Median Household Income Gap
About
The Median Household Income Gap measures the ratio between the median income of households headed by a Black individual versus the median income of households headed by a White individual in a county. Individuals from both Hispanic and non-Hispanic ethnicities are included. According to the U.S. Census Bureau’s 2022 data, the median household income for Black Households was $52,860, while for White households was $81,060. This indicates that Black households earned approximately 65% of what White households earned, highlighting a significant income disparity between these groups 1.
Why is the Median Household Income Gap important to the Structural Racism and Discrimination (SRD) Index?
This gap highlights inequity in economic opportunities between Black vs White communities in many instances caused by a legacy of slavery and segregation policies in this country that continues even today through institutional policies denying improved housing opportunities for communities of color via housing and mortgage discrimination 2,3. This measure is crucial for understanding economic disparities that affect one’s quality of life and community health. It is important to address these systemic issues to close the income gap and combat racial discrimination in your neighborhood.
What is the expected relation to Structural Racism and Discrimination?
A higher value of the Median Household Income Gap between Black and White households contributes to the higher value or score of the SRD Index.
How is the Median Household Income Gap calculated?
Data Source
We obtained data from the IPUMS National Historical Geographic Information System (NHGIS) 4. The data is publicly available.
Data
We used the following two variables at the county level.
| Variables* | Year | Unit |
|---|---|---|
| Median Household Income in the Past 12 Months (in Inflation-Adjusted Dollars) (Black Alone Householder) | 2000 | 2010 | 2020 | US Dollars ($) |
| Median Household Income in the Past 12 Months (in Inflation-Adjusted Dollars) (White Alone Householder) | 2000 | 2010 | 2020 | US Dollars ($) |
* Individuals from both Hispanic and non-Hispanic ethnicities are included.
Methodology
We calculated the Median Household Income Gap using a ratio formula:
$$
\text{RBWhMedHHInc} = \frac{\text{BlMedHHInc}}{\text{WhMedHHInc}}
$$
Where:
RBlWhMedHHInc: Ratio between the median income of Black households versus median income of White households
BlMedHHInc: Median Household Income for Black population
WhMedHHInc: Median Household Income for White population
Missing Data
We replaced missing values by using functions that were rooted in Tobler’s First Law of Geography, i.e., “everything is related to everything else, but near things are more related than distant things” 5. This law also informs the concept of Spatial Autocorrelation (SA). The indicators were highly spatially autocorrelated and the missing values were imputed using the median value of the eight nearest neighbors. The eight nearest neighbors were identified using the KDTree algorithm in Python’s scipy.spatial module 6. After imputation of missing data, we have 13 counties with no data in 2020, and none for the 2010 and 2000 years.
Limitations
Data is not available in 1990.
References
1. Guzman, G., & Kollar, M. (2023). Income in the United States: 2022. Current population reports. United States Census Bureau. Retrieved February, 26, 2024.
2. Feagin, J., & Bennefield, Z. (2014). Systemic racism and US health care. Social science & medicine, 103, 7-14.
3. Quillian, L., Lee, J. J., & Honoré, B. (2020). Racial discrimination in the US housing and mortgage lending markets: a quantitative review of trends, 1976– 2016. Race and Social Problems, 12, 13-28.
4. Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., & Ruggles, S. (2024). IPUMS National Historical Geographic Information System: Version 19.0 [Dataset]. IPUMS.
5. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic geography, 46(sup1), 234-240.
6. Virtanen, P., Gommers, R., Burovski, E., Oliphant, T. E., Weckesser, W., Cournapeau, D., … & Feng, Y. (2021). scipy/scipy: SciPy 1.6. 0. Zenodo.