Nowcasting the Finnish economy with a large Bayesian vector autoregressive model
Itkonen, Juha; Juvonen, Petteri (18.12.2017)
Numero
6/2017Julkaisija
Bank of FinlandSuomen Pankki
2017
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:bof-201712181708Tiivistelmä
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.