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Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications

Author

Listed:
  • Qimeng Pan

    (KPMG Advisory (China) Limited, Beijing 100738, China)

  • Lysa Porth

    (Gordon S. Lang School of Business and Economics, University of Guelph, Guelph, ON N1G 2W1, Canada)

  • Hong Li

    (Gordon S. Lang School of Business and Economics, University of Guelph, Guelph, ON N1G 2W1, Canada)

Abstract

This paper investigates the effectiveness of the Actuaries Climate Index (ACI), a climate index jointly launched by multiple actuarial societies in North America in 2016, on predicting crop yields and (re)insurance ratemaking. The ACI is created using a variety of climate variables reflecting extreme weather conditions in 12 subregions in the US and Canada. Using data from eight Midwestern states in the US, we find that the ACI has significant predictive power for crop yields. Moreover, allowing the constituting variables of the ACI to have data-driven rather than pre-determined weights could further improve the predictive accuracy. Furthermore, we create the county-level ACI index using high-resolution climate data and investigate its predictive power on county-level corn yields, which are more relevant to insurance practices. We find that although the self-constructed ACI index leads to a slightly worse fit due to noisier county-specific yield data, the predictive results are still reasonable. Our findings suggest that the ACI index is promising for crop yield forecasting and (re)insurance ratemaking, and its effectiveness could be further improved by allowing for the data-driven weights of the constituting variables and could be created at higher resolution levels.

Suggested Citation

  • Qimeng Pan & Lysa Porth & Hong Li, 2022. "Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications," Sustainability, MDPI, vol. 14(11), pages 1-24, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6916-:d:832511
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    References listed on IDEAS

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