IDEAS home Printed from https://ideas.repec.org/p/snb/snbwpa/2015-10.html
   My bibliography  Save this paper

Ben Bernanke vs. Janet Yellen: Exploring the (a)symmetry of individual and aggregate inflation expectations

Author

Listed:
  • Nikola Mirkov
  • Andreas Steinhauer

Abstract

We conducted a simple, anonymous survey at the beginning of 2014, asking around 200 economists worldwide to reveal their inflation expectations, conditional on either Ben Bernanke or Janet Yellen being the chair of the Board of Governors of the Federal Reserve. We use the change in the Fed's leadership to focus attention on the difference in conditional expectations, while we are interested in the distribution of those expectations. The outcome of the survey shows that a significant share of respondents revealed asymmetric inflation expectations and that the deviation from symmetry is sizeable. Nonetheless, individual asymmetry in forecasts appears to be irrelevant for the aggregate distribution, as the number of respondents who factor in excess inflation broadly matches the number of those who gave more weight to disinflationary outcomes. The aggregate distribution we obtain is largely comparable to the outcome of the Survey of Professional Forecasters for the first quarter of 2014.

Suggested Citation

  • Nikola Mirkov & Andreas Steinhauer, 2015. "Ben Bernanke vs. Janet Yellen: Exploring the (a)symmetry of individual and aggregate inflation expectations," Working Papers 2015-10, Swiss National Bank.
  • Handle: RePEc:snb:snbwpa:2015-10
    as

    Download full text from publisher

    File URL: https://www.snb.ch/en/publications/research/working-papers/2015/working_paper_2015_10
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
    2. Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
    3. Lahiri, Kajal & Teigland, Christie & Zaporowski, Mark, 1988. "Interest Rates and the Subjective Probability Distribution of Inflation Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 20(2), pages 233-248, May.
    4. Garcí­a, Juan Angel & Manzanares, Andrés, 2007. "What can probability forecasts tell us about inflation risks?," Working Paper Series 825, European Central Bank.
    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. Nikola Mirkov & Andreas Steinhauer, 2014. "Are subjective distributions in inflation expectations symmetric?," ECON - Working Papers 173, Department of Economics - University of Zurich.
    2. 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.
    3. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
    4. Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
    5. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    6. Michael P. Clements, 2014. "US Inflation Expectations and Heterogeneous Loss Functions, 1968–2010," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 1-14, January.
    7. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    8. Philip Hans Franses & Max Welz, 2022. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 829-839, July.
    9. Gianna Boero & Jeremy Smith & KennethF. Wallis, 2008. "Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters," Economic Journal, Royal Economic Society, vol. 118(530), pages 1107-1127, July.
    10. Montes, Gabriel Caldas & Curi, Alexandre, 2017. "Disagreement in expectations about public debt, monetary policy credibility and inflation risk premium," Journal of Economics and Business, Elsevier, vol. 93(C), pages 46-61.
    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. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    13. Manzanares, Andrés & Garcí­a, Juan Angel, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 836, European Central Bank.
    14. Paul Söderlind, 2011. "Inflation Risk Premia and Survey Evidence on Macroeconomic Uncertainty," International Journal of Central Banking, International Journal of Central Banking, vol. 7(2), pages 113-133, June.
    15. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
    16. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)," Other publications TiSEM 38fac5ce-fe8f-4b61-a679-f, Tilburg University, School of Economics and Management.
    17. Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
    18. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    19. Huang, Rong & Pilbeam, Keith & Pouliot, William, 2022. "Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 706-724.
    20. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.

    More about this item

    Keywords

    inflation expectations; subjective probability distributions;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    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:snb:snbwpa:2015-10. 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: Enzo Rossi (email available below). General contact details of provider: https://edirc.repec.org/data/snbgvch.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.