IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v40y2024i2p796-810.html
   My bibliography  Save this article

Quantifying subjective uncertainty in survey expectations

Author

Listed:
  • Krüger, Fabian
  • Pavlova, Lora

Abstract

An increasing number of household and firm surveys ask for subjective probabilities that the inflation rate falls into various outcome ranges. We provide a new measure of the uncertainty implicit in such probabilities. The measure has several advantages over existing methods: It is robust, trivial to implement, requires no functional form assumptions, and is well-defined for all logically possible probabilities. These advantages are particularly relevant when analyzing microdata from extensive consumer surveys. We illustrate the new measure using data from the Survey of Consumer Expectations.

Suggested Citation

  • Krüger, Fabian & Pavlova, Lora, 2024. "Quantifying subjective uncertainty in survey expectations," International Journal of Forecasting, Elsevier, vol. 40(2), pages 796-810.
    • Handle: RePEc:eee:intfor:v:40:y:2024:i:2:p:796-810
    DOI: 10.1016/j.ijforecast.2023.06.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207023000699
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2023.06.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar, 2018. "How Do Firms Form Their Expectations? New Survey Evidence," American Economic Review, American Economic Association, vol. 108(9), pages 2671-2713, September.
    2. James E. Matheson & Robert L. Winkler, 1976. "Scoring Rules for Continuous Probability Distributions," Management Science, INFORMS, vol. 22(10), pages 1087-1096, June.
    3. Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger, 2016. "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 505-562, June.
    4. Becker, Christoph & Duersch, Peter & Eife, Thomas & Glas, Alexander, 2021. "Extending the Procedure of Engelberg et al. (2009) to Surveys with Varying Interval-Widths," Working Papers 0707, University of Heidelberg, Department of Economics.
    5. Bartosz Mackowiak & Mirko Wiederholt, 2009. "Optimal Sticky Prices under Rational Inattention," American Economic Review, American Economic Association, vol. 99(3), pages 769-803, June.
    6. Andrew Schotter & Isabel Trevino, 2014. "Belief Elicitation in the Laboratory," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 103-128, August.
    7. Olesya Grishchenko & Sarah Mouabbi & Jean‐Paul Renne, 2019. "Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(5), pages 1053-1096, August.
    8. Itzhak Ben-David & John R. Graham, 2013. "Managerial Miscalibration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(4), pages 1547-1584.
    9. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    10. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
    12. Charles F. Manski, 2018. "Survey Measurement of Probabilistic Macroeconomic Expectations: Progress and Promise," NBER Macroeconomics Annual, University of Chicago Press, vol. 32(1), pages 411-471.
    13. Marc-André Gosselin & Mikael Khan, 2015. "A Survey of Consumer Expectations for Canada," Bank of Canada Review, Bank of Canada, vol. 2015(Autumn), pages 14-23.
    14. Olivier Armantier & Giorgio Topa & Wilbert Van der Klaauw & Basit Zafar, 2017. "An overview of the Survey of Consumer Expectations," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 51-72.
    15. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    16. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    17. Wei, Wei & Balabdaoui, Fadoua & Held, Leonhard, 2017. "Calibration tests for multivariate Gaussian forecasts," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 216-233.
    18. 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.
    19. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2011. "Scoring rules and survey density forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 379-393.
    20. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    21. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    22. Michael P. Clements, 2014. "Forecast Uncertainty- Ex Ante and Ex Post : U.S. Inflation and Output Growth," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 206-216, April.
    23. Armantier, Olivier & Koşar, Gizem & Pomerantz, Rachel & Skandalis, Daphné & Smith, Kyle & Topa, Giorgio & van der Klaauw, Wilbert, 2021. "How economic crises affect inflation beliefs: Evidence from the Covid-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 443-469.
    24. Tilmann Gneiting & Fadoua Balabdaoui & Adrian E. Raftery, 2007. "Probabilistic forecasts, calibration and sharpness," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 243-268, April.
    25. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    26. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    27. 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.
    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. Joris Wauters & Zivile Zekaite & Garo Garabedian, 2024. "Owner-occupied housing costs, policy communication, and inflation expectations," Working Paper Research 449, National Bank of Belgium.
    2. Hana Braitsch & James Mitchell & Taylor Shiroff, 2024. "Practice Makes Perfect: Learning Effects with Household Point and Density Forecasts of Inflation," Working Papers 24-25, Federal Reserve Bank of Cleveland.
    3. Niklas Valentin Lehmann, 2024. "Mechanisms for belief elicitation without ground truth," Papers 2409.07277, arXiv.org, revised Dec 2024.

    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. Krüger, Fabian & Pavlova, Lora, 2019. "Quantifying subjective oncertainty in survey expectations," Working Papers 0664, University of Heidelberg, Department of Economics.
    2. Eyting, Markus & Schmidt, Patrick, 2021. "Belief elicitation with multiple point predictions," European Economic Review, Elsevier, vol. 135(C).
    3. Dovern, Jonas, 2024. "Eliciting expectation uncertainty from private households," International Journal of Forecasting, Elsevier, vol. 40(1), pages 113-123.
    4. Brent Meyer & Nicholas B. Parker & Xuguang Sheng, 2021. "Unit Cost Expectations and Uncertainty: Firms' Perspectives on Inflation," FRB Atlanta Working Paper 2021-12a, Federal Reserve Bank of Atlanta.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
    7. Altig, David & Barrero, Jose Maria & Bloom, Nicholas & Davis, Steven J. & Meyer, Brent & Parker, Nicholas, 2022. "Surveying business uncertainty," Journal of Econometrics, Elsevier, vol. 231(1), pages 282-303.
    8. Armantier, Olivier & Koşar, Gizem & Pomerantz, Rachel & Skandalis, Daphné & Smith, Kyle & Topa, Giorgio & van der Klaauw, Wilbert, 2021. "How economic crises affect inflation beliefs: Evidence from the Covid-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 443-469.
    9. Markus Eyting & Patrick Schmidt, 2019. "Belief Elicitation with Multiple Point Predictions," Working Papers 1818, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 16 Nov 2020.
    10. Alexander Glas & Matthias Hartmann, 2022. "Uncertainty measures from partially rounded probabilistic forecast surveys," Quantitative Economics, Econometric Society, vol. 13(3), pages 979-1022, July.
    11. Becker, Christoph & Duersch, Peter & Eife, Thomas, 2023. "Measuring Inflation Expectations: How the Response Scale Shapes Density Forecasts," Working Papers 0727, University of Heidelberg, Department of Economics.
    12. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    13. repec:zbw:bofrdp:037 is not listed on IDEAS
    14. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    15. Abe, Naohito & Ueno, Yuko, 2016. "The Mechanism of Inflation Expectation Formation among Consumers," RCESR Discussion Paper Series DP16-1, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    16. Dovern, Jonas & Müller, Lena Sophia & Wohlrabe, Klaus, 2020. "How Do Firms Form Expectations of Aggregate Growth? New Evidence from a Large-scale Business Survey," Working Papers 15, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    17. Christopher Roth & Johannes Wohlfart, 2020. "How Do Expectations about the Macroeconomy Affect Personal Expectations and Behavior?," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 731-748, October.
    18. Zohar, Osnat, 2024. "Cyclicality of uncertainty and disagreement," Journal of Monetary Economics, Elsevier, vol. 143(C).
    19. 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.
    20. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
    21. Dovern, Jonas & Müller, Lena Sophia & Wohlrabe, Klaus, 2023. "Local information and firm expectations about aggregates," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 1-13.

    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:eee:intfor:v:40:y:2024:i:2:p:796-810. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.