, School of Economics, University of Surrey, number 1219, Jun.
- 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, Monash University, Department of Econometrics and Business Statistics, number 12/19.