2016: Full-Time Matriculants Trickle Up

[2016-12-26: This post has been updated due to minor miscalculations.]

The ABA’s standard 509 information reports are out now. Unlike last year there is no need for preliminaries about the data. The names of the law schools line up for the most part, so users do not need to worry about combing around for Lincoln Memorial or some other new law school. They might, however, want to download reports for Hamline and William Mitchell because some calendar-year 2016 data were separately reported before the Mitchell|Hamline merger officially went into effect. As of now, there are no reports for Rutgers-Camden and Rutgers-Newark, so now Rutgers is one.

In calendar year 2016, there were 33,075 full-time matriculants to 201 ABA-accredited law schools, up 468 matriculants from 2015 (+1.4 percent). That year saw an 838-matriculant decline, so the crunch has reversed for the law schools. (These figures exclude the three law school in Puerto Rico, as I usually do.)

Full-time applicant acceptance rates are largely flat, except at the 90th percentile.


Matriculant yields are up to 24.1 percent overall compared to 22.9 percent last year, but ultimately about 21 law schools account for half of the decline in matriculants since the last trough year, 2007, which I believe is a better comparison year for this measure than 2010, a peak year.

Meanwhile, application growth rates are still accelerating. At the median it’s flat.


102 law schools saw a growth in applications, which is much higher than last year. First place goes to (and you’ll love this) … Indiana Tech (235.4 percent), which will close at the end of the academic year. It received 332 applications, extended only 128 offers, and admitted but 39 full-time students. Indiana Tech’s 75th percentile full-time applicant received a 152 on the LSAT. It preferred to close than accept 204 applicants (~60 percent). Numbers two and three for application growth were Florida (98.9 percent) and Concordia (71.0 percent).

Before anyone gets excited about rising law-school applications, though, I note that 72.5 percent of the rise can be attributed to U.S. News‘ top 14 law schools. Thus, things probably don’t look any better for most schools since last year. In the last two years, I’ve commented on the possibility that applicants believe that now is the best time to go to an elite law school, and while that sentiment dissipated last year, it’s back now for sure.

More on these topics later.

Here’s information on enrollments from prior years:

Week 49: 53,100 Applicants Projected for 2017

And the LSAC’s three-year applicant volume comparison is out of the starting gate! It finds 14,892 law-school applicants as of week 49 of this year, a 5.1 percent drop from last year, when 28 percent of all applicants had applied at least once. As of now, it appears that there will be 53,186 applicants by the fall; there were 56,126 in August 2016.

The first reported week of applicant activity can be volatile. Last year at week 48, the projected number of final applicants was 55,524, which was about 1 percent off. I would not make any serious bets on where it will go, but perhaps there will be another applicant decline this year. The New York Times published another withering article on legal education in 2016, but the number of LSAT takers ticked up in September/October. Early in the cycle last year, applicant counts were up from the prior year.

Applications have fallen 1.7 percent compared to week 49 of 2015, so applications per applicant are higher now, 5.49 versus 5.3. This measure tends to rise during the year.

Last year I focused on two issues that are still relevant: One, the distribution of applications to law schools, and two, the extent to which applicants backload their applications later in the cycle. The distribution question will have to wait until the ABA releases its Standard 509 data, but many law schools could still be living in a law-school crunch despite the flat number of applicants. The second point is not something I can evaluate this year because the LSAC started reporting all applicants rather than just fall applicants as of 2016.

That’s all. Peace.

Past reporting on this topic:


WSJ’s Editorial Page Blames Obama for Preventing Student Loan Defaults

I wrote that the WSJ’s reporting on student loans had improved slightly. Its editorial responding to the GAO report on the Department of Education’s cost estimate of income-driven repayment plans, on the other hand, backslides. It’s really more of a rant than an editorial, but here’s a digest of what I think it was arguing:

  • Cutting out banks as middle-men for federal student loans costs taxpayers money, even though it didn’t, and that change had nothing to do with IDR plans.
  • Democrats knew that student loans would never be repaid when it federalized student lending. Again, even if true, this claim has nothing to do with IDR plans, which were authorized by prior administrations.
  • IDR plans keep default rates “artificially low,” which while technically accurate doesn’t explain how debtors are supposed to pay loans they can’t repay. What would the WSJ propose if all these people default instead?
  • The Obama administration allowed borrowers to retroactively sign on to IDR plans, which is true but doesn’t explain how debtors would repay the loans otherwise since they probably would not be able to discharge them in bankruptcy.
  • IDR is an “entitlement” that can be “exploited,” even though there’s no evidence student debtors could repay their loans without it. Assuming the GAO’s report is correct, IDR plans are doing exactly what they are supposed to do. The problem is that too many people have too much debt.
  • The Obama administration is responsible for the shoddy accounting of student loans’ ultimate costs—which I’ll accept—but it doesn’t blame lending programs passed by the Bush II administration that created these unpayable debts to begin with. Seriously, the WSJ threw the 2000s down the memory hole.
  • The Obama administration used costly IDR plans to buy votes. No evidence is given, and didn’t younger voters bail on the Democrats in this election? Nice bribe, Obama.
  • Implicitly, the Republican-controlled Congress bears no responsibility for failing to create more jobs or raise incomes, even though it was more concerned with slashing the budget, shutting down the government, and threatening to default on the national debt despite trifling interest rates.

I feel bad for the reporter who carefully tried to explain the GAO’s report and was just upstaged by an incompetent, partisan editorial. (I hope it’s not the same author.)

There’s much blame to place at Obama’s feet regarding the value of college education and student loans. One of these days I’d like to summarize my coverage of him to gauge my fairness towards the outgoing administration. Hopefully, I’ve been consistently non-partisan in my analysis, but perhaps not. However, if the best the WSJ can do is blame Obama for preventing defaults on loans that could not be repaid given the Congresses he had to work with, I’m confident my final assessment will smell like roses by comparison.

WSJ’s Student Loan Coverage Improves: More Facts, Fewer ‘Deadbeats’

And not just facts, neutral facts, which is how reporting is supposed to be. I’ve criticized The Wall Street Journal‘s student loan coverage, but its most recent article on the topic, “U.S. to Forgive at Least $108 Billion in Student Debt in Coming Years,” is a start in the right direction.

Okay, the title could use some work. More accurately, it should be something like: “GAO Projects U.S. Will Forgive $108 Billion in Student Loans in Coming Years.” It’s 76 characters, which is too long for most SEO-obsessed editors, but it doesn’t characterize a possibility as a certainty.

Conversely, the WSJ neglects to cite another GAO study on the subject of student debtors’ earnings. Its data are nearly two years old, but they show that 72 percent of people on income-sensitive repayment plans were earning $20,000 annually or less. Not even 10 percent of IBR and PAYE participants (157,000) made more than $40,000 per year.

Thus, the WSJ’s reasoning still follows a shaky line of reasoning:

(1) IBR participants’ debts are high,

(2) High debts are only feasible for grad students taking out Grad PLUS loans,

(3) Graduates tend to find jobs with high incomes and have low unemployment rates,

(4) So the benefits of IBR go to high-income people.

The prior GAO study pokes holes in (3) and (4). Income is the independent variable, not debt, and incomes are low. Still, the WSJ’s reporting this time inserts enough adverbs to qualify these claims that I’m going to give this an earned “C.” There is no grade inflation on this blog.

Oddly, in its haste to cover the GAO’s attacks on the government’s accounting for student loans, the WSJ neglects to include immanent compensating factors that will raise student debtors’ incomes: tax cuts, stimulus, job growth, a harried Fed, and 3-4 percent growth in the near future. Things will rapidly get better for America’s student debtors.

Gini Coefficients: How to Calculate Them in Excel and What The F They Mean

Social scientists and wonk readers are familiar with Gini coefficients, and while I’ve used them a few times myself, I have no idea what they really mean.

Okay, fine, I know what a Lorenz curve is, and I can explain it mathematically. But ultimately any understanding of the Gini coefficient is inherently relative, e.g. “They say .3 is good for income distribution, but anything above .5 is bad. The U.S. is .45, so that’s bad … ish.” It doesn’t say anything about the actual distribution.

Indeed, the first two Wonkblog posts I found in a brief Internet search describe the Gini coefficient essentially as a (well-known) measure of inequality. No details.

Vox is slightly better: “[I]t’s an incredibly abstract idea that’s difficult to verbally describe. [Thanks, Vox.] The advantage to using a gini coefficent is that in principle it summarizes all the information about the distribution of income and thus facilitates easy comparisons.”

Easy comparisons? To what? Other Gini coefficients? Whatever.

Still, aside from eyeballing a bunch of Lorenz curves—fun fact: I’m going to make you eyeball a bunch of Lorenz curves today—a Gini coefficient is totally undescriptive because it’s a decimal without any units.

This post tries to remedy that, but first, per the title here’s a big ol’ array formula for calculating Gini coefficients in MS Excel. The source is Excel and UDF Performance Stuff. I chose the Angus Deaton version and improved on it by replacing the ROW formulae with COUNTIFs because those account for blank cells in the data. It also avoids the pitfall of negative data numbers, which mess up Lorenz curves. However, as an array formula, it must be entered with CTRL-SHIFT-ENTER otherwise it won’t work. Behold:


*Where “Datarange” is something like, “$B$1:$B$1000”.

The Web site contains a few other methods, but this one is the most comprehensive and isn’t limited to 4,000 data points. I’ve tested this version with hand-cranked Ginis, that is, sorting the data by size, creating a cumulative sum of them (the Lorenz curve), calculating a bunch of trapezoids among them to find the area under the Lorenz curve, adding those up, subtracting them by equivalent triangle of equality, and then dividing them by that triangle.

So what does the Gini coefficient mean? In other words, what kind of distribution can one imagine when provided with a given Gini number?


Good News: Legal Services Industry Grew 2.0 Percent in 2015

Since I started writing here more than six years ago, it’s always been bad news for the legal services industry. Dwindling output, year in, year out. This time, no longer. We have growth: 2.0 percent in 2015.


(Source: Bureau of Economic Analysis (BEA))

And yes, thanks to an alert reader I can now show the BEA’s complete GDP-by-industry dataset going back to 1963! We can now see that if the legal services industry had maintained its mid-20th century growth rate it would be nearly double its current size. Imagine how much better law practice would be. You might think there’d be a need for more law schools to meet the demand.

Arguably, the government’s definition of the industry or its composition has changed over the decades as it has for other industries, but I doubt it. It’s mostly lawyers’ offices. Undeniably, though, the typical product of the legal services industry has changed. I’d bet that the weighted-average hour of legal work is very different now than in 1975. Even so, it’s still possible to give a dollar figure of how much stuff private practice lawyers are producing.

…And it ain’t much. The legal services industry produced less in 2015 than in 2012, 1995, and 1988. There’s room for a lot of growth. The sector peaked in 2008, and since then it’s shrunk more than 20 percent.

The other caveat is that the legal services industry’s growth this year is mostly attributable to the gross operating surplus (what goes to firm owners, partners, solos) as opposed to employee compensation, which better indicates budding demand for new lawyers. The breakdown is: gross operating surplus, +1.5 percent; taxes on production and imports, +0.5 percent; and compensation of employees, +0.0 percent.

Yeah. You read that right. 0.

However, compensation has shaved off growth since 2007, so maybe a zero year isn’t so bad. Here’s the chart of the industry’s components, which still only goes back to 1987:


Compensation of employees in the legal services industry peaked in 2003 at $121 billion (2009 $). Now it’s $97 billion, a similar 20 percent decline.

Finally, although the legal services sector did well in 2015, the rest of the economy did better: GDP grew 2.6 percent, of which 1.9 percent went to compensation of employees. Things still look better for non-law.

Finally, legal services as a share of household expenditures grew for the first time in thirteen years.


At its maximum, households spent $99.5 billion on lawyers in 2003. Now it’s $87.9 billion, down 11.7 percent.

I’ve written elsewhere that the legal services sector can’t shrink forever into nothing. It’s like estimates of the year Japan’s population reaches zero. So we were bound to have some good years. What we need is evidence of sustained growth, especially in employee compensation. Instead, that’s not going anywhere, but at least it’s not falling anymore.

LSAT Tea-Leaf Reading: September/October 2016 Edition

It only took the LSAC 40 days since the September/October LSAT administration to update its Web site, which is a noticeable improvement over June and February. Frankly, I’m finding that more interesting than the actual numbers: 33,563 for September/October, up 1.0 percent from last year.


Because of the rise in test takers, The four-period moving sum budged up 0.3 percent to 106,030. Essentially, the trend is flat, but I thought it would continue falling because of the New York Times article a few months back. I think it’s safe to say that if the Times can’t discourage people from law school, then the low-hanging fruit of easily dissuaded potential applicants has been exhausted.

Still, we don’t know anything about people who don’t choose to take the LSAT because they think it’s a bad idea. I question whether that’s a logically valid category. On the whole, we can expect another poor haul for law schools. Maybe others will consider going the Indiana Tech route.

Speaking of Indiana Tech, I recommend reading J-Dog’s gloating on the subject. He earned the privilege.