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Detecting year-of-birth mortality patterns with limited data

By Michael J. Murphy


In his recent paper Richards (2008) discussed ways to detect mortality cohort effects in England and Wales. This is one of a series of papers in the past decade on this topic by, for example, Willets (2004), Willets et al. (2004) and Richards et al. (2006) particularly relating to those born in the period 1925–1945, which is often referred to in the actuarial literature as the ‘Golden generations’, ‘The importance of birth cohorts in mortality patterns re-emerged at the end of the 20th century when Willets (1999) highlighted strong emerging cohort-based improvements in mortality among males in the UK population’ (Richards (2008), page 279), although the contribution of official statisticians should not be ignored. The existence of cohort-based patterns and possible explanations for it had been discussed in detail from the early 1990s, to the extent that it was partially included in the 1991-based and fully incorporated in the British 1992-based population projections: ‘a … higher than average rate of improvement is a special feature of generations born between 1925 and 1945 (which more detailed charts show to be centred on the generation born in 1931). It is not yet understood precisely why the members of the generation born about 1931 have been enjoying so much lower death rates throughout adult life than the preceding generation …’ (Office of Population Censuses and Surveys (1995), page 10). There are some errors and inconsistencies in this paper that mean that the conclusions are less valid than the author claims. These will be covered under three main heads: the definition of ‘cohort effects’, the use of death distribution data models to identify such cohort effects and the use of statistical models to establish the existence of such cohort effects

Topics: GF Human ecology. Anthropogeography, HB Economic Theory, QA Mathematics
Publisher: Wiley on behalf of the Royal Statistical Society
Year: 2010
DOI identifier: 10.1111/j.1467-985X.2010.00650_1.x
OAI identifier:
Provided by: LSE Research Online
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