Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands

BACKGROUND With the rapid aging of the population, mortality forecasting becomes increasingly important, especially for the insurance and pension industries. However, a wide variety of projection methods are in use, both between and within countries, that produce different outcomes. OBJECTIVE We rev...

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Main Authors: Lenny Stoeldraijer, Coen van Duin, L.J.G van Wissen, Fanny Janssen
Format: Article
Language:English
Published: Max Planck Institute for Demographic Research 2013-08-01
Series:Demographic Research
Subjects:
Online Access:http://www.demographic-research.org/volumes/vol29/13/
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author Lenny Stoeldraijer
Coen van Duin
L.J.G van Wissen
Fanny Janssen
author_facet Lenny Stoeldraijer
Coen van Duin
L.J.G van Wissen
Fanny Janssen
author_sort Lenny Stoeldraijer
collection DOAJ
description BACKGROUND With the rapid aging of the population, mortality forecasting becomes increasingly important, especially for the insurance and pension industries. However, a wide variety of projection methods are in use, both between and within countries, that produce different outcomes. OBJECTIVE We review the different mortality forecasting methods and their assumptions in Europe, and assess their impact on projections of future life expectancy for the Netherlands. METHODS For the Netherlands, we assess the projections of life expectancy at birth (e0) and at age 65 (e65) up to 2050 resulting from different methods using similar explicit assumptions regarding the historical period and the jump-off rates. We compare direct linear extrapolation, the Lee-Carter model, the Li-Lee model, a cohort model, separate projections of smoking- and non-smoking-related mortality, and the official forecast. RESULTS In predicting mortality, statistical offices in Europe mostly use simple linear extrapolation methods. Countries with less linear trends employ other approaches or different assumptions. The approaches used in the Netherlands include explanatory models, the separate projection of smoking- and non-smoking-related mortality, and the projection of the age profile of mortality. There are clear differences in the explicit assumptions used, including assumptions regarding the historical period. The resulting e0 in 2050 varies by approximately six years. Using the same historical period (1970-2009) and the observed jump-off rates, the findings generated by different methods result in a range of 2.1 years for women and of 1.8 years for men. For e65, the range is 1.4 and 1.9 years, respectively. CONCLUSIONS As the choice of the explicit assumptions proved to be more important than the choice of the forecasting method, the assumptions should be carefully considered when forecasting mortality.
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spelling doaj.art-6411db3f18c14b57b9d508bf668d5c4b2022-12-22T03:20:51ZengMax Planck Institute for Demographic ResearchDemographic Research1435-98712013-08-012913Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the NetherlandsLenny StoeldraijerCoen van DuinL.J.G van WissenFanny JanssenBACKGROUND With the rapid aging of the population, mortality forecasting becomes increasingly important, especially for the insurance and pension industries. However, a wide variety of projection methods are in use, both between and within countries, that produce different outcomes. OBJECTIVE We review the different mortality forecasting methods and their assumptions in Europe, and assess their impact on projections of future life expectancy for the Netherlands. METHODS For the Netherlands, we assess the projections of life expectancy at birth (e0) and at age 65 (e65) up to 2050 resulting from different methods using similar explicit assumptions regarding the historical period and the jump-off rates. We compare direct linear extrapolation, the Lee-Carter model, the Li-Lee model, a cohort model, separate projections of smoking- and non-smoking-related mortality, and the official forecast. RESULTS In predicting mortality, statistical offices in Europe mostly use simple linear extrapolation methods. Countries with less linear trends employ other approaches or different assumptions. The approaches used in the Netherlands include explanatory models, the separate projection of smoking- and non-smoking-related mortality, and the projection of the age profile of mortality. There are clear differences in the explicit assumptions used, including assumptions regarding the historical period. The resulting e0 in 2050 varies by approximately six years. Using the same historical period (1970-2009) and the observed jump-off rates, the findings generated by different methods result in a range of 2.1 years for women and of 1.8 years for men. For e65, the range is 1.4 and 1.9 years, respectively. CONCLUSIONS As the choice of the explicit assumptions proved to be more important than the choice of the forecasting method, the assumptions should be carefully considered when forecasting mortality.http://www.demographic-research.org/volumes/vol29/13/EuropeextrapolationLee-Carter modelNetherlandsnon-linear modelssmoking
spellingShingle Lenny Stoeldraijer
Coen van Duin
L.J.G van Wissen
Fanny Janssen
Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
Demographic Research
Europe
extrapolation
Lee-Carter model
Netherlands
non-linear models
smoking
title Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
title_full Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
title_fullStr Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
title_full_unstemmed Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
title_short Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands
title_sort impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy the case of the netherlands
topic Europe
extrapolation
Lee-Carter model
Netherlands
non-linear models
smoking
url http://www.demographic-research.org/volumes/vol29/13/
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AT ljgvanwissen impactofdifferentmortalityforecastingmethodsandexplicitassumptionsonprojectedfuturelifeexpectancythecaseofthenetherlands
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