Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence

16 Pages Posted: 17 Jan 2013 Last revised: 31 Jan 2013

See all articles by Severine Arnold (-Gaille)

Severine Arnold (-Gaille)

University of Lausanne - Faculty of Business and Economics

Michael Sherris

UNSW Business School

Date Written: January 14, 2013

Abstract

Longevity risk is amongst the most important factors to consider for pricing and risk management of longevity products. Past improvements in mortality over many years, and the uncertainty of these improvements, have attracted the attention of experts, both practitioners and academics. Since aggregate mortality rates reflect underlying trends in causes of death, insurers and demographers are increasingly considering cause-of-death data to better understand risks in their mortality assumptions. The relative importance of causes of death has changed over many years. As one cause reduces, others increase or decrease. The dependence between mortality for different causes of death is important when projecting future mortality. However, for scenario analysis based on causes of death, the assumption usually made is that causes of death are independent. Recent models, in the form of Vector Error Correction Models (VECM), have been developed for multivariate dynamic systems and capture time dependency with common stochastic trends. These models include long-run stationary relations between the variables, and thus allow a better understanding of the nature of this dependence. This paper applies VECM to cause-of-death mortality rates in order to assess the dependence between these competing risks. We analyze the five main causes of death in Switzerland. Our analysis confirms the existence of a long-run stationary relationship between these five causes. This estimated relationship is then used to forecast mortality rates, which are shown to be an improvement over forecasts from more traditional ARIMA processes, that do not allow for cause-of-death dependencies.

Keywords: Mortality forecasts, Causes of death, VECM, Dependence, Common trends

JEL Classification: C32, C52, J11, G22, I13

Suggested Citation

Arnold (-Gaille), Severine and Sherris, Michael, Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence (January 14, 2013). UNSW Australian School of Business Research Paper No. 2013ACTL02, Available at SSRN: https://ssrn.com/abstract=2202608 or http://dx.doi.org/10.2139/ssrn.2202608

Severine Arnold (-Gaille)

University of Lausanne - Faculty of Business and Economics ( email )

University of Lausanne
DSA
Lausanne, Vaud 1015
Switzerland
+41 21 692 33 72 (Phone)

HOME PAGE: http://www.hec.unil.ch/people/sarnold

Michael Sherris (Contact Author)

UNSW Business School ( email )

Sydney, NSW 2052
Australia

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