Variance in death and its implications for modeling and forecasting mortality

Shripad Tuljapurkar and Ryan Edwards ()
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Shripad Tuljapurkar: Stanford University

Demographic Research, 2011, vol. 24, issue 21, 497-526

Abstract: The slope and curvature of the survivorship function reflect the considerable amount of variance in length of life found in any human population. This is due in part to the well-known variation in life expectancy between groups: large differences in 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 in the temporal dimension.

Keywords: inequality; entropy; proportional hazards (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (27)

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Related works:
Working Paper: Variance in Death and Its Implications for Modeling and Forecasting Mortality (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:dem:demres:v:24:y:2011:i:21

DOI: 10.4054/DemRes.2011.24.21

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