Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records

Joshua R. Goldstein (), Maria Osborne (), Serge Atherwood () and Casey F. Breen ()
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Joshua R. Goldstein: University of California, Berkeley
Maria Osborne: University of California, Berkeley
Serge Atherwood: University of San Francisco
Casey F. Breen: University of California, Berkeley

Population Research and Policy Review, 2023, vol. 42, issue 3, No 7, 20 pages

Abstract: Abstract New advances in data linkage provide mortality researchers with access to administrative datasets with millions of mortality records and rich demographic covariates. Although these new datasets allow for high-resolution mortality research, administrative mortality records often have technical limitations, such as limited mortality coverage windows and incomplete observation of survivors. We describe a method for fitting truncated distributions that can be used for estimating mortality differentials in administrative data. We apply this method to the CenSoc datasets, which link the United States 1940 Census records to Social Security administrative mortality records. Our approach may be useful in other contexts where administrative data on deaths are available. As a companion to the paper, we release the R package gompertztrunc, which implements the methods introduced in this paper.

Keywords: Mortality estimation; Truncation; Statistical methods; Gompertz (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11113-023-09785-z

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