IDEAS home Printed from https://ideas.repec.org/p/zbw/imfswp/183.html
   My bibliography  Save this paper

Has the reaction function of the European Central Bank changed over time?

Author

Listed:
  • Tatar, Balint

Abstract

I have assessed changes in the monetary policy stance in the euro area since its inception by applying a Bayesian time-varying parameter framework in conjunction with the Hamiltonian Monte Carlo algorithm. I find that the estimated policy response has varied considerably over time. Most of the results suggest that the response weakened after the onset of the financial crisis and while quantitative measures were still in place, although there are also indications that the weakening of the response to the expected inflation gap may have been less pronounced. I also find that the policy response has become more forceful over the course of the recent sharp rise in inflation. Furthermore, it is essential to model the stochastic volatility relating to deviations from the policy rule as it materially influences the results.

Suggested Citation

  • Tatar, Balint, 2023. "Has the reaction function of the European Central Bank changed over time?," IMFS Working Paper Series 183, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
  • Handle: RePEc:zbw:imfswp:183
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/271089/1/1844789152.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Krippner, Leo, 2013. "Measuring the stance of monetary policy in zero lower bound environments," Economics Letters, Elsevier, vol. 118(1), pages 135-138.
    2. Orphanides, Athanasios, 2004. "Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 151-175, April.
    3. Boivin, Jean, 2006. "Has U.S. Monetary Policy Changed? Evidence from Drifting Coefficients and Real-Time Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1149-1173, August.
    4. Maritta Paloviita & Markus Haavio & Pirkka Jalasjoki & Juha Kilponen, 2021. "What Does "Below, but Close to, 2 Percent" Mean? Assessing the ECB's Reaction Function with Real-Time Data," International Journal of Central Banking, International Journal of Central Banking, vol. 17(2), pages 125-169, June.
    5. Stefan Gerlach & John Lewis, 2014. "ECB Reaction Functions and the Crisis of 2008," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 137-158, March.
    6. Kim, Chang-Jin & Nelson, Charles R., 2006. "Estimation of a forward-looking monetary policy rule: A time-varying parameter model using ex post data," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1949-1966, November.
    7. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tatar, Balint & Wieland, Volker, 2025. "Policy rules and the inflation surge: The case of the ECB," Economics Letters, Elsevier, vol. 252(C).

    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. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    2. Andreas Beyer & Vitor Gaspar & Christina Gerberding & Otmar Issing, 2013. "Opting Out of the Great Inflation: German Monetary Policy after the Breakdown of Bretton Woods," NBER Chapters, in: The Great Inflation: The Rebirth of Modern Central Banking, pages 301-346, National Bureau of Economic Research, Inc.
    3. Yüksel, Ebru & Metin-Ozcan, Kivilcim & Hatipoglu, Ozan, 2013. "A survey on time-varying parameter Taylor rule: A model modified with interest rate pass-through," Economic Systems, Elsevier, vol. 37(1), pages 122-134.
    4. Christina Anderl & Guglielmo Maria Caporale, 2024. "Time-varying parameters in monetary policy rules: a GMM approach," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(9), pages 148-176, January.
    5. Chang-jin Kim & N. Kundan Kishor & Charles R Nelson, 2006. "A Time-Varying Parameter Model for a Forward-Looking Monetary Policy Rule Based on Real-Time Data," Working Papers UWEC-2007-32, University of Washington, Department of Economics.
    6. Gießler, Stefan, 2020. "The evolution of monetary policy in Latin American economies: Responsiveness to inflation under different degrees of credibility," IWH Discussion Papers 9/2020, Halle Institute for Economic Research (IWH).
    7. Yanbin Chen & Zhen Huo, 2009. "A Conjecture of Chinese Monetary Policy Rule: Evidence from Survey Data, Markov Regime Switching, and Drifting Coefficients," Annals of Economics and Finance, Society for AEF, vol. 10(1), pages 111-153, May.
    8. Best, Gabriela, 2017. "Policy Preferences And Policy Makers' Beliefs: The Great Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 21(8), pages 1957-1995, December.
    9. 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.
    10. Jurkšas, Linas & Pereira, Francisco Gomes, 2024. "Fiscal stance role for ECB monetary policy," Journal of Policy Modeling, Elsevier, vol. 46(6), pages 1210-1227.
    11. Zhang, Chengsi & Dang, Chao, 2018. "Is monetary policy forward-looking in China?," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 4-14.
    12. Dennis Wesselbaum, 2022. "Cheap Talk in a New Keynesian Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 661-691, September.
    13. Michael D. Bauer & Eric T. Swanson, 2023. "A Reassessment of Monetary Policy Surprises and High-Frequency Identification," NBER Macroeconomics Annual, University of Chicago Press, vol. 37(1), pages 87-155.
    14. Creel, Jérôme & Hubert, Paul, 2015. "Has Inflation Targeting Changed The Conduct Of Monetary Policy?," Macroeconomic Dynamics, Cambridge University Press, vol. 19(1), pages 1-21, January.
    15. ZHENG, Tingguo & WANG, Xia & GUO, Huiming, 2012. "Estimating forward-looking rules for China's Monetary Policy: A regime-switching perspective," China Economic Review, Elsevier, vol. 23(1), pages 47-59.
    16. Kishor, N. Kundan, 2012. "A Note On Time Variation In A Forward-Looking Monetary Policy Rule: Evidence From European Countries," Macroeconomic Dynamics, Cambridge University Press, vol. 16(S3), pages 422-437, November.
    17. Kevin Lee & James Morley & Kalvinder Shields, 2015. "The Meta Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 73-98, February.
    18. Cour-Thimann, Philippine & Jung, Alexander, 2021. "Interest-rate setting and communication at the ECB in its first twenty years," European Journal of Political Economy, Elsevier, vol. 70(C).
    19. Davide Debortoli & Ricardo Nunes, 2014. "Monetary Regime Switches and Central Bank Preferences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(8), pages 1591-1626, December.
    20. 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.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    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:imfswp:183. 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/hoffmde.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.