BAYESIAN APPROACH TO EVALUATE THE IMPACT OF EXTERNAL SHOCKS ON RUSSIAN MACROECONOMICS INDICATORS

Abstract

One of the promising approaches of macroeconomic modeling and quantitative assessment of the impact of external and internal factors on macroeconomy of a country, which is actively used abroad, is a Bayesian approach to the estimation of vector autoregressions. In this paper we examine Bayesian vector autoregression model (BVAR) to assess the impact of external shocks, such as the price of Brent crude oil, the volatility index VIX and the Shanghai Stock Exchange Composite index, on Russian macroeconomic indicators. The results allow us to estimate the contribution of external factors as a significant in the dynamics of Russia economic variables. This approach can be successfully applied for the analysis of Russian data, which was confirmed by the results presented in the article.

Keywords

• BVAR
• байесовская векторная авторегрессия
• внешнеэкономические шоки
• макроэкономика
• распределение Миннесоты
• BVAR
• Bayesian methods
• external shocks
• macroeconomics
• Minnesota prior