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Bayesian approach to evaluate the impact of external shocks on Russian macroeconomics indicators

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  • Shevelev A.A.

    (Новосибирский государственный университет)

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.

Suggested Citation

  • Shevelev A.A., 2017. "Bayesian approach to evaluate the impact of external shocks on Russian macroeconomics indicators," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 17(1), pages 26-40.
  • Handle: RePEc:nos:wjflnh:2017_1_03e
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    References listed on IDEAS

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    Cited by:

    1. И Управления Мир Экономики, 2017. "Байесовский подход к анализу влияния монетарной политики на макроэкономические показатели России. Bayesian approach to the analysis of monetary policy impact on Russian macroeconomics indicators," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(4), pages 53-70.
    2. Mariya A. Shchepeleva, 2020. "Modeling the Balance Sheet Channel of Monetary Transmission in Russia," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 2, pages 39-56, April.

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    More about this item

    Keywords

    BVAR; Bayesian methods; external shocks; macroeconomics; Minnesota prio;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General

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