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Bayesian estimation of monetary policy in Russia

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  • Lomivorotov, Rodion

    (Higher School of Economics, Moscow;)

Abstract

In this research we implement Bayesian Vector Autoregressive model (BVAR) to analyze effect of internal and external shocks on Russian economy. This method allows to identify main transmission channels of monetary policy changes, as well as external shocks. Compared with traditional methods BVAR provides more consistent and accurate identifications for models with large number of variables and estimated on small samples. Bayesian model also produce more accurate out-of-sample forecasts compared with traditional SVAR model, FAVAR and Random Walk.

Suggested Citation

  • Lomivorotov, Rodion, 2015. "Bayesian estimation of monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 41-63.
  • Handle: RePEc:ris:apltrx:0264
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    References listed on IDEAS

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    Cited by:

    1. Константин Орлов // Konstantin Orlov, 2021. "Построение большой байесовской авторегрессионной модели для Казахстана // Building a Large Bayesian Vector Autoregression Model for Kazakhstan," Working Papers #2021-1, National Bank of Kazakhstan.
    2. Andrey Feliksovich Bedin & Alexander Vladimirovich Kulikov & Andrey Vladimirovich Polbin, 2021. "A Markov Switching VECM Model for Russian Real GDP, Real Exchange Rate and Oil Prices," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 402-412.
    3. M. Tiunova G. & М. Тиунова Г., 2018. "Влияние Внешних Шоков На Российскую Экономику // The Impact Of External Shocks On The Russian Economy," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 146-170.
    4. Daniil Lomonosov & Andrey Polbin & Nikita Fokin, 2021. "The Impact of Global Economic Activity, Oil Supply and Speculative Oil Shocks on the Russian Economy," HSE Economic Journal, National Research University Higher School of Economics, vol. 25(2), pages 227-262.
    5. Borzykh, Olga, 2016. "Bank lending channel in Russia: A TVP-FAVAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 96-117.
    6. Salmanov, Oleg & Zaernjuk, Victor & Lopatina, Olga & Drachena, Irina & Vikulina, Evgeniya, 2016. "Investigating the Impact of Monetary Policy using the Vector Autoregression Method," MPRA Paper 112280, University Library of Munich, Germany, revised 01 Jun 2016.
    7. O. Borzykh., 2017. "The impact of banks’ capital adequacy ratio on bank lending channel of monetary transmission in Russia," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 7.
    8. 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.
    9. Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
    10. Борзых Ольга Алексеевна, 2016. "«Антиэффект» Ликвидности В Российской Банковской Системе," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(3), pages 377-414.
    11. Lomonosov, Daniil & Polbin, Andrey & Fokin, Nikita, 2020. "Влияние Шоков Мировой Деловой Активности, Предложения Нефти И Спекулятивных Нефтяных Шоков На Экономику Рф [The impact of global economic activity, oil supply and speculative oil shocks on the Russ," MPRA Paper 106019, University Library of Munich, Germany.
    12. A. Polbin., 2017. "Econometric estimation of the impact of oil prices shock on the Russian economy in VECM model," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 10.
    13. Egorov, Aleksei V. (Егоров, Алексей В.) & Borzykh, Olga A. (Борзых, Ольга А.), 2018. "Asymmetric Interest Rate Pass-Through in Russia [Асимметрия Процентного Канала Денежной Трансмиссии В России]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 92-121, February.

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    More about this item

    Keywords

    monetary policy; external shocks; Bayesian estimation; forecasts;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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