Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/212808 
Year of Publication: 
2014
Series/Report no.: 
BOFIT Discussion Papers No. 22/2014
Publisher: 
Bank of Finland, Institute for Economies in Transition (BOFIT), Helsinki
Abstract: 
We apply an econometric approach developed specifically to address the 'curse of dimensionality' in Russian data and estimate a Bayesian vector autoregression model comprising 14 major domestic real, price and monetary macroeconomic indicators as well as external sector variables. We conduct several types of exercise to validate our model: impulse response analysis, recursive forecasting and counter factual simulation. Our results demonstrate that the employed methodology is highly appropriate for economic modelling in Russia. We also show that post-crisis real sector developments in Russia could be accurately forecast if conditioned on the oil price and EU GDP (but not if conditioned on the oil price alone). Publication
Subjects: 
Bayesian vector autoregression
forecasting
Russia
JEL: 
E32
E44
E47
C32
Persistent Identifier of the first edition: 
ISBN: 
978-952-323-010-1
Document Type: 
Working Paper

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