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Variance in Death and Its Implications for Modeling and Forecasting Mortality

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Author Info
Shripad Tuljapurkar
Ryan D. Edwards

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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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15288.

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Date of creation: Aug 2009
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Handle: RePEc:nbr:nberwo:15288

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Find related papers by JEL classification:
I1 - Health, Education, and Welfare - - Health
J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends and Forecasts
N3 - Economic History - - Labor and Consumers, Demography, Education, Income, and Wealth

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  1. Shripad Tuljapurkar & Carl Boe, . "Mortality Change and Forecasting: How Much and How Little Do We Know?," Pension Research Council Working Papers 98-2, Wharton School Pension Research Council, University of Pennsylvania. [Downloadable!]
  2. Ryan D. Edwards, 2009. "The Cost of Cyclical Mortality," The B.E. Journal of Macroeconomics, Berkeley Electronic Press, vol. 9(1). [Downloadable!]
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This page was last updated on 2009-11-25.


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