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Comparing input interfaces to elicit belief distributions

Author

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  • Paolo Crosetto

    (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes)

  • Thomas de Haan

    (UiB - University of Bergen)

Abstract

This paper introduces a new software interface to elicit belief distributions of any shape: Click-and-Drag . The interface was tested against the state of the art in the experimental literature—a text-based interface and multiple sliders—and in the online forecasting industry—a distribution-manipulation interface similar to the one used by the most popular crowd-forecasting website. By means of a pre-registered experiment on Amazon Mechanical Turk, quantitative data on the accuracy of reported beliefs in a series of induced-value scenarios varying by granularity, shape, and time constraints, as well as subjective data on user experience were collected. Click-and-Drag outperformed all other interfaces by accuracy and speed, and was self-reported as being more intuitive and less frustrating, confirming the pre-registered hypothesis. Aside of the pre-registered results, Click-and-Drag generated the least drop-out rate from the task, and scored best in a sentiment analysis of an open-ended general question. Further, the interface was used to collect homegrown predictions on temperature in New York City in 2022 and 2042. Click-and-Drag elicited distributions were smoother with less idiosyncratic spikes. Free and open source, ready to use oTree, Qualtrics and Limesurvey plugins for Click-and-Drag, and all other tested interfaces are available at https://beliefelicitation.github.io/ .

Suggested Citation

  • Paolo Crosetto & Thomas de Haan, 2023. "Comparing input interfaces to elicit belief distributions," Post-Print hal-04263759, HAL.
    • Handle: RePEc:hal:journl:hal-04263759
    DOI: 10.1017/jdm.2023.21
    Note: View the original document on HAL open archive server: https://hal.science/hal-04263759v1
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    1. Olivier Armantier & Scott Nelson & Giorgio Topa & Wilbert van der Klaauw & Basit Zafar, 2016. "The Price Is Right: Updating Inflation Expectations in a Randomized Price Information Experiment," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 503-523, July.
    2. Stefan T. Trautmann & Gijs Kuilen, 2015. "Belief Elicitation: A Horse Race among Truth Serums," Economic Journal, Royal Economic Society, vol. 125(589), pages 2116-2135, December.
    3. Kryvtsov, Oleksiy & Petersen, Luba, 2021. "Central bank communication that works: Lessons from lab experiments," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 760-780.
    4. Andrew Schotter & Isabel Trevino, 2014. "Belief Elicitation in the Laboratory," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 103-128, August.
    5. Kriti Jain & Kanchan Mukherjee & J. Neil Bearden & Anil Gaba, 2013. "Unpacking the Future: A Nudge Toward Wider Subjective Confidence Intervals," Management Science, INFORMS, vol. 59(9), pages 1970-1987, September.
    6. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    7. Wändi Bruine De Bruin & Charles F. Manski & Giorgio Topa & Wilbert van der Klaauw, 2011. "Measuring consumer uncertainty about future inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(3), pages 454-478, April.
    8. Glenn W. Harrison & Andre Hofmeyr & Harold Kincaid & Brian Monroe & Don Ross & Mark Schneider & J. Todd Swarthout, 2022. "Subjective beliefs and economic preferences during the COVID-19 pandemic," Experimental Economics, Springer;Economic Science Association, vol. 25(3), pages 795-823, June.
    9. Ernan Haruvy & Yaron Lahav & Charles N. Noussair, 2007. "Traders' Expectations in Asset Markets: Experimental Evidence," American Economic Review, American Economic Association, vol. 97(5), pages 1901-1920, December.
    10. Fairley, Kim & Parelman, Jacob M. & Jones, Matt & Carter, R. McKell, 2019. "Risky health choices and the Balloon Economic Risk Protocol," Journal of Economic Psychology, Elsevier, vol. 73(C), pages 15-33.
    11. repec:cup:judgdm:v:9:y:2014:i:1:p:1-14 is not listed on IDEAS
    12. Lionel Page & Daniel G. Goldstein, 2016. "Subjective beliefs about the income distribution and preferences for redistribution," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 47(1), pages 25-61, June.
    13. David Danz & Lise Vesterlund & Alistair J. Wilson, 2022. "Belief Elicitation and Behavioral Incentive Compatibility," American Economic Review, American Economic Association, vol. 112(9), pages 2851-2883, September.
    14. Jeff Dominitz & Charles F. Manski, 2004. "How Should We Measure Consumer Confidence?," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 51-66, Spring.
    15. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd & Ulm, Eric R., 2017. "Scoring rules for subjective probability distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 430-448.
    16. Rholes, Ryan & Petersen, Luba, 2021. "Should central banks communicate uncertainty in their projections?," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 320-341.
    17. repec:cup:judgdm:v:10:y:2015:i:5:p:456-468 is not listed on IDEAS
    18. Leemann, Lucas & Stoetzer, Lukas F. & Traunmüller, Richard, 2021. "Eliciting Beliefs as Distributions in Online Surveys," Political Analysis, Cambridge University Press, vol. 29(4), pages 541-553, October.
    19. Kröger, Sabine & Pierrot, Thibaud, 2019. "What point of a distribution summarises point predictions?," Discussion Papers, Research Unit: Market Behavior SP II 2019-212, WZB Berlin Social Science Center.
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    Cited by:

    1. 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.
    2. Pedro Gonzalez-Fernandez, 2024. "Belief Bias Identification," Papers 2404.09297, arXiv.org, revised Nov 2024.

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    More about this item

    Keywords

    Belief elicitation; Forecasting; Scoring rules; Interfaces;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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