1. BAYESIAN APPROACH TO EVALUATE THE IMPACT OF EXTERNAL SHOCKS ON RUSSIAN MACROECONOMICS INDICATORS
- Author
-
A. A. Shevelev
- Subjects
Macroeconomics ,0209 industrial biotechnology ,Bayesian methods ,Bayesian probability ,02 engineering and technology ,распределение Миннесоты ,symbols.namesake ,020901 industrial engineering & automation ,Stock exchange ,0202 electrical engineering, electronic engineering, information engineering ,Economics ,Quantitative assessment ,макроэкономика ,байесовская векторная авторегрессия ,Minnesota prior ,Volatility index ,lcsh:HB71-74 ,lcsh:Economics as a science ,macroeconomics ,Bayesian vector autoregression ,external shocks ,внешнеэкономические шоки ,Brent Crude ,symbols ,020201 artificial intelligence & image processing ,Composite index ,BVAR - 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 description of macroeconomic processes. 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.
- Published
- 2017