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Deaths without denominators: using a matched dataset to study mortality patterns in the United States

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  • Alexander, Monica

Abstract

To understand national trends in mortality over time, it is important to study differences by demographic, socioeconomic and geographic characteristics. One issue with studying mortality inequalities, particularly by socioeconomic status, is that there are few micro-level data sources available that link an individual's SES with their eventual age and date of death. In this paper, a new dataset for studying mortality disparities and changes over time in the United States is presented. The dataset, termed 'CenSoc', uses two large-scale datasets: the full-count 1940 Census to obtain demographic, socioeconomic and geographic information; and that is linked to the Social Security Deaths Masterfile (SSDM) to obtain mortality information. This paper also develops mortality estimation methods to better use the 'deaths without denominators' information contained in CenSoc. Bayesian hierarchical methods are presented to estimate truncated death distributions over age and cohort, allowing for prior information in mortality trends to be incorporated and estimates of life expectancy and associated uncertainty to be produced.

Suggested Citation

  • Alexander, Monica, 2018. "Deaths without denominators: using a matched dataset to study mortality patterns in the United States," SocArXiv q79ye, Center for Open Science.
    • Handle: RePEc:osf:socarx:q79ye
    DOI: 10.31219/osf.io/q79ye
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    Cited by:

    1. Casey Breen & Joshua R. Goldstein, 2022. "Berkeley Unified Numident Mortality Database: Public administrative records for individual-level mortality research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(5), pages 111-142.
    2. Goldstein, Joshua R. & Osborne, Maria & Atherwood, Serge & Breen, Casey, 2022. "Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records," SocArXiv efdzh, Center for Open Science.
    3. Joshua R. Goldstein & Maria Osborne & Serge Atherwood & Casey F. Breen, 2023. "Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(3), pages 1-20, June.
    4. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294, Center for Open Science.
    5. Breen, Casey & Seltzer, Nathan, 2023. "The Unpredictability of Individual-Level Longevity," SocArXiv znsqg, Center for Open Science.
    6. Breen, Casey, 2024. "Black-White Mortality Crossover: New Evidence from Social Security Mortality Records," SocArXiv ax9u3, Center for Open Science.
    7. Breen, Casey, 2023. "The Longevity Benefits of Homeownership," SocArXiv 7ya3f, Center for Open Science.

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