IDEAS home Printed from https://ideas.repec.org/p/bkr/wpaper/note3.html
   My bibliography  Save this paper

Money stock composition and inflation risks

Author

Listed:
  • Alexey Ponomarenko

    (Bank of Russia, Russian Federation)

Abstract

Revaluation of ruble value of foreign currency deposits and use of the Reserve Fund to finance budget deficit resulted in fast growth of broad money supply. The related inflation risks are currently moderate given that the money stock components with the fastest growth rates are not closely related to the aggregate demand. Nevertheless, inflation risks may increase in future if demand for liquid components of money supply grows and the composition of M2Y monetary aggregate returns to its 2011-2013 average values. We estimate that in this case the annual growth of household expenditures on final consumption may go up by 1.5 pp within two years, which may have negative inflation spillovers in 2017-2018.

Suggested Citation

  • Alexey Ponomarenko, 2016. "Money stock composition and inflation risks," Bank of Russia Working Paper Series note3, Bank of Russia.
    • Handle: RePEc:bkr:wpaper:note3
    as

    Download full text from publisher

    File URL: http://www.cbr.ru/Content/Document/File/87598/analytic_note_3_e.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexey Ponomarenko & Elena Vasilieva & Franziska Schobert, 2014. "Feedback to the ECB’s Monetary Analysis: The Bank of Russia’s Experience with Some Key Tools," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 2(2), pages 116-150, November.
    2. Elena Deryugina & Alexey Ponomarenko, 2015. "Accounting for Post-Crisis Macroeconomic Developments in Russia: A Large Bayesian Vector Autoregression Model Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(6), pages 1261-1275, November.
    3. Deryugina, Elena & Ponomarenko, Alexey, 2014. "A large Bayesian vector autoregression model for Russia," BOFIT Discussion Papers 22/2014, Bank of Finland Institute for Emerging Economies (BOFIT).
    Full references (including those not matched with items on IDEAS)

    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. Ramis Khabibullin & Alexey Ponomarenko & Sergei Seleznev, 2018. "Forecasting the implications of foreign exchange reserve accumulation with an agent-based model," Bank of Russia Working Paper Series wps37, Bank of Russia.
    2. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? : The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland, Institute for Economies in Transition.
    3. Mikhail Mamonov & Vera Pankova & Renat Akhmetov & Anna Pestova, 2020. "Financial Shocks and Credit Cycles," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 45-74, December.
    4. repec:zbw:bofitp:2019_013 is not listed on IDEAS
    5. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. 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.
    7. El-Shagi, Makram & Tochkov, Kiril, 2022. "Divisia monetary aggregates for Russia: Money demand, GDP nowcasting and the price puzzle," Economic Systems, Elsevier, vol. 46(4).
    8. Prüser Jan & Hanck Christoph, 2021. "A Comparison of Approaches to Select the Informativeness of Priors in BVARs," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(4), pages 501-525, August.
    9. Deryugina, Elena & Ponomarenko, Alexey, 2014. "A large Bayesian vector autoregression model for Russia," BOFIT Discussion Papers 22/2014, Bank of Finland Institute for Emerging Economies (BOFIT).
    10. Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
    11. Egorov D.A. (Егоров, Д.А.) & Perevyshina E.A. (Перевышина, Е.А.), 2016. "Modelling of Inflationary Processes in Russia [Моделирование Инфляционных Процессов В России]," Working Papers 2138, Russian Presidential Academy of National Economy and Public Administration.
    12. Usman Shakoor & Mudassar Rashid & Ashfaque Ali Baloch & Muhammad Iftikhar ul Husnain & Abdul Saboor, 2021. "How Aging Population Affects Health Care Expenditures in Pakistan? A Bayesian VAR Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 585-607, January.
    13. repec:zbw:bofitp:urn:nbn:fi:bof-201503111111 is not listed on IDEAS
    14. repec:bof:bofitp:urn:nbn:fi:bof-201503111111 is not listed on IDEAS
    15. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.
    16. 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.
    17. E. A. Fedorova & D. D. Airapetyan & S. O. Musienko & D. O. Afanas’ev & F. Yu. Fedorov, 2018. "Influence of Import Substitution Policy on the Industrial Production Level in Russia: Sector-Specific Issues," Studies on Russian Economic Development, Springer, vol. 29(2), pages 167-173, March.
    18. Elena Deryugina & Alexey Ponomarenko, 2017. "Money-based underlying inflation measure for Russia: a structural dynamic factor model approach," Empirical Economics, Springer, vol. 53(2), pages 441-457, September.
    19. Elena Deryugina & Olga Kovalenko & Irina Pantina & Alexey Ponomarenko, 2015. "Disentangling loan demand and supply shocks in Russia," Bank of Russia Working Paper Series wps3, Bank of Russia.
    20. Elena Deryugina & Olga Kovalenko & Irina Pantina & Alexey Ponomarenko, 2015. "Disentangling loan demand and supply shocks in Russia," Bank of Russia Working Paper Series wps3, Bank of Russia.
    21. repec:zbw:bofitp:2015_008 is not listed on IDEAS

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bkr:wpaper:note3. 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: BoR Research (email available below). General contact details of provider: https://edirc.repec.org/data/cbrgvru.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.