Life Expectancy Decomposition
Life-expectancy decomposition answers a question that a single number cannot: when life expectancy rises over time, or differs between two populations, exactly which ages and which causes of death are responsible? The family of methods takes two life tables and splits their gap in e0 (or ex at any age) into additive contributions from mortality differences in each age interval, with the contributions summing exactly to the total gap. Eduardo Arriaga's 1984 stepwise discrete method became the field standard because it is exact, intuitive, and easy to extend to a cause-of-death breakdown, separating a 'direct' effect of changed survival within an interval from an 'indirect plus interaction' effect that the change propagates to later ages. John Pollard's continuous formulation expresses the same decomposition as an integral of age-specific mortality differences weighted by their leverage on life expectancy, providing the theoretical underpinning and a cross-check. This page treats the general decomposition pipeline; the dedicated Arriaga and Pollard pages cover each estimator in depth.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Arriaga, E. E. (1984). Measuring and explaining the change in life expectancies. Demography, 21(1), 83-96. · DOI 10.2307/2061029
- Pollard, J. H. (1988). On the decomposition of changes in expectation of life and differentials in life expectancy. Demography, 25(2), 265-276. · DOI 10.2307/2061293
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.