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Identification and forecasting in mortality models

Nielsen, B. & Nielsen, J. P. (2014). Identification and forecasting in mortality models. The Scientific World Journal, 2014, pp. 1-24. doi: 10.1155/2014/347043


Mortality models often have inbuilt identification issues challenging the statistician. The statistician can choose to work with well-defined freely varying parameters, derived as maximal invariants in this paper, or with ad hoc identified parameters which at first glance seem more intuitive, but which can introduce a number of unnecessary challenges. In this paper we describe the methodological advantages from using the maximal invariant parameterisation and we go through the extra methodological challenges a statistician has to deal with when insisting on working with ad hoc identifications. These challenges are broadly similar in frequentist and in Bayesian setups. We also go through a number of examples from the literature where ad hoc identifications have been preferred in the statistical analyses.

Publication Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics
R Medicine > RA Public aspects of medicine
Departments: Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:
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