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Enhanced Agriculture Insurance with Climate Forecast

Author

Listed:
  • Lanlan Li

    (Accounting Department of Business School, Hunan International Economics University, Changsha 410205, China)

  • Zhengqiao Liu

    (Department of Applied Economics, School of Economics and Management, Yango University, Fuzhou 350015, China)

  • Jing-Yi Chen

    (Department of Insurance and Finance, National Taichung University, Taichung 403336, Taiwan)

  • Yang-Che Wu

    (Department of Finance, College of Finance, Feng Chia University, Taichung 407102, Taiwan)

  • Hong Li

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

Abstract

This paper presents a model to study how climate forecasts and the agricultural production function affect the effectiveness of government policies (disaster bailouts and agricultural income tax) and agricultural insurance (both compulsory and voluntary). In the base model with a neoclassical production function, we find that these programs could increase farmers’ expected profit and reduce its volatility. Furthermore, credible climate forecasts enable farmers, insurance companies, and governments to make more informed cultivate and insurance decisions, and therefore increase the benefit of these insurance programs to farmers. The results suggest that climate forecasts, combined with agriculture policies and insurance, can play an important role in securing farmers’ profits and providing climate risk management guidance for agriculture production.

Suggested Citation

  • Lanlan Li & Zhengqiao Liu & Jing-Yi Chen & Yang-Che Wu & Hong Li, 2022. "Enhanced Agriculture Insurance with Climate Forecast," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10617-:d:897855
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    References listed on IDEAS

    as
    1. Cornaggia, Jess, 2013. "Does risk management matter? Evidence from the U.S. agricultural industry," Journal of Financial Economics, Elsevier, vol. 109(2), pages 419-440.
    2. Miguel A. Carriquiry & Daniel E. Osgood, 2012. "Index Insurance, Probabilistic Climate Forecasts, and Production," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 79(1), pages 287-300, March.
    3. Deborah Panepinto & Vincenzo A. Riggio & Mariachiara Zanetti, 2021. "Analysis of the Emergent Climate Change Mitigation Technologies," IJERPH, MDPI, vol. 18(13), pages 1-11, June.
    4. Wu, Yang-Che, 2015. "Reexamining the feasibility of diversification and transfer instruments on smoothing catastrophe risk," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 54-66.
    5. Jesús Antón & Shingo Kimura & Jussi Lankoski & Andrea Cattaneo, 2012. "A Comparative Study of Risk Management in Agriculture under Climate Change," OECD Food, Agriculture and Fisheries Papers 58, OECD Publishing.
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    Cited by:

    1. Cheng, Louis T.W. & Shen, Jianfu & Wojewodzki, Michal, 2023. "A cross-country analysis of corporate carbon performance: An international investment perspective," Research in International Business and Finance, Elsevier, vol. 64(C).

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