The Linear Link: Deriving Age-Specific Death Rates from Life Expectancy

Marius D. Pascariu, Ugofilippo Basellini, José Manuel Aburto and Vladimir Canudas-Romo
Additional contact information
Marius D. Pascariu: Biometric Risk Modelling Chapter, SCOR Global Life SE, 75795 Paris, France
Ugofilippo Basellini: Max Planck Institute for Demographic Research (MPIDR), 18057 Rostock, Germany
José Manuel Aburto: Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, 5000 Odense, Denmark
Vladimir Canudas-Romo: School of Demography, The Australian National University, Canberra 2600, Australia

Risks, 2020, vol. 8, issue 4, 1-18

Abstract: The prediction of human longevity levels in the future by direct forecasting of life expectancy offers numerous advantages, compared to methods based on extrapolation of age-specific death rates. However, the reconstruction of accurate life tables starting from a given level of life expectancy at birth, or any other age, is not straightforward. Model life tables have been extensively used for estimating age patterns of mortality in poor-data countries. We propose a new model inspired by indirect estimation techniques applied in demography, which can be used to estimate full life tables at any point in time, based on a given value of life expectancy at birth. Our model relies on the existing high correlations between levels of life expectancy and death rates across ages. The methods presented in this paper are implemented in a publicly available R package.

Keywords: indirect estimation; life expectancy; forecasting; death rates; age patterns of mortality (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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