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Report NEP-FOR-2022-08-15
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:
- Francis X. Diebold & Maximilian Goebel & Philippe Goulet Coulombe, 2022, "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Papers, arXiv.org, number 2206.10721, Jun, revised Jun 2023.
- Sylvia Kaufmann, 2022, "Covid-19 outbreak and beyond: A retrospect on the information content of registered short-time workers for GDP now- and forecasting," Working Papers, Swiss National Bank, Study Center Gerzensee, number 22.02R, Jul.
- Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022, "Nowcasting the Portuguese GDP with Monthly Data," Papers, arXiv.org, number 2206.06823, Jun.
- Item repec:cam:camjip:2213 is not listed on IDEAS anymore
- Jyldyz Djumalieva & Stef Garasto & Cath Sleeman, 2020, "Evaluating a new earnings indicator. Can we improve the timeliness of existing statistics on earnings by using salary information from online job adverts?," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2020-19, Dec.
- Timo Dimitriadis & Yannick Hoga, 2022, "Dynamic CoVaR Modeling and Estimation," Papers, arXiv.org, number 2206.14275, Jun, revised Jan 2025.
- Jeonggil Song, 2022, "Predicting Economic Welfare with Images on Wealth," Papers, arXiv.org, number 2206.14810, Jun.
- Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022, "On the impact of serial dependence on penalized regression methods," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number 2022/21, Jul.
- S. Roderick Zhang & Bilal Farooq, 2022, "Interpretable and Actionable Vehicular Greenhouse Gas Emission Prediction at Road link-level," Papers, arXiv.org, number 2206.09073, Jun.