Evaluating the Accuracy of 2020 Census Block-Level Estimates in California.
2020 Census
Data quality
Population enumeration
Small-area estimates
Journal
Demography
ISSN: 1533-7790
Titre abrégé: Demography
Pays: United States
ID NLM: 0226703
Informations de publication
Date de publication:
01 Dec 2023
01 Dec 2023
Historique:
pubmed:
27
11
2023
medline:
27
11
2023
entrez:
27
11
2023
Statut:
ppublish
Résumé
In this study, we provide an assessment of data accuracy from the 2020 Census. We compare block-level population totals from a sample of 173 census blocks in California across three sources: (1) the 2020 Census, which has been infused with error to protect respondent confidentiality; (2) the California Neighborhoods Count, the first independent enumeration survey of census blocks; and (3) projections based on the 2010 Census and subsequent American Community Surveys. We find that, on average, total population counts provided by the U.S. Census Bureau at the block level for the 2020 Census are not biased in any consistent direction. However, subpopulation totals defined by age, race, and ethnicity are highly variable. Additionally, we find that inconsistencies across the three sources are amplified in large blocks defined in terms of land area or by total housing units, blocks in suburban areas, and blocks that lack broadband access.
Identifiants
pubmed: 38009227
pii: 383963
doi: 10.1215/00703370-11075209
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1903-1921Informations de copyright
Copyright © 2023 The Authors.