Academic Journal
Modelling and forecasting adult age-at-death distributions.
| Τίτλος: | Modelling and forecasting adult age-at-death distributions. |
|---|---|
| Συγγραφείς: | Basellini, Ugofilippo1,2, Camarda, Carlo Giovanni1 |
| Πηγή: | Population Studies. Mar2019, Vol. 73 Issue 1, p119-138. 20p. 5 Charts, 8 Graphs. |
| Θεματικοί όροι: | *Death forecasting, *Mortality -- Mathematical models, *Multiple correspondence analysis (Statistics), Life expectancy, Longevity |
| Περίληψη: | Age-at-death distributions provide an informative description of the mortality pattern of a population but have generally been neglected for modelling and forecasting mortality. In this paper, we use the distribution of deaths to model and forecast adult mortality. Specifically, we introduce a relational model that relates a fixed 'standard' to a series of observed distributions by a transformation of the age axis. The proposed Segmented Transformation Age-at-death Distributions (STAD) model is parsimonious and efficient: using only three parameters, it captures and disentangles mortality developments in terms of shifting and compression dynamics. Additionally, mortality forecasts can be derived from parameter extrapolation using time-series models. We illustrate our method and compare it with the Lee-Carter model and variants for females in four high-longevity countries. We show that the STAD fits the observed mortality pattern very well, and that its forecasts are more accurate and optimistic than the Lee-Carter variants. [ABSTRACT FROM AUTHOR] |
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