Modeling Mortality of Related Populations via Parameter Shrinkage

25 Pages Posted: 2 Jan 2019

See all articles by Gary Venter

Gary Venter

University of New South Wales (UNSW) - School of Actuarial Studies; Columbia University

Şule Şahin

University of Liverpool - Institute for Financial and Actuarial Mathematics; Hacettepe University - Department of Actuarial Sciences

Date Written: December 15, 2018

Abstract

Parameter shrinkage is known to reduce fitting and prediction errors in linear models. When the variables are dummies for age, period, etc. shrinkage is more commonly applied to differences between adjacent parameters, perhaps by fitting cubic splines or piecewise-linear curves (linear splines) across the parameters. A common problem in mortality is modeling related populations where some commonality is desired. We do this by shrinking slope changes of linear splines for the largest population, then shrinking differences from those slope changes for the other populations.

There are frequentist and Bayesian approaches to shrinkage, and they have a good deal of similarity. Here we use a unified approach that compromises a bit with both of these paradigms. It uses Bayesian tools without some of the historical Bayesian concepts, and pushes the random-effects framework slightly to accommodate.

Modeling Swedish and Danish male mortality data is used as an illustration.

Keywords: Joint Estimation, Parameter Shrinkage, MCMC, Mortality

JEL Classification: C02, C11, C22, C30, C51, C52, C58, C65, G22

Suggested Citation

Venter, Gary and Şahin, Şule, Modeling Mortality of Related Populations via Parameter Shrinkage (December 15, 2018). Available at SSRN: https://ssrn.com/abstract=3301981 or http://dx.doi.org/10.2139/ssrn.3301981

Gary Venter (Contact Author)

University of New South Wales (UNSW) - School of Actuarial Studies ( email )

Sydney, NSW 2052
Australia

Columbia University ( email )

116th and Broadway
New York, NY 10027
United States

Şule Şahin

University of Liverpool - Institute for Financial and Actuarial Mathematics ( email )

Liverpool
United Kingdom

Hacettepe University - Department of Actuarial Sciences ( email )

Ankara
Turkey

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