IDEAS home Printed from https://ideas.repec.org/a/bla/buecrs/v67y2015i1p65-82.html
   My bibliography  Save this article

Are Long-Term Inflation Expectations Well-Anchored? Evidence From The Euro Area And The United States

Author

Listed:
  • Tsvetomira Tsenova

Abstract

type="main"> This paper analyses the stability of long-term inflation expectations and uncertainty, based on their sensitivity to innovations to observed inflation, short- and medium-term forecast news. News is defined in a subjective sense and derived from revisions to shorter-term fixed-target forecasts. The assessment tests for presence of non-linear effects, including regime changes during disinflation in the USA in the 1990s and the recent financial crisis. Stability is also investigated in terms of level evolution, based on a structural non-linear and non-Gaussian learning model to uncover the presence of a common trend underlying the long-term dynamics of inflation, individual expectations, and uncertainty.

Suggested Citation

  • Tsvetomira Tsenova, 2015. "Are Long-Term Inflation Expectations Well-Anchored? Evidence From The Euro Area And The United States," Bulletin of Economic Research, Wiley Blackwell, vol. 67(1), pages 65-82, January.
  • Handle: RePEc:bla:buecrs:v:67:y:2015:i:1:p:65-82
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1467-8586.2012.00474.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    2. Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
    3. Athanasios Orphanides & John C. Williams, 2005. "Inflation scares and forecast-based monetary policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 498-527, April.
    4. Orphanides, Athanasios & Williams, John C., 2007. "Robust monetary policy with imperfect knowledge," Journal of Monetary Economics, Elsevier, vol. 54(5), pages 1406-1435, July.
    5. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
    6. Goodfriend, Marvin & King, Robert G., 2005. "The incredible Volcker disinflation," Journal of Monetary Economics, Elsevier, vol. 52(5), pages 981-1015, July.
    7. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, June.
    8. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
    9. Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2008. "Here is the news: forecast revisions in the Bank of England survey of external forecasters," National Institute Economic Review, National Institute of Economic and Social Research, vol. 203(1), pages 68-77, January.
    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. Catherine Mathieu & Henri Sterdyniak, 2015. "What future for taxation in the EU?," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 5-13.
    2. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.
    3. repec:zbw:bofrdp:2018_024 is not listed on IDEAS
    4. repec:zbw:bofrdp:2016_015 is not listed on IDEAS
    5. Tsvetomira Tsenova, 2014. "International monetary transmission with bank heterogeneity and default risk," Annals of Finance, Springer, vol. 10(2), pages 217-241, May.
    6. Oinonen, Sami & Paloviita, Maritta & Viren, Matti, 2018. "Effects of monetary policy decisions on professional forecasters’ expectations and expectations uncertainty," Research Discussion Papers 24/2018, Bank of Finland.
    7. Tomasz Łyziak & Maritta Paloviita, 2017. "Formation of inflation expectations in turbulent times. Recent evidence from the European Survey of Professional Forecasters," NBP Working Papers 261, Narodowy Bank Polski.
    8. Oinonen, Sami & Viren, Matti, 2021. "Effects of Monetary Policy Decisions on Professional Forecasters' Expectations and Expectation Uncertainty," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 74(2), pages 245-280.
    9. Sami Oinonen & Maritta Paloviita, 2017. "How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(2), pages 139-163, November.
    10. repec:zbw:bofrdp:2017_013 is not listed on IDEAS
    11. Sami Oinonen & Maritta Paloviita, 2017. "How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(2), pages 139-163, November.
    12. repec:hal:spmain:hal-03459745 is not listed on IDEAS
    13. Catherine Mathieu & Henri Sterdyniak, 2015. "What future for taxation in the EU?," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 5-13.
    14. repec:hal:spmain:info:hdl:2441/6m2bi4eoh48hnr5ile6iol143v is not listed on IDEAS
    15. Łyziak, Tomasz & Paloviita, Maritta, 2017. "Formation of inflation expectations in turbulent times : Can ECB manage inflation expectations of professional forecasters?," Research Discussion Papers 13/2017, Bank of Finland.

    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. Huisman, Ronald & Van der Sar, Nico L. & Zwinkels, Remco C.J., 2021. "Volatility expectations and disagreement," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 379-393.
    2. Svetlana Makarova, 2014. "Risk and Uncertainty: Macroeconomic Perspective," UCL SSEES Economics and Business working paper series 129, UCL School of Slavonic and East European Studies (SSEES).
    3. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
    4. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    5. Andrade, P. & Ghysels, E. & Idier, J., 2012. "Tails of Inflation Forecasts and Tales of Monetary Policy," Working papers 407, Banque de France.
    6. repec:zbw:bofrdp:037 is not listed on IDEAS
    7. Gauvin, L. & McLoughlin, C. & Reinhardt, D., 2013. "Policy Uncertainty Spillovers to Emerging Markets - Evidence from Capital Flows," Working papers 435, Banque de France.
    8. Robert Rich & Joseph Tracy, 2021. "A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 233-253, February.
    9. Andreas Dibiasi & David Iselin, 2021. "Measuring Knightian uncertainty," Empirical Economics, Springer, vol. 61(4), pages 2113-2141, October.
    10. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
    11. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    12. Steffen R. Henzel & Malte Rengel, 2017. "Dimensions Of Macroeconomic Uncertainty: A Common Factor Analysis," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 843-877, April.
    13. repec:zbw:bofrdp:2017_037 is not listed on IDEAS
    14. Andrea Carriero & Sarah Mouabbi & Elisabetta Vangelista, 2018. "UK term structure decompositions at the zero lower bound," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 643-661, August.
    15. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    16. Travaglini, Guido, 2007. "The U.S. Dynamic Taylor Rule With Multiple Breaks, 1984-2001," MPRA Paper 3419, University Library of Munich, Germany, revised 15 Jun 2007.
    17. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    18. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2014. "Inflation uncertainty revisited: a proposal for robust measurement," Empirical Economics, Springer, vol. 47(4), pages 1497-1523, December.
    19. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 215-228.
    20. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
    21. Kajal Lahiri & Fushang Liu, 2006. "Modelling multi‐period inflation uncertainty using a panel of density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219, December.
    22. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).

    More about this item

    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:bla:buecrs:v:67:y:2015:i:1:p:65-82. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0307-3378 .

    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.