Blog (Kelchen on Education)

The 2019 Higher Education Top Ten List

In my seventh annual top ten list (see past lists here), I present the ten events of the year that I consider to be the most important or influential. (My slightly irreverent list of “not top ten” events comes out tomorrow.) As always, I’d love to hear your thoughts about the list and what I missed!

(10) The NCAA faces pressure to change its athletic scholarship model to give more money to student-athletes in revenue-generating sports. In March, the NCAA lost a class-action lawsuit brought by former athletes who claimed that the NCAA broke antitrust laws by restricting athletic scholarships to the standard cost of attendance. The NCAA must now develop policies to allow for additional items such as study abroad or future graduate studies to be included in scholarships. What may be even more important is efforts from a number of states, including a new law passed in California, that would allow athletes in those states to get compensated for the use of their likenesses. This led the NCAA to pass a policy in October to allow athletes to be compensated, although it is unclear whether the NCAA’s future policy will go as far as many states want.

(9) Elite college admissions got a lot of attention thanks to a well-publicized scandal and a high-profile court case. In what was once a rather inane tweet, actress Felicity Huffman asked for some advice about the back-to-school season.

I don’t know if participating in an admissions scandal that promptly resulted in a Lifetime movie came from her Twitter request for advice, but she served 11 days of a 14-day jail sentence for paying someone $15,000 to correct her daughter’s SAT exam. In other news affecting a tiny—but visible—portion of American higher education, Harvard won the lawsuit it was facing from a group alleging that the university discriminated against Asian-American applicants. This case is widely expected to go to the Supreme Court at some point in time, which is likely to make much of traditional higher education nervous.

(8) Higher education plays a prominent role in the 2020 Democratic presidential primary. Concerns about student loan debt and the return on investment of higher education have made higher education a much more prominent issue than in past election cycles. Nearly every major Democratic presidential candidate has unveiled plans designed to forgive at least some existing student debt and make at least some types of college tuition-free (with major divides between more liberal and moderate candidates), and the Trump administration is reportedly seeking its own splashy policy proposal. Inside Higher Ed and the National Association of Student Financial Aid Administrators both have handy trackers of existing proposals. Keep an eye on candidates’ stances on childcare and PK-12 educational issues since I expect these areas to end up getting additional funding before higher ed at the end of the day.

(7) The University of Alaska had a rough year. In general, this year was pretty solid yet again for state funding for public higher education as state appropriations generally kept up with inflation. But this did not hold true in every state. The governor of Alaska, which was struggling with a large budget deficit amid stagnant oil prices, sought to cut the University of Alaska’s budget by $130 million or 41 percent. The state legislature, which couldn’t even agree on where to meet, did not override the vetoes. This led the university to declare financial exigency in late July—an incredibly rare action for a public university that would allow it to more easily fire tenured faculty. This was reversed in late August after the budget cut was reduced to $25 million this year and a total of $70 million over three years [updated to correct an error–thanks, Khrys in the comments section!]. The university also seriously considered consolidating its accreditation before abandoning that idea, preferring instead to pursue other cost-cutting exercises.

(6) For the first time, the federal government published data on graduates’ debt and earnings at the program level. A number of states have published these types of data for years (see Virginia’s data dashboard for some great examples), and there is a fascinating partnership between the Census Bureau and some universities to provide earnings data. But for most colleges, the first available program-level data came from the College Scorecard’s program-level data releases this year. (I wrote about the data here, here, and here.) The Trump administration officially repealed Obama-era gainful employment regulations that disproportionately affected the for-profit sector this year (see my new working paper on the impacts of that policy), with part of the justification being that data would now be available for a larger group of programs. My expectation: the information will affect prospective grad students far more than undergraduates, and colleges will use the data to close low-performing programs outside of the liberal arts.

(5) Accrediting agencies had a challenging year. The organizations tasked with safeguarding academic quality have long been caught in a vise between being pushed to tighten standards and keeping the economic engines of local communities operating. This year was no exception. A report by the UNCF alleged that the largest accreditor of historically black colleges and universities disproportionately sanctioned these institutions, with the implication that unnecessary pressures from accreditors put HBCUs at risk of closure. While Congress did not act on accreditation this year, the Department of Education released new regulations that weaken the power of regional accreditors in particular. The year ends with the possibility of ED taking action against the struggling accreditor ACICS, which I still think will end up closing soon.

(4) The College Board bungled the rollout of its effort to provide context to admissions offices about students’ backgrounds. A longstanding concern with standardized test scores is that they are correlated with race/ethnicity and family income. To provide more context for students’ backgrounds, the College Board (which runs the SAT) created a new tool designed to give college admissions counselors information about the community in which the student attended high school. While the idea was noble, the PR effort flopped. The Wall Street Journal’s exclusive report on the tool mentioned an “adversity score,” and the College Board lost control of the narrative around their Landscape initiative. Finally, both the College Board and ACT got some coal in their stockings last week thanks to a lawsuit claiming that the University of California’s standardized test score requirement is discriminatory.

(3) The 2020-21 admissions cycle may look much different following threats from the U.S. Department of Justice. For many years, May 1 has been the key date in the selective college admissions process—the day which students are supposed to commit to attending a particular institution. (But as I state in my most popular blog post of all time, this day has been overrated for years.) But now National College Decision Day is no more, thanks to threats from the U.S. Department of Justice. The National Association for College Admission Counseling agreed to eliminate policies that the federal government viewed as a “restraint of trade.” The DOJ sued and then immediately settled last week after NACAC got rid of the May 1 deadline and restrictions against soliciting transfer students. The 2020-21 admissions cycle should be interesting, and my condolences go to the enrollment management folks at colleges who have to predict admissions yield in a new environment.

(2) Academic publishing companies and universities appear to be entering a standoff over journal access amid rising price tags. The issue of academic journal subscription fees seems pretty arcane and unimportant at first glance—until the price tags get taken into account. Subscription prices for academic journals have been rising by six to seven percent per year, with publishers creating massive bundles of journals across disciplines in an effort to leverage their market power. Amid rising price tags, a number of high-profile universities ended their contracts with publishers in an effort to save money. This includes the University of California, which ended its deal with publishing giant Elsevier in February. Also keep an eye on open-access publishing agreements, which Carnegie Mellon reached with Elsevier last month. In the next few years, expect struggles between publishers and universities about journal access and pricing to intensify.

(1) College closures and mergers continue to get more attention, even if the rate of closures is still modest. An increasingly dominant narrative among the public is that higher education is in crisis and that a large number of colleges will close. While there was a spike of consolidations and closures in the for-profit sector in recent years, the rate of nonprofit college closures has only ticked up slightly in recent years and credit ratings agency Moody’s recently upgraded its view of the sector from negative to stable. And Bennett College avoided closure this year after raising $5 million with the help of High Point University (which is normally not a college that I say nice things about).

With that being said, not all parts of the country are faring as well. Vermont saw three closures this year, and Massachusetts is implementing regulations to examine the financial health of private colleges annually after a number of recent closures. (The U.S. Department of Education is also watching this issue.) Population declines and concerns about affordability are the main driver of closures in the Northeast and Midwest, but some colleges effectively hastened their own demise. Cincinnati Christian University announced in October that it is closing this month after spending a large amount of money starting a football team and hiring a leader with a troubled financial past. Expect more states to try to ramp up their oversight of private colleges while getting pushback from leaders who worry about scrutiny pushing their institutions over the edge.

Honorable mentions: Federal Student Aid chief quits and announces a Senate bid based on massive student debt forgiveness, ED completed a massive (and contentious) round of negotiated rulemaking and officially repealed Obama-era gainful employment regulations, I learned that college meat judging is a real thing, billionaire Robert F. Smith wiped out the student and parent loan debt of Morehouse College’s 2019 graduates, a major change to student loan servicing progresses with a key staff addition, Higher Education Act reauthorization appears stalled yet again.

A Look at High and Low Earning Programs of Study

Not surprisingly, last week’s release of program-level earnings data in the newest version of the College Scorecard got a lot of attention both inside and outside the higher education community. I have gotten quite a few requests from reporters to dive deeper into the data, and I am happy to oblige with a look at which programs have graduates with the highest and lowest median salaries approximately one year after graduation.

First, a few methodological notes. I decided to look at three groups of credentials: certificates and associate degrees from two-year colleges, bachelor’s degrees from four-year colleges, and graduate credentials (certificates, master’s degrees and doctoral/first professional degrees) from research universities. I defined my samples by merging 2018 Carnegie classifications into the Scorecard data and only analyzing colleges with more than five programs that had enough observations in the dataset to have median earnings reported. So think of this as a look at some of the larger programs of study, with the caveat that the Scorecard’s definition of “program” often encompasses multiple academic majors as they are typically defined.

Now that the methods are set forth, let’s dive into the data. 175 two-year colleges met the above requirements for being in the sample, with 176 programs being represented for minimum and maximum earnings due to ties. Nursing programs were more than one-third of the highest earning programs, while criminal justice was the most common low-earning program.

Most common programs for lowest and highest earnings, two-year colleges.

Lowest earnings (n=176) Highest earnings (n=176)
Criminal justice (n=31) Nursing (n=65)
Health/medical administration (n=27) Information technology (n=18)
Teacher education (n=23) Fire protection (n=14)
Liberal arts (n=16) Allied health diagnostics (n=12)
Cosmetology (n=11) HR management (n=8)
Human development (n=8) Medical assisting (n=7)
Allied health (n=8) Dental support services (n=6)
Median earnings: $21,000 Median earnings: $51,800

At the bachelor’s degree level, 958 colleges were represented with more than five programs. Liberal arts programs in fields such as psychology, drama, and English had the lowest earnings, but biology was the third most common program to have the lowest earnings at the institution. On the high end, nursing was by far the most common program, followed by a number of STEM and business-related degrees.

Most common programs for lowest and highest earnings, bachelor’s degrees.

Lowest earnings (n=972) Highest earnings (n=964)
Psychology (n=92) Nursing (n=352)
Drama/theatre arts (n=84) Computer science (n=93)
Biology (n=77) Information technology (n=75)
English language/literature (n=77) Electronics engineering (n=57)
Fine and studio arts (n=68) Accounting (n=49)
Health and fitness (n=42) Business administration (n=34)
Music (n=37) Computer engineering (n=31)
Median earnings: $22,400 Median earnings: $63,150

 I then looked at the 323 Carnegie doctoral/research universities that had more than five graduate programs with data. The patterns for programs with the lowest earnings are similar, with music, health and fitness, and fine arts popping up on the bachelor’s degree and graduate credential lists. And again, nursing is the most common program with the highest earnings. (Is there a trend?)

Most common programs for lowest and highest earnings, graduate programs.

Lowest earnings (n=330) Highest earnings (n=323)
Music (n=45) Nursing (n=100)
Student counseling (n=32) Business administration (n=42)
Social work (n=24) Pharmacy (n=39)
Health and fitness (n=15) Allied health diagnostics (n=27)
Teacher education (n=14) Educational administration (n=21)
Fine and studio arts (n=13) Dentistry (n=10)
Mental/social health services (n=13) Advanced dentistry (n=8)
Median earnings: $35,700 Median earnings: $103,900

Naturally, when I dug into the data, I wanted to see how my program looked in the College Scorecard data. The doctoral program in educational administration at Seton Hall has median graduate earnings of $110,200 one year after completion, which makes it the university’s highest-paid program (nursing is second at $96,000). Educational administration programs do pretty well, thanks in large part to serving adult students working as principals, superintendents, or higher education administrations. But this is a broad category, including EdD programs in K-12 and higher education and a PhD program in higher education. So can I tell my students with certainty what they will make as higher education professionals? No. But is some information better than none? I think so.

A First Look at Program-Level Earnings Data by Credential Level

The U.S. Department of Education has been promising program-level earnings data in the College Scorecard for several months now following the release of program-level debt data back in May. Debt data are interesting, but I think everyone was waiting for earnings data to come out. And it came out today, sending me scrambling to get into the data in between meetings, teaching, and other responsibilities of a tenured faculty member. The data can be found here, and please do read the documentation before digging into the data.

Before I get back to meetings, here are a few takeaways:

(1) Debt and earnings data are based on different samples of students. Debt data only include people with federal loans, while earnings data include people with any type of financial aid. At community colleges, these samples are quite different because more students typically get Pell Grants than loans. But for graduate programs, the numbers really only differ by a few work-study students.

(2) Most programs aren’t covered in the data, but most students are. For the most recent data file, there are 216,638 programs listed. Of these programs, 45,371 have earnings data and 51,423 have debt data.

(3) Earnings data are soon after graduation. Earnings were measured in 2016-17 for students graduating in 2014-15 and 2015-16. More years of data will be included in the future.

(4) Want to make money? Be a dentist. The program with highest earnings was (The) Ohio State University’s dental program, with earnings of $231,200 and debt of $173,309. Dental and other health sciences programs dominated the top of the earnings distributions, with a few law and business programs thrown in. Most of these programs have high debt burdens. On the other hand, Parker University’s chiropractic program brought up the rear with debt of $193,328 and earnings of $2,700. Something strange is probably going on with the data there.

(5) Earnings and debt vary considerably by credential level. In general, both debt and earnings increase across credential levels, but debt increases at a higher rate. As shown below, the median debt-to-earnings ratio across first professional (law, medicine, etc.) programs was 191%. Earnings often increase quickly in future years, but the first few years won’t be fun.

I look forward to seeing a whole host of (responsible) analyses using the new data, so keep me posted of any good takes. This has the potential to influence families and colleges alike, and I’m particularly interested to see if the data release affects whether colleges close low-performing programs (as I discussed in my last blog post).

New Working Paper on the Effects of Gainful Employment Regulations

As debates regarding Higher Education Act reauthorization continue in Washington, one of the key sticking points between Democrats and Republicans is the issue of accountability for the for-profit sector of higher education. Democrats typically want to have tighter for-profit accountability measures, while Republicans either want to loosen regulations or at the very least hold all colleges to the same standards where appropriate.

The case of federal gainful employment (GE) regulations is a great example of partisan differences regarding for-profit accountability. The Department of Education spent much of its time during the Obama administration trying to implement regulations that would have stripped away aid from programs (mainly at for-profit colleges) that could not pass debt-to-earnings ratios. They finally released the first year of data in January 2017—in the final weeks of the Obama administration. The Trump administration then set about undoing the regulations and finally did so earlier this year. (For those who like reading the Federal Register, here is a link to all of the relevant documents.)

There has been quite a bit of talk in the higher ed policy world that GE led colleges to close poor-performing programs, and Harvard closing its poor-performing graduate certificate program in theater right after the data dropped received a lot of attention. But to this point, there has been no rigorous empirical research examining whether the GE regulations changed colleges’ behaviors.

Until now. Together with my sharp PhD student Zhuoyao Liu, I set out to examine whether the owners of for-profit colleges closed lousy programs or colleges after receiving information about their performance.

You can download our working paper, which we are presenting at the Association for the Study of Higher Education conference this week, here.

For-profit colleges can respond more quickly to new information than nonprofit colleges due to a more streamlined governance process and a lack of annoying tenured faculty, and they are also more motivated to make changes if they expect to lose money going forward. It is worth noting that no college should have expected to lose federal funding due to poor GE performance since the Trump administration was on its way in when the dataset was released.

Data collection for this project took a while. For 4,998 undergraduate programs at 1,462 for-profit colleges, we collected information on whether the college was still open using the U.S. Department of Education’s closed school database. Looking at whether programs were still open took a lot more work. We went to college websites, Facebook pages for mom-and-pop operations, and used the Wayback Machine to find information on whether a program appeared to still be open as of February 2019.

After doing that, we used a regression discontinuity research design to look at whether passing GE outright (relative to not passing) or being in the oversight zone (versus failing) affected the likelihood of college or program closures. While the results for the zone versus fail analyses were not consistently significant across all of our bandwidth and control variable specifications, there were some interesting findings for the passing versus not passing comparisons. Notably, programs that passed GE were much less likely to close than those that did not pass. This suggests that for-profit colleges, possibly encouraged by accrediting agencies and/or state authorizing agencies, closed lower-performing programs and focused their resources on their best-performing programs.

We are putting this paper out as a working paper as a first form of peer review before undergoing the formal peer review process at a scholarly journal. We welcome all of your comments and hope that you find this paper useful—especially as the Department of Education gets ready to release program-level earnings data in the near future.

Twenty-Two Thoughts on House Democrats’ Higher Education Act Reauthorization Bill

House Democrats released the framework for the College Affordability Act today, which is their effort for a comprehensive reauthorization of the long-overdue Higher Education Act. This follows the release of Senator Lamar Alexander’s (R-TN) more targeted version last month. As I like to do when time allows, I live-tweeted my way through the 16-page summary document. Below are my 22 thoughts on certain parts of the bill (annotating some of my initial tweets with references) and what the bill means going forward.

(1) Gainful employment would go back in effect for the same programs covered in the Obama-era effort. (Did that policy induce programs to close? Stay tuned for a new paper on that…I’m getting back to work on it right after putting up this blog post!)

(2) In addition to lifting the student unit record ban, the bill would require data to be disaggregated based on the American Community Survey definitions of race (hopefully with a crosswalk for a couple of years).

(3) Federal Student Aid’s office would have updated performance goals, but there is no mention of a much-needed replacement of the National Student Loan Data System (decidedly unsexy and not cheap, though).

(4) Regarding the federal-state partnership, states would have access to funds to “support the adoption and expansion of evidence-based reforms and practices.” I would love to see a definition of “evidence”—is it What Works Clearinghouse standards or something less?

(5) The antiquated SEOG allocation formula would be phased out and replaced with a new formula based on unmet need and percent low-income. Without new money, this may work as well as the 1980 effort (which flopped). Here is my research on the topic.

(6) Same story for federal work-study. Grad students would still be allowed to participate, which doesn’t seem like the best use of money to me.

(7) Students would start repaying loans at 250% of the federal poverty line, up from 150%. Automatically recertifying income makes a lot of sense.

(8) There are relatively small changes to Public Service Loan Forgiveness, mainly regarding old FFEL loans and consolidation (they would benefit quite a few people). But people still have to wait ten years and hope for the best.

(9) I’m in a Halloween mood after seeing the awesome Pumpkin Blaze festival in the Hudson Valley last night. So, on that note, Zombie Perkins returns!

The Statue of Liberty, made entirely out of pumpkins. Let HEA reauthorization ring???

(10) ED would take a key role in cost of attendance calculations, with a requirement that they create at least one method for colleges to use. Here is my research on the topic, along with a recent blog post showing colleges with very low and very high living allowances.

(11) And if that doesn’t annoy colleges, a requirement about developing particular substance abuse safety programs will. Campus safety and civil rights requirements may also irk some colleges, but will be GOP nonstarters.

(12) The bill places a larger role on accreditors and state authorizers for accountability while not really providing any support. Expect colleges to sue accreditors/states…and involve their members of Congress.

(13) Improving the cohort default rate metric is long-overdue, and a tiered approach could be promising. (More details needed.)

(14) There would be a new on-time loan repayment metric, defined as the share of borrowers who made 33 of 36 payments on time. $0 payments and educational deferments count as payments, and ED would set the threshold with waivers possible.

(15) This is an interesting metric, and I would love to see it alongside the Scorecard repayment rate broken down by IDR and non-IDR students. But if the bill improves IDR, expect the on-time rate to (hopefully!) be high.

(16) It would be great to see new IPEDS data on marketing, recruitment, advertising, and lobbying expenses. Definitions matter a lot here, and the Secretary gets to create them. These are the types of metrics that the field showed interest in when the IPEDS folks asked Tammy Kolbe and me to do a landscape analysis of higher ed finance metrics.

(17) Most of higher ed wants financial responsibility scores to be updated (see my research on this), and this would set up a negotiated rulemaking panel to work on it.

(18) There is also language about “rebalancing” who participates in neg reg. The legislative text will be fun to parse.

(19) Teach for America will be reauthorized, but it’s in a list of programs with potential changes. Democrats will watch that closely.

(20) And pour one out for the programs that were authorized in the last Higher Education Act back in 2008, but never funded. This bill wants to get rid of some of them.

(21) So what’s next? Expect this to get a committee vote fairly quickly, but other events might swamp it (pun intended) in the House. I doubt the Senate will take it up as Alexander has his preferred bill.

(22) Then why do this? It’s a good messaging tool that can keep higher ed in the spotlight. Both parties are positioning for 2021, and this bill (which is moderate by Dem primary standards) is a good starting place for Democrats.

Thanks for reading!

Income-Based Repayment Becoming a Costly Solution to Student Loan Debt

This post was originally published at The Conversation.

When Congress established the income-driven repayment for federal student loans back in 2007, it was touted as a way to help student loan borrowers save money by capping monthly payments at a certain percentage of a borrower’s income.

Since then, student loan debt has risen from US$500 billion to where it is now approaching the $1.5 trillion threshold. The federal government expects to forgive over $100 billion of the $350 billion in loans under income-driven repayment as of 2015. That means taxpayers are picking up the bill.

This has put the entire income-driven repayment system in jeopardy as there have been proposals by congressional Republicans and the Trump administration to reduce the amount of loans forgiven and end the Public Service Loan Forgiveness program, which is a special repayment option for people in public service fields. So far, these proposals have failed to become law, but expect to see them put forth again in the future as concerns about program costs continue to grow.

As a researcher who specializes in higher education policy and financial aid, here are some of my insights on how income-driven repayment works, why its future is now in jeopardy and some potential options that can protect the most vulnerable borrowers while also helping taxpayers.

How it works

Six months after they leave college, students who took out a federal student loan are automatically put into a repayment plan with fixed monthly payments over 10 years. This is similar to how mortgages and car loans work. However, repayment can often be a major burden for student loan borrowers who take low-paying jobs or struggle to find employment after college.

To address this issue, Congress and the Department of Education created a number of options during the George W. Bush and Barack Obama presidencies that tied student loan borrowers’ payments to their discretionary income, that is, how much money they have left after meeting their basic needs.

Most students who take out federal loans today qualify for a plan called Pay As You Earn. This plan – known as PAYE – limits monthly payments to 10% of a student loan borrower’s discretionary income for up to 20 years.

There are two requirements. First, student loan borrowers must fill out paperwork each year with their income to be eligible for income-driven repayment. In recent years, more than half of federal student loan borrowers have failed to complete the paperwork on time, putting them back into the standard plan. Second, if any part of the loan is not repaid within 20 years, the remaining balance is forgiven. But this forgiveness counts as income and taxes must be paid on it in that year.

Borrowers who work for government agencies and certain nonprofit organizations can qualify for Public Service Loan Forgiveness, which limits payments to 10% of discretionary income for as little as ten years with no income tax penalty. So far, just 1% of borrowers who applied for forgiveness have had their loans forgiven, but this rate will likely increase over time as the Department of Education gets better at managing the forgiveness process.

Problems abound

In some respects, the biggest problem with income-driven repayment is that too many people are taking advantage of it.

The share of students who reduced their loan balances by even one dollar within five years of leaving college has fallen from 67% to 51% over the last five years as low monthly payments under income-driven repayment mean that many borrowers’ balances are growing instead of shrinking. This has increased the projected price tag of these programs to the federal government well beyond expectations.

These programs tend to be used more frequently by borrowers with large debt burdens – especially those who have more than $100,000 in debt. Data from the Department of Education show that students who owe $100,000 or more make up just over one-third of all outstanding student debt but nearly half of all borrowers in income-driven repayment.

Trying to pay back $100,000 in student loans is certainly not easy, and I can speak from experience thanks to my wife’s law school debt. But most of the borrowers with large student debt burdens tend to be professionals with graduate degrees and reasonably high incomes. Many of the borrowers who have the greatest difficulty repaying their loans never earned a college degree and thus did not see substantial financial benefits from their investment.

What can be done?

As a researcher of student financial aid, my concern is that policymakers might throw the proverbial baby out with the bathwater and get rid of the entire income-driven repayment system.

In my view, a better way to stop borrowers with $100,000 in debt from getting most of the benefits is to limit the amount forgiven. This can be done by capping the amount of loans that can be repaid through income-based repayment or extending the repayment term.

President Obama proposed limiting Public Service Loan Forgiveness to the first $57,500 in loans, although this did not pass Congress. His administration also implemented a program that required graduate students to pay for five more years than undergraduate students.

The savings from requiring higher-income borrowers with large loans to repay more of their loans can then be used to help the most vulnerable borrowers. Students who dropped out of college after a semester or two could see their debt forgiven more quickly and without having to pay additional income taxes. This may be a tough political sell, but this could also encourage students – especially those who are the first in their families to attend college – to give college a shot.

Some of the money could also be used to support larger Pell Grants to reduce the need for borrowing in the first place. Cutting the total amount of loans forgiven in half would allow for an increase of about 20%, or $1,200 per year, in the maximum Pell Grant, which is $6,195 for the 2019-2020 academic year. This would help cover much of the tuition increases over the last decade and reduce student loan debt.

The Conversation

Highlighting Some Interesting Living Allowance Estimates

As a self-proclaimed higher education data nerd, I was thrilled to see the U.S. Department of Education release the first of the 2018-19 data via its Integrated Postsecondary Education Data System (IPEDS) website. Among the new components released today was fresh data on tuition, fees, and other components of the total cost of attendance. After taking a little bit of time to update my datasets (a tip to users: investing in using the full data files instead of the point-and-click interface is well worth it), I’m surfacing with a look at some of the more interesting living allowance estimates for off-campus students.

Some quick details on why this is important: colleges are responsible for setting the cost of attendance (COA) for students, which includes estimated expenses for room and board, books and supplies, and other miscellaneous expenses like transportation and personal care. Students can access financial aid up to the COA, and the net price of attendance (a key accountability measure) is derived by subtracting grant aid from the COA. Colleges are thus caught in a bind between giving students access to the aid—often loans—they need to succeed while not looking too expensive or raising concerns about ‘overborrowing’ (which I am generally skeptical of at the undergraduate level).

Building on previous work that I did with Sara Goldrick-Rab of Temple University and Braden Hosch of Stony Brook University (here is a publicly-available version of our journal article), I pulled colleges’ reported on-campus and off-campus room and board estimates for the 2018-19 academic year.[1] To put this information in comparison, I also pulled in the average county-level nine-month rent for a two-bedroom apartment that is shared with a roommate. To make this fully comparable, I also added $1,800 for nine months to account for food; this amount falls between the USDA’s current cost estimates for their thrifty and low-cost food plans.

Here is a link to the data for all 3,403 colleges that reported off-campus room and board data for the 2018-19 academic year.[2] Below, I highlight some colleges on the high end and on the low end of the estimated living allowances.

Extremely low living allowances

Thirty colleges listed living allowances of $3,000 or below in the 2018-19 academic year. Given that food is approximately $1,800 for nine months, this leaves less than $150 per month for rent. Even in affordable parts of the country, this is essentially impossible. For example, Wilmington College in Ohio is in a reasonably affordable region with the price tag of sharing a two-bedroom apartment coming in at about $350 per month. But an off-campus allowance of $2,650 for nine months is insufficient to cover this and food. (The on-campus price tag is $9,925 for nine months, suggesting that price-sensitive students are probably looking to live off campus as much as possible.)

name state On-campus room and board, 2018-19 Off-campus room and board, 2018-19 Off-campus room and board, 2017-18 Estimated off-campus room and board, 2018-19
Southern California University of Health Sciences CA N/A 1600 4800 9859.5
University of the People CA N/A 2001 2001 9859.5
Wellesley College MA 16468 2050 2050 11673
Kehilath Yakov Rabbinical Seminary NY 2800 2100 2100 9787.5
Western International University AZ N/A 2160 2160 6628.5
Central Georgia Technical College GA N/A 2184 2600 5823
Washington Adventist University MD 9370 2226 2226 9292.5
The Southern Baptist Theological Seminary KY 7150 2460 2460 5638.5
The College of Wooster OH 11850 2500 2500 5107.5
Ohio Institute of Allied Health OH N/A 2500 2500 5346
Agnes Scott College GA 12330 2500 2500 6777
Sharon Regional School of Nursing PA N/A 2500 4800 4995
John Brown University AR 9224 2500 2500 5211
Elmira College NY 12000 2500 2500 5553
Estelle Medical Academy IL N/A 2500 2500 7254
Mountain Empire Community College VA N/A 2600 2600 4995
Wilmington College OH 9925 2650 2650 4945.5
Cleveland Community College NC N/A 2700 2700 4882.5
Michigan Career and Technical Institute MI 6156 2716 2664 5823
Hope College MI 10310 2760 2790 5733
Bryant & Stratton College-Online NY N/A 2800 2800 5571
Allegheny Wesleyan College OH 3600 2880 2880 4869
Daemen College NY 12915 2900 2900 5571
George C Wallace Community College-Dothan AL N/A 2983 2983 4630.5
Long Island Business Institute NY N/A 3000 3000 10039.5
Uta Mesivta of Kiryas Joel NY 6000 3000 3000 7857
Wytheville Community College VA N/A 3000 3000 4959
Skokie Institute of Allied Health and Technology IL N/A 3000 N/A 7254
Rabbinical College Ohr Yisroel NY 3000 3000 3000 10039.5
Bishop State Community College AL N/A 3000 3000 5616

 

Extremely high living allowances

On the high end, 28 colleges checked in with nine-month living allowances above $19,000. Even for colleges in expensive areas, students could easily afford splitting a two-bedroom apartment and eating reasonably well with this allowance. For example, Pace University in New York has a room and board allowance of $19,774 for nine months while splitting a two-bedroom apartment and buying food checks in at $10,040. But if the student has a child and needs a two-bedroom apartment, this estimate is almost spot-on.

name state On-campus room and board, 2018-19 Off-campus room and board, 2018-19 Off-campus room and board, 2017-18 Estimated off-campus room and board, 2018-19
Acupuncture and Massage College FL N/A 19144 16880 8343
Central California School of Continuing Education CA N/A 19210 19210 8739
Arcadia University PA 13800 19292 18365 7200
University of Baltimore MD N/A 19350 14200 7839
Circle in the Square Theatre School NY N/A 19375 18500 10039.5
Little Priest Tribal College NE 7000 19440 19440 4950
Pace University NY 18529 19774 18756 10039.5
New York Film Academy CA N/A 19800 19800 9859.5
Fashion Institute of Technology NY 14480 19968 19558 10039.5
Miami Ad School at Portfolio Center GA N/A 20000 14520 6777
Atlantic Cape Community College NJ N/A 20100 19600 7555.5
John F. Kennedy University CA N/A 20112 N/A 11367
Hofstra University NY 14998 20323 19850 10381.5
School of Visual Arts NY 20400 20400 19600 10039.5
California Institute of Arts & Technology CA N/A 20496 19271 11106
Hawaii Medical College HI N/A 20712 19152 11101.5
Ocean County College NJ N/A 20832 20496 8455.5
Colorado School of Healing Arts CO N/A 20940 12267 8586
New York School of Interior Design NY 21300 21300 21000 10039.5
Monterey Peninsula College CA N/A 21753 17298 8730
School of Professional Horticulture, New York Botanical Garden NY N/A 22000 22000 10039.5
The University of America CA N/A 23000 N/A 7344
Carolinas College of Health Sciences NC N/A 24831 24108 6426
Long Island University NY 14020 25000 25000 10381.5
Carlos Albizu University-Miami FL N/A 25536 25083 8343
Miami Ad School-San Francisco CA N/A 29400 29400 16065
Miami Ad School-New York NY N/A 29400 29400 10039.5
Miami Ad School-Wynwood FL N/A 29400 29400 8343

 

As a final note in this post, I would like to say that I frequently hear from colleges that I am using incorrect data for their institution in my analyses. My response to that is to remind them to make sure the data they provide to the U.S. Department of Education is correct. I do my best not to highlight colleges that had massive changes from year to year, as that could be a reporting error. But ultimately, it’s up to the college to get the data right until the federal government finally decides to audit a few colleges’ data each year as a quality assurance tool.

[1] This excludes colleges that report living allowances for the entire length of the program to allow for a consistent comparison across nine-month academic years. Additionally, room and board estimates are for students living off campus away from their families, as students living ‘at home’ do not have living allowance data in IPEDS.

[2] If a college requires all first-year students to live on campus, they may be missing from this dataset.

How the New Carnegie Classifications Scrambled College Rankings

Carnegie classifications are one of the wonkiest, most inside baseball concepts in the world of higher education policy. Updated every three years by the good folks at Indiana University, these classifications serve as a useful tool to group similar colleges based on their mix of programs, degree offerings, and research intensity. And since I have been considered “a reliable source of deep-weeds wonkery” in the past, I wrote about the most recent changes to Carnegie classifications earlier this year.

But for most people outside institutional research offices, the first time the updated Carnegie classifications really got noticed was with this fall’s college rankings season. Both the Washington Monthly rankings that I compile and the U.S. News rankings that I get asked to comment about quite a bit rely on Carnegie classifications to define the group of national universities. We both use the Carnegie doctoral/research university category for this, putting master’s institutions to a master’s university category (us) or regional universities (U.S. News). With the number of Carnegie research universities spiking from 334 in the 2015 classifications to 423 in the most recent 2018 classifications, this introduces a bunch of new universities into the national rankings.

To be more exact, 92 universities appeared in Washington Monthly’s national university rankings for the first time this year, with nearly all of these universities coming out of the master’s rankings last year. The full dataset of these colleges and their rankings in both the US News and Washington Monthly rankings can be downloaded here, but I will highlight a few colleges that cracked the top 100 in either ranking below:

Santa Clara University: #54 in US News, #137 in Washington Monthly

Loyola Marymount University: #64 in US News, #258 in Washington Monthly

Gonzaga University: #79 in US News, #211 in Washington Monthly

Elon University: #84 in US News, #282 in Washington Monthly

Rutgers University-Camden: #166 in US News, #57 in Washington Monthly

Towson University: #197 in US News, #59 in Washington Monthly

Mary Baldwin University: #272 in US News, #35 in Washington Monthly

These new colleges appearing in the national university rankings means that other colleges got squeezed down the rankings. Given the priority that many colleges and their boards place on the US News rankings, it’s a tough day on some campuses. Meanwhile, judging by press releases, the new top-100 national universities are probably having a good time right now.

Some Updates on the State Performance Funding Data Project

Last December, I publicly announced a new project with Justin Ortagus of the University of Florida and Kelly Rosinger of Pennsylvania State University that would collect data on the details of states’ performance-based funding (PBF) systems. We have spent the last nine months diving even deeper into policy documents and obscure corners of the Internet as well as talking with state higher education officials to build our dataset. Now is a good chance to come up for air for a few minutes and provide an update on our project and our status going forward.

First, I’m happy to share that data collection is moving along pretty well. We gave a presentation at the State Higher Education Executives Officers Association’s annual policy conference in Boston in early August and were also able to make some great connections with people from more states at the conference. We are getting close to having a solid first draft of a 20-plus year dataset on state-level policies, and are working hard to build institution-level datasets for each state. As we discuss in the slide deck, our painstaking data collection process is leading us to question some of the prior typologies of performance funding systems. We will have more to share on that in the coming months, but going back to get data on early PBF systems is quite illuminating.

Second, our initial announcement about the project included a one-year, $204,528 grant from the William T. Grant Foundation to fund our data collection efforts. We recently received $373,590 in funding from Arnold Ventures and the Joyce Foundation to extend the project through mid-2021. This will allow us to build a project website, analyze the data, and disseminate results to policymakers and the public.

Finally, we have learned an incredible amount about data collection over the last couple of years working together as a team. (And I couldn’t ask for better colleagues!) One thing that we learned is that there is little guidance to researchers on how to collect the types of detailed data needed to provide useful information to the field. We decided to write up a how-to guide on data collection and analyses, and I’m pleased to share our new article on the topic in AERA Open. In this article (which is fully open access), we share some tips and tricks for collecting data (the Wayback Machine might as well be a member of our research team at this point), as well as how to do difference-in-differences analyses with continuous treatment variables. Hopefully, this article will encourage other researchers to launch similar data collection efforts while helping them avoid some of the missteps that we made early in our project.

Stay tuned for future updates on our project, as we will have some exciting new research to share throughout the next few years!