Modelling old age mortality rates: An extrapolation method based on the mode and the compression of

Modelling old age mortality rates: An extrapolation method based on the mode and the compression of

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Speakers: Santiago Fiallos, Vincent Noel

In the last century, life expectancy has increased significantly due to medical advances and changes in lifestyle. As the aged population grows, the estimation and the modelling of mortality rates at very old ages is a major challenge. Evidence supports a complex evolution of mortality driven by three components: the decrease in premature deaths, the shift of the mortality mode to ever higher ages and the increase of the mortality compression around the mode.

Current models used to project mortality rates do not allow to reflect these three components of the mortality structure. Though current models reflect the decrease in premature mortality quite well, the shift of the mode is not properly assessed and compression of mortality around the mode over time is not allowed for.

We therefore propose an extrapolation method that explicitly assesses both the mode and the compression of mortality for old ages. We show that, for the French population, these two parameters present high historical correlations for different socio-economic categories and therefore we propose a formula to derive the compression from the mode for a given sub-group of the national population.
Evidence also supports a strong link between the mode and mid-age mortality rates (60-65 years) over time. We therefore propose a method to estimate the mode of a given sub-group of the French population based on observed mid-age mortality rates.

Backtesting performed on historical French data showed high accuracy for both male and female populations. Preliminary results on Japanese and Swedish populations show that the proposed methodology could be extended to other countries.

The proposed method allows the production of more consistent life tables for sub-groups based on observable data and could also be used to anticipate long-term trends of the mortality structure based on projections of the mode and the compression.

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