IDEAS home Printed from https://ideas.repec.org/p/lie/wpaper/123.html
   My bibliography  Save this paper

The term structure of judgement: interpreting survey disagreement

Author

Listed:
  • Federica Brenna

    (Bank of Lithuania and Vilnius University)

  • Zymantas Budrys

    (Bank of Lithuania and Vilnius University)

Abstract

Consensus forecasts by professionals are highly accurate, yet hide large heterogeneity. We develop a framework to extract the judgement component from survey forecasts and analyse the extent to which it contributes to respondents’ disagreement. For the average respondent, we find a substantial contribution of judgement about the current quarter, which often steers unconditional forecasts towards the realisation, thereby improving accuracy. We identify the structural components of judgement by exploiting stochastic volatility and give an economic interpretation to expected future shocks. For individual respondents, just over one-third of the disagreement is due to differences in the coefficients or models used, and the remainder is due to different assessments of future shocks; the latter mostly concerns the size of the shocks, while there is general agreement on their source.

Suggested Citation

  • Federica Brenna & Zymantas Budrys, 2024. "The term structure of judgement: interpreting survey disagreement," Bank of Lithuania Working Paper Series 123, Bank of Lithuania.
  • Handle: RePEc:lie:wpaper:123
    as

    Download full text from publisher

    File URL: https://www.lb.lt/uploads/publications/docs/46288_3913ac42a0e15500a05a7db5f47435c1.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Expectations Formation; Identification via Stochastic Volatility; Judgement; Survey of Professional Forecasters;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:lie:wpaper:123. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Aurelija Proskute (email available below). General contact details of provider: https://edirc.repec.org/data/lbanklt.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.