Estimation of the Impact of Global Shocks on the Russian Economy and GDP Nowcasting Using a Factor Model

This study estimates the contribution of global supply and demand shocks and global commodity shocks to the dynamics of Russian macroeconomic indicators. The main research tool is a factor-augmented vector autoregression model, which allows for the identification of global factors in a wide range of variables. Both sign and short-term restrictions are used to identify global shocks. Through impulse response function analysis of a set of Russian indicators, it is found that all of the identified global shocks have an impact on the Russian economy. A forecast error variance decomposition reveals a significant contribution from external shocks, up to 70%, to the dynamics of key real macroeconomic indicators, while price indices and trade turnover prove to be more sensitive to domestic shocks, with a contribution of up to 50%. We also study the evolution of the impact of the shocks in question on macroeconomic variables over time, estimating the model over two sub-periods, whereby we find a qualitative change in the impact of external shocks on a number of variables, such as exports and consumption. In addition, a reduced factor model for Russian GDP nowcasting is constructed, which outperforms the medium-sized Bayesian vector autoregression model and other alternatives in terms of predictive power.