Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/278605
Authors: 
Year of Publication: 
2023
Series/Report no.: 
IRENE Working Paper No. 23, 02
Publisher: 
University of Neuchâtel, Institute of Economic Research (IRENE), Neuchâtel
Abstract: 
This paper evaluates whether publicly available daily news lead texts help nowcasting Swiss GDP growth. I collect titles and lead texts from three Swiss newspapers and calculate text-based indicators for various economic concepts. A composite indicator calculated from these indicators is highly correlated with low-frequency macroeconomic data and survey-based indicators. In a pseudo out-of-sample nowcasting exercise for Swiss GDP growth, the indicator outperforms a monthly Swiss business cycle indicator if one month of information is available. Improvements in nowcasting accuracy mainly occur in times of economic distress.
Subjects: 
Mixed-frequency data
composite leading indicator
news sentiment
recession
natural language processing
nowcasting
JEL: 
C53
E32
E37
Document Type: 
Working Paper

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