IDEAS home Printed from https://ideas.repec.org/a/fip/fedfel/103483.html

Using Inflation Shock Patterns to Help Forecast Inflation

Author

Abstract

A new indicator—the Inflation Shock Momentum Index—can help identify emerging inflationary or disinflationary pressures in real time. The index tracks the shares of consumer spending categories that are experiencing consecutive positive or negative monthly inflation shocks, allowing detection of shifts in the underlying inflation environment. The index improves inflation forecasts at one-year to three-year horizons and responds to macroeconomic shocks in line with accepted theory. Recent index readings have fluctuated above and below zero, indicating that inflation may remain near current levels in the near to medium term.

Suggested Citation

  • Kevin J. Lansing & Adam Hale Shapiro, 2026. "Using Inflation Shock Patterns to Help Forecast Inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, vol. 2026(18), pages 1-6, July.
  • Handle: RePEc:fip:fedfel:103483
    as

    Download full text from publisher

    File URL: https://www.frbsf.org/wp-content/uploads/el2026-18.pdf
    File Function: PDF - view
    Download Restriction: no

    File URL: https://www.frbsf.org/research-and-insights/publications/economic-letter/2026/07/using-inflation-shock-patterns-to-help-forecast-inflation/
    File Function: FRBSF - view
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kevin J. Lansing & Adam Hale Shapiro, 2026. "Measuring Inflation Shock Momentum," Working Paper Series 2026-10, Federal Reserve Bank of San Francisco.
    2. Diego R. Känzig, 2021. "The Macroeconomic Effects of Oil Supply News: Evidence from OPEC Announcements," American Economic Review, American Economic Association, vol. 111(4), pages 1092-1125, April.
    3. Romer, Christina D. & Romer, David H., 2024. "Lessons from history for successful disinflation," Journal of Monetary Economics, Elsevier, vol. 148(S).
    4. 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.
    5. James H. Stock & Mark W. Watson, 2007. "Erratum to “Why Has U.S. Inflation Become Harder to Forecast?”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    6. Kevin J. Lansing, 2022. "Untangling Persistent versus Transitory Shocks to Inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, vol. 2022(13), pages 1-05, May.
    7. 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. Kevin J. Lansing & Adam Hale Shapiro, 2026. "Measuring Inflation Shock Momentum," Working Paper Series 2026-10, Federal Reserve Bank of San Francisco.
    2. Bonaparte, Yosef & Fabozzi, Frank J. & Peron, Matt, 2025. "Measuring transitory inflation: Implications for monetary policy and stock market volatility," Journal of International Money and Finance, Elsevier, vol. 153(C).
    3. Drobysheva, Alexandra (Дробышева, Александра) & Merzlyakov, Sergey (Мерзляков, Сергей), 2024. "The Forward Guidance Puzzle and Anchored Inflation Expectations," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, issue 6, pages 6-25.
    4. Gertjan Vlieghe, 2025. "Core strength: international evidence on the impact of energy prices on core inflation," Economica, London School of Economics and Political Science, vol. 92(366), pages 406-419, April.
    5. 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).
    6. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    7. Marcus Buckmann & Galina Potjagailo & Philip Schnattinger, 2025. "Blockwise Boosted Inflation: Non-linear determinants of inflation using machine learning," Bank of England Staff Working Paper series 1143, Bank of England.
    8. 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.
    9. Ruhollah Eskandari & Morteza Zamanian, 2023. "Heterogeneous responses to corporate marginal tax rates: Evidence from small and large firms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1018-1047, November.
    10. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    11. Lukmanova, Elizaveta & Rabitsch, Katrin, 2023. "Evidence on monetary transmission and the role of imperfect information: Interest rate versus inflation target shocks," European Economic Review, Elsevier, vol. 158(C).
    12. Anjara Lalaina Jocelyn Rakotoarisoa, 2024. "Modélisations Univariées de l’Inflation Mensuelle à Madagascar : l’Atout du Modèle LSTM, un Réseau de Neurones Récurrents," Post-Print hal-04766563, HAL.
    13. Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
    14. repec:uta:papers:2025-01 is not listed on IDEAS
    15. Kishaba, Yui & Okuda, Tatsushi, 2025. "The slope of the Phillips curve for service prices in Japan: Regional panel data approach," Journal of the Japanese and International Economies, Elsevier, vol. 78(C).
    16. Chen, Jiazi & Hong, Zhiwu & Niu, Linlin, 2025. "Forecasting interest rates with shifting endpoints: The role of the functional demographic age distribution," International Journal of Forecasting, Elsevier, vol. 41(1), pages 153-174.
    17. Pär Österholm & Aubrey Poon, 2023. "Trend Inflation in Sweden," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4707-4716, October.
    18. Nguyen Duc Do, 2025. "Using a Wage–Price‐Setting Model to Forecast US Inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 803-832, March.
    19. John O’Trakoun, 2023. "An alternative measure of core inflation: the Trimmed Persistence PCE price index," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 58(4), pages 205-223, October.
    20. Siklos, Pierre L., 2021. "The macroeconomic response to real and financial factors, commodity prices, and monetary policy: International evidence," Economic Systems, Elsevier, vol. 45(1).
    21. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.

    More about this item

    Keywords

    ;
    ;

    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:fip:fedfel:103483. 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: Federal Reserve Bank of San Francisco Research Library (email available below). General contact details of provider: https://edirc.repec.org/data/frbsfus.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.