Using the Developing Countries Mortality Database (DCMD) to Probabilistically Evaluate the Completeness of Death Registration at Old Ages

Nan Li (), Hong Mi () and Xiaotong Tang ()
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Nan Li: Population Division, Department of Economic and Social Affairs, United Nations
Hong Mi: Zhejiang University, School of Public Affairs
Xiaotong Tang: Zhejiang University, School of Public Affairs

Chapter Chapter 10 in Demography of Population Health, Aging and Health Expenditures, 2020, pp 133-149 from Springer

Abstract: Abstract Like the ratio of registered deaths to total deaths, the deterministic completeness of death registration (DR) cannot be exactly 1 in practice. Consequently, it is impossible to use deterministic completeness to check whether a DR is complete, which is a problem for developed countries. We propose a probabilistic completeness whose samples are the values of deterministic completeness. When the difference between 1 and the mean of probabilistic completeness is statistically insignificant, the DR is probabilistically complete. But using intercensal population change to estimate deaths and deterministic completeness is still an issue, because it requires unrealistic assumptions about migration and census errors. Focusing on old age and the level of mortality rather than the number of deaths, the effects of migration and census errors are largely reduced in the Developing Countries Mortality Database (DCMD, www.lifetables.org ), which is used in this paper to provide applications of the probabilistic evaluation.

Date: 2020
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DOI: 10.1007/978-3-030-44695-6_10

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