IDEAS home Printed from https://ideas.repec.org/p/zbw/i4rdps/174.html
   My bibliography  Save this paper

A Replication of Anchored Inflation Expectations

Author

Listed:
  • Blagov, Boris
  • Guljanov, Gaygysyz
  • Kharazi, Aicha

Abstract

Carvalho et al. (2023) propose a theoretical framework that explains longrun inflation expectations' dynamic using short-run inflation surprises and beliefs about monetary policy. In an empirical exercise, they show that this concise framework predicts long-term inflation expectations well over long periods and across a multitude of countries. In this study we look at the reproducibility of the work and the robustness of the results across two dimensions - the strength of the empirical results and the robustness of the estimation methodology. Across the empirical dimension, we extend the model with data past the global pandemic and study the robustness of the results before 2020 as well as the strength of the conclusion after 2020. With respect to the methodological application, we utilise a different sampler to estimate the main non-linear specification. The original findings remain intact across both dimensions.

Suggested Citation

  • Blagov, Boris & Guljanov, Gaygysyz & Kharazi, Aicha, 2024. "A Replication of Anchored Inflation Expectations," I4R Discussion Paper Series 174, The Institute for Replication (I4R).
  • Handle: RePEc:zbw:i4rdps:174
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/305222/1/I4R-DP174.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlos Carvalho & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2023. "Anchored Inflation Expectations," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 1-47, January.
    2. Edward P. Herbst & Frank Schorfheide, 2016. "Bayesian Estimation of DSGE Models," Economics Books, Princeton University Press, edition 1, number 10612.
    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. Dominik Hecker & Maik Wolters & Maik H. Wolters, 2025. "Nonlinear Estimation of a New Keynesian Model with Endogenous Inflation De-Anchoring," CESifo Working Paper Series 12280, CESifo.
    2. 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.
    3. Kocięcki, Andrzej & Kolasa, Marcin, 2023. "A solution to the global identification problem in DSGE models," Journal of Econometrics, Elsevier, vol. 236(2).
    4. Hogen, Yoshihiko & Okuma, Ryoichi, 2025. "The anchoring of inflation expectations in Japan: A learning-approach perspective," Japan and the World Economy, Elsevier, vol. 73(C).
    5. Alexander Mihailov & Giovanni Razzu & Zhe Wang, 2019. "Heterogeneous effects of single monetary policy on unemployment rates in the largest EMU economies," Economics Discussion Papers em-dp2019-07, Department of Economics, University of Reading.
    6. Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What's Up with the Phillips Curve?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.
    7. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    8. Grimaud, Alex & Salle, Isabelle & Vermandel, Gauthier, 2025. "A Dynare toolbox for social learning expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    9. Corsello, Francesco & Neri, Stefano & Tagliabracci, Alex, 2021. "Anchored or de-anchored? That is the question," European Journal of Political Economy, Elsevier, vol. 69(C).
    10. Punnoose Jacob & Thomas van Florenstein Mulder, 2019. "The flattening of the Phillips curve: Rounding up the suspects," Reserve Bank of New Zealand Analytical Notes series AN2019/06, Reserve Bank of New Zealand.
    11. Mitsuru Katagiri, 2016. "Forward Guidance as a Monetary Policy Rule," Bank of Japan Working Paper Series 16-E-6, Bank of Japan.
    12. Fleischhacker, Jan, 2024. "Fiscal policy and the business cycle: An argument for non-linear policy rules," MPRA Paper 122497, University Library of Munich, Germany.
    13. Alok Johri & Muhebullah Karimzada, 2021. "Learning efficiency shocks, knowledge capital and the business cycle: A Bayesian evaluation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(3), pages 1314-1360, November.
    14. Yasufumi Gemma & Takushi Kurozumi & Mototsugu Shintani, 2023. "Trend Inflation and Evolving Inflation Dynamics:A Bayesian GMM Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 506-520, December.
    15. Lux, Thomas, 2020. "Bayesian estimation of agent-based models via adaptive particle Markov chain Monte Carlo," Economics Working Papers 2020-01, Christian-Albrechts-University of Kiel, Department of Economics.
    16. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    17. Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
    18. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
    19. DJINKPO, Medard, 2019. "A DSGE model for Fiscal Policy Analysis in The Gambia," MPRA Paper 97874, University Library of Munich, Germany, revised 30 Dec 2019.

    More about this item

    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:i4rdps:174. 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://www.i4replication.org/ .

    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.