News Media vs. FRED-MD for Macroeconomic Forecasting
Jon Ellingsen,
Vegard Larsen and
Leif Thorsrud
No 8639, CESifo Working Paper Series from CESifo
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: forecasting; real-time; machine learning; news; text data (search for similar items in EconPapers)
JEL-codes: C53 C55 E27 E37 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp8639.pdf (application/pdf)
Related works:
Working Paper: News media vs. FRED-MD for macroeconomic forecasting (2020) 
Working Paper: News media vs. FRED-MD for macroeconomic forecasting (2020) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_8639
Access Statistics for this paper
More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().