Information Matrix

We have often written about how modelling the force of mortality, μx, is superior to using the rate of mortality, qx.

Trends in cause of death can be an instructive way of looking at past mortality, although we have previously seen that we have to be very careful that an apparent "trend" is not due to changes in recording.  Leaving aside the problems of shifting classification over time, what of the categories themselves?

There are two fundamentally different ways of thinking about how mortality evolves over time: (a) think of mortality as a time series (the approach of the Lee-Carter model and its generalizations in the Cairns-Blake-Dowd family); (b) think of mortality as a smooth surface (the approach of the 2D P-spline models of Currie, Durban and Eilers and the smooth versions of the Lee-Carter model).

When projecting mortality rates it is common for people to ask what sort of changes in causes of death might be required to achieve a particular scenario.  Often one is asked to posit what causes of death have to be "eliminated", and the results can lead to the conclusion that a particular projection is unlikely and therefore too prudent.

We have written before about how survival models make better use of available data. 

Previously I wrote about how mortality rates by cause of death vary by deprivation index (and, by implication, socio-economic group). This substantially complicates any attempt to use cause-of-death data to make projections of mortality for annuity portfolios and defined-benefit pension schemes.

Last night an paper on the management of annuities was presented to the Faculty of Actuaries in Edinburgh.

Boxing Clever

In an earlier blog I wrote about how stochastic volatility in run-off increases with age. This applies when you exactly know (or think you know) the current and future mortality rates.

Insurers and reinsurers throughout the EU are facing up to the implementation of Solvency II, a radical overhaul of regulatory standards for insurance business.  Recently we explored how much Solvency II demands stochastic models.