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Published on: January 7, 2013
Variance in Death and Its Implications for Modeling and Forecasting Mortality
Shripad Tuljapurkar1, Ryan D Edwards1
1Morrison Professor of Population Studies, Department of Biological Sciences, Stanford University, Herrin Labs 454, Stanford, CA 94305-5020. tulja@stanford.edu .
Abstract:
The slope and curvature of the survivorship function reflect the considerable amount of variance in length of life found in any human population. Part is due to the well-known variation in life expectancy between groups: large differences according to race, sex, socioeconomic status, or other covariates. But within-group variance is large even in narrowly defined groups, and changes substantially and inversely with the group average length of life. We show that variance in length of life is inversely related to the Gompertz slope of log mortality through age, and we reveal its relationship to variance in a multiplicative frailty index. Our findings bear a variety of implications for modeling and forecasting mortality. In particular, we examine how the assumption of proportional hazards fails to account adequately for differences in subgroup variance, and we discuss how several common forecasting models treat the variance along the temporal dimension.
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