Abstract
Influential existing research has suggested that rather than being static, mortality declines decelerate at young ages and accelerate at old ages. Without accounting for this feature, the forecast mortality rates of the popular Lee-Carter (LC) model are less reliable in the long run. To provide more accurate mortality forecasting, we introduce a time-varying coefficients extension of the LC model by adopting the effective kernel methods. With two frequently used kernel functions, Epanechnikov (LC-E) and Gaussian (LC-G), we demonstrate that the proposed extension is easy to implement, incorporates the rotating patterns of mortality decline and is straightforwardly extensible to multi-population cases. Using a large sample of 15 countries over 1950-2019, we show that LC-E and LC-G, as well as their multi-population counterparts, can consistently improve the forecasting accuracy of the competing LC and Li-Lee models in both single- and multi-population scenarios.
Original language | English |
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Article number | 743 |
Pages (from-to) | 1-20 |
Number of pages | 20 |
Journal | Healthcare (Basel, Switzerland) |
Volume | 11 |
Issue number | 5 |
DOIs | |
Publication status | Published - 3 Mar 2023 |
Bibliographical note
Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Lee–Carter model
- life expectancy
- mortality rates
- rotated age pattern
- time-varying coefficients