A Large Bayesian Vector Autoregression Model for Russia

24 Pages Posted: 16 Dec 2014 Last revised: 17 May 2016

Date Written: December 4, 2014

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 keywords: Bayesian vector autoregression, forecasting, Russia

JEL Classification: E32, E44, E47, C32

Suggested Citation

Deryugina, Elena and Ponomarenko, Alexey A., A Large Bayesian Vector Autoregression Model for Russia (December 4, 2014). BOFIT Discussion Paper No. 22/2014, Available at SSRN: https://ssrn.com/abstract=2686550

Elena Deryugina (Contact Author)

Bank of Russia ( email )

12 Neglinnaya Street
Moscow, 107016
Russia

Alexey A. Ponomarenko

Central Bank of Russia ( email )

12 Neglinnaya Street
Moscow, 107016
Russia

HOME PAGE: http://http.//www.cbr.ru

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