Template-Type: ReDIF-Paper 1.0

Author-Name: Elena Deryugina
Author-Email: DeryuginaEB@cbr.ru
Author-Workplace-Name: Bank of Russia, Russian Federation

Author-Name: Alexey Ponomarenko
Author-Email: PonomarenkoAA@cbr.ru
Author-Workplace-Name: Bank of Russia, Russian Federation


Title:  A large Bayesian vector autoregression model for Russia
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 macroeco-nomic indicators as well as external sector variables. We conduct several types of exercise to validate our model: im-pulse response analysis, recursive forecasting and counter factual simulation. Our results demonstrate that the em-ployed 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).

Length: 23 pages
Creation-Date: 2015-03
Revision-Date:
Publication-Status:
File-URL: http://www.cbr.ru/Content/Document/File/87554/wps_1_e.pdf
File-Format: Application/pdf
File-Function:
Number:wps1
Classification-JEL: E32, E44, E47, C32
Keywords: Bayesian vector autoregression, forecasting, Russia
Handle: RePEc:bkr:wpaper:wps1