The 8 OMB Categories
The 2020 U.S. census made available a large number of racial and ethnic categories. These options helped capture the diversity of the United States’ people. However, analyzing population data across these categories is somewhat difficult, given the sheer number of different categories. Simplifying the data by combining various categories helps make analysis easier.
One such simplification is the Office of Management and Budget’s (OMB) racial and ethnic categorization that place every person in the United States into one of 8 categories:
- Non-Hispanic (NH) white
- NH Black plus NH Black and white
- NH Asian plus NH Asian and white
- NH American Indian plus NH American Indian and white
- NH Pacific Islander plus NH Pacific Islander and white
- NH Some Other Races Alone plus NH Some Other Race Alone and white
- NH Other Multiple Race (where more than one minority race listed)
- Hispanic
2020 Census Data by OMB Category
According to the 2020 census data, 57.9% of the United States population falls into the first OMB category, Non-Hispanic white. The totals for the different categories are shown below:
| Non-Hispanic (NH) White Alone | NH Black Alone plus NH Black and White | NH Asian Alone + NH Asian and White | NH American Indian Alone + NH American Indian and White | NH Pacific Islander Alone + NH Pacific Islander and White | NH Some Other Race Alone + NH Some Other Race and White | NH Other Multiple-Race (where more than one minority race listed) | Hispanic | |
|---|---|---|---|---|---|---|---|---|
| U.S. Population | 57.9% | 12.8% | 6.7% | 1.8% | 0.2% | 1.2% | 0.7% | 18.7% |
Electoral “Representation” by OMB Category
One interesting question to consider, in light of these number, is how “well-represented” these groups are in American electoral politics. In particular, I was curious to know, for a given OMB category and electoral level, what percentage of seats or districts have that group as the largest (plurality) population.
As an example, people who identify as either Non-Hispanic American Indian or Non-Hispanic American Indian and white may encompass 1.8% of the population, but in how many congressional districts are they the largest OMB group?
Please note: For my analyses “largest” refers to the plurality OMB group of the total population in that district, and does not capture variations in population age, citizenship status or voting-registration.)
If you blindly took ~1.8% (this group’s percentage of the total U.S. population) and multiplied it by 435 (the total number of U.S. Congressional seats), you might expect there to be ~10 such Congressional Districts. While this is a reasonable enough estimate, in fact, there are actually 0 2022 Congressional Districts where people who identify as either Non-Hispanic American Indian or Non-Hispanic American Indian and white comprise the largest of the 8 OMB groups.
One important consideration in the gap between the “expected” seats and the actual seats is how population is spread across the United States. While Non-Hispanic whites comprise 57.9% of the U.S.’ population, they are spread throughout the country in sufficient concentrations to encompass the largest OMB group in 80.2% of U.S. Congressional Districts. Other considerations might include gerrymandering, legislative district sizes, and other state redistricting requirements.
Values in this table may be interesting to consider in light of the anticipated “majority-minority” demographics of the United States.
Values for other OMB groups at other electoral levels are shown in the table below. Please note that there are three rows each for the State Legislative Lower (SLL) district and State Legislative Upper (SLU) district levels.
The first row for each level “SL(L/U) Districts as Largest Group (%)” does not consider multi-member districts and simply tracks the percentage of districts where a particular OMB group is the largest.
The second row for each level “SL(L/U) Rep.’s Districts* as Largest Group (%)” considers multi-member districts and tracks the percentage of representatives for whom’s district a particular OMB group is the largest.
An example differentiating between the first and second rows would be a 2-member district whose largest OMB group is Non-Hispanic white alone. In the first row, this would be counted as just one district, in the second two.
Finally, the third row “SL(L/U) Rep.’s Districts (Norm.) as Largest Group (%)” considers multi-member districts similar to the second row, but also normalizes by the size of the state’s particular legislature. For example, the Alaska State House has only 40 members, whereas the New Hampshire State House has 400 members. In this row, totals in Alaska State House would be divided by 40 and totals in the New Hampshire State House by 400.
Data Table
| Non-Hispanic (NH) White Alone | NH Black Alone plus NH Black and White | NH Asian Alone + NH Asian and White | NH American Indian Alone + NH American Indian and White | NH Pacific Islander Alone + NH Pacific Islander and White | NH Some Other Race Alone + NH Some Other Race and White | NH Other Multiple-Race (where more than one minority race listed) | Hispanic | |
|---|---|---|---|---|---|---|---|---|
| U.S. Population | 57.9% | 12.8% | 6.7% | 1.8% | 0.2% | 1.2% | 0.7% | 18.7% |
| Cong. Districts as Largest Group (%) | 80.2% | 6.0% | 1.6% | 0.0% | 0.0% | 0.0% | 0.0% | 12.2% |
| SLL Districts as Largest Group (%) | 83.8% | 8.4% | 1.1% | 0.5% | 0.0% | 0.0% | 0.0% | 6.2% |
| SLL Rep.’s Districts* as Largest Group (%) | 84.6% | 8.0% | 1.0% | 0.5% | 0.0% | 0.0% | 0.0% | 5.9% |
| SLL Rep.’s Districts* (Norm.) as Largest Group (%) | 83.3% | 7.2% | 1.8% | 0.8% | 0.1% | 0.0% | 0.0% | 6.8% |
| SLU Districts as Largest Group (%) | 84.6% | 7.2% | 1.2% | 0.7% | 0.1% | 0.0% | 0.0% | 6.3% |
| SLU Rep.’s Districts as Largest Group (%) | 84.8% | 7.0% | 1.2% | 0.7% | 0.1% | 0.0% | 0.0% | 6.2% |
| SLU Rep.’s Districts (Norm.) as Largest Group (%) | 84.8% | 6.4% | 1.6% | 0.7% | 0.1% | 0.0% | 0.0% | 6.4% |
| Senate Seats as Largest Group (%) | 94.0% | 0.0% | 2.0% | 0.0% | 0.0% | 0.0% | 0.0% | 4.0% |
Sources
National Block Assignment File + 2020 PL Census Data from the Redistricting Data Hub.