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Learning from COVID-19: A catastrophe mortality bond solution in the post-pandemic era

Author

Listed:
  • Chen, Ze
  • Li, Hong
  • Mao, Yu
  • Zhou, Kenneth Q.

Abstract

The development of robust financial instruments to mitigate pandemic-induced mortality risks has become increasingly critical, particularly for the insurance sector, in the aftermath of COVID-19. This paper introduces a novel pandemic bond designed to alleviate the financial burden on life insurers and reinsurers exposed to pandemic-related mortality risks. The bond's payouts are linked to publicly available pandemic data, enhancing transparency, ensuring timely payments, and mitigating the risks of information asymmetry and moral hazard. A stochastic Susceptible-Infected-Recovered-Deceased (SIRD) model is developed to evaluate the pricing and hedging performance of the PAN bond. Numerical analysis based on U.S. COVID-19 data illustrates the proposed SIRD model's effectiveness in generating reliable probabilistic forecasts of excess mortality and demonstrates the bond's potential as an effective hedge against pandemic-induced mortality risks.

Suggested Citation

  • Chen, Ze & Li, Hong & Mao, Yu & Zhou, Kenneth Q., 2025. "Learning from COVID-19: A catastrophe mortality bond solution in the post-pandemic era," Insurance: Mathematics and Economics, Elsevier, vol. 123(C).
    • Handle: RePEc:eee:insuma:v:123:y:2025:i:c:s0167668725000605
    DOI: 10.1016/j.insmatheco.2025.103113
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    More about this item

    Keywords

    Pandemic mortality risk; SIRD model; Catastrophe bond; Risk management; COVID-19;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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