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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.
Bozick et al. (Mon,) studied this question.