IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v182y2019i2p443-466.html
   My bibliography  Save this article

The predictive power of subjective probabilities: probabilistic and deterministic polling in the Dutch 2017 election

Author

Listed:
  • Jochem de Bresser
  • Arthur van Soest

Abstract

The paper evaluates the predictive validity of stated intentions for actual behaviour. In the context of the 2017 Dutch parliamentary election, we compare how well polls based on probabilistic and deterministic questions line up with subsequent votes. Our empirical strategy is built around a randomized experiment in a representative panel. Respondents were either asked which party they will vote for or were asked to allocate probabilities of voting for each party. The results show that probabilities predict individual behaviour better than deterministic statements for a large majority of respondents. There is, however, substantial heterogeneity in the predictive power of subjective probabilities. We find evidence that they work better for those with higher probability numeracy, even though probability numeracy was measured 8 years earlier.

Suggested Citation

  • Jochem de Bresser & Arthur van Soest, 2019. "The predictive power of subjective probabilities: probabilistic and deterministic polling in the Dutch 2017 election," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 443-466, February.
  • Handle: RePEc:bla:jorssa:v:182:y:2019:i:2:p:443-466
    DOI: 10.1111/rssa.12409
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssa.12409
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssa.12409?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Romuald Meango, 2023. "Identification of Ex Ante Returns Using Elicited Choice Probabilities," Papers 2303.03009, arXiv.org.
    2. Poinas, François & Méango, Romuald, 2023. "The (Option-)Value of Overstaying," TSE Working Papers 23-1478, Toulouse School of Economics (TSE).
    3. Juerg Schweri, 2021. "Predicting polytomous career choices in healthcare using probabilistic expectations data," Health Economics, John Wiley & Sons, Ltd., vol. 30(3), pages 544-563, March.
    4. Romauld Méango, 2023. "Identification of ex ante returns using elicited choice probabilities," Economics Series Working Papers 1007, University of Oxford, Department of Economics.
    5. Romuald Meango, 2023. "Using Probabilistic Stated Preference Analyses to Understand Actual Choices," Papers 2307.13966, arXiv.org.

    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:jorssa:v:182:y:2019:i:2:p:443-466. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.