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Measuring Risk Literacy: The Berlin Numeracy Test

Author

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  • Cokely, Edward T.
  • Galesic, Mirta
  • Schulz, Eric
  • Ghazal, Saima
  • Garcia-Retamero, Rocio

Abstract

We introduce the Berlin Numeracy Test, a new psychometrically sound instrument that quickly assesses statistical numeracy and risk literacy. We present 21 studies (n=5336) showing robust psychometric discriminability across 15 countries (e.g., Germany, Pakistan, Japan, USA) and diverse samples (e.g., medical professionals, general populations, Mechanical Turk web panels). Analyses demonstrate desirable patterns of convergent validity (e.g., numeracy, general cognitive abilities), discriminant validity (e.g., personality, motivation), and criterion validity (e.g., numerical and non-numerical questions about risk). The Berlin Numeracy Test was found to be the strongest predictor of comprehension of everyday risks (e.g., evaluating claims about products and treatments; interpreting forecasts), doubling the predictive power of other numeracy instruments and accounting for unique variance beyond other cognitive tests (e.g., cognitive reflection, working memory, intelligence). The Berlin Numeracy Test typically takes about three minutes to complete and is available in multiple languages and formats, including a computer adaptive test that automatically scores and reports data to researchers (http://www.riskliteracy.org). The online forum also provides interactive content for public outreach and education, and offers a recommendation system for test format selection. Discussion centers on construct validity of numeracy for risk literacy, underlying cognitive mechanisms, and applications in adaptive decision support.

Suggested Citation

  • Cokely, Edward T. & Galesic, Mirta & Schulz, Eric & Ghazal, Saima & Garcia-Retamero, Rocio, 2012. "Measuring Risk Literacy: The Berlin Numeracy Test," Judgment and Decision Making, Cambridge University Press, vol. 7(1), pages 25-47, January.
    • Handle: RePEc:cup:judgdm:v:7:y:2012:i:1:p:25-47_3
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    Citations

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    Cited by:

    1. Prakashan Chellattan Veettil & Yashodha Yashodha & Joseph Vecci, 2025. "Hypothetical bias and cognitive ability: Farmers' preference for crop insurance products†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 107(3), pages 888-924, May.
    2. Maximilian Germann & Christoph Merkle, 2023. "Algorithm aversion in delegated investing," Journal of Business Economics, Springer, vol. 93(9), pages 1691-1727, November.
    3. repec:plo:pone00:0211269 is not listed on IDEAS
    4. Elnaz Bajoori & Leonard Wolk & Ronald Peeters, 2019. "Security auctions with cash- and equity-bids: An experimental study," Department of Economics Working Papers 58167, University of Bath, Department of Economics, revised 08 Mar 2023.
    5. Gruener, Sven & Mußhoff, Oliver, 2025. "Behavioral climate change: Does thinking about future consequences of climate change affect risk preferences and cooperation?," OSF Preprints 7vdu6_v1, Center for Open Science.
    6. Inmaculada Otero & Pamela Alonso, 2023. "Cognitive reflection test: The effects of the items sequence on scores and response time," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-15, January.
    7. repec:osf:socarx:x8efq_v1 is not listed on IDEAS
    8. repec:plo:pone00:0208004 is not listed on IDEAS
    9. Villanova, Daniel & Pandelaere, Mario, 2024. "A Numeracy-Task interaction model of perceived differences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 185(C).
    10. repec:plo:pone00:0208601 is not listed on IDEAS
    11. repec:plo:pone00:0201474 is not listed on IDEAS
    12. Peeters, Ronald & Veiga, Helena & Vorsatz, Marc, 2025. "An experimental analysis of contagion in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    13. Robin Bodenberger & Kirsten Thommes, 2025. "Words or Numbers? How Framing Uncertainties Affects Risk Assessment and Decision-Making," Papers 2502.06241, arXiv.org, revised Feb 2025.

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