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Coping with Systemic Risk in Index-based Crop Insurance

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  • Shen, Zhiwei
  • Odening, Martin

Abstract

The implementation of index-based crop insurance is often impeded by the existence of systemic risk of insured losses. We assess the effectiveness of two strategies for coping with systemic risk: regional diversification and securitization with catastrophe (CAT) bonds. The analysis is conducted in an equilibrium pricing framework which allows the optimal price of the insurance and the number of traded contracts to be determined. We also explore the role of basis risk and risk aversion of market agents. The model is applied to a hypothetical area yield insurance for rice producers in northeast China. If yields in two regions are positively correlated, we find that enlarging the insured area leads to an increasing insurance premium. Unless capital market investors are very risk averse, a CAT bond written on an area yield index outperforms regional diversification in terms of certainty equivalents of both farmers and insurers.

Suggested Citation

  • Shen, Zhiwei & Odening, Martin, 2012. "Coping with Systemic Risk in Index-based Crop Insurance," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122555, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaa123:122555
    DOI: 10.22004/ag.econ.122555
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    Citations

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    Cited by:

    1. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    2. Wu, Yang-Che, 2020. "Equilibrium in natural catastrophe insurance market under disaster-resistant technologies, financial innovations and government interventions," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 116-128.
    3. Lavorato, Mateus & Braga, Marcelo José, 2021. "On the Risk Efficiency of a Weather Index Insurance Product for the Brazilian Semi-Arid Region," 2021 Conference, August 17-31, 2021, Virtual 315193, International Association of Agricultural Economists.
    4. Martínez-Salgueiro, Andrea & Tarrazón-Rodón, María-Antonia, 2020. "Is diversification effective in reducing the systemic risk implied by a market for weather index-based insurance in Spain?," MPRA Paper 119924, University Library of Munich, Germany, revised 19 May 2021.
    5. Xiaotao Li & Jinzheng Ren & Beibei Niu & Haiping Wu, 2020. "Grain Area Yield Index Insurance Ratemaking Based on Time–Space Risk Adjustment in China," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    6. Shuoli Zhao & Chengyan Yue, 2020. "Risk preferences of commodity crop producers and specialty crop producers: An application of prospect theory," Agricultural Economics, International Association of Agricultural Economists, vol. 51(3), pages 359-372, May.
    7. Li, Hong & Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2021. "Improved index insurance design and yield estimation using a dynamic factor forecasting approach," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 208-221.
    8. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.

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    Keywords

    Risk and Uncertainty;

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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