Alternative Forecasts of Danish Life Expectancy

Marie-Pier Bergeron-Boucher (), Søren Kjæ Rgaard, Marius D. Pascariu, José Manuel Aburto, Jesús-Adrián Alvarez, Ugofilippo Basellini, Silvia Rizzi and James W. Vaupel
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Marie-Pier Bergeron-Boucher: University of Southern Denmark, Interdisciplinary center on population dynamics
Søren Kjæ Rgaard: University of Southern Denmark, Interdisciplinary center on population dynamics
Marius D. Pascariu: SCOR Global Life, Biometric Risk Modeling Chapter
José Manuel Aburto: University of Southern Denmark, Interdisciplinary center on population dynamics
Jesús-Adrián Alvarez: University of Southern Denmark, Interdisciplinary center on population dynamics
Ugofilippo Basellini: Max Planck Institute for Demographic Research (MPIDR), Laboratory of Digital and Computational Demography
Silvia Rizzi: University of Southern Denmark, Interdisciplinary center on population dynamics
James W. Vaupel: University of Southern Denmark, Interdisciplinary center on population dynamics

Chapter Chapter 7 in Developments in Demographic Forecasting, 2020, pp 131-151 from Springer

Abstract: Abstract In the last three decades, considerable progress in mortality forecasting has been achieved, with new and more sophisticated models being introduced. Most of these forecasting models are based on the extrapolation of past trends, often assuming linear (or log-linear) development of mortality indicators, such as death rates or life expectancy. However, this assumption can be problematic in countries where mortality development has not been linear, such as in Denmark. Life expectancy in Denmark experienced stagnation from the 1980s until the mid-1990s. To avoid including the effect of the stagnation, Denmark’s official forecasts are based on data from 1990 only. This chapter is divided into three parts. First, we highlight and discuss some of the key methodological issues for mortality forecasting in Denmark. How many years of data are needed to forecast? Should linear extrapolation be used? Second, we compare the forecast performance of 11 models for Danish females and males and for period and cohort data. Finally, we assess the implications of the various forecasts for Danish society, and, in particular, their implications for future lifespan variability and age at retirement.

Date: 2020
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DOI: 10.1007/978-3-030-42472-5_7

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