Longevity and concentration in survival times: the log-scale-location family of failure time models

Chiara Gigliarano (), Ugofilippo Basellini () and Marco Bonetti ()
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Chiara Gigliarano: Department of Economics, University of Insubria
Ugofilippo Basellini: Max Planck International Research Network on Aging and European Doctoral School of Demography
Marco Bonetti: Bocconi University and Dondena Centre for Research on Social Dynamics and Public Policy

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2017, vol. 23, issue 2, No 5, 254-274

Abstract: Abstract Evidence suggests that the increasing life expectancy levels at birth witnessed over the past centuries are associated with a decreasing concentration of the survival times. The purpose of this work is to study the relationships that exist between longevity and concentration measures for some regression models for the evolution of survival. In particular, we study a family of survival models that can be used to capture the observed trends in longevity and concentration over time. The parametric family of log-scale-location models is shown to allow for modeling different trends of expected value and concentration of survival times. An extension towards mixture models is also described in order to take into account scenarios where a fraction of the population experiences short term survival. Some results are also presented for such framework. The use of both the log-scale-location family and the mixture model is illustrated through an application to period life tables from the Human Mortality Database.

Keywords: Survival analysis; Longevity; Gini concentration index; Life table (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10985-016-9356-1

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