Jointly estimating subnational mortality for multiple populations
Ameer Dharamshi,
Magali Barbieri,
Monica Alexander and
Celeste Winant
Additional contact information
Ameer Dharamshi: University of Washington
Magali Barbieri: Institut National d'Études Démographiques (INED)
Monica Alexander: University of Toronto
Celeste Winant: University of California, Berkeley
Demographic Research, 2025, vol. 52, issue 3, 71-110
Abstract:
Background: Understanding patterns in mortality across subpopulations is essential for local health policy decision-making. One of the key challenges of subnational mortality rate estimation is the presence of small populations and zero or near zero death counts. When studying differences between subpopulations, this challenge is compounded as the small populations are further divided along socioeconomic or demographic lines. Objective: We aim to develop a model to estimate subnational age-specific mortality rates that accounts for the dependencies in mortality experiences across subpopulations. Methods: We develop a Bayesian hierarchical principal components-based model that shows correlations across subpopulations. Results: We test this approach in a simulation study and also use the model to estimate age- and sex-specific mortality rates for counties in the United States. The model performs well in validation exercises and the US estimates suggest substantial variation in mortality trends over time across geographic lines. Contribution: Our proposed model jointly estimates age-specific mortality rates for multiple subpopulations at the subnational level. By sharing information across subpopulations, our model improves on previous approaches that treat subpopulations as independent. Additionally, we demonstrate that ancillary correlation parameters are a useful tool for studying the convergence and divergence of mortality patterns over time.
Keywords: mortality rates; Bayesian hierarchical model; principal components analysis; subnational; estimation; US counties; joint estimation (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.demographic-research.org/volumes/vol52/3/52-3.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:dem:demres:v:52:y:2025:i:3
DOI: 10.4054/DemRes.2025.52.3
Access Statistics for this article
More articles in Demographic Research from Max Planck Institute for Demographic Research, Rostock, Germany
Bibliographic data for series maintained by Editorial Office ().