Fuzzy clustering of the healthy life expectancy decomposition: A multi-population analysis

Leonardo Salvatore Alaimo, Susanna Levantesi and Andrea Nigri

Socio-Economic Planning Sciences, 2024, vol. 92, issue C

Abstract: This work analyses healthy life expectancy, which combines information on the period life table with the age-specific disability prevalence data in a single indicator. We quantify how much mortality and disability contributed to changes in healthy life expectancy over a fixed time horizon by age group and population to understand if life expectancy is increasing faster than the decline of disability. The prominent heterogeneity in mortality and health worldwide calls for a cross-country comparative analysis. The methodology used is decomposition, which splits the difference between two times of an aggregate index by assigning the difference to its components. Besides, through a cluster analysis, we categorize countries according to the age-specific contributions of mortality and disability simultaneously, using the healthy life expectancy decomposition results. This allows us to ease the interpretation and better outline the outcomes. Since health is increasingly considered a crucial aspect of economic growth, monitoring health expectancies is essential to assess the financial sustainability of the health and social security system. Some policy implications are finally discussed.

Keywords: Healthy life expectancy; Fuzzy clustering; Decomposition model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:92:y:2024:i:c:s0038012124000041

DOI: 10.1016/j.seps.2024.101805

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