Estimation of Russia's GDP Losses Due to Sanctions Using the Global Vector Autoregression Model

Abstract

Using mathematical and statistical methods, the authors made an attempt to estimate the losses in the domestic economy under the impact of the imposed sanctions. As a measurement tool is proposed a global vector autoregression model. In this model, the dynamics of GDP is considered as the main performance characteristic, and the rate of change in foreign trade turnover with key partners is used as the key prerequisites for the forecast. The use of this model building scheme is explained by the fact that the economic sanctions imposed on Russia have a negative impact on domestic macroeconomic indicators, and this happens through a variety of channels, key ones being the restriction of external demand and supply, leading to a decrease in trade turnover with the main trading partners, and change in oil revenues. This approach takes into account the relationship between the economies of different countries and their dependence on global markets. To obtain quantitative estimates, conditional forecasts are used as part of scenario analysis.According to the authors’ approach the losses from economic sanctions are measured by the decrease in the volume of Russia's foreign trade with key foreign trade partners, as well as by the discount for Russian oil compared to its global price. In addition to the forecast estimates, the validity of the approach is proofed with the forecast for the crisis period of 2014–2015 as an example. Based on the analysis of the current situation in foreign trade, Russian GDP in 2022 in the baseline scenario may fall by 5.4%, but with some reorientation of trade a decrease may be around 3.7%.