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The Life Table pp 141-169 | Cite as

Parameterisation as a tool in analysing age, period and cohort effects on mortality: A case study of the Netherlands

  • Ewa Tabeau
  • Frans Willekens
  • Frans van Poppel
Chapter
Part of the European Studies of Population book series (ESPO, volume 11)

Abstract

Parameterisation models have been applied by demographers, medical scientists, and actuaries for about 250 years, being always a useful tool in the analysis of mortality. Their usefulness has been limited in the past to smoothing data, eliminating and/or reducing errors, constructing life tables, estimating missing data, facilitating comparisons of mortality, and forecasting (Keyfitz, 1982; Manton, Stallard, 1991). Recently, the role of parameterisation models has considerably broadened. Completely new areas of applications for parameterisation emerged, such as modelling disease processes (Manton, Stallard, 1984; 1988), solving specification problems of the traditional ageperiod-cohort (apc) models (Holford, Zhang, McKey, 1994), and contributing to a new type of symptomatic models for mortality (Lee, Carter, 1992). The symptomatic nature of parameterisation models is also subject of this chapter. First of all, however, some technical questions are discussed. In the technical part of this contribution, an attempt is made to systemise parameterisation functions for mortality and in particular to decide which representations of mortality are preferable as dependent variables in these functions. This goal is a natural consequence of the fact that the number of existing parameterisation models is rather high and some guidelines are needed to select a proper function. Secondly, we show how useful parameterisation can be in analysing age, period,and cohort effects on mortality. The motivation for the second goal originates from the opinion that parameterisation can be seen as an alternative to age, period, and cohort modelling.

Keywords

Mean Absolute Percentage Error Mean Absolute Error Absolute Percentage Error Compete Risk Model Accuracy Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • Ewa Tabeau
  • Frans Willekens
  • Frans van Poppel

There are no affiliations available

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