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Autor:innen: 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
IRENE Working Paper No. 23-02
Verlag: 
University of Neuchâtel, Institute of Economic Research (IRENE), Neuchâtel
Zusammenfassung: 
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.
Schlagwörter: 
Mixed-frequency data
composite leading indicator
news sentiment
recession
natural language processing
nowcasting
JEL: 
C53
E32
E37
Dokumentart: 
Working Paper

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