IDEAS home Printed from https://ideas.repec.org/p/zbw/bofitb/317789.html

What do simple short-term models say about the latest economic trends in Russia?

Author

Listed:
  • Simola, Heli

Abstract

We consider the applicability of simple statistical models to Russia's short-term economic trends in a wartime context. We develop several composite indicators combining economic variables to predict Russian GDP trends both before and after the invasion if Ukraine in 2022. In addition, our SVAR model estimations highlight the exceptionality of wartime. Russia's actual GDP performance in 2022 is considerably weaker than predicted by our model. The situation then reverses in 2023 and particularly at end-2024 the GDP outperforms model predictions.

Suggested Citation

  • Simola, Heli, 2025. "What do simple short-term models say about the latest economic trends in Russia?," BOFIT Policy Briefs 9/2025, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Handle: RePEc:zbw:bofitb:317789
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/317789/1/1925831442.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
    2. Jouko Rautava, 2013. "Oil Prices, Excess Uncertainty and Trend Growth," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 77-87.
    3. Simola, Heli, 2024. "Detecting irregularities in Russian economic statistics," BOFIT Policy Briefs 9/2024, 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. Simone Auer & Emidio Cocozza & Andrea COlabella, 2016. "The financial systems in Russia and Turkey: recent developments and challenges," Questioni di Economia e Finanza (Occasional Papers) 358, Bank of Italy, Economic Research and International Relations Area.
    2. Nikita Fokin, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
    3. Deryugina, Elena & Ponomarenko, Alexey, 2014. "A large Bayesian vector autoregression model for Russia," BOFIT Discussion Papers 22/2014, Bank of Finland, Institute for Economies in Transition.
    4. Ivan Stankevich, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    5. 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.
    6. Ivan Stankevich, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    7. Andrey Polbin & Mikhail Andreyev & Andrey Zubarev, 2018. "How Commodity Prices Influence the Members of the Eurasian Economic Union," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 623-637.
    8. 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).
    9. Salmsnov, Oleg & Babina, Natalia & Koba, Ekaterina & Koba, Ekaterina & Lopatina, Olga, 2017. "Efficiency of Monetary Policy Mechanisms Before and After the 2008 Financial Crisis in the Russian Economy," MPRA Paper 112276, University Library of Munich, Germany, revised 01 Jul 2017.
    10. Parviainen, Sinikka & Pyle, William, 2025. "Household well-being under sanctions: Insights from the Russian longitudinal monitoring survey," BOFIT Policy Briefs 8/2025, Bank of Finland Institute for Emerging Economies (BOFIT).
    11. A. Polbin, 2017. "Modeling the real ruble exchange rate under monetary policyregime change," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    12. Kudrin, Alexey & Gurvich, Evsey, 2015. "A new growth model for the Russian economy1," Russian Journal of Economics, Elsevier, vol. 1(1), pages 30-54.
    13. Idrisov, Georgy & Kazakova, Maria & Polbin, Andrey, 2015. "A theoretical interpretation of the oil prices impact on economic growth in contemporary Russia," Russian Journal of Economics, Elsevier, vol. 1(3), pages 257-272.
    14. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
    15. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2020. "The Performance Of Business And Consumer Sentiment For Early Estimates Of Gdp Growth: Old Turning Points And New Challenges Of The Corona Crisis," HSE Working papers WP BRP 110/STI/2020, National Research University Higher School of Economics.
    16. Polbin, Andrey, 2017. "Моделирование Реального Курса Рубля В Условиях Изменения Режима Денежно-Кредитной Политики [Modeling the real ruble exchange rate under monetary policy regime change]," MPRA Paper 78139, University Library of Munich, Germany.
    17. M. S. Gusev & V. S. Ustinov & R. E. Rakoch, 2025. "Results for Short-Term Forecasting of Economic Dynamics Based on Bridge Equations and Time Series Extrapolation," Studies on Russian Economic Development, Springer, vol. 36(3), pages 304-312, June.
    18. Bozhechkova, Alexandera V. (Божечкова, Александра В.) & Polbin, Andrey V. (Полбин, Андрей В.), 2018. "Evidence for the Interest Rate Channel in the IS Curve for the Russian Economy [Тестирование Наличия Процентного Канала В Кривой Is Для Российской Экономики]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 70-91, February.
    19. 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.
    20. Svetlana Zenchenko & Wadim Strielkowski & Luboš Smutka & Tomáš Vacek & Yana Radyukova & Vladislav Sutyagin, 2022. "Monetization of the Economies as a Priority of the New Monetary Policy in the Face of Economic Sanctions," JRFM, MDPI, vol. 15(3), pages 1-18, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:zbw:bofitb:317789. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/bofitfi.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.