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Modeling Mortality with a Bayesian Vector Autoregression

Carolyn Njenga () and Michael Sherris ()
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Carolyn Njenga: School of Risk and Actuarial Studies and ARC Centre of Excellence in Population Ageing Research, Australian School of Business, University of New South Wales
Michael Sherris: School of Risk and Actuarial Studies and ARC Centre of Excellence in Population Ageing Research, Australian School of Business, University of New South Wales

No 201105, Working Papers from ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales

Abstract: 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.

Keywords: Mortality; parameter risk; vector auto-regression; Bayesian; Heligman-Pollard model (search for similar items in EconPapers)
JEL-codes: J11 C11 G22 (search for similar items in EconPapers)
Date: 2011-03
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