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  • NCLIM22050786B Manuscript, no cover page

    Rights statement: The final publication is available at Springer via http://dx.doi.org/10.1038/s41558-022-01467-6

    Accepted author manuscript, 3.55 MB, PDF document

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Prediction-market innovations can improve climate-risk forecasts

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Prediction-market innovations can improve climate-risk forecasts. / Roulston, Mark; Kaplan, Todd; Day, Brett et al.
In: Nature Climate Change, Vol. 12, No. 10, 31.10.2022, p. 879-880.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Roulston, M, Kaplan, T, Day, B & Kaivanto, K 2022, 'Prediction-market innovations can improve climate-risk forecasts', Nature Climate Change, vol. 12, no. 10, pp. 879-880. https://doi.org/10.1038/s41558-022-01467-6

APA

Roulston, M., Kaplan, T., Day, B., & Kaivanto, K. (2022). Prediction-market innovations can improve climate-risk forecasts. Nature Climate Change, 12(10), 879-880. https://doi.org/10.1038/s41558-022-01467-6

Vancouver

Roulston M, Kaplan T, Day B, Kaivanto K. Prediction-market innovations can improve climate-risk forecasts. Nature Climate Change. 2022 Oct 31;12(10):879-880. Epub 2022 Sept 1. doi: 10.1038/s41558-022-01467-6

Author

Roulston, Mark ; Kaplan, Todd ; Day, Brett et al. / Prediction-market innovations can improve climate-risk forecasts. In: Nature Climate Change. 2022 ; Vol. 12, No. 10. pp. 879-880.

Bibtex

@article{510bba9f3c6a48bd9f735fd65104dead,
title = "Prediction-market innovations can improve climate-risk forecasts",
abstract = "Forward-looking information about climate risks is critical for decision makers, but the provision and accuracy of such information is limited. Innovative prediction-market designs could provide a mechanism to enhance applied climate research in an incentive-compatible way.",
keywords = "prediction market, climate risk, circularity problem, two-dimensional market, conditional forecasts",
author = "Mark Roulston and Todd Kaplan and Brett Day and Kim Kaivanto",
year = "2022",
month = oct,
day = "31",
doi = "10.1038/s41558-022-01467-6",
language = "English",
volume = "12",
pages = "879--880",
journal = "Nature Climate Change",
issn = "1758-678X",
publisher = "Nature Publishing Group",
number = "10",

}

RIS

TY - JOUR

T1 - Prediction-market innovations can improve climate-risk forecasts

AU - Roulston, Mark

AU - Kaplan, Todd

AU - Day, Brett

AU - Kaivanto, Kim

PY - 2022/10/31

Y1 - 2022/10/31

N2 - Forward-looking information about climate risks is critical for decision makers, but the provision and accuracy of such information is limited. Innovative prediction-market designs could provide a mechanism to enhance applied climate research in an incentive-compatible way.

AB - Forward-looking information about climate risks is critical for decision makers, but the provision and accuracy of such information is limited. Innovative prediction-market designs could provide a mechanism to enhance applied climate research in an incentive-compatible way.

KW - prediction market

KW - climate risk

KW - circularity problem

KW - two-dimensional market

KW - conditional forecasts

U2 - 10.1038/s41558-022-01467-6

DO - 10.1038/s41558-022-01467-6

M3 - Journal article

VL - 12

SP - 879

EP - 880

JO - Nature Climate Change

JF - Nature Climate Change

SN - 1758-678X

IS - 10

ER -