Stephen Richards

With the exception of dressmaking, bias is generally undesirable. This is particularly the case when projecting future mortality rates for reserving for pension liabilities. 

A good general-purpose formula for describing pensioner mortality rates is the logistic function: q = exp(α) / (1 + exp(α)) where the value of α varies by age.

An important concept is demography is the ecological fallacy.  This is where aggregate data for a group are used to draw erroneous inferences about individuals belonging to the group. 

Amongst its other claims to fame, Scotland produced one of the earliest prominent anti-smoking campaigners — our very own King James VI was an early opponent of tobacco consumption and smoking

Last year Iain wrote about a smooth model to identify mortality shocks, using Swedish population data to illustrate the impact of the 1918 influenza pandemic. 

One of the most written-about models for stochastic mortality projections is that from Lee & Carter (1992). 

A particular leitmotif of 2010 is productivity — getting more work done with the time and resources available.  Often this is about controlling costs, but in the insurance sector in the European Union it is also about adapting to scarcity of resources: with Solvency II looming, there is strong Europe-wide demand for actuarial expertise.

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?

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.