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Causes-of-Death Mortality: What Do We Know on Their Dependence?

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  • Séverine Arnold (-Gaille)
  • Michael Sherris

Abstract

Over the last century, the assumption usually made was that causes of death are independent, although it is well-known that dependancies exist. Recent developments in econometrics allow, through Vector Error Correction Models (VECMs), to model multivariate dynamic systems including time dependency between economic variables. Common trends that exist between the variables may then be highlighted, the relation between these variables being represented by a long-run equilibrium relationship. In this work, VECMs are developed for causes-of-death mortality. We analyze the five main causes of death across 10 major countries representing a diversity of developed economies. The World Health Organization website provides cause-of-death information for about the last 60 years. Our analysis reveals that long-run equilibrium relationships exist between the five main causes of death, improving our understanding of the nature of dependence between these competing risks over recent years. It also highlights that countries usually had different past experience in regard to cause-of-death mortality trends, and, thus, applying results from one country to another may be misleading.

Suggested Citation

  • Séverine Arnold (-Gaille) & Michael Sherris, 2015. "Causes-of-Death Mortality: What Do We Know on Their Dependence?," North American Actuarial Journal, Taylor & Francis Journals, vol. 19(2), pages 116-128, April.
    • Handle: RePEc:taf:uaajxx:v:19:y:2015:i:2:p:116-128
    DOI: 10.1080/10920277.2015.1011279
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    Cited by:

    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Boumezoued, Alexandre & Hardy, Héloïse Labit & El Karoui, Nicole & Arnold, Séverine, 2018. "Cause-of-death mortality: What can be learned from population dynamics?," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 301-315.
    3. Shang, Han Lin & Haberman, Steven, 2017. "Grouped multivariate and functional time series forecasting:An application to annuity pricing," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 166-179.
    4. Zhang, Xuanming & Huang, Fei & Hui, Francis K.C. & Haberman, Steven, 2023. "Cause-of-death mortality forecasting using adaptive penalized tensor decompositions," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 193-213.
    5. Han Lin Shang & Yang Yang, 2021. "Forecasting Australian subnational age-specific mortality rates," Journal of Population Research, Springer, vol. 38(1), pages 1-24, March.
    6. Li, Han & Li, Hong & Lu, Yang & Panagiotelis, Anastasios, 2019. "A forecast reconciliation approach to cause-of-death mortality modeling," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 122-133.
    7. Han Lin Shang, 2017. "Reconciling Forecasts of Infant Mortality Rates at National and Sub-National Levels: Grouped Time-Series Methods," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 36(1), pages 55-84, February.
    8. Han Lin Shang & Rob J Hyndman, 2016. "Grouped functional time series forecasting: An application to age-specific mortality rates," Monash Econometrics and Business Statistics Working Papers 4/16, Monash University, Department of Econometrics and Business Statistics.
    9. Dorota Toczydlowska & Gareth W. Peters & Man Chung Fung & Pavel V. Shevchenko, 2017. "Stochastic Period and Cohort Effect State-Space Mortality Models Incorporating Demographic Factors via Probabilistic Robust Principal Components," Risks, MDPI, vol. 5(3), pages 1-77, July.
    10. Arnold, Séverine & Glushko, Viktoriya, 2021. "Cause-specific mortality rates: Common trends and differences," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 294-308.
    11. Camille Delbrouck & Jennifer Alonso-García, 2024. "COVID-19 and Excess Mortality: An Actuarial Study," Risks, MDPI, vol. 12(4), pages 1-27, March.
    12. Nicholas Bett & Juma Kasozi & Daniel Ruturwa, 2023. "Dependency Modeling Approach of Cause-Related Mortality and Longevity Risks: HIV/AIDS," Risks, MDPI, vol. 11(2), pages 1-18, February.

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