So far, Tiffani has noted some significant and remarkable findings from her Ethnoracial Equity Neighborhood Dataset. She has gained insight on the neighborhoods-based view of the ethnoracial representation numbers across Metro Atlanta and how these households are distributed across certain neighborhood types. She has been able to deepen her understanding of Black homeownership in Metro Atlanta by tying a simple yet significant finding on Black homeownership equity to a larger context that shows that comparatively high Black homeownership is occurring in neighborhoods that lean towards economically advantaged.
Fully focused on building a strong case for her upcoming presentation, Tiffani now turns her attention to ethnoracial groups as a whole. She navigates to the cross tabulation data-sheets to get a full picture of which neighborhood types are home to the largest shares of each ethnoracial group and to also make note of their overall distribution across neighborhood types. This exercise marks a continuation of her focus on socioeconomic neighborhood types and kickstarts a new focus on ethnoracial neighborhood types. In totality, her curated dataset identifies a total of six ethnoracial neighborhood types, with data-sheets dedicated to each of them. Out of these six, three neighborhood types endure throughout the dataset: 1) majority-White, 2) majority-Black, and 3) neither neighborhoods, which are neighborhoods that are neither majority-White nor majority-Black. This neither category is inclusive of the remaining three ethnoracial neighborhood types: 1) majority-Asian, 2) majority-Latino, and 3) ethnoracially mixed neighborhoods, where no single group is in the majority. She loves having ready access to lists of neighborhoods for each classification.
Source: US Census Bureau. 2024. "American Community Survey, Five-Year Estimates."
Tiffani previously noted the neighborhood type thresholds where group majorities could be found going from the top of the socioeconomic ladder and moving downward. After quickly producing the graph above, she now sees the full picture. She is able to note some quick facts regarding the disadvantaged neighborhood types, such as how less than 1-in-4 Asian households and slightly more than 1-in-4 White households reside in either semi-disadvantaged or disadvantaged neighborhoods. Within the same context, this number jumps to nearly 40 percent of Latino households. For Black households, both segments of disadvantaged neighborhoods represent the environment for more than half of the population (56.3 percent).
Next, Tiffani eyes the neighborhood types with the largest share of a group’s households. She has already documented that semi-disadvantaged neighborhoods have the largest share of Black households (32.4 percent). So, she adds to her notes the fact that the same context applies to Latino households, with 29.3 percent of this group living in semi-disadvantaged neighborhoods. Lastly, Tiffani notes that White and Asian households also share the same neighborhood context when it comes to their largest shares, this context being semi-advantaged neighborhoods. These neighborhoods are the setting for 30.9 percent of White households and 32.8 percent of Asian households.
Source: US Census Bureau. 2024. "American Community Survey, Five-Year Estimates."
Although she is far from finished with exploring the relationship between ethnoracial representation and the socioeconomic stratification of neighborhoods, Tiffani pivots to analyzing the cross tabulations (CrossTabs) devoted to ethnoracial neighborhood types. She is interested in finding out how ethnoracial households are distributed across the three primary neighborhood types: majority-Black, majority-White, and the neither neighborhoods. Building from the available CrossTabs, Tiffani finds that 57.1 percent of Black households reside in majority-Black neighborhoods and 72.5 percent of White households reside in majority-White neighborhoods. Going in reverse, she easily spots that 19.0 percent of Black households live in majority-White neighborhoods and 8.1 percent of White households live in majority-Black neighborhoods. Tiffani also notes that a larger share of Black households reside in neighborhoods that are neither majority-Black nor majority-White (23.9 percent) compared to the White share of households (19.4 percent) in these neighborhoods.
Interestingly, the pattern for Asian and Latino households is quite distinct from the Black and White households pattern. Neither group has more than 50 percent of their households residing in one ethnoracial neighborhood type. At the same time, the largest share of households for both groups live in neither neighborhoods. 48.2 percent of Asian households and 49.5 percent of Latino households live in these settings. Tiffani is mindful that neither neighborhoods consist of a relatively small number that live in either majority-Latino or majority-Asian neighborhoods and a much larger share living in ethnoracially mixed neighborhoods. She also finds that a considerably higher percentage of Asian households (42.0 percent) reside in majority-White neighborhoods in comparison to Latino households (32.7 percent), which translates to a larger share of Latino households (17.9 percent) living in majority-Black neighborhoods in comparison to Asian households (9.8 percent).
Despite taking in so much data, Tiffani can’t help but think about what it means for the Asian share of households living in majority-Black neighborhoods to be larger than the White share of households, especially given the fact that Asians have the larger share of households residing in advantaged neighborhoods. On a mission to integrate these findings into her report and presentation on housing equity and policy innovation, Tiffani continues to explore the dataset tailored to her needs and featuring over 19 data-sheets worth of curated neighborhood data.
I hope you enjoyed this three-part series and going on a dataset journey with Tiffani. I am thrilled to offer this service in the name of supporting the essential work being done to move housing policy and affordable housing strategies forward. Until next time, keep believing that a better world is possible and continue bending that arc.