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A multi-parameter-level model for simulating future mortality scenarios with COVID-alike effects

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  • Zhou, Rui
  • Li, Johnny Siu-Hang

Abstract

There has been a growing interest among pension plan sponsors in envisioning how the mortality experience of their active and deferred members may turn out to be if a pandemic similar to the COVID-19 occurs in the future. To address their needs, we propose in this paper a stochastic model for simulating future mortality scenarios with COVID-alike effects. The proposed model encompasses three parameter levels. The first level includes parameters that capture the long-term pattern of mortality, whereas the second level contains parameters that gauge the excess age-specific mortality due to COVID-19. Parameters in the first and second levels are estimated using penalised quasi-likelihood maximisation method which was proposed for generalised linear mixed models. Finally, the third level includes parameters that draw on expert opinions concerning, for example, how likely a COVID-alike pandemic will occur in the future. We illustrate our proposed model with data from the United States and a range of expert opinions.

Suggested Citation

  • Zhou, Rui & Li, Johnny Siu-Hang, 2022. "A multi-parameter-level model for simulating future mortality scenarios with COVID-alike effects," Annals of Actuarial Science, Cambridge University Press, vol. 16(3), pages 453-477, November.
  • Handle: RePEc:cup:anacsi:v:16:y:2022:i:3:p:453-477_4
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    Cited by:

    1. Maria Francesca Carfora & Albina Orlando, 2023. "A Preliminary Investigation of a Single Shock Impact on Italian Mortality Rates Using STMF Data: A Case Study of COVID-19," Data, MDPI, vol. 8(6), pages 1-12, June.
    2. Camille Delbrouck & Jennifer Alonso-GarcĂ­a, 2024. "COVID-19 and Excess Mortality: An Actuarial Study," Risks, MDPI, vol. 12(4), pages 1-27, March.

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