Variance in Death and Its Implications for Modeling and Forecasting Mortality

Shripad Tuljapurkar and Ryan Edwards ()

No 15288, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Entropy, or the gradual decline through age in the survivorship function, reflects 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 very large even in narrowly defined groups, and it varies strongly 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.

JEL-codes: I1 J11 N3 (search for similar items in EconPapers)
Date: 2009-08
New Economics Papers: this item is included in nep-age, nep-for and nep-hea
Note: AG EH
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Citations: View citations in EconPapers (3)

Published as Tuljapurkar, Shripad and Ryan D. Edwards (2011) “Variance in Death and Its Implications for Modeling and Forecasting Mortality,” Demographic Research 24(21): 497-526.

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Journal Article: Variance in death and its implications for modeling and forecasting mortality (2011)
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