Non-Parametric Likelihood Enhancements to Parametric Graduations

Abstract

ABSTRACTParametric graduation may fail to achieve satisfactory results without overparameterisation. Whittaker-Henderson graduation tends to constrain the graduated values towards a low-order polynomial. Non-parametric methods do not generally make direct use of true likelihood functions. This paper suggests a method of enhancing the likelihood of a parametric graduation by means of non-parametric methods, thus reducing the disadvantages of both methods.The parametric graduation is taken to be ideally smooth by definition and is adjusted by using constrained maximum likelihood estimation to obtain better fidelity to the experience. The constraint imposes a minimum sacrifice of smoothness, in terms of a quantitative smoothness criterion, from the initial ideal. The method is not entirely objective in that, in some cases, professional judgement is required in order to assess the degree of smoothness that can be imposed. In other cases the method provides an objective optimum. In either case, by quantifying the degrees of departure from perfect fidelity and from ideal smoothness, the suggested method provides useful and theoretically sound criteria for the purposes of the optimisation process. In particular, by inverting the parametric graduation formula for the purposes of defining the smoothness criterion, the method ensures that the smoothness criterion is consistent over the whole age range, thus resolving the main objection to non-parametric graduation.The method is applied to the 1979-82 experience for life office pensioners in the United Kingdom with positive results.