Census Bureau Releases Estimates of Undercount and Overcount in the 2020 Census
-0.24% TOTAL UNDERCOUNT NATIONWIDE
(compared to +0.01% overcount in 2010)
-3.30% TOTAL UNDERCOUNT AMONG AFRICAN AMERICANS
(compared to -2.06% undercount in 2010)
-4.99% TOTAL UNDERCOUNT AMONG HISPANIC AMERICANS
(compared to -1.54% undercount in 2010)
-5.64% TOTAL UNDERCOUNT AMONG NATIVES LIVING ON RESERVATIONS
(compared to -4.88% undercount in 2010)
+1.64% OVERCOUNT AMONG NON-HISPANIC WHITE AMERICANS
(compared to +0.83% overcount in 2010)
+2.62% OVERCOUNT AMONG ASIAN AMERICANS
(compared to 0.00% in 2010)
+1.28% OVERCOUNT AMONG NATIVE HAWAIIANS AND PACIFIC ISLANDERS
(compared to +1.02% overcount in 2010)
Undercount means the true estimated population is higher than what was recorded
Overcount means the true estimated population is lower than what was recorded
Interesting that both Asians and Pacific Islanders were overcounted by more than Non-Hispanic Whites. Wonder if this is correlated with the one-drop rule being applied to mixed-race folks, as seems to be the case on here.
https://archive.ph/tycWl
Overcounted individuals were individuals who were counted in multiple locations, like college students being counted at their parents’ homes rather than at school, families with multiple homes, children with shared custody, or households that moved during the decennial count. A similar post-enumeration survey for the 2010 Census revealed essentially no overcount or undercount for both groups, with net coverage rates of 0 percent and -1.02 percent for Asian Americans and Native Hawaiians and Pacific Islanders, respectively, though neither measure was statistically significant from zero. Positive net coverage rates indicate a net overcount and negative net coverage rates indicate a net undercount.
Even though net coverage rates for AANHPI communities indicated no net undercount, we know from previous censuses and other government surveys that there are significant differences between the members of our community who are overcounted and those who are undercounted. With the examples above, we see that those who are most likely to be overcounted tend to be more economically advantaged, while those who are most likely to be undercounted include economically disadvantaged groups, such as recent immigrants, low-income families, young children, and refugees. While the two types of errors in the Census balance each other out for AANHPIs, the biases in who is overcounted and who is undercounted impacts the underlying disaggregated data. This is another case where aggregated data for AANHPI communities ends up hiding a significant issue, in this case, the challenges of outreach to specific ethnic groups or geographic areas within AANHPI populations.
More importantly, when we examine the components of 2020 Census coverage, we find that the biggest improvement in census coverage for AANHPI communities occurred in the decrease in the rate of omissions. The Census Bureau defines omissions as people who should have been enumerated, but were not. The omissions rate for Asian Americans dropped from 5.3 percent in 2010 to 3.5 percent in 2020, while the rate for Native Hawaiians and Pacific Islanders fell from 7.9 percent in 2010 to 6.6 percent in 2020. The decrease in omissions rate for Asian Americans was statistically significant, but the decrease for Native Hawaiians and Pacific Islanders was not.
