![handle is hein.journals/genus73 and id is 1 raw text is: Bohk-Ewald and Rau Genus (2017) 73:1
DOI 10.1186/s41118-016-0017-8
Genus
S .. A * S.- l- [I LE:.. :-. . .,.: rr c e
Probabilistic mortality forecasting with
varying age-specific survival improvements
Christina Bohk-Ewald* and Roland Rau1,2
Correspondence:
Boh kEwald@demogr.mpg.de
]Max Planck Institute for
Demographic Research,
Konrad-Zuse-Strafe 1, 18057
Rostock, Germany
Fu ist of author nformation s
available at the end of the article
I Springer Open
Introduction
Few activities of demographers receive as much attention from society as population
forecasts. Many areas of public policy are affected by the increasing number of the elderly
in a population as a result of improved chances of survival (Preston and Stokes 2012).
Financing old-age pensions and health care and the provision of long-term care are only
the tip of the iceberg. However, not only public policy is affected. Private companies also
require reliable estimates for future mortality. Pension funds represent the most obvious
example (OECD 2011; Soneji and King 2012).
Despite their great societal relevance, the recent track record of demographic fore-
casts is not praiseworthy. Even though longer time series became available as well as
presumably better methodology and more computing power were on-hand, Keilman
(2008) concluded for European countries that Demographic Forecasts Have Not
Become More Accurate Over the Past 25 Years. Projecting only mortality-as one of
the three parameters, besides fertility and migration, that determine the size of a
population and shape its age-structure-does not yield satisfactory results either
(Keilman 2008, p. 146).
© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International
License (http//creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if chances were made.
CrossMark
Abstract
Many mortality forecasting approaches extrapolate past trends. Their predictions of
the future development can be quite precise as long as turning points and/or age-shifts
of mortality decline are not present. To account even for such mortality dynamics, we
propose a model that combines recently developed ideas in a single framework. It (1)
uses rates of mortality improvement to model the aging of mortality decline, and it (2)
optionally combines the mortality trends of multiple countries to catch anticipated
turning points. We use simulation-based Bayesian inference to estimate and run this
model that also provides prediction intervals to quantify forecast uncertainty. Validating
mortality forecasts for British and Danish women from 1991 to 2011 suggest that our
model can forecast regular and irregular mortality developments and that it can
perform at least as well as other widely accepted approaches like, for instance, the
Lee-Carter model or the UN Bayesian approach. Moreover, prospective mortality
forecasts from 2012 to 2050 suggest gradual increases for British and Danish life
expectancy at birth.
Keywords: Mortality forecasts, Rates of mortality improvement, Prediction intervals,
Bayesian inference, Coherent mortality forecasts](ViewImageLocal?handle=hein.journals/genus73&div=1&collection=&method=preview&ext=.png&size=3)
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