Robustness and convergence in the Lee–Carter model with cohort effects
Andrew Hunt and
Andrés M. Villegas
Insurance: Mathematics and Economics, 2015, vol. 64, issue C, 186-202
Abstract:
Interest in cohort effects in mortality data has increased dramatically in recent years, with much of the research focused on extensions of the Lee–Carter model incorporating cohort parameters. However, some studies find that these models are not robust to changes in the data or fitting algorithm, which limits their suitability for many purposes. It has been suggested that these robustness problems may be the result of an unresolved identifiability issue. In this paper, after investigating systemically the robustness of cohort extensions of the Lee–Carter model and the convergence of the algorithms used to fit it to data, we demonstrate the existence of such an identifiability issue and propose an additional approximate identifiability constraint which solves many of the problems found.
Keywords: Lee–Carter model; Cohort effects; Mortality modelling; Robustness; Convergence (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167668715000852
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:64:y:2015:i:c:p:186-202
DOI: 10.1016/j.insmatheco.2015.05.004
Access Statistics for this article
Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu
More articles in Insurance: Mathematics and Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().