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Optimal reinsurance analysis from a crop insurer's perspective

Author

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  • Lysa Porth
  • Ken Seng Tan
  • Chengguo Weng

Abstract

Purpose - The purpose of this paper is to analyze the optimal reinsurance contract structure from the crop insurer's perspective. Design/methodology/approach - A very powerful and flexible empirical‐based reinsurance model is used to analyze the optimal form of the reinsurance treaty. The reinsurance model is calibrated to unique data sets, including private reinsurance experience for Manitoba, and loss cost ratio (LCR) experience for all of Canada, under the assumption of the standard deviation premium principle and conditional tail expectation risk measure. Findings - The Vasicek distribution is found to provide the best statistical fit for the Canadian LCR data, and the empirical reinsurance model stipulates that a layer reinsurance contract structure is optimal, which is consistent with market practice. Research limitations/implications - While the empirical reinsurance model is able to reproduce the optimal shape of the reinsurance treaty, the model produces some inconsistencies between the implied and observed attachment points. Future research will continue to explore the reinsurance model that will best recover the observed market practice. Practical implications - Private reinsurance premiums can account for a significant portion of a crop insurer's budget, therefore, this study should be useful for crop insurance companies to achieve efficiencies and improve their risk management. Originality/value - To the best of the authors' knowledge, this is the first paper to show how a crop insurance firm can optimally select a reinsurance contract structure that minimizes its total risk exposure, considering the total losses retained by the insurer, as well as the reinsurance premium paid to private reinsurers.

Suggested Citation

  • Lysa Porth & Ken Seng Tan & Chengguo Weng, 2013. "Optimal reinsurance analysis from a crop insurer's perspective," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 73(2), pages 310-328, July.
    • Handle: RePEc:eme:afrpps:v:73:y:2013:i:2:p:310-328
    DOI: 10.1108/AFR-11-2012-0061
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    Citations

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    Cited by:

    1. Najafabadi, Amir T. Payandeh & Bazaz, Ali Panahi, 2018. "An optimal multi-layer reinsurance policy under conditional tail expectation," Annals of Actuarial Science, Cambridge University Press, vol. 12(1), pages 130-146, March.
    2. Lysa Porth & Milton Boyd & Jeffrey Pai, 2016. "Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 163-191, September.
    3. Chengguo Weng & Lysa Porth & Ken Seng Tan & Ryan Samaratunga, 2017. "Modelling the Sustainability of the Canadian Crop Insurance Program: A Reserve Fund Process Under a Public–Private Partnership Model," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(2), pages 226-246, April.
    4. Driedger, Jonathon & Porth, Lysa & Boyd, Milton, 2016. "The Potential to Use Futures and Options to Manage Crop Insurance Losses," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235747, Agricultural and Applied Economics Association.
    5. Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2016. "A Relational Model for Predicting Farm-Level Crop Yield Distributions in the Absence of Farm-Level Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236278, Agricultural and Applied Economics Association.
    6. Lysa Porth & Milton Boyd & Jeffrey Pai, 2016. "Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 163-191, September.

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