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A stochastic implementation of the APCI model for mortality projections

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  • Richards, S. J.
  • Currie, I. D.
  • Kleinow, T.
  • Ritchie, G. P.

Abstract

The Age-Period-Cohort-Improvement (APCI) model is a new addition to the canon of mortality forecasting models. It was introduced by Continuous Mortality Investigation as a means of parameterising a deterministic targeting model for forecasting, but this paper shows how it can be implemented as a fully stochastic model. We demonstrate a number of interesting features about the APCI model, including which parameters to smooth and how much better the model fits to the data compared to some other, related models. However, this better fit also sometimes results in higher value-at-risk (VaR)-style capital requirements for insurers, and we explore why this is by looking at the density of the VaR simulations.

Suggested Citation

  • Richards, S. J. & Currie, I. D. & Kleinow, T. & Ritchie, G. P., 2019. "A stochastic implementation of the APCI model for mortality projections," British Actuarial Journal, Cambridge University Press, vol. 24, pages 1-1, January.
    • Handle: RePEc:cup:bracjl:v:24:y:2019:i::p:-_13
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    Cited by:

    1. Graziani, Rebecca & NIGRI, ANDREA, 2023. "An Age–Period–Cohort Model in a Dirichlet Framework: A Coherent Causes of Death Estimation," SocArXiv 856yw, Center for Open Science.

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