Work

Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records

Year: 2023

Type: article

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 packagegompertztrunc, which implements the methods introduced in this paper.

Source: Population Research and Policy Review

DOI: 10.1007/s11113-023-09785-z

Authors: Joshua R. Goldstein, Maria Osborne, Serge Atherwood, Casey F. Breen

Institutions: University of California, Berkeley, Philip R. Lee Institute for Health Policy Studies, University of San Francisco

Language: English

Topic: Insurance, Mortality, Demography, Risk Management

Subfield: Demography

Field: Social Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,990