Friday, February 27, 2015

Ten Years of Endowment Data

While the endowment of a private university is not a big investment pot from which universities draw income to spend at their discretion (some portion of every endowment is restricted to certain use), it's a very good proxy for institutional wealth.  What's always been interesting is the enormous size of the top five or six institutions, always led by Harvard, in comparison to everyone else.  And yet Princeton, which enrolls fewer students, has the largest per-FTE endowment.

This visualization shows two things.  On the top chart, it's a tree map, or what I like to call a sheet cake map.  Think of all the money in all the endowments as one big bowl of batter baked into a cake, and then, once baked, sliced up into pieces.  The size of the piece is that institution's endowment as a part of the whole.

The bottom chart shows ten years of endowments, measured at the start of the fiscal year shown, so you can see the hits in 2008--2009 and the overall growth over time.  Of interest There are only three private universities in US who had a total endowment in 2012 equal to the ten-year growth of Harvard's.

If you click on an institution, the line chart at the bottom will filter to just that college over time.  If you hover over a line on the bottom chart, it will highlight the instituion on the top so you can see its place in the endowment universe.

What do you see?



Wednesday, February 18, 2015

Four years of Ivy League Tax Returns

I love the Internet.  Thirty years ago, I couldn't have imagined being able to look up several years of tax returns for the Ivy League Colleges and Universities (let alone being interested in them.)  But Guidestar (a great site you should check out, in case you don't know it) comes to the rescue.  The documents are pdf, unfortunately, but you learn a lot by inputting the data manually into a spreadsheet.

For your information: By law, all universities that receive Title IV funding must make tax returns available to the public, so there is nothing clandestine about this.

The tax returns can show you, albeit at a very high level, at how the Ivy League Institutions generate revenue, and how they spend it. To no one's surprise, salaries and benefits dominate at almost all colleges and universities, and if you're really curious, the returns list in detail how much the officers and highest paid non-officers make.

But as I once suggested, the most interesting thing is the massive investment return these institutions generate; even the "poorest" of them--Brown University--averaged about $124 million in investment return over these four years.  Collectively, the investment return of these eight institutions averaged over $550 million per year, for a grand total of $18 billion over the four years. To put that in some perspective, there are about 1,553 private, not-for-profit, four-year colleges and universities in America with revenue data in IPEDS; 1,506 of them had total revenues of less than $550 million in 2013.

Take a spin around this.  It's fairly interesting for the most part, and very interesting for one reason: Princeton's 2013 data (from the 2012 Tax Return, which I've put here in case you want to take a look.)  The return shows an operating deficit of almost $1.3 billion, driven by an investment loss of over $800 million. I asked an expert on university finance (not affiliated with my own institution) about this, and here is what he said:

We were doing some analysis using IPEDS finance info and it showed some really weird results, with Princeton being the strangest of all.  It caused me to pull their audited financial statements and examine them.  Here’s a link to the statements in case you’re curious.  Nothing weird showed up in the statements so I attributed the problem to IPEDS and the Department of Education.  Now having looked at the 990, I believe Princeton has suffered some turnover among its finance staff and the folks doing their reporting don’t know what they’re doing.  As you will see, the financial statements appear to be quite different from what was reported in the tax return.

So, take this, and everything you read from publicly available data, with a grain of salt.




Friday, February 13, 2015

The Race Goes On

Unless you live under a rock, you probably know that colleges are, in general, interested in increasing the number of students who apply for admission.  There are a couple reasons for this, but they're all mostly based on the way things used to be: That is, before colleges started trying to intentionally increase applications.  The good old days, some might say.

In general, increasing applications used to mean a) you could select better students, who would be easier to teach, and who might reflect well on your college, or b) you as an admissions director could sleep a little better, because you were more certain you could fill the class, or c) your admission rate would go down, which is generally considered a sign of prestige.  After all, the best colleges have low admission rates, right?

Well, yes, one does have to admit that the colleges that spring to mind when one says "excellent" all tend to have low admission rates.  Lots of people want to go there, and thus, it must be good.  The trained eye might be able to spot the forgery, but what about the average person?

This week, we have another journalistic treatise presumably exposing colleges for the ways in which they attempt to increase applications.  The tactics listed in this article are nothing new: Reduce the essay, waive the fee, encourage more low-income kids.  Barely mentioned was the "Fast App/VIP app/Priority App," many colleges use that allow them to count an "applicant" as anyone who clicks an email link that says "Start your application."

However, application increases only pay off when you generate them from students who have a reasonable propensity to enroll.  Prestige can be measured by a little-used variable that punishes you when you increase applications to try to look more selective at the cost of deceasing your yield: It's called the Draw Rate, and it's a powerful indicator of market position.  It's a simple calculation: Yield rate/admit rate.

Here's a secret: For some percent of the freshman class, let's say 33%, recruitment doesn't come into play at all.  A large chunk of your enrollment is natural; that is, those students are likely to enroll no matter what you do.  The next 33% are going to enroll presuming you do everything correctly, make it affordable, and help them understand how they fit. But the last group, that final third, comes from students who have little predisposition to enroll.  Your recruitment tactics focus on them, and you spend most of your time trying to find them, get them to apply, and then to enroll.  They may make up as much as 75% of your pool.  They enter your applicant pool with a lower level of interest.

The problem is that usually, a big increase in applications comes not from the first or second group, and not even the third, but rather a fourth group, the "Ain't no way I'm going to enroll short of a miracle" group.  The bigger problem is that you don't always know exactly who these students are. This is one of the reasons demonstrated interest has become a topic of discussion.

When you artificially increase applications, and you have to cover your ass by admitting more, your yield is going to drop.  And so will your draw rate.

So, let's look at the data.  These charts start out very busy, so you should interact by selecting just a region or Carnegie type.  But even at their busy mess stage, you can see: a) applications are up, b) admits are up, and c) yield rates are down at almost every type of institution, with the exception of the big, private, research universities.  The ones you can rattle off without thinking too much.

But look at the Draw Rates, on the last two charts.  Draw rates are down across the board, mostly because capacity is relatively constant, the supply of students is down, and competition is up.  The only winners in the battle to increase prestige? The ones who were prestigious in the first place.  The money spent trying to join that club, or sometimes even just to look more like them, could have been put to better use.

Use the boxes across the top to see the six points of this Tableau Story Points visualization.  Note that the last one exposes some data anomalies which are inherent in IPEDS, often due to typos or new IR staff who count the wrong thing (my alma mater in 2010-2011, for instance.)

What do you see? And what do you think?  Is the race for prestige dooming us? Or is it just the latest evolutionary stage in the natural process of competition?




Thursday, February 12, 2015

Degrees Awarded by State

Frankly, the data are a little boring when you first try to visualize them.  When you're looking at the number of degrees awarded by discipline and by state, California, Texas, and New York win pretty much everything.  That's no surprise, of course, as they're the largest states with the most college students.

So I broke it into regions, thinking there must be some differences in the degrees awarded in different parts of the country.  Nope.  The Middle Atlantic wins.  That's where the people are.

Finally, I looked at each state by the percentage of degrees in certain fields, and voila! Something interesting. Different states award different types of degrees in dramatically different proportions. Some of this can be answered easily: A high percentage of business and computer science degrees in Arizona is driven by the University of Phoenix, but others are not so obvious. Why is there such disparity when you look at humanities, engineering, or health professions?

To interact, just select the type of degree in the purple box at the top.  It starts with business, but you can choose anything.  The maps and the bar charts will update to show each state, and the percentage of bachelor's degrees in that state in the discipline selected.

Any explanations?


Thursday, February 5, 2015

When Infographics Fail

There are a lot of bad infographics floating around the Internet.  When they concern things like the difference between cats and dogs, or how many hot dogs and hamburgers Americans eat over the 4th of July, it's no big deal.

But this blog is about higher education data, and when I see bad infographics on that topic, I feel compelled to respond.  This one is so bad it's almost in the "I can't even," category.  It takes very interesting and compelling data--The graduation rates of Black male athletes--and compares it to overall graduation rates at several big football schools in the nation.  Here it is:


For starters, this chart appears to stack bars when they shouldn't be stacked: A graduation rate of 40% for one group and 40% for another group shouldn't add up to 80%.  The effect is that it distorts much of what your brain tries to figure out.  For instance, look at the overall rates (longer bars) for Georgia Tech and Pittsburgh;  Georgia Tech at 79% is shorter than Pittsburgh's at 77%, because they started at different points.

But wait, they can't be stacked; Louisville's 44% + 47% is way longer than Notre Dame's 81%. Stacked bars on dual axes?

These also look at first like they could be two sets of bars, with one (the overall graduation rate, which is always higher) behind the Black male graduation rate.  But that can't be, either.  The effect is that you look at Notre Dame and see very long gap between 81% and 96% (a 15-point spread) that appears to be longer than the 37-point spread at Virginia.

In short, I cannot tell you how this chart was made, or what the assumptions are, let alone what the story really is.

And the image behind the picture is even worse; it makes it hard to see.

Finally, a third element might have been interesting here: The graduation rate of Black males who are not athletes.  It might shed more light on the problem, although if the same designer did it, I'd not be confident.

Here's the data presented three ways, each of which tells the story differently, but each better in at least one way. This was literally 15 minutes of work.

What do you think?






Tuesday, February 3, 2015

A Remake of the Pell Institute Data

I would have written a shorter letter, but I did not have time. --Pascal

And sometimes it's that way with data visualization, too.  What starts out as a simple project--one you think will take a few minutes--gets slightly more complicated.  This morning, I came across this interesting Chronicle of Higher Education story, showing Pell Institute Data on Economic Diversity. If you don't want to look at the article, here is a screen grab of the chart.  Click on it to enlarge.


It's not a bad chart, but I found myself taking more time than I thought I should to figure out the story, which is that for-profit institutions enroll far higher percentages of low-income students than public institutions.  (Another problem with this that I can't fix is that the data are not complete; for instance, there is no data on private Baccalaureate or Master's Institutions included in the set.) Additionally, notice the subtle changes in color when you move from the overall category to any of the institutional types. I think that can be confusing.  And finally, as is the case with all stacked bar charts, it's hard to compare middle values.

The biggest problem, though, is that, there are too many things to take in at once. The story can get lost in the chart.

So I did an attempt at a quick visualization, but a small data set (seven columns by five rows) seems to make it harder to get good insight, and I spent a lot more time on this than I thought I would.

This is still not perfect, of course. For instance, it's hard to compare one institutional type to another, unless you have a good memory.  But clicking the drop down box to change the type of institution shown on the bars, and comparing that to the average (orange lines) seems to work pretty well. 

Let me know what you think: Does this make it easier to see the story?