The Theil index (represented by redness)is a statistic used to measure economic inequality. The Theil index measures an entropic "distance" the population is away from the "ideal" egalitarian state of everyone having the same income. The numerical result is in terms of negative entropy so that a higher number indicates more order that is further away from the "ideal" of maximum disorder. Formulating the index to represent negative entropy instead of entropy allows it to be a measure of inequality rather than equality.
Circle size → Population size
Circle color →
medium/light orange and blue represents male dominant gender gap
Dark orange represents female dominant gender gap
We can see that for the majority of the country, males make more than females. The gender gap is skewed towards males. This is incredibly upsetting. If we analyze the map further, we can see that the east coast is less slightly more gender equal than the west coast and midwest. You might ask why this is the case?
This is something we found really interesting. After considering multiple explanations for why this is the case, we hypothesized that low incomes are a significant part that low income jobs weigh more heavily towards female success rate being higher than male success rate. This hypothesis is most consistent with our next finding (reversal of gender gap at the 25th percentile)
This data compares people’s wages at age 30 compared to their parent’s income percentile. This graph demonstrates the apparent income gender gap that exists at all different parent income percentiles. At every parent income percentile, females make lower wages than males. Super upsetting right! In fact, this gap becomes wider at higher income levels.
We can see that males are employed at lower rates than females at lower parent income percentiles. However, we see an interesting reversal at about the 25th parent income percentile mark where a higher percentage of males are employed than females.
As we saw in the above scatter plot, children growing up in the
lowest quantile of household incomes experience an employment rate
gender gap later in life in which women actually have higher
employment rates than men.
For a small case study, lets take a look at the employment rates of
men and women in two very different states, New York and North
Carolina.
You can see that for the first quantile of parent incomes, this gap
is present in both states. But are there other factors that
correlate with gaps like these? And what other factors correlate
with the larger gender gap in North Carolina?
The regional differences in these gender gaps are closely correlated
with commonly accepted proxies for neighborhood disadvantage,
especially factors that are tied to race and histories of segregated
communities and education systems.
For example, North Carolina has a significantly higher high school
dropout rate when compared to New York. This is closely correlated
with its greater gender gap for lower income childhoods, and this
correlation holds across other states as well.
Another factor with a very close correlation to the employment
gender gap for first-income-quantile childhood environments is a
region's fraction of black citizens claiming residence there.
For example, North Carolina's larger gender gap for lower income
childhoods is closely correlated with its larger black population.
These are just a few of the segregation and economic
opportunity-related factors with a close correlation to the gender
gap, but we hope the point has been made clear that disadvanted
neighborhoods consistently are sources of the type of employment
gender gaps shown above in the scatter plot.