Addressing the life expectancy gap in pension policy

Bibliographic Details
Main Author: Bravo, Jorge M.
Publication Date: 2021
Other Authors: Ayuso, Mercedes, Holzmann, Robert, Palmer, Edward
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/117836
Summary: Bravo, J. M., Ayuso, M., Holzmann, R., & Palmer, E. (2021). Addressing the life expectancy gap in pension policy. Insurance: Mathematics and Economics, 99, 200-221. https://doi.org/10.1016/j.insmatheco.2021.03.025 ---%ABS3%
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spelling Addressing the life expectancy gap in pension policyBayesian Model EnsembleIntergenerational fairnessMortality forecastingPension indexationPension reformsPeriod and cohort life expectancySustainability factorStatistics and ProbabilityEconomics and EconometricsStatistics, Probability and UncertaintySDG 3 - Good Health and Well-beingBravo, J. M., Ayuso, M., Holzmann, R., & Palmer, E. (2021). Addressing the life expectancy gap in pension policy. Insurance: Mathematics and Economics, 99, 200-221. https://doi.org/10.1016/j.insmatheco.2021.03.025 ---%ABS3%Understanding the systematic relationship between period and cohort life expectancy and how the relationship evolves over time are critical issues in formulating the design of retirement income products, evaluating the actuarial balance of pension schemes, and more generally for all analyses where demographic projections are involved. In this study, estimates of the life expectancy gap at all ages are performed using data for 1960–2018 from the Human Mortality Database and projections are generated through 2050 for the 42 national populations, disaggregated by sex. Contrary to previous research that often uses a single deemed to be «best» model to forecast mortality rates, we use a novel adaptive Bayesian Model Ensemble of heterogeneous parametric generalized age-period-cohort stochastic mortality models, principal component methods, and smoothing approaches. The procedure involves both the selection of the model confidence set and the determination of optimal weights. Model-averaged Bayesian credible prediction intervals are derived accounting for both the uncertainty arising from model error and parameter uncertainty. With intergenerational actuarial fairness and neutrality as the guiding principles the study then explores potential policy interventions to address the consequences of the life expectancy gap - spanning over adjustments in the accumulation, benefit determination, and payout stages. Comprehensive numerical results are provided for two policy options: (i) introducing a sustainability factor; and (ii) conditional pension indexation. The results show that: (i) the life expectancy gap is positive and significant for almost all countries and years studied, (ii) it will continue to increase, (iii) the magnitude of the subsidy rates between generations can be sizeable demanding important initial pension benefit reduction and/or a gradual diminution in the annual indexation rate of pensions to correct them.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNBravo, Jorge M.Ayuso, MercedesHolzmann, RobertPalmer, Edward2024-12-28T01:31:53Z2021-07-012021-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article22application/pdfhttp://hdl.handle.net/10362/117836eng0167-6687PURE: 29764980https://doi.org/10.1016/j.insmatheco.2021.03.025info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-12-30T01:33:48Zoai:run.unl.pt:10362/117836Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:24:16.321210Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Addressing the life expectancy gap in pension policy
title Addressing the life expectancy gap in pension policy
spellingShingle Addressing the life expectancy gap in pension policy
Bravo, Jorge M.
Bayesian Model Ensemble
Intergenerational fairness
Mortality forecasting
Pension indexation
Pension reforms
Period and cohort life expectancy
Sustainability factor
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 3 - Good Health and Well-being
title_short Addressing the life expectancy gap in pension policy
title_full Addressing the life expectancy gap in pension policy
title_fullStr Addressing the life expectancy gap in pension policy
title_full_unstemmed Addressing the life expectancy gap in pension policy
title_sort Addressing the life expectancy gap in pension policy
author Bravo, Jorge M.
author_facet Bravo, Jorge M.
Ayuso, Mercedes
Holzmann, Robert
Palmer, Edward
author_role author
author2 Ayuso, Mercedes
Holzmann, Robert
Palmer, Edward
author2_role author
author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Bravo, Jorge M.
Ayuso, Mercedes
Holzmann, Robert
Palmer, Edward
dc.subject.por.fl_str_mv Bayesian Model Ensemble
Intergenerational fairness
Mortality forecasting
Pension indexation
Pension reforms
Period and cohort life expectancy
Sustainability factor
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 3 - Good Health and Well-being
topic Bayesian Model Ensemble
Intergenerational fairness
Mortality forecasting
Pension indexation
Pension reforms
Period and cohort life expectancy
Sustainability factor
Statistics and Probability
Economics and Econometrics
Statistics, Probability and Uncertainty
SDG 3 - Good Health and Well-being
description Bravo, J. M., Ayuso, M., Holzmann, R., & Palmer, E. (2021). Addressing the life expectancy gap in pension policy. Insurance: Mathematics and Economics, 99, 200-221. https://doi.org/10.1016/j.insmatheco.2021.03.025 ---%ABS3%
publishDate 2021
dc.date.none.fl_str_mv 2021-07-01
2021-07-01T00:00:00Z
2024-12-28T01:31:53Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/117836
url http://hdl.handle.net/10362/117836
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0167-6687
PURE: 29764980
https://doi.org/10.1016/j.insmatheco.2021.03.025
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 22
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596672191496192

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