IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v68y2025i6d10.1007_s00181-024-02709-6.html
   My bibliography  Save this article

Empirical similarity for revealing the US interest rate policy: modeling case-based decisions of the FOMC

Author

Listed:
  • Vasyl Golosnoy

    (Ruhr-Universität Bochum)

  • Yarema Okhrin

    (University of Augsburg)

  • Michael W. M. Roos

    (Ruhr-Universität Bochum)

Abstract

We model the Fed’s decisions about interest rate adjustments via the flexible nonlinear empirical similarity (ES) concept which relies on ideas of case-based reasoning particularly suitable for decision making under uncertainty. We postulate that the Fed’s adjustment decision in a given situation should be close to those in similar economic situations. We evaluate the empirical fit of the ES concept in comparison with the linear reaction function related to the Taylor rule for the period from 1987 till 2008. We identify and analyze critical time points particularly for those Fed decisions which were conducted in rather uncertain economic environments.

Suggested Citation

  • Vasyl Golosnoy & Yarema Okhrin & Michael W. M. Roos, 2025. "Empirical similarity for revealing the US interest rate policy: modeling case-based decisions of the FOMC," Empirical Economics, Springer, vol. 68(6), pages 2799-2828, June.
    • Handle: RePEc:spr:empeco:v:68:y:2025:i:6:d:10.1007_s00181-024-02709-6
    DOI: 10.1007/s00181-024-02709-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-024-02709-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-024-02709-6?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    2. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
    3. Olivier Coibion & Yuriy Gorodnichenko, 2011. "Monetary Policy, Trend Inflation, and the Great Moderation: An Alternative Interpretation," American Economic Review, American Economic Association, vol. 101(1), pages 341-370, February.
    4. I. Gilboa & A. Postlewaite & L. Samuelson & D. Schmeidler, 2015. "Economic models as analogies," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    5. Frederic S. Mishkin, 2011. "Monetary Policy Strategy: Lessons from the Crisis," NBER Working Papers 16755, National Bureau of Economic Research, Inc.
    6. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    7. Gayer Gabrielle & Gilboa Itzhak & Lieberman Offer, 2007. "Rule-Based and Case-Based Reasoning in Housing Prices," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-37, April.
    8. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    9. Alan S. Blinder & Ricardo Reis, 2005. "Understanding the Greenspan standard," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 11-96.
    10. Antoine Billot & Itzhak Gilboa & David Schmeidler, 2012. "Axiomatization of an Exponential Similarity Function," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 10, pages 245-257, World Scientific Publishing Co. Pte. Ltd..
    11. repec:bla:intfin:v:5:y:2002:i:1:p:129-37 is not listed on IDEAS
    12. John B. Taylor, 2012. "Monetary Policy Rules Work and Discretion Doesn’t: A Tale of Two Eras," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1017-1032, September.
    13. Paul De Grauwe, 2002. "Central Banking as Art or Science?: Lessons from the Fed and the ECB," International Finance, Wiley Blackwell, vol. 5(1), pages 129-137.
    14. Alan S. Blinder & Ricardo Reis, 2005. "Understanding the Greenspan standard," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 11-96.
    15. Jinho Bae & Chang-Jin Kim & Dong Kim, 2012. "The evolution of the monetary policy regimes in the U.S," Empirical Economics, Springer, vol. 43(2), pages 617-649, October.
    16. Gnabo, Jean-Yves & Moccero, Diego Nicolas, 2015. "Risk management, nonlinearity and aggressiveness in monetary policy: The case of the US Fed," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 281-294.
    17. Alan Greenspan, 2004. "Risk and Uncertainty in Monetary Policy," American Economic Review, American Economic Association, vol. 94(2), pages 33-40, May.
    18. Vasyl Golosnoy & Jens Hogrefe, 2013. "Signaling NBER turning points: a sequential approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 438-448, February.
    19. Vasyl Golosnoy & Iryna Okhrin & Wolfgang Schmid, 2012. "Statistical Surveillance of Volatility Forecasting Models," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 513-543, June.
    20. Michael Woodford, 2003. "Optimal Interest-Rate Smoothing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(4), pages 861-886.
    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. Ahmad, Saad, 2016. "A multiple threshold analysis of the Fed's balancing act during the Great Moderation," Economic Modelling, Elsevier, vol. 55(C), pages 343-358.
    2. Gnabo, Jean-Yves & Moccero, Diego Nicolas, 2015. "Risk management, nonlinearity and aggressiveness in monetary policy: The case of the US Fed," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 281-294.
    3. Olivier Coibion & Yuriy Gorodnichenko, 2011. "Monetary Policy, Trend Inflation, and the Great Moderation: An Alternative Interpretation," American Economic Review, American Economic Association, vol. 101(1), pages 341-370, February.
    4. Narek Ohanyan & Aleksandr Grigoryan, 2021. "Measuring monetary policy: rules versus discretion," Empirical Economics, Springer, vol. 61(1), pages 35-60, July.
    5. Jiang, Lei, 2014. "Stock liquidity and the Taylor rule," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 202-214.
    6. Robert Tchaidze & Alina Carare, 2004. "The Use and Abuse of Taylor Rules: How precisely can we estimate them?," Econometric Society 2004 Latin American Meetings 132, Econometric Society.
    7. Jinshun Wu & Luyao Wu, 2024. "Bayesian Local Likelihood Estimation of Time-Varying DSGE Models: Allowing for Indeterminacy," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2437-2476, October.
    8. Drakos, Anastassios A. & Kouretas, Georgios P., 2015. "The conduct of monetary policy in the Eurozone before and after the financial crisis," Economic Modelling, Elsevier, vol. 48(C), pages 83-92.
    9. Caggiano, Giovanni & Castelnuovo, Efrem & Nodari, Gabriela, 2018. "Risk management-driven policy rate gap," Economics Letters, Elsevier, vol. 171(C), pages 235-238.
    10. Francois Gourio & Jonas Fisher, 2015. "Risk Management for Monetary Policy at the Zero Lower Bound," 2015 Meeting Papers 665, Society for Economic Dynamics.
    11. Dibooglu, Sel & Erdogan, Seyfettin & Yildirim, Durmus Cagri & Cevik, Emrah Ismail, 2020. "Financial conditions and monetary policy in the US," Economic Systems, Elsevier, vol. 44(4).
    12. Jamol Bahromov, 2022. "Regime-switching empirical similarity model: a comparison with baseline models," Empirical Economics, Springer, vol. 63(5), pages 2655-2674, November.
    13. Cendejas Bueno, José Luis & Castañeda, Juan Enrique & Muñoz, Félix, 2015. "Business cycles and monetary regimes in the U.S. (1960 – 2014): A plea for monetary stability," Working Papers in Economic Theory 2015/05, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    14. Bordo, Michael & Istrefi, Klodiana, 2023. "Perceived FOMC: The making of hawks, doves and swingers," Journal of Monetary Economics, Elsevier, vol. 136(C), pages 125-143.
    15. Marco Del Negro & Frank Schorfheide, 2009. "Monetary Policy Analysis with Potentially Misspecified Models," American Economic Review, American Economic Association, vol. 99(4), pages 1415-1450, September.
    16. Enrico Sergio Levrero, 2022. "The Taylor Rule and its Aftermath: Elements for an Interpretation along Classical-Keynesian lines," Centro Sraffa Working Papers CSWP59, Centro di Ricerche e Documentazione "Piero Sraffa".
    17. Cúrdia, Vasco & Ferrero, Andrea & Ng, Ging Cee & Tambalotti, Andrea, 2015. "Has U.S. monetary policy tracked the efficient interest rate?," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 72-83.
    18. Jagjit S. Chadha & Luisa Corrado, 2006. "On the Determinacy of Monetary Policy under Expectational Errors," CDMA Working Paper Series 200603, Centre for Dynamic Macroeconomic Analysis, revised 15 Apr 2007.
    19. Bhavesh Salunkhe & Anuradha Patnaik, 2018. "The IS Curve and Monetary Policy Transmission in India: A New Keynesian Perspective," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 12(1), pages 41-66, February.
    20. van der Ploeg, Frederick, 2004. "Prudent Monetary Policy: Applications of Cautious LQG Control and Prediction," CEPR Discussion Papers 4222, C.E.P.R. Discussion Papers.

    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:spr:empeco:v:68:y:2025:i:6:d:10.1007_s00181-024-02709-6. 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.