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Monetary Policy Surprises in Russia

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  • Alexander Tishin

    (Bank of Rusia)

Abstract

This paper studies the monetary policy transmission in the Russian economy. The key question of this research is to determine how monetary policy affects the economy through currency exchange rates. I construct a series of monetary policy surprises for the Russian economy using the high-frequency identification approach. Many papers use futures on interest rates as monetary policy instruments; however, we do not have these futures on the Russian financial market. Therefore, I use different currency futures as monetary surprises because these futures are liquid, and they may reveal market sentiments. I take the dates when the Board of Directors of the Bank of Russia made a decision on the key rate and look at the changes in the currency exchange market in a tiny 30-minute window. Next, I construct a structural vector autoregression model to show the effect of these surprises on macroeconomic variables. In the identification process, I use the external instruments approach a la Gertler and Karadi (2015). Finally, I compare the results with other methods (Cholesky decomposition). I find that a tightening monetary policy significantly increases the bond rate; moreover, the effect on inflation is not immediate, but appears after a couple of months.

Suggested Citation

  • Alexander Tishin, 2019. "Monetary Policy Surprises in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 78(4), pages 48-70, December.
  • Handle: RePEc:bkr:journl:v:78:y:2019:i:4:p:48-70
    DOI: 10.31477/rjmf.201904.48
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    References listed on IDEAS

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    1. Kuttner, Kenneth N., 2001. "Monetary policy surprises and interest rates: Evidence from the Fed funds futures market," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 523-544, June.
    2. Emi Nakamura & Jón Steinsson, 2018. "High-Frequency Identification of Monetary Non-Neutrality: The Information Effect," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1283-1330.
    3. Ambrogio Cesa-Bianchi & Gregory Thwaites & Alejandro Vicondoa, 2016. "Monetary Policy Transmission in an Open Economy: New Data and Evidence from the United Kingdom," Discussion Papers 1612, Centre for Macroeconomics (CFM), revised Aug 2016.
    4. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    5. Cieslak, Anna & Schrimpf, Andreas, 2019. "Non-monetary news in central bank communication," Journal of International Economics, Elsevier, vol. 118(C), pages 293-315.
    6. Christina D. Romer & David H. Romer, 2004. "A New Measure of Monetary Shocks: Derivation and Implications," American Economic Review, American Economic Association, vol. 94(4), pages 1055-1084, September.
    7. Refet S Gürkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    8. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    9. 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.
    10. Swanson, Eric T., 2021. "Measuring the effects of federal reserve forward guidance and asset purchases on financial markets," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 32-53.
    11. Lutz Kilian, 2013. "Structural vector autoregressions," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 22, pages 515-554, Edward Elgar Publishing.
    12. Mr. Andrea Pescatori, 2018. "Central Bank Communication and Monetary Policy Surprises in Chile," IMF Working Papers 2018/156, International Monetary Fund.
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    Cited by:

    1. Tretyakov, Dmitriy & Fokin, Nikita, 2020. "Помогают Ли Высокочастотные Данные В Прогнозировании Российской Инфляции? [Does the high-frequency data is helpful for forecasting Russian inflation?]," MPRA Paper 109556, University Library of Munich, Germany.
    2. 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.
    3. Brandao-Marques, Luis & Narita, Machiko & Nier, Erlend & Gelos, Gaston, 2021. "Leaning Against the Wind: An Empirical Cost-Benefit Analysis," CEPR Discussion Papers 15693, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    monetary policy transmission; external instruments; high-frequency identification; SVAR; currency futures;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • 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

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