IDEAS home Printed from https://ideas.repec.org/a/aiy/jnjaer/v24y2025i1p59-90.html
   My bibliography  Save this article

Analysis of the Relationship between Inflation, Exchange Rate and Household Expenditures in the Russian Economy Using Wavelet Analysis

Author

Listed:
  • Leonid A. Serkov

Abstract

This article presents an analysis of the relationship between the inflation rate, the ruble to the US dollar exchange rate and household spending in the Russian economy. This study used econometric tools and the multivariate wavelet analysis (MWA) method, which includes multiple and partial wavelet coherence to analyze the relationship between the analyzed variables in different frequency and time ranges, partial phase difference and partial wavelet gain coefficient to estimate the magnitude of the relationship. In fact, the MWA method is a regression in the frequency-time range. The results obtained by means of multivariate wavelet analysis, on the one hand, coincide with the results of the econometric method, and on the other hand, show the advantages of multivariate wavelet analysis over econometric analysis due to the frequency-time localization of time series features. It is shown that household expenditures in both the short and long term are a more important determinant compared to the exchange rate in the dependence of the inflation rate on these variables. Of particular interest are the results obtained by the MWA method for the current time period characterized by the presence of sanctions imposed on the Russian economy by unfriendly countries. In particular, in the current period from 2022 to the second quarter of 2024, there is a short-term and medium-term two-way causality between the inflation rate and household expenditures. At the same time, the partial wavelet gain coefficient during this period is constantly increasing and reaches a maximum in the second quarter of 2024. That is, the mutual elasticities of the inflation rate by expenditures and household expenditures by inflation are constantly increasing. The results of the analysis of high-frequency cycles are of interest to short-term decision makers. The results obtained for medium and low-frequency cycles are of interest to those developing plans for the medium and long term.

Suggested Citation

  • Leonid A. Serkov, 2025. "Analysis of the Relationship between Inflation, Exchange Rate and Household Expenditures in the Russian Economy Using Wavelet Analysis," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 24(1), pages 59-90.
  • Handle: RePEc:aiy:jnjaer:v:24:y:2025:i:1:p:59-90
    DOI: https://doi.org/10.15826/vestnik.2025.24.1.003
    as

    Download full text from publisher

    File URL: https://journalaer.ru//fileadmin/user_upload/site_15934/2025/03_Serkov.pdf
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.15826/vestnik.2025.24.1.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Svensson, Lars E. O., 2000. "Open-economy inflation targeting," Journal of International Economics, Elsevier, vol. 50(1), pages 155-183, February.
    2. Olivier Coibion & Dimitris Georgarakos & Yuriy Gorodnichenko & Maarten van Rooij, 2023. "How Does Consumption Respond to News about Inflation? Field Evidence from a Randomized Control Trial," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 109-152, July.
    3. Aguiar-Conraria, Luis & Martins, Manuel M.F. & Soares, Maria Joana, 2018. "Estimating the Taylor rule in the time-frequency domain," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 122-137.
    4. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    5. Rüdiger Bachmann & Tim O. Berg & Eric R. Sims, 2015. "Inflation Expectations and Readiness to Spend: Cross-Sectional Evidence," American Economic Journal: Economic Policy, American Economic Association, vol. 7(1), pages 1-35, February.
    6. Cosimo Magazzino & Mihai Mutascu, 2019. "A wavelet analysis of Italian fiscal sustainability," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-13, December.
    7. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    8. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    9. Jordi Galí, 2008. "Introduction to Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework," Introductory Chapters, in: Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework, Princeton University Press.
    10. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
    11. Carl E. Walsh, 2010. "Monetary Theory and Policy, Third Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262013770, December.
    12. Krüger, Jens J., 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149598, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Magazzino, Cosimo & Mele, Marco, 2021. "On the relationship between transportation infrastructure and economic development in China," Research in Transportation Economics, Elsevier, vol. 88(C).
    14. Duca-Radu, Ioana & Kenny, Geoff & Reuter, Andreas, 2021. "Inflation expectations, consumption and the lower bound: Micro evidence from a large multi-country survey," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 120-134.
    15. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    16. Sara El Aboudi & Youssef Jouali & Mounir El Bakkouchi & Abdellah Echaoui, 2024. "Analyzing the Dynamics of Inflation, Exchange Rates and Economic Growth through the Gini Index: Modeling VAR in Morocco," International Journal of Economics and Financial Issues, Econjournals, vol. 14(6), pages 136-144, October.
    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. Bui, Dzung & Dräger, Lena & Hayo, Bernd & Nghiem, Giang, 2020. "Consumer Sentiment During the COVID-19 Pandemic: The Role of Others‘ Beliefs," Hannover Economic Papers (HEP) dp-680, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Apr 2021.
    2. Lena Dräger & Michael J. Lamla, 2024. "Consumers' macroeconomic expectations," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 427-451, April.
    3. Andrade, Philippe & Gautier, Erwan & Mengus, Eric, 2023. "What matters in households’ inflation expectations?," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 50-68.
    4. Binder, Carola Conces & Kamdar, Rupal & Ryngaert, Jane M., 2024. "Partisan expectations and COVID-era inflation," Journal of Monetary Economics, Elsevier, vol. 148(S).
    5. Janet Hua Jiang & Rupal Kamdar & Kelin Lu & Daniela Puzzello, 2024. "How Do Households Respond to Expected Inflation? An Investigation of Transmission Mechanisms," Staff Working Papers 24-44, Bank of Canada.
    6. Krüger, Jens J., 2024. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149438, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    8. Niizeki, Takeshi & Hori, Masahiro, 2023. "Inflation expectations and household expenditure: Evidence from pseudo-panel data in Japan," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 308-324.
    9. Bairoliya, Neha & McKiernan, Kathleen, 2024. "The welfare costs of misinformation," Journal of Economic Dynamics and Control, Elsevier, vol. 169(C).
    10. Mundra, Sruti & Bicchal, Motilal, 2024. "Financial cycle comovement with monetary and macroprudential policy and global factors: Evidence from India," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    11. Andreani, Michele & Giri, Federico, 2024. "Mortgages, house prices, and business cycle dynamic: A medium-run exploration using the continuous wavelet transform," International Review of Economics & Finance, Elsevier, vol. 94(C).
    12. Seiler, Volker, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 160-179.
    13. Alan S. Blinder & Michael Ehrmann & Jakob de Haan & David-Jan Jansen, 2024. "Central Bank Communication with the General Public: Promise or False Hope?," Journal of Economic Literature, American Economic Association, vol. 62(2), pages 425-457, June.
    14. Qian, Wei, 2023. "House price expectations and household consumption," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    15. Sören Harrs & Lara Marie Müller & Bettina Rockenbach, 2021. "How Optimistic and Pessimistic Narratives about COVID-19 Impact Economic Behavior," ECONtribute Discussion Papers Series 091, University of Bonn and University of Cologne, Germany.
    16. George Tzagkarakis & Frantz Maurer, 2020. "An energy-based measure for long-run horizon risk quantification," Annals of Operations Research, Springer, vol. 289(2), pages 363-390, June.
    17. Kenny, Geoff & Duca, Ioana, 2021. "Can consumers’ inflation expectations help stabilise the economy?," Research Bulletin, European Central Bank, vol. 79.
    18. Philippe Andrade & Gaetano Gaballo & Eric Mengus & Benoît Mojon, 2019. "Forward Guidance and Heterogeneous Beliefs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(3), pages 1-29, July.
    19. Dräger, Lena & Lamla, Michael J. & Pfajfar, Damjan, 2020. "The Hidden Heterogeneity of Inflation and Interest Rate Expectations: The Role of Preferences," Hannover Economic Papers (HEP) dp-666, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Feb 2023.
    20. Shomesh E. Chaudhuri & Andrew W. Lo, 2019. "Dynamic Alpha: A Spectral Decomposition of Investment Performance Across Time Horizons," Management Science, INFORMS, vol. 65(9), pages 4440-4450, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

    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:aiy:jnjaer:v:24:y:2025:i:1:p:59-90. 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: Natalia Starodubets (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.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.