An Age Grouping Framework for Multi-Population Mortality Modeling

This study extends existing mortality prediction frameworks by incorporating information borrowed from population–gender–age subgroups that exhibit similar mortality patterns. The borrowed information is integrated into classical mortality models to improve the accuracy of future mortality rate forecasts. To capture structural similarities among mortality trajectories, several distance measures are evaluated in combination with four linkage methods, particularly when each subgroup comprises multiple age-specific mortality trajectories. Extensive empirical analyses using data from the Human Mortality Database demonstrate the superior predictive performance of the proposed approach.

Authors

Institutions

Publication Details

Journal
Risks
Published
2026-03-09
DOI
https://doi.org/10.3390/risks14030059
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Age Grouping Framework for Multi-Population Mortality Modeling

Cezar Câmpeanu, Yechao Meng
Risks
Insurance, Mortality, Demography, Risk Management
article

An Age Grouping Framework for Multi-Population Mortality Modeling

Cezar Câmpeanu, Yechao Meng
article en

Abstract

This study extends existing mortality prediction frameworks by incorporating information borrowed from population–gender–age subgroups that exhibit similar mortality patterns. The borrowed information is integrated into classical mortality models to improve the accuracy of future mortality rate forecasts. To capture structural similarities among mortality trajectories, several distance measures are evaluated in combination with four linkage methods, particularly when each subgroup comprises multiple age-specific mortality trajectories. Extensive empirical analyses using data from the Human Mortality Database demonstrate the superior predictive performance of the proposed approach.

RisksVol. 14(3)
University of Prince Edward Island (CA)
Good health and well-being
Openalex Percentile: Top 42%
Insurance, Mortality, Demography, Risk Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.