News media vs. FRED-MD for macroeconomic forecasting

Jon Ellingsen, Vegard Larsen and Leif Thorsrud

No No 08/2020, Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School

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.

Keywords: Forcasting; Real-time; Machine Learning; News; Text data (search for similar items in EconPapers)
Pages: 45 pages
Date: 2020-10
New Economics Papers: this item is included in nep-big and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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https://hdl.handle.net/11250/2682897

Related works:
Working Paper: News media vs. FRED-MD for macroeconomic forecasting (2020)
Working Paper: News Media vs. FRED-MD for Macroeconomic Forecasting (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:bny:wpaper:0091

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