Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/229457 
Year of Publication: 
2020
Series/Report no.: 
CESifo Working Paper No. 8639
Publisher: 
Center for Economic Studies and Ifo Institute (CESifo), Munich
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.
Subjects: 
forecasting
real-time
machine learning
news
text data
JEL: 
C53
C55
E27
E37
Document Type: 
Working Paper
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