IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0299.html
   My bibliography  Save this article

Bank lending channel in Russia: A TVP-FAVAR approach

Author

Listed:
  • Borzykh, Olga

    (Central Bank of the Russian Federation (Bank of Russia), Moscow, Russian Federation)

Abstract

Implementation of inflation targeting by the Bank of Russia depends on the effectiveness of the channels of monetary policy transmission mechanism. In this article we use a TVP-FAVAR model to examine the bank lending channel. This channel describes the connection between monetary policy impulses and the amount of bank loans that are among the main sources of investments in Russia. In order to answer the main question we analyze the connection between the amount of bank loans and the money market interest rate MIACR which is the main operational target of the Bank of Russia. The use of TVP-FAVAR model allowed to solve a problem of omitted variables and to take into account gradual changes which occurred in the Russian economy during the period from January 2004 to December 2015. It is shown that the bank lending channel works only through the group of big banks that does not include biggest state-owned banks.

Suggested Citation

  • 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.
    • Handle: RePEc:ris:apltrx:0299
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2016_43_096-117.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitris Korobilis, 2013. "Assessing the Transmission of Monetary Policy Using Time-varying Parameter Dynamic Factor Models-super-," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 157-179, April.
    2. 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.
    3. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    4. repec:zbw:bofitp:2009_008 is not listed on IDEAS
    5. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, Oxford University Press, vol. 120(1), pages 387-422.
    6. repec:zbw:bofitp:2011_020 is not listed on IDEAS
    7. Colin Ellis & Haroon Mumtaz & Pawel Zabczyk, 2014. "What Lies Beneath? A Time‐varying FAVAR Model for the UK Transmission Mechanism," Economic Journal, Royal Economic Society, vol. 0(576), pages 668-699, May.
    8. Sergey Drobyshevsky & Pavel Trunin & M. Kamenskikh, 2008. "Analysis of Transmission Mechanisms of Money and Credit Policy in Russia's Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 116P.
    9. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
    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. Silvo Dajčman & Alenka Kavkler & Sergey Merzlyakov & Sergey E. Pekarski & Dejan Romih, 2022. "International Transmission of Conventional and Unconventional Monetary Policy and Financial Stress Shocks from the Euro Area to Russia," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(1), pages 227-247.
    2. Ono, Shigeki, 2021. "The effects of monetary policy in Russia: A factor-augmented VAR approach," Economic Systems, Elsevier, vol. 45(3).
    3. Filipp Prokopev, 2021. "Balance Sheet Channel of Monetary Policy Evidence from Credit Spreads of Russian Firms," Russian Journal of Money and Finance, Bank of Russia, vol. 80(4), pages 3-30, December.
    4. Kurovskiy, Gleb, 2019. "Disentanglement of natural interest rate shocks and monetary policy shocks nexus," MPRA Paper 97547, University Library of Munich, Germany.
    5. 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.
    6. 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.
    7. 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]," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 48-75, August.
    8. 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.
    9. Aizhan Bolatbayeva & Alisher Tolepbergen & Nurdaulet Abilov, 2020. "A macroeconometric model for Russia," Russian Journal of Economics, ARPHA Platform, vol. 6(2), pages 114-143, June.
    10. Irina Semina, 2020. "Modelling the Risk-taking Channel of Monetary Policy in the Russian Economy," Russian Journal of Money and Finance, Bank of Russia, vol. 79(3), pages 30-57, September.

    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. Esteban Prieto & Sandra Eickmeier & Massimiliano Marcellino, 2016. "Time Variation in Macro‐Financial Linkages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1215-1233, November.
    2. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.
    3. Anastasios Evgenidis & Costas Siriopoulos, 2015. "What are the International Channels Through Which a US Policy Shock is Transmitted to The World Economies? Evidence from a Time Varying FAVAR," Working Papers 190, Bank of Greece.
    4. Huber, Florian & Punzi, Maria Teresa, 2020. "International Housing Markets, Unconventional Monetary Policy, And The Zero Lower Bound," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 774-806, June.
    5. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
    6. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    7. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    8. Glocker, Christian & Sestieri, Giulia & Towbin, Pascal, 2019. "Time-varying government spending multipliers in the UK," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 180-197.
    9. Njindan Iyke, Bernard, 2016. "Are Monetary Policy Disturbances Important in Ghana? Some Evidence from Agnostic Identification," MPRA Paper 70205, University Library of Munich, Germany.
    10. Olli-Matti Juhani Laine, 2020. "The effect of the ECB’s conventional monetary policy on the real economy: FAVAR-approach," Empirical Economics, Springer, vol. 59(6), pages 2899-2924, December.
    11. Jan Prüser & Alexander Schlösser, 2020. "The effects of economic policy uncertainty on European economies: evidence from a TVP-FAVAR," Empirical Economics, Springer, vol. 58(6), pages 2889-2910, June.
    12. Prüser, Jan & Schlösser, Alexander, 2018. "On the time-varying effects of economic policy uncertainty on the US economy," Ruhr Economic Papers 761, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    14. Jan Prüser & Alexander Schlösser, 2020. "On the Time‐Varying Effects of Economic Policy Uncertainty on the US Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1217-1237, October.
    15. Anastasios Evgenidis & Dionisis Philippas & Costas Siriopoulos, 2019. "Heterogeneous effects in the international transmission of the US monetary policy: a factor-augmented VAR perspective," Empirical Economics, Springer, vol. 56(5), pages 1549-1579, May.
    16. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
    17. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    18. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    19. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "Dynamics of the term structure of UK interest rates," Bank of England working papers 363, Bank of England.
    20. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.

    More about this item

    Keywords

    monetary policy; bank lending channel; the Russian banks; groups of banks; TVP-FAVAR approach;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:ris:apltrx:0299. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    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: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.