Nowcasting the Finnish economy with a large Bayesian vector autoregressive model

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Title: Nowcasting the Finnish economy with a large Bayesian vector autoregressive model
Author: Itkonen, Juha ; Juvonen, Petteri
Organization: Bank of Finland
Suomen Pankki
Series: BoF Economics Review
Series year: 2017
Series number: 6/2017
Year of publication: 2017
Publication date: 18.12.2017
Pages: 22
Subject (yso): taloudelliset mallit; taloudelliset ennusteet; bruttokansantuote
Keywords: ennusteet; mallit; BVAR; Suomi; bkt
JEL: C52; C53; E32; E37
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.
Rights: https://helda.helsinki.fi/bof/copyright


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