Academics Andrew Hunt and David Blake have developed a new method for forecasting mortality rates. It applies to any set of data to construct a mortality model to fit all ages across the population.
Recently, a large number of new mortality models have been proposed to analyse historic mortality rates and project them into the future.
“Many of these suffer from being over-parametrised or have terms added in an ad hoc manner which cannot be justified in terms of demographic significance”, Hunt and Blake say.
They add that poor specification of a model can lead to period effects in the data being wrongly attributed to cohort effects which results in the model making implausible projections. “We present a general procedure for constructing mortality models using a combination of a toolkit of functions and expert judgement.”
By following the general procedure, it is possible to identify sequentially every significant demographic feature in the data and give it a parametric structural form. Hunt and Blake demonstrate that the general procedure produces a relatively parsimonious model that nevertheless has a good fit to the data.
In addition to producing more economical models than those generated using a mechanical algorithm, the procedure also gave well-specified cohort effects, which the institute said are essential for reliable forecasting of mortality rates.