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View Submission - CFE
Title: Nowcasting Euro area GDP with news sentiment: A tale of two crises Authors:  Julian Ashwin - London Business School (United Kingdom) [presenting]
Lorena Saiz - European Central Bank (Germany)
Eleni Kalamara - Kings College London (United Kingdom)
Abstract: The aim is to show that newspaper articles contain signals that can materially improve real-time nowcasts of real GDP growth for the euro area. Using articles from fifteen popular European newspapers, which are machine translated into English, we create daily sentiment metrics and assess their value for nowcasting, comparing to competitive and rigorous benchmarks. We find that newspaper text is especially helpful early in the quarter before other indicators are available. We also find that general-purpose sentiment measures perform better than more economics-focused ones in response to unanticipated events, and non-linear supervised models can help capture extreme movements in growth, but require sufficient training data in order to be effective.