Using Deepest Dependency Paths to Enhance Life Expectancy Estimation

Irene Albarrán-Lozano (), Pablo J. Alonso-González () and Aurea Grané ()
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Irene Albarrán-Lozano: Universidad Carlos III de Madrid, Statistics Department
Pablo J. Alonso-González: Universidad de Alcalá, Statistics Department
Aurea Grané: Universidad Carlos III de Madrid, Statistics Department

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2018, pp 25-31 from Springer

Abstract: Abstract The aim of this work is to estimate life expectancy free of dependency (LEFD) using categorical data and individual dependency trajectories that are obtained using the whole medical history concerning the dependency situation of each individual from birth up to 2008, contained in database EDAD 2008. In particular, we estimate LEFD in several scenarios attending to age, gender, proximity-group and dependency degree. Proximity-groups are established according to an L 2-type distance from the dependency trajectories to a central trend within each age-gender group, using functional data techniques.

Keywords: Cox Regression; Dependency; Disability; Functional data (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-89824-7_5

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DOI: 10.1007/978-3-319-89824-7_5

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