Modeling Mortality with a Bayesian Vector Autoregression

Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages.

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Year of publication:	2011-03
Authors:	Njenga, Carolyn ; Sherris, Michael
Institutions:	ARC Centre of Excellence in Population Ageing Research (CEPAR), UNSW Business School
Subject:	Mortality \| parameter risk \| vector auto-regression \| Bayesian \| Heligman-Pollard model

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Extent:	application/pdf
Series:	Working Papers.
Type of publication:	Book / Working Paper
Notes:	Number 201105 39 pages
Classification:	J11 - Demographic Trends and Forecasts ; C11 - Bayesian Analysis ; G22 - Insurance; Insurance Companies
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010551692