CREAT: Census Research Exploration and Analysis Tool

Education and Mortality: Evidence for the Silent Generation from Linked Census and Administrative Data

August 2025

Working Paper Number:

CES-25-56

Abstract

We quantify the effect of education on mortality using a linkage of the full count 1940, 2000, and 2010 US census files and the Numident death records file. Our sample is composed of children aged 0-18 in 1940, observed living with at least one parent, for whom we can construct a rich set of parental and neighborhood characteristics. We estimate effects of educational attainment in 1940 on survival to 2000, as well as the effects of completed education, observed in 2000, on 10-year survival to 2010. The educational gradients in longevity that we estimate are robust to the inclusion of detailed individual, parental, household, neighborhood and county covariates. Given our full population census sample, we also explore rich patterns of heterogeneity and examine the effect of mediators of the education-mortality relationship. The mediators we consider in this study explain more than half of the relationship between education and mortality. We further show that the mechanisms underlying the education-mortality gradient might be different at different margins of educational attainment.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
respondent, ethnicity, retirement, population, educated, education, graduate, socioeconomic, disparity, schooling, mortality, cohort, adulthood, death

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

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:
Yale University, Social Security Administration, Department of Economics, Health and Retirement Study, Protected Identification Key, NUMIDENT, Census Bureau Disclosure Review Board, Integrated Public Use Microdata Series, Federal Statistical Research Data Center

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