Skip to main content

The Highly Rejective Colleges

If you're not following Akil Bello on Twitter, you should be.  His timeline is filled with great insights about standardized testing, and he takes great effort to point out racism (both subtle and not-so-subtle) in higher education, all while throwing in references to the Knicks and his daughter Enid, making the experience interesting, compelling, and sometimes, fun.

Recently, he created the term "highly rejective colleges" as a more apt description for what are otherwise called "highly selective colleges."  As I've said before, a college that admits 15% of applicants really has a rejections office, not an admissions office.  The term appears to have taken off on Twitter, and I hope it will stick.

So I took a look at the highly rejectives (really, that's all I'm going to call them from now on) and found some interesting patterns in the data.

Take a look:  The 1,132 four-year, private colleges and universities with admissions data in IPEDS are included here, but this initial view is filtered down to just 70, all with an admit rate at or below 25%.  To make it interesting, I plotted admit rate (x-axis) against the percentage of core revenues from tuition and fees.  Then, I sized the bubbles by the draw rate, and colored by what I call "freshman importance."

A few words about those points:

Admit rate means the percentage of freshman applicants offered admission.  (If you want to narrow or broaden this, use the filter at the top).

Percentage of core revenue from tuition and fees is just that.  In IPEDS, it's defined as "revenues from all tuition and fees assessed against students (net of refunds and discounts and allowances) for educational purposes." Core Revenues do not include hospital revenues, but do include research dollars.  Essentially, it tells you where a college gets the revenue it needs to operate.

Draw rate is yield rate/admit rate.  It's a measure of market power.  Stanford's is 20; the national average is about 0.4.  It's a better indicator than selectivity.

And freshman importance is the size of the freshman class divided by total headcount enrollment.  You'd think this might be close to about 25% at most liberal arts colleges, but at major research universities, it's much lower. 

Look especially at the lower left of this chart.  These are all the names you know:  They all have admit rates below 10%; all get less than a third of core revenues from tuition and fees, are large (that is, large draw rates), and are more likely to be orange (where freshman are of lesser importance to the overall enterprise.)  If you want to find an institution, type part of its name in the Highlight Box.  Hover over a dot for details.

Think about the implications of those variables, and think about how much the April admissions press releases mean to the reputation of these institutions, and then ask yourself if this makes sense.

(I bet you'll think not.)  As always, let me know if you have questions or spot anything especially interesting.

Reminder: I appreciate support for webhosting and other costs associated with creating Higher Ed Data Stories.  You can support these efforts here.


Popular posts from this blog

Yes, your yield rate is still falling, redux (2021)

I've been creating this data visualization, or some form of it, for several years now .  I think it's most useful for higher education enrollment professionals who have to explain to people at their university why their yield rate is falling.  The short answer is that applications and admits are increasing faster than student populations: If a student today applies to an average of seven colleges, compared to four colleges twenty years ago, yield rate almost has to go down.  I'm sure AI will fix this, and all our problems, very soon. But I've spoken to others who use this other ways: To work with students to talk about chances for admission; to show parents how things have changed in the past twenty years; or to help journalists understand the lay of the land.  Whatever you use this for, I hope it's instructive, and I hope you feel free to share it widely. And if you work in a college or university and save yourself some time by using this, or if you work with clien

Freshman Migration, 1986 to 2020

(Note: I discovered that in IPEDS, Penn State Main Campus now reports with "The Pennsylvania State University" as one system.  So when you'd look at things over time, Penn State would have data until 2018, and then The Penn....etc would show up in 2020.  I found out Penn State main campus still reports its own data on the website, so I went there, and edited the IPEDS data by hand.  So if you noticed that error, it should be corrected now, but I'm not sure what I'll do in years going forward.) Freshman migration to and from the states is always a favorite visualization of mine, both because I find it a compelling and interesting topic, and because I had a few breakthroughs with calculated variables the first time I tried to do it. If you're a loyal reader, you know what this shows: The number of freshman and their movement between the states.  And if you're a loyal viewer and you use this for your work in your business, please consider supporting the costs