Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/212991 
Year of Publication: 
2017
Series/Report no.: 
BoF Economics Review No. 6/2017
Publisher: 
Bank of Finland, Helsinki
Abstract: 
Timely and accurate assessment of current macroeconomic activity is crucial for policymakers and other economic agents. Nowcasting aims to forecast the current economic situation ahead of official data releases. We develop and apply a large Bayesian vector autoregressive (BVAR) model to nowcast quarterly GDP growth rate of the Finnish economy. We study the BVAR model’s out-of-sample performance at different forecasting horizons, and compare to various bridge models and a dynamic factor model.
Subjects: 
ennusteet
mallit
BVAR
Suomi
bkt
JEL: 
C52
C53
E32
E37
Persistent Identifier of the first edition: 
Document Type: 
Research Report

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