Information Matrix

The Advocate General of the European Court has recently opined that "the use of actuarial factors based on sex is incompatible with the principle of equal treatment for men and women".

In the UK the Board for Actuarial Standards (BAS) has published a series of Technical Actuarial Standards (TAS).  At the time of writing there are three standards which are either in force or shortly will be: one for data (TAS-D), one for reports (TAS-R) and one for actuarial models (TAS-M).

Earlier I described a problem in mathematical computing for mortality modelling.  This was where an intermediate step resulted in a number too big for the computer to handle, causing the entire calculation to overflow and fail. 

At it's core, the study of mortality is based on a simple ratio — the number of deaths, D, divided by the population exposed to the risk of death, E

In the debate about how fast mortality will improve in the future, sometimes it is useful to remind ourselves how far we have come. 

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.