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Two novel methods of life expectancy estimation, applied to various annual reported demographic datasets, are proposed. First, for datasets that fully recorded birth date and death date of all dead individuals, we rely on the well-known Kaplan–Meier estimation method to provide an accurate estimation framework of life expectancy. Our proposed method can be used as a gold standard in the accuracy investigation of other life expectancy estimation methods. The method can be applied for small areas, where complete mortality data are regularly produced by routine annual surveys. The second new created method, called as local parametric method, based on the theoretical background of survival process with local parametric Weibull distributions, estimates life expectancy using abridged survival data. Experiments on real longitudinal datasets show the new method provides very exact life expectancy estimations for 10 among 15 one-year datasets, whilst the method of Chiang often yields overestimations.

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The analysis in Sect. 4 of this study has been realized by using the longitudinal dataset of FilaBavi—Ba Vi Epidemiological Field Laboratory. Thanks are due to Prof. Dr. Nguyen Thi Kim Chuc, the main coordinator of FilaBavi, and to other scientists and workers who participated in conducting many years surveys and processing to produce the dataset, that plays a critical role for this study.

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Correspondence to Phuc Ho Dang.

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Communicated by Luiz Duczmal.

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Ho Dang, P., Nguyen, T.N. New methods of life expectancy estimation. Environ Ecol Stat 29, 587–606 (2022).

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