A Look at Philadelphia. How Poverty, Education, and Work-force…
By: Justin Cocco
Tags: Maps, R, Data Science, In Depth Analysis, Poverty

Comparison of Zip Codes by Disparity

In comparing the zip codes by demographic equity, one must choose base-level poverty to compare. That is, if in the village, we investigated the per-capita disparity poverty level to group A, the dominant group, one would find that of the 80 members, 20 of them are in poverty. Thus, if group A represents the dominant group within the village, by comparing the other groups’ availability or accessibility to resources to the dominant group, one could directly gauge the level of disparity.

The level of disparity-model poverty for group A is 2,500 per 10,000 persons in group A. Group B has a disparity model poverty of 7,500 per 10,000 members in group B. Thus, comparing the two, we see that group B has a disparity-level of 3.0 (7,500 / 2,500). That is, group B is over-represented in poverty by a factor of 3 as compared to the dominant group.

The disparity-level is a de-facto equity number. The number represents how over-represented one group is in terms of poverty. The line of reasoning in quantifying this as an equity number is that one presumes that resources’ availability is inversely related to the level of poverty a community would experience. Thus, comparing two groups, especially one minority group to a majority group, in terms of poverty and resource allocation throughout the city at the racial level can be established.

It is worth noting that another way would be to measure the level of disparity poverty against the average level of disparity throughout the United States. Although useful in establishing the level of deviations in resources or quality of life (measured through poverty levels), this metric would provide insights into how the zip codes of Philadelphia are situated; it would provide little benefit if attempting to look at the relative differences within Philadelphia itself. Thus a base-group must be established within Philadelphia. Although there are Zip codes in Philadelphia wherein the dominant demographic is Black, it seemed unreasonable to consider the Black community within that zip code as the resource-dominant group such that one zip-code-community’s influence would be minimal compared to the level of influence the white community has had nation-wide.

Furthermore, comparing the zip-codes by the equity-model helps identify areas of increased poverty per demographic groups in complicated or overly saturated systems, such as Philadelphia. By normalizing demographics against a known or a base-amount (in this case, the nationally dominant demographic cohort), wide-spread poverty can be simmered down into patterns.

In summary, it will be seen that the disparity-model can be used to compare zip codes throughout the Philadelphia region to gain insight into the different levels of resource allocation (as measured through poverty) differs between zip codes.

Black Cohort comparison with White Cohort in terms of the Disparity Model of Poverty

Here we see a difference in the equity of the poverty of the black community per zip code compared to the equity of the white community’s poverty. There is over-representation, particularly in the West Philadelphia zip code of 19130 (darkest red). Yet, it is difficult to see if there is over or under-representation as in totality. As such, the following graph helps answer the question: “In which zip codes are the black communities over-represented in poverty?”.

Figure 13: A look at the comparison between the per capita poverty levels per demographics compared throughout the city. The higher the value, the more over-represented the Black community is within Poverty compared to the White community’s disparity-poverty model. NOTE: 19113 and 19112 not included due to insufficient data.

These graphs are incredibly insightful. They demonstrate that the black community is over-represented in poverty in a larger number of zip codes than may not have been elucidated by looking at the equality maps or even the raw count maps compared to the raw counts of population. For even in the predominately black communities of West and North Philadelphia, when controlling for both per-capita poverty rates and relative population counts, when compared to the white cohort, there is still an over-representation of poverty within these demographics.

Figure 14: A look at which zip codes have an over-representation or an under-representation of the black community in poverty. NOTE: 19113 and 19112 not included due to insufficient data.

Interestingly, the areas that demonstrated the highest level of per-capita values of poverty for the black community show diminished over-representation levels compared to the equity white poverty levels. This suggests that both the white and black poverty levels are abnormally and comparatively high in some zip codes.

Hispanic Cohort comparison with White Cohort in terms of the Disparity Model of Poverty

Using the same methodology, we can look at the Hispanic cohorts poverty levels. Below are two graphs, the first demonstrating the relative amount of equity poverty levels for the Hispanic community compared to the white cohorts’ equity poverty counts within the same zip code. The second shows whether or not the Hispanic community is over or underrepresented in the poverty pool distinctly.

Figure 15: A look at the equity poverty metrics for the Hispanic community compared to the equity metrics of poverty for the White community. NOTE: 19113 and 19112 not included due to insufficient data.

Again, as with the black community, the Hispanic community seems to be over-represented in the poverty pool throughout Philadelphia compared to the level of poverty of the white community to a greater level than was observed using simple equality and even equity models. Here, the over-representation of the Hispanic community’s poverty extends significantly from the isolated North Philadelphia region noted previously. Now, it can be seen that West Philadelphia and North Philadelphia regions have even greater levels of disequilibrium in poverty.