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Constrained Kriging for smoothing and forcasting mortality rates

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  • Djibril Gueye

    (Quantlabs - Quanteam)

Abstract

Mortality surface is a function of age and year with the main characteristic of being increasing with respect to ages from a given age. One of the major challenges of its construction is to take this last specificity into account. In this paper, we propose to use constrained Kriging for such a construction. Our approach is based on the finite dimensional approximation of the Gaussian process. We first show the ability of Kriging to construct mortality surfaces and then compare its performance against classical Kriging models with trend functions such as those used in [LRZ18]. Our empirical study based on mortality data from three countries (France, Italy and Germany) showed the need to add a constraint of convexity in age and illustrated through an RMSE criterion that Kriging constraint provided better results in terms of out-of-sample forcasting.

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  • Djibril Gueye, 2021. "Constrained Kriging for smoothing and forcasting mortality rates," Working Papers hal-03454856, HAL.
    • Handle: RePEc:hal:wpaper:hal-03454856
    Note: View the original document on HAL open archive server: https://hal.science/hal-03454856
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    References listed on IDEAS

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    1. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    2. Ludkovski, Mike & Risk, Jimmy & Zail, Howard, 2018. "Gaussian Process Models For Mortality Rates And Improvement Factors €“ Corrigendum," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1349-1349, September.
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