IDEAS home Printed from https://ideas.repec.org/a/spr/sorede/v35y2024i1d10.1134_s1075700724010027.html
   My bibliography  Save this article

Inflational Surge in the Second Half of the 2020s. Forecast Based on US Data on Commodity Prices and Minimum Wage Since 1946

Author

Listed:
  • S. V. Anureev

    (Financial University under the Government of the Russian Federation)

Abstract

The article proves a number of the author’s hypotheses about inflation in the United States: unexpected jumps in inflation are required to reduce the budget deficit and public debt to inflated GDP; these jumps and their fading are caused by greater amplitude of commodity prices; the key leading indicator of inflation is the level and plans to increase the federal minimum wage (FMW), as a reflection of the indexation of budget expenditures; there are usually two inflation spikes, with an intermediate fading to lower inflation expectations. These indicators are studied through data analysis since 1946, as well as a formalized logical-statistical model, similar to fundamental and technical analysis of financial markets. The next jump in US consumer prices is projected for 2025–2027 in the level of inflation in 2021–2022, which will require an increase in commodity prices, important for the Russian economy.

Suggested Citation

  • S. V. Anureev, 2024. "Inflational Surge in the Second Half of the 2020s. Forecast Based on US Data on Commodity Prices and Minimum Wage Since 1946," Studies on Russian Economic Development, Springer, vol. 35(1), pages 116-125, February.
  • Handle: RePEc:spr:sorede:v:35:y:2024:i:1:d:10.1134_s1075700724010027
    DOI: 10.1134/S1075700724010027
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1134/S1075700724010027
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1134/S1075700724010027?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stephen G. Cecchetti & Rita S. Chu & Charles Steindel, 2000. "The unreliability of inflation indicators," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 6(Apr).
    2. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    3. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    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. Hillebrand, Eric & Lukas, Manuel & Wei, Wei, 2021. "Bagging weak predictors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 237-254.
    2. Afees A. Salisu & Raymond Swaray & Hadiza Sa'id, 2021. "Improving forecasting accuracy of the Phillips curve in OECD countries: The role of commodity prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2946-2975, April.
    3. Kazeem O. Isah & Abdulkader C. Mahomedy & Elias A. Udeaja & Ojo J. Adelakun & Yusuf Yakubu & Danmecca Musa, 2022. "Revisiting the accuracy of inflation forecasts in Nigeria: The oil price–exchange rate–asymmetry perspectives," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 329-348, September.
    4. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    6. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
    7. Verbrugge, Randal & Zaman, Saeed, 2023. "The hard road to a soft landing: Evidence from a (modestly) nonlinear structural model," Energy Economics, Elsevier, vol. 123(C).
    8. Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024. "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1521-1538.
    9. Canelli, Rosa & Fontana, Giuseppe & Realfonzo, Riccardo & Passarella, Marco Veronese, 2024. "Energy crisis, economic growth and public finance in Italy," Energy Economics, Elsevier, vol. 132(C).
    10. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    11. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    12. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    13. Miyazaki, Tomomi & Hiraga, Kazuki & Kozuka, Masafumi, 2024. "Stock market response to public investment under the zero lower bound: Cross-industry evidence from Japan," Journal of the Japanese and International Economies, Elsevier, vol. 71(C).
    14. 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.
    15. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    16. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    17. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    18. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2023. "Understanding trend inflation through the lens of the goods and services sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 751-766, August.
    19. Winkelried, Diego, 2023. "Simple interpolations of inflation expectations," Economics Letters, Elsevier, vol. 229(C).
    20. James M. Nason & Gregor W. Smith, 2021. "Measuring the slowly evolving trend in US inflation with professional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.

    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:spr:sorede:v:35:y:2024:i:1:d:10.1134_s1075700724010027. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.