IDEAS home Printed from https://ideas.repec.org/a/fip/fedpbr/00010.html

Forecast disagreement in the Survey of Professional Forecasters

Author

Listed:
  • Keith Sill

Abstract

To enact effective policies and spend resources efficiently, firms, policymakers, and markets need accurate economic forecasts. But even though economists generally work with similar models and data, their projections often range widely. To better understand why, Keith Sill explores what the evidence and theories say about how forecasters form their views.

Suggested Citation

  • Keith Sill, 2014. "Forecast disagreement in the Survey of Professional Forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Q2, pages 15-24.
    • Handle: RePEc:fip:fedpbr:00010
    as

    Download full text from publisher

    File URL: https://www.philadelphiafed.org/-/media/frbp/assets/economy/articles/business-review/2014/q2/brQ214_forecast_disagreement.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    2. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    3. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    4. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    5. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    6. Clements, Michael P., 2012. "Do professional forecasters pay attention to data releases?," International Journal of Forecasting, Elsevier, vol. 28(2), pages 297-308.
    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. Gillmann, Niels & Kim, Alisa, 2021. "Quantification of Economic Uncertainty: a deep learning approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242421, Verein für Socialpolitik / German Economic Association.
    2. Vania Esady, 2022. "Real and nominal effects of monetary shocks under time-varying disagreement," Bank of England working papers 1007, Bank of England.
    3. Vania Esady, 2019. "Real and Nominal Effects of Monetary Shocks under Time-Varying Disagreement," CESifo Working Paper Series 7956, CESifo.

    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. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    2. Candian, Giacomo, 2019. "Information frictions and real exchange rate dynamics," Journal of International Economics, Elsevier, vol. 116(C), pages 189-205.
    3. Roberto Casarin & Antonio Peruzzi & Davide Raggi, 2025. "Multiple Equilibria and the Phillips Curve: Do Agents Always Underreact?," Working Papers 2025: 10, Department of Economics, University of Venice "Ca' Foscari".
    4. de Mendonça, Helder Ferreira & Vereda, Luciano & Araujo, Mateus de Azevedo, 2022. "What type of information calls the attention of forecasters? Evidence from survey data in an emerging market," Journal of International Money and Finance, Elsevier, vol. 129(C).
    5. Alfarano Simone & Milakovic Mishael, 2012. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-23, October.
    6. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.
    7. Hur, Joonyoung, 2018. "Time-varying information rigidities and fluctuations in professional forecasters' disagreement," Economic Modelling, Elsevier, vol. 75(C), pages 117-131.
    8. Candia, Bernardo & Coibion, Olivier & Gorodnichenko, Yuriy, 2024. "The inflation expectations of U.S. firms: Evidence from a new survey," Journal of Monetary Economics, Elsevier, vol. 145(S).
    9. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    10. Zhang, Fang, 2014. "Monetary policy for rationally inattentive economies with staggered price setting," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 184-208.
    11. Cheng CHEN & Tatsuro SENGA & Chang SUN & Hongyong ZHANG, 2020. "Information Acquisition and Price Setting under Uncertainty: New Survey Evidence," Discussion papers 20078, Research Institute of Economy, Trade and Industry (RIETI).
    12. Ou, Shengliang & Zhang, Donghai & Zhang, Renbin, 2021. "Information frictions, monetary policy, and the paradox of price flexibility," Journal of Monetary Economics, Elsevier, vol. 120(C), pages 70-82.
    13. Andreas Fuster & Ricardo Perez-Truglia & Mirko Wiederholt & Basit Zafar, 2022. "Expectations with Endogenous Information Acquisition: An Experimental Investigation," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 1059-1078, December.
    14. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    15. Nathan Goldstein & Ohad Raveh, 2024. "Looking up the sky: unidentified aerial phenomena and macroeconomic attention," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-25, December.
    16. Jeffrey Schafer, 2022. "Inflation Expectations and Their Formation: Working Paper 2022-03," Working Papers 57398, Congressional Budget Office.
    17. Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2015. "Models, Inattention and Expectation Updates," Discussion Papers 1602, Centre for Macroeconomics (CFM).
    18. Kenza Benhima & Isabella Blengini, 2020. "Optimal Monetary Policy when Information is Market-Generated," The Economic Journal, Royal Economic Society, vol. 130(628), pages 956-975.
    19. Oleksiy Kryvtsov, 2005. "Information Flows and Aggregate Persistence," Computing in Economics and Finance 2005 416, Society for Computational Economics.
    20. George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.

    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:fip:fedpbr:00010. 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: Beth Paul (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.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.