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News media vs. FRED-MD for macroeconomic forecasting

Author

Listed:
  • Jon Ellingsen
  • Vegard H. Larsen
  • Leif Anders Thorsrud
Abstract
Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments.

Suggested Citation

  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0091
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    File URL: https://hdl.handle.net/11250/2682897
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    Cited by:

    1. Szymon Sacher & Laura Battaglia & Stephen Hansen, 2021. "Hamiltonian Monte Carlo for Regression with High-Dimensional Categorical Data," Papers 2107.08112, arXiv.org, revised Feb 2024.
    2. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    3. Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).

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    More about this item

    Keywords

    Forcasting; Real-time; Machine Learning; News; Text data;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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