# Law Grad Jobs Unequal Like Income in Corrupt Countries

Readers might recall several months back when I crafted a modified Lorenz curve of full-time law school applications against the U.S. News rankings. It occurred to me that I could expand my use of this rankings-adjusted Lorenz curve to law school employment outcomes for the class of 2014. Now, I’ve finally made the time to do it.

As a refresher, a Lorenz curve plots the distribution of two variables cumulatively, most commonly cumulative income against cumulative population, starting with the individuals with the lowest incomes. Such an analysis would be able to allow you to claim, for example, that the bottom 50 percent of households earn only 10 percent of the income. Because the dependent variable is rarely distributed equally, the Lorenz Curve isn’t a triangle, and the more concave the curve, the more unequal the distribution.

Furthermore, if you subtract the area under the Lorenz curve from the total area of the triangle representing perfect equality, and then divide that by the same triangle’s area, you get the Gini coefficient. ((Triangle – Area) / Triangle)

Normally, a Lorenz curve of each category of law school outcomes should be sorted with the smallest contributors first, but I want a commonly understood, “neutral” independent variable that allows comparisons among employment outcomes. As a result, the Lorenz curves below squiggle and deviate quite a bit. They also come out convex for some outcomes.

Here are the four major employment statuses that people care about, less school-funded jobs (to show the “real” demand for graduates’ labor) and excluding the three Puerto Rico law schools.

This doesn’t look too bad. Unemployment is a tad convex, and full-time, long-term bar-passage-required jobs are fairly evenly distributed. JD-advantage jobs look very evenly distributed.

Digging deeper into employment types, we find that jobs aren’t doled out evenly at all. Private practice jobs in particular are given out directly according to ranking.

The same goes for public interest jobs and federal clerkships.

I’ve also calculated the Gini coefficients for these outcomes irrespective of the U.S. News rankings. My idea was to see how some of these outcomes compare to income inequality in various countries, since that’s something people might be familiar with.

EMPLOYMENT STATUS GINI COEFFICIENT PROPORTION OF TOTAL GRADS
Employed – Bar Passage Required FTLT 0.31 25,344 / 43,195
Employed – JD Advantage FTLT 0.36 4,774 / 43,195
Employed – Profession Position FTLT 0.53 1,371 / 43,195
Employed – Non Profession Position FTLT 0.72 200 / 43,195
Employed – Undeterminable 0.93 21 / 43,195
Employed – Pursuing Graduate Degree 0.44 693 / 43,195
Unemployed – Start Date Deferred 0.64 313 / 43,195
Unemployed – Not Seeking 0.54 553 / 43,195
Unemployed – Seeking 0.43 4,103 / 43,195
Employment Status Unknown 0.67 841 / 43,195
EMPLOYMENT TYPE GINI COEFFICIENT PROPORTION OF TOTAL GRADS
Solo-FTLT 0.53 803 / 43,195
2-10-FTLT 0.33 6,695 / 43,195
11-25-FTLT 0.38 1,796 / 43,195
26-50-FTLT 0.42 990 / 43,195
51-100-FTLT 0.46 771 / 43,195
101-250-FTLT 0.51 1,057 / 43,195
251-500-FTLT 0.66 1,068 / 43,195
501-FTLT 0.79 3,934 / 43,195
Unknown-FTLT 0.83 186 / 43,195
Government-FTLT 0.32 4,569 / 43,195
Public Interest-FTLT 0.52 1,744 / 43,195
Federal Clerkship-FTLT 0.68 1,247 / 43,195
State Local Clerkship-FTLT 0.57 1,982 / 43,195
Other-FTLT 0.96 26 / 43,195