IDEAS home Printed from https://ideas.repec.org/a/rnp/ecopol/ep1926.html
   My bibliography  Save this article

Monetary Policy Shocks in the Russian Economy and Their Macroeconomic Effects
[Шоки Процентной Политики Банка России И Оценка Их Макроэкономических Эффектов]

Author

Listed:
  • Pestova, Anna A. (Пестова, Анна)

    (Russian Presidential Academy of National Economy and Public Administration)

  • Mamonov, Mikhail E. (Мамонов, Михаил)

    (Russian Presidential Academy of National Economy and Public Administration)

  • Rostova, Natalia A. (Ростова, Наталья)

    (Russian Presidential Academy of National Economy and Public Administration)

Abstract

This section conducts an estimate of the impulse response function of key macroeconomic variables to monetary policy shocks in Russia. The estimates are carried out through a dynamic factor model (DFM) of the Russian economy with structural identification of shocks by imposing various sets of sign restrictions on the behavior of endogenous variables. We restricted first the monetary aggregate M2 only (a decrease in response to an increase of the Key rate), and then—simultaneously—M2, real effective exchange rate (an increase), and GDP (a decrease). We estimated the DFM using a large dataset of 58 macroeconomic and financial variables. The estimation results suggest that there is no decreasing response of consumer prices to an exogenous tightening of the interest rate policy of the Central Bank of Russia. This empirical evidence is supported implicitly by DFMbased predictions that under the imposition of such a decreasing response as an identifying restriction to the model, a positive interest rate shock is not transmitted through the interest rate channel of monetary policy to expected increases of the interest rates on commercial loans and private deposits. However, existing empirical evidence refutes this model-based result. Therefore, this study supports the view according to which a tightening of monetary policy in Russia is inefficient in terms of restraining inflation. In addition, monetary policy shocks negatively affect investments, retail sales, export and import, real wages, and employment. Different economic activities react differently to monetary policy shocks: exportoriented activities are not sensitive to these shocks, whereas domestic pro-cyclical activities (e.g. construction) can be substantially depressed in response to unexpected increases of interest rates. Finally, the expectations of economic agents are also significantly affected by shocks in the interest rate policy of the Bank of Russia.

Suggested Citation

  • Pestova, Anna A. (Пестова, Анна) & Mamonov, Mikhail E. (Мамонов, Михаил) & Rostova, Natalia A. (Ростова, Наталья), 2019. "Monetary Policy Shocks in the Russian Economy and Their Macroeconomic Effects [Шоки Процентной Политики Банка России И Оценка Их Макроэкономических Эффектов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 48-75, August.
    • Handle: RePEc:rnp:ecopol:ep1926
    as

    Download full text from publisher

    File URL: https://repec.ranepa.ru/rnp/ecopol/ep1926.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. A. Pestova., 2018. "On the effects of monetary policy in Russia: The role of the space of spanned shocks and the policy regime shifts," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 2.
    2. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    3. Drobyshevsky, Sergey M. (Дробышевский, Сергей) & Kiyutsevskaya, Anna M. (Киюцевская, Анна) & Trunin, Pavel V. (Трунин, Павел), 2018. "Scope of Interest Rate Policy of Central Banks [Возможности Процентной Политики Центральных Банков]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 42-61, August.
    4. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    5. Yury Achkasov, 2016. "Nowcasting of the Russian GDP Using the Current Statistics: Approach Modification," Bank of Russia Working Paper Series wps8, Bank of Russia.
    6. Mallick, Sushanta K. & Sousa, Ricardo M., 2012. "Real Effects Of Monetary Policy In Large Emerging Economies," Macroeconomic Dynamics, Cambridge University Press, vol. 16(S2), pages 190-212, September.
    7. 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.
    8. Mamonov, M., 2018. "Lending Channel of Monetary Policy in Russia: Microeconomic Estimates for Retail and Corporative Segments of Credit Market," Journal of the New Economic Association, New Economic Association, vol. 37(1), pages 112-144.
    9. Valery Charnavoki & Juan J. Dolado, 2014. "The Effects of Global Shocks on Small Commodity-Exporting Economies: Lessons from Canada," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(2), pages 207-237, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Valeria Zvereva & Olga Demidova & Dmitry Korshunov & Alexander Myasnikov, 2024. "Impact of Intraregional Income Inequality on the Operation of the Bank of Russia's Monetary Policy Transmission Mechanism," Russian Journal of Money and Finance, Bank of Russia, vol. 83(1), pages 3-31, March.
    2. Kurovskiy, Gleb, 2020. "Disentanglement of natural interest rate shocks and monetary policy shocks nexus," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 128-143.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pestova, Anna, 2020. "“Credit view” on monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 72-88.
    2. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    3. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    4. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.
    5. Baumeister, Christiane & Hamilton, James D., 2021. "Reprint: Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 114(C).
    6. Luke Mosley & Tak-Shing Chan & Alex Gibberd, 2023. "sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings," Papers 2303.14125, arXiv.org.
    7. Baumeister, Christiane & Hamilton, James D., 2020. "Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 109(C).
    8. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    9. Horvath, Jaroslav & Zhong, Jiansheng, 2019. "Unemployment dynamics in emerging countries: Monetary policy and external shocks," Economic Modelling, Elsevier, vol. 76(C), pages 31-49.
    10. Grebenkina, A. & Khandruev, A., 2021. "Difference in intensity of exchange rate factors in countries with targeting inflation regime," Journal of the New Economic Association, New Economic Association, vol. 51(3), pages 125-143.
    11. Stefano Neri & Tiziano Ropele, 2015. "The macroeconomic effects of the sovereign debt crisis in the euro area," Temi di discussione (Economic working papers) 1007, Bank of Italy, Economic Research and International Relations Area.
    12. Ono, Shigeki, 2021. "The effects of monetary policy in Russia: A factor-augmented VAR approach," Economic Systems, Elsevier, vol. 45(3).
    13. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    14. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    15. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    16. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    17. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Chinese liquidity increases and the U.S. economy," Economic Modelling, Elsevier, vol. 52(PB), pages 764-771.
    18. Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Swiss Finance Institute Research Paper Series 22-81, Swiss Finance Institute.
    19. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    20. Fan, Jianqing & Liao, Yuan & Shi, Xiaofeng, 2015. "Risks of large portfolios," Journal of Econometrics, Elsevier, vol. 186(2), pages 367-387.

    More about this item

    Keywords

    monetary policy; dynamic factor model (DFM); principal component analysis; structural identification; monetary policy shocks;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rnp:ecopol:ep1926. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RANEPA maintainer (email available below). General contact details of provider: https://edirc.repec.org/data/aneeeru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.