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Lévy CARMA models for shocks in mortality

Author

Listed:
  • Asmerilda Hitaj

    (University of Milano-Bicocca)

  • Lorenzo Mercuri

    (University of Milan
    Japan Science and Technology Agency CREST)

  • Edit Rroji

    (Politecnico di Milano)

Abstract

Recent literature on mortality modeling suggests to include in the dynamics of mortality rates the effects of time, age, the interaction of these two and a term for possible shocks. In this paper we investigate models that use Legendre polynomials for the inclusion of age and cohort effects. In order to capture the dynamics of the shock term it is suggested to consider continuous autoregressive moving average (CARMA) models due to their flexibility in reproducing different autoregressive profiles of the shock term. In order to validate the proposed model, different life tables are considered. In particular the male life tables for New Zealand, Taiwan and Japan are used for the presentation of in-sample fitting. Empirical analysis suggests that the inclusion of more flexible models such as higher-order CARMA(p,q) models leads to better in-sample fitting.

Suggested Citation

  • Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019. "Lévy CARMA models for shocks in mortality," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 205-227, June.
    • Handle: RePEc:spr:decfin:v:42:y:2019:i:1:d:10.1007_s10203-019-00248-9
    DOI: 10.1007/s10203-019-00248-9
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    References listed on IDEAS

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    1. Francesca Perla & Salvatore Scognamiglio, 2023. "Locally-coherent multi-population mortality modelling via neural networks," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 46(1), pages 157-176, June.

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    More about this item

    Keywords

    Force of mortality; CARMA(p; q) model; Lévy process;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • 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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