A continuous-time stochastic model for the mortality surface of multiple populations

Peter Jevtic () and Luca Regis ()
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Peter Jevtic: Department of Mathematics and statistics, McMaster University, Canada

No 03/2016, Working Papers from IMT School for Advanced Studies Lucca

Abstract: We formulate, study and calibrate a continuous-time model for the joint evolution of the mortality surface of multiple populations. We model the mortality intensity by age and population as a mixture of stochastic latent factors, that can be either population-specific or common to all populations. These factors are described by affine time-(in)homogenous stochastic processes. Traditional, deterministic mortality laws can be extended to multi-population stochastic counterparts within our framework. We detail the calibration procedure when factors are Gaussian, using centralized data-fusion Kalman filter. We provide an application based on the mortality of UK males and females. Although parsimonious, the specification we calibrate provides a good fit of the observed mortality surface (ages 0-99) of both sexes between 1960 and 2013.

Keywords: multi-population mortality; mortality surface; continuous-time stochastic mortality; Kalman filter estimation; centralized data fusion (search for similar items in EconPapers)
JEL-codes: C13 C38 G22 J11 (search for similar items in EconPapers)
Pages: 31
Date: 2016-07, Revised 2016-07
New Economics Papers: this item is included in nep-age, nep-ecm, nep-evo and nep-hea
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Published in EIC working paper series

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https://eprints.imtlucca.it/3518/1/EIC_WP_3_2016.pdf First version, 2016 (application/pdf)

Related works:
Journal Article: A continuous-time stochastic model for the mortality surface of multiple populations (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ial:wpaper:03/2016

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