Printed from https://ideas.repec.org/n/nep-for/2019-11-04.html
Report NEP-FOR-2019-11-04
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:
- Tae-Hwy Lee & Eric Hillebrand & Huiyu Huang & Canlin Li, 2018, "Using the Entire Yield Curve in Forecasting Output and Inflation," Working Papers, University of California at Riverside, Department of Economics, number 201903, Aug.
- Tae-Hwy Lee & Yundong Tu, 2018, "Forecasting Using Supervised Factor Models," Working Papers, University of California at Riverside, Department of Economics, number 201909, Dec.
- Gergely Ganics & Florens Odendahl, 2019, "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers, Banque de France, number 733.
- Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019, "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers, University of Pretoria, Department of Economics, number 201977, Oct.
- Tae-Hwy Lee & Bai Huang & Aman Ullah, 2018, "A Combined Random Effect and Fixed Effect Forecast for Panel Data Models," Working Papers, University of California at Riverside, Department of Economics, number 201906, Dec.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019, "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economics Research Papers, Friedrich-Schiller-University Jena, number 2019-006, Sep.
- González-Rivera, Gloria & Luo, Yun & Ruiz Ortega, Esther, 2019, "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de EstadÃstica, number 29054, Oct.
- Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019, "Prediction Regions for Interval-valued Time Series," Working Papers, University of California at Riverside, Department of Economics, number 201921, Sep.
- Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019, "Testing Forecast Rationality for Measures of Central Tendency," Papers, arXiv.org, number 1910.12545, Oct, revised Jul 2024.
- Masayuki MORIKAWA, 2019, "Uncertainty in Long-Term Macroeconomic Forecasts: Ex post Evaluation of Forecasts by Economics Researchers," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 19084, Oct.
- Masayuki MORIKAWA, 2019, "Uncertainty in Long-Term Economic Forecasts (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 19058, Oct.
- Ooft, G. & Bhaghoe, S. & Franses, Ph.H.B.F., 2019, "Forecasting Annual Inflation in Suriname," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2019-32, Sep.
- Domenico Delli Gatti & Jakob Grazzini, 2019, "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series, CESifo, number 7894.
- Halbleib, Roxana & Dimitriadis, Timo, 2019, "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy, Verein für Socialpolitik / German Economic Association, number 203669.
- Hinterlang, Natascha, 2019, "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy, Verein für Socialpolitik / German Economic Association, number 203503.
- Michael Coelli & Jeff Borland, 2019, "Behind the headline number: Why not to rely on Frey and Osborne’s predictions of potential job loss from automation," Melbourne Institute Working Paper Series, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, number wp2019n10, Oct.
- Tae-Hwy Lee & Yiyao Wang, 2018, "Evaluation of the Survey of Professional Forecasters in the Greenbook’s Loss Function," Working Papers, University of California at Riverside, Department of Economics, number 201904, Aug.