Stephen Richards

We have written extensively about the use of postcodes and geodemographics for mortality modelling.  Two peer-reviewed papers recently presented to the Institute of Actuaries in London have testified to the power of geodemographics when applied to pensioner mortality: Richards (2008) and Madrigal et al (2009).

Examining past trends in cause of death can be very instructive.  However, in some quarters it has become popular to try to extrapolate trends in causes of death to create a forecast of future mortality rates.

Effective risk modelling is about grouping people with shared characteristics which affect this risk.  In mortality analysis by far the most important risk factor is age, so it is not a good idea to mix the young and old if it can be avoided. 

In an earlier post we also showed how the U.K. was top of the obesity league amongst major EU nations.   Happily, the U.K. is top of a more constructive EU league table, namely the (lack of) affordability of cigarettes.

The Institute of Actuaries' sessional meeting on 28th September 2009 discussed an interesting paper.  It covered similar material to that in Richards (2008), but used different methods and different data.

Stochastic projections of future mortality are increasingly used not just to set future best-estimates, but also to inform on stress tests such as for ICAs in the UK.

The Scots are an innovative bunch, including the inventor of the telephone and the discoverer of penicillin.

In an earlier post we described a problem when fitting GLMs for qx over multiple years.  The key mistake is to divide up the period over which the individual was observed in a model for individual mortality. 

With many stochastic models of mortality, projections of future mortality rates are done using a time series.  In a landmark paper, Currie, Durban and Eilers (2004) introduced the idea of using P-splines as an alternative means of generating a forecast.

It is quite common for a pension scheme to want to reduce its risk, but to be unable to afford a full buy-out.  The question is how best to reduce risk with the funds available, i.e. which liabilities to buy out first.