Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/319609 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
Bank of Finland Research Discussion Papers No. 6/2025
Verlag: 
Bank of Finland, Helsinki
Zusammenfassung: 
We analyse the accuracy of an econometric model for nowcasting GDP growth in a true real-time setting. The analysis is based on a unique sample of nowcasts that were produced in real time and stored. Our results support the use of econometric models for nowcasting because the accuracy of these real-time nowcasts is found to be comparable to the first GDP estimates of the statistical authority. The nowcasts are produced by a large Bayesian vector autoregressive model. We find the model fares well against other statistical models, and the results suggest that its performance has been more robust to COVID-19 fluctuations than that of a dynamic factor model. We also analyse comments on the nowcast tweets published on Twitter in real time.
Schlagwörter: 
Nowcasting
Real-time analysis
Vector autoregressions
Bayesian methods
Mixed frequency
Business cycles
JEL: 
C11
C52
C53
E32
E37
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
2.08 MB





Publikationen in EconStor sind urheberrechtlich geschützt.