New Research on Brain Drain and Recent College Graduates

As I discussed in my previous post, I believe there is value in education scholars using social media in spite of the concerns that being active on venues like Twitter can raise. One example of this occurred last April, when Doug Webber of Temple University ran some numbers from the American Community Survey looking at the percentage of young college graduates who left New York (in the context of the state’s proposed Excelsior Scholarship program). The numbers got quite a bit of attention in a very nerdy portion of higher ed Twitter and led me to encourage Doug to write up the results.

He then reached out to me about working on the paper with him, which ended up being a lot of fun to write. After going through the peer review process (one substantive and one minor round of changes), our resulting article is now online at Educational Researcher. (And a big kudos to the ER reviewers and editorial team for taking the paper from initial submission to appearing online in just eight months!)

We ended up looking at state-level interstate mobility rates among young (age 22-24) bachelor’s degree recipients using ACS data, focusing on the 2005-2015 period to examine pre-recession and post-recession patterns. Overall mobility rates dropped from 12.7% in 2005 to 10.4% in 2015, which is a surprising finding given that people have historically tended to move at higher rates during economic downturns. We found quite a bit of variation across states in net interstate mobility rates both pre-recession (2005-07) and post-recession (2013-15), as summarized in the table below.

State-level changes in the number of young adults with bachelor’s degrees.
  Gain/loss of young adults w/BAs (pct)
State 2005-2007 2013-2015
Alabama -4.0 -4.6
Alaska 3.9 -5.0
Arizona 4.2 -0.5
Arkansas -1.4 -2.7
California 3.9 3.7
Colorado 0.7 8.0
Connecticut -2.3 -4.1
Delaware -17.5 -7.2
District of Columbia 20.0 19.0
Florida 2.6 1.0
Georgia 6.5 -1.0
Hawaii 7.6 8.1
Idaho -3.9 -10.8
Illinois 3.6 3.4
Indiana -12.9 -7.2
Iowa -5.1 -8.1
Kansas -10.3 -4.6
Kentucky -1.2 -2.8
Louisiana -8.3 3.4
Maine -12.5 -8.7
Maryland 4.9 -1.5
Massachusetts 0.7 2.1
Michigan -8.7 -5.6
Minnesota 1.9 -1.2
Mississippi -2.3 -10.8
Missouri -0.7 -2.6
Montana -23.4 -13.3
Nebraska 3.6 -4.3
Nevada 13.3 10.0
New Hampshire -4.6 -10.0
New Jersey 3.0 -3.4
New Mexico 4.3 2.1
New York -0.2 -0.3
North Carolina 3.6 4.2
North Dakota -9.0 -1.8
Ohio -5.9 -3.5
Oklahoma -5.8 -4.4
Oregon -2.1 1.4
Pennsylvania -6.2 -6.1
Rhode Island -19.1 -11.3
South Carolina -2.7 -2.8
South Dakota -8.0 0.0
Tennessee -1.6 1.9
Texas 3.5 3.4
Utah -12.4 -3.7
Vermont -15.4 -10.9
Virginia 3.6 2.8
Washington 6.2 6.8
West Virginia -12.7 -1.9
Wisconsin -3.3 -0.2
Wyoming 6.1 3.5
Notes:
(1) The percentages reflect changes over the number of 22-24 year olds with a bachelor’s degree who were in the state in a given year.
(2) These values represent averages across the years referenced above.

This article reflects a great example of how a willingness to share some preliminary data on social media results in a publication that is both (hopefully) policy-relevant and a chance to work with a new collaborator. I can’t say enough great things about working with Doug—and I hope to have more of these types of collaborations in the future!

Don’t Expect a Wave of Private Nonprofit College Closures

American higher education certainly faces its share of challenges. Overall higher education enrollment has dropped from its post-recession high, students and their families are increasingly skeptical of the value of higher education, and the credit rating agency Moody’s recently downgraded the sector to negative from neutral over revenue concerns. These challenges have led to some doomsday predictions regarding college closures; Clayton Christensen of Harvard predicted back in 2011 that half of all colleges would close within 10 to 15 years and since doubled down on his prediction.

To this point, the data tell a different story. While a sizable number of for-profit colleges merge or close in a given year, nonprofit higher education is remarkably stable (and public colleges rarely ever close). According to the U.S. Department of Education, eight degree-granting private nonprofit colleges closed in 2015-16 (the most recent year of data available). Yet the number of degree-granting private nonprofit colleges increased from 1,672 to 1,701—the largest number in 20 years.

Among private nonprofit colleges, there are a few clear risk factors for closure. Small, less-selective institutions with tiny endowments are at a higher risk of closure, particularly if they are located in parts of the country where the pool of traditional-age students is drying up. But these risk factors have existed for decades, yet there is rarely a year in which ten private nonprofit colleges close. (Moody’s expects the number to rise to about 15 per year going forward.)

A recent article published in The Journal of Higher Education helps to provide some data on how resilient small private colleges can be. Melissa Tarrant of the University of West Georgia led a team of researchers who looked back at a 1972 paper by Alexander Astin and Calvin Lee called “The Invisible Colleges.” In that paper, Astin and Calvin identified 491 private, broad-access institutions with fewer than 2,500 students—exactly the type of college that is of greater risk of closure. Yet Tarrant and colleagues showed that 354 of the colleges (more than 70%) were still operating as standalone private nonprofit institutions and only 80 had closed in the following four decades. A failure rate of less than 20% over 40 years does not bode well for predictions that higher education as we know it is going away anytime soon.

A case can be made that the current number of small private colleges is more than would exist if the higher education system were to be designed from scratch to meet the needs of today’s students. But Christensen misses the loyalty of campus communities and alumni (the saga of Sweet Briar College was a great recent example) and the sheer tenacity of institutions as they face extreme financial difficulties. More colleges may consider mergers and strategic alliances, but the rate of college closures in nonprofit higher education is likely to only tick up slightly in the coming decade.

My 2017 Higher Education Finance Reading List

The middle of July marks the two-thirds point in my academic summer, so I’m spending time getting ready for the fall semester in addition to packing in as much research and fun into this wonderful time of year. I am teaching a higher education finance class at Seton Hall University for the fourth time this fall semester and just posted my syllabus for my students to look at before the semester begins.

Here is the reading list I am assigning my students for the course, which is my best effort to capture the current state of knowledge in higher education finance. I teach students who are primarily administrators and practitioners, so I especially value articles that are clearly-written and explain research methods in a concise manner. I link to the final versions of the articles whenever possible, but those without access to an academic library should note that earlier versions of many of these articles are available online via a quick Google search.

I hope you enjoy the list!

 

Introduction to higher education finance

Lumina Foundation video on how the federal government distributes financial aid to students: https://www.luminafoundation.org/looking-back-to-move-forward-4

Chetty, R., Friedman, J. N., Saez, E., Turner, N., & Yagan, D. (2017). Mobility report cards: The role of colleges in intergenerational mobility. Working paper. (Also, look at their website for data on how your favorite college fares: http://www.equality-of-opportunity.org/college/.)

Ehrenberg, R. G. (2012). American higher education in transition. Journal of Economic Perspectives, 26(1), 193-216. (link)

Madzelan, D. (2013). The politics of student aid. Washington, DC: American Enterprise Institute. (link)

Schanzenbach, D. W., Bauer, L., & Breitwieser, A. (2017). Eight economic facts on higher education. Washington, DC: The Hamilton Project. (link)

National Center for Education Statistics (2015). IPEDS data center user manual. Washington, DC: Author. (skim as a reference) (link)

 

Institutional budgeting

Barr, M.J., & McClellan, G.S. (2010). Understanding budgets. In Budgets and financial management in higher education (pp. 55-85). San Francisco, CA: Jossey-Bass. (link)

Varlotta, L.E. (2010). Becoming a leader in university budgeting. New Directions for Student Services, 129, 5-20. (link)

Seton Hall’s FY 2016 Forms 990 and 990-T to the Internal Revenue Service: https://www13.shu.edu/offices/finance/index.cfm

The College of New Jersey’s FY 2016 audited financial statements: https://treasurer.tcnj.edu/files/2016/02/FY2016-Audited-Financials-and-Schedules-of-Federal-State-Awards.pdf

Moody’s credit rating report for The College of New Jersey: https://treasurer.tcnj.edu/files/2016/09/Moodys-TCNJ-Final-Report-8.15.2016.pdf

Information on The College of New Jersey’s budgeting cycle: https://treasurer.tcnj.edu/files/2012/06/FY2018-TCNJ-Strategic-Budget-Planning-Cycle.pdf

 

Policy analysis and higher education finance

DesJardins, S.L. (2001). Understanding and using efficiency and equity criteria in the study of higher education policy. In J.C. Smart & W.G. Tierney (Eds.), Higher education: Handbook of theory and research, Vol. 17 (pp. 173-220). Norwell, MA: Kluwer Academic Publishers. (link)

Ness, E. C. (2010). The role of information in the policy process: Implications for the examination of research utilization in higher education policy. In J. C. Smart (Ed.), Higher education: Handbook of theory and research, Vol. 25 (pp. 1-49). Dordrecht, The Netherlands: Springer. (link)

Weimer, D.L., & Vining, A.R. (1999). Thinking strategically about adoption and implementation. In Policy analysis: Concepts and practice (3rd Ed.) (pp. 382-416). Upper Saddle River, NJ: Prentice-Hall. (link)

Winston, G. C. (1999). Subsidies, hierarchy and peers: The awkward economics of higher education. Journal of Economic Perspectives, 13(1), 13-36. (link)

 

Higher education expenditures

Altonji, J. G., & Zimmerman, S. D. (2017). The costs of and net returns to college major. Cambridge, MA: National Bureau of Economic Research Working Paper 23029. (link)

Archibald, R. B., & Feldman, D. H. (2008). Explaining increases in higher education costs. The Journal of Higher Education, 79(3), 268-295.

Cheslock, J. J., & Knight, D. B. (2015). Diverging revenues, cascading expenditures, and ensuing subsidies: The unbalanced and growing financial strain of intercollegiate athletics on universities and their students. The Journal of Higher Education, 86(3), 417-447. (link)

Hurlburt, S., & McGarrah, M. (2016). Cost savings or cost shifting? The relationship between part-time contingent faculty and institutional spending. New York, NY: TIAA Institute. (link)

Commonfund Institute (2015). 2015 higher education price index. Wilton, CT: Author. (skim) (link)

Desrochers, D. M., & Hurlburt, S. (2016). Trends in college spending: 2003-2013. Washington, DC: American Institutes for Research. (skim) (link)

 

Federal sources of revenue

Cellini, S. R. (2010). Financial aid and for-profit colleges: Does aid encourage entry? Journal of Policy Analysis and Management, 29(3), 526-552. (link)

Kirshstein, R. J., & Hurlburt, S. (2012). Revenues: Where does the money come from? Washington, DC: American Institutes for Research. (link)

Pew Charitable Trusts (2015). Federal and state funding of higher education. Washington, DC: Author. (link)

Pew Charitable Trusts (2017). How governments support higher education through the tax code. Washington, DC: Author. (link)

(Note: I will add a draft paper I’m working on looking at whether law, medical, and business schools responded to a 2006 increase in Grad PLUS loan limits by raising tuition later in the semester. I’ll have a public draft of the paper to share in early November, but I think it’s good that students see a really rough draft to see how the research process works.)

 

State sources of revenue

Chatterji, A. K., Kim, J., & McDevitt, R. C. (2016). School spirit: Legislator school ties and state funding for higher education. Working paper. (link)

Doyle, W., & Zumeta, W. (2014). State-level responses to the access and completion challenge in the new era of austerity. The ANNALS of the American Academy of Political and Social Science, 655, 79-98. (link)

Fitzpatrick, M. D., & Jones, D. (2016). Post-baccalaureate migration and merit-based scholarships. Economics of Education Review, 54, 155-172. (link)

Hillman, N. W. (2016). Why performance-based funding doesn’t work. New York, NY: The Century Foundation. (link)

State Higher Education Executive Officers Association (2017). State higher education finance: FY 2017. Boulder, CO: Author. (skim) (link)

 

College pricing, tuition revenue, and endowments

Goldrick-Rab, S., & Kendall, N. (2016). The real price of college. New York, NY: The Century Foundation. (link)

Jaquette, O., Curs, B. R., & Posselt, J. R. (2016). Tuition rich, mission poor: Nonresident enrollment growth and the socioeconomic and racial composition of public research universities. Journal of Higher Education, 87(5), 635-673. (link)

Kelchen, R. (2016). An analysis of student fees: The roles of states and institutions. The Review of Higher Education, 39(4), 597-619. (link)

Levin, T., Levitt, S. D., & List, J. A. (2016). A glimpse into the world of high capacity givers: Experimental evidence from a university capital campaign. Cambridge, MA: National Bureau of Economic Research Working Paper 22099. (link)

Yau, L., & Rosen, H. S. (2016). Are universities becoming more unequal? The Review of Higher Education, 39(4), 479-514. (link)

Ma, J., Baum, S., Pender, M., & Welch, M. (2016). Trends in college pricing 2016. Washington, DC: The College Board. (skim) (link)

National Association of College and University Budget Offices (2017). 2016 NACUBO-Commonfund study of endowment results. http://www.nacubo.org/Research/NACUBO-Commonfund_Study_of_Endowments/Public_NCSE_Tables.html (skim)

 

Student debt and financing college

Akers, B., & Chingos, M. M. (2016). Game of loans: The rhetoric and reality of student debt (p. 13-37). Princeton, NJ: Princeton University Press. (link)

Boatman, A., Evans, B. J., & Soliz, A. (2017). Understanding loan aversion in education: Evidence from high school seniors, community college students, and adults. AERA Open, 3(1), 1-16. (link)

Chakrabarti, R., Haughwout, A., Lee, D., Scally, J., & van der Klaauw, W. (2017). Press briefing on household debt, with focus on student debt. New York, NY: Federal Reserve Bank of New York. (link)

Houle, J. N., & Warner, C. (2017). Into the red and back to the nest? Student debt, college completion, and returning to the parental home among young adults. Sociology of Education, 90(1), 89-108. (link)

Kelchen, R., & Li. A. Y. (2017). Institutional accountability: A comparison of the predictors of student loan repayment and default rates. The ANNALS of the American Academy of Political and Social Science, 671, 202-223. (link)

 

Financial aid practices, policies, and impacts

Watch the Lumina Foundation’s video on the history of the Pell Grant: https://www.luminafoundation.org/looking-back-to-move-forward-3

Bird, K., & Castleman, B. L. (2016). Here today, gone tomorrow? Investigating rates and patterns of financial aid renewal among college freshmen. Research in Higher Education, 57(4), 395-422. (link)

Carruthers, C. K., & Ozek, U. (2016). Losing HOPE: Financial aid and the line between college and work. Economics of Education Review, 53, 1-15. (link)

Goldrick-Rab, S., Kelchen, R., Harris, D. N., & Benson, J. (2016). Reducing income inequality in educational attainment: Experimental evidence on the impact of financial aid on college completion. American Journal of Sociology, 121(6), 1762-1817. (link)

Schudde, L., & Scott-Clayton, J. (2016). Pell Grants as performance-based scholarships? An examination of satisfactory academic progress requirements in the nation’s largest need-based aid program. Research in Higher Education, 57(8), 943-967. (link)

Baum, S., Ma, J., Pender, M., & Welch, M. (2016). Trends in student aid 2016. Washington, DC: The College Board. (skim) (link)

 

Free college programs/proposals

Deming, D. J. (2017). Increasing college completion with a federal higher education matching grant. Washington, DC: The Hamilton Project. (link)

Goldrick-Rab, S., & Kelly, A. P. (2016). Should community college be free? Education Next, 16(1), 54-60. (link)

Harnisch, T. L., & Lebioda, K. (2016). The promises and pitfalls of state free community college plans. Washington, DC: American Association of State Colleges and Universities. (link)

Murphy, R., Scott-Clayton, J., & Wyness, G. (2017). Lessons from the end of free college in England. Washington, DC: The Brookings Institution. (link)

Map of college promise/free college programs: https://ahead-penn.org/creating-knowledge/college-promise

 

Returns to education

Deterding, N. M., & Pedulla, D. S. (2016). Educational authority in the “open door” marketplace: Labor market consequences of for-profit, nonprofit, and fictional educational credentials. Sociology of Education, 89(3), 155-170. (link)

Doyle, W. R., & Skinner, B. T. (2017). Does postsecondary education result in civic benefits? The Journal of Higher Education. doi: 10.1080/00221546.2017.1291258. (link)

Giani, M. S. (2016). Are all colleges equally equalizing? How institutional selectivity impacts socioeconomic disparities in graduates’ labor outcomes. Research in Higher Education, 39(3), 431-461. (link)

Ma, J., Pender, M., & Welch, M. (2016). Education pays 2016: The benefits of higher education for individuals and society. Washington, DC: The College Board. (link)

Webber, D. A. (2016). Are college costs worth it? How ability, major, and debt affect the returns to schooling. Economics of Education Review, 53, 296-310. (link)

What Does a Professor Do During the Summer?

It’s safe to say that full-time faculty members at American colleges and universities have work schedules and expectations that are often not well understood by the general public. I often get two kinds of questions from people who are trying to figure out how I spend my time:

(1) You only teach two evenings per week. What do you do the rest of the time?

(2) You really have a three-month summer vacation? How do you fill up all of that free time?

I just finished my fourth year as an assistant professor at Seton Hall University, so right now I hear that second question quite a bit. In this post, I share some insights into what my summer looks like as a tenure-track faculty member at a university with substantial (but not extreme) research expectations. (And yes, I will take some time off this summer, as well.)

You don’t have a 12-month contract?

Like our colleagues in K-12 education, most faculty members are paid to work 9-10 months per year. This means that at least in theory, two or three months per year are completely ours. But although it’s common to say that the best three things about being a teacher are June, July, and August, faculty still have to do work outside the contract window in order to do their job well. My nine-month contract ended May 15, and there is absolutely no way I would meet the research or teaching expectations for tenure without using the summer as a way to get ahead. (Similarly, it’s hard for K-12 teachers to do course preps just within their contract period.) But service expectations grind to a halt during the summer, which does provide more time to do other work.

So what does your summer look like?

My biggest project this summer is to work on a paper looking at whether law, medical, and business schools responded to substantially increased Grad PLUS loan limits after 2006 by raising tuition or living allowances. (This is a new look at the Bennett Hypothesis—and I’ve summarized the existing research here.) I received a grant from the AccessLex Institute and the Association for Institutional Research to support this work, which provides me with a month and a half of additional salary and a grad student to help me with data work for 20 hours per week this summer as well as funds to buy out a course in the fall semester. This is my first successful external grant application after eight failed attempts, so it’s good to have some additional support for the summer.

My other important project on the research front is to put the finishing touches on my forthcoming book on higher education accountability, which should be out in early 2018 through Johns Hopkins University Press. I will spend several weeks working on copy editing, putting together an index, and checking page proofs. While I will get a portion of the book’s sales when it comes out, I can safely say that writing a book isn’t a great get-rich-quick scheme. (But journal articles rarely pay any money.)

I am in a fortunate position in which I can supplement my income as a faculty member with consulting or contract work. Each year since 2012, I have compiled Washington Monthly magazine’s college rankings, which comes with a small stipend along with the more important benefit of building connections with the higher education policy community. I also have the opportunity to write occasional policy briefs or white papers on a contract basis; different organizations ask me to explore a topic of interest to them while leaving me with complete editorial freedom to approach the topic as desired. Some of these turn into well-cited papers or articles, such as a paper I wrote at the request of the American Enterprise Institute in 2015 on the landscape of competency-based education.

While I will not teach any formal classes this summer, I will work with my group of dissertation students over the summer (as they pay tuition to work with me over the summer and I get a small stipend from the university). Based on some of the experiences I had in graduate school, I am getting my students together as a group six times over the course of the summer to share their progress and workshop draft chapters. The first meeting was yesterday, and it was a lot of fun. I will also work to update my higher education finance class for the fall semester, as quite a bit has changed since the last time I taught the class (the spring 2016 syllabus is here). I have a folder of 63 potential new readings to incorporate into the class, so it’ll take me a while to narrow this down to 20-30 articles to use in place of what was the state of the art in late 2015.

Academic summers are a wonderful thing—and the flexibility these summers offer are one of the reasons why many of us like this job so much. But even though we have a lot of flexibility about when we do the work, it still needs to get done. I hope this post provides some insights into what June, July, and August look like for at least a certain type of faculty member, and I’d love to hear what summers look like for other academics in the comments section below.

Which Factors Affect Student Loan Repayment and Default Rates?

As student loan debt has surpassed $1.25 trillion, policymakers and members of the public are increasingly concerned about whether students are able to manage rising (but often still modest) loan burdens. The federal government has relied on a measure called cohort default rates—the percentage of former borrowers who defaulted on their loans within a few years of entering repayment—to deny federal financial aid access to colleges with a high percentage of struggling students. Yet default rates can be easily manipulated using strategies such as deferment and forbearance (which often don’t help students in the long run), meaning that default rates are a very weak measure of students’ post-college outcomes.

The 2015 release of the College Scorecard dataset included a new measure—student loan repayment rates, defined as the percentage of borrowers repaying any principal within a certain period of entering repayment. This gets at whether students are paying down their loans, which seems to be a more helpful indicator than relying heavily on default rates. But since repayment rates are a new measure, colleges had no incentive to manipulate repayment rates as they did default rates. This creates a research opportunity to examine whether colleges may have been acting strategically to lower default rates even as their students’ underlying financial situations did not change.

I teamed up with Amy Li, an assistant professor at the University of Northern Colorado, to examine whether the factors affecting loan repayment rates differ from those factors affecting default rates—and whether the factors affecting repayment rates varied based on the number of years after the student entered repayment. Our article on this topic is now out in the ANNALS of the American Academy of Political and Social Science, with a pre-publication version available on my personal website.

We used default and repayment data on students who entered repayment in fiscal years 2006 and 2007 so we could track repayment rates over time. Default rates at the time covered the same time period as the one-year repayment rate, while we also looked at repayment rates three, five, and seven years after entering repayment. (And we had to scramble to redo our analyses this January, as the Department of Education announced a coding error in their repayment rate data in the last week of the Obama Administration that significantly lowered loan repayment rates. If my blog post on the error was particularly scathing, trying to revise this paper during the journal editing process was why!) We then used regressions to see which institutional-level factors were associated with both default and non-repayment rates.

Our key findings were the following:

(1) Being a traditionally underrepresented student was a stronger predictor of non-repayment than default. Higher percentages of first-generation, independent, first-generation, or African-American students were much more strongly associated with not repaying loans than defaulting after controlling for other factors. This suggests that students may be avoiding default (perhaps with some help from their former colleges), but they are struggling to pay down principal soon after leaving college.

(2) For-profit colleges had higher non-repayment rates than default rates. Being a for-profit college (compared to a public college) was associated with a 1.7 percent increase in default rates, yet an 8.5% increase in non-repayment. Given the pressure colleges face to keep default rates below the threshold needed to maintain federal loan eligibility—and the political pressures for-profit colleges have faced—this result strongly suggests that colleges are engaging in default management strategies.

(3) The factors affecting repayment rates changed relatively little in importance over time. Although there were some statistically significant differences in coefficients between one-year and seven-year repayment rates, the general story is that a higher percentage of underrepresented students was associated with higher levels of non-repayment across time.

As loan repayment rates (hopefully!) continue to be reported in the College Scorecard, it will be interesting to see whether colleges try to manipulate that measure by helping students close to repaying $1 in principal get over that threshold. If the factors affecting repayment rates significantly change for students who entered repayment after 2015, that is another powerful indicator that colleges try to look good on performance metrics. On the other hand, the growth of income-driven repayment systems that allow students to be current on their loans without repaying principal, could also change the relationships. In either case, as colleges adapt to a new accountability system, policymakers would be wise to consider additional metrics in order to get a better measure of a college’s true performance.

Which Factors Affect Student Fees?

Tuition increases tend to get the most focus in discussions about college affordability, but a number of other factors also affect the total price tag of a college education. In addition to researching living allowances for off-campus students, I have looked into the often-confusing world of student fees at public colleges. These fees are used for a variety of purposes, such as supporting core instructional activities, funding athletics, paying for student activities, or even seismic safety. The University of California-Santa Cruz lists over 30 mandatory fees that all undergraduates must pay, ranging from $.75 per year to fund a marine discovery center to $1,020 per year for student services. At the typical four-year public college, student fees were nearly $1,300 in the 2012-13 academic year, roughly 20% of median tuition and nearly double their 1999-2000 rate after adjusting for inflation.

In a new article that was just published in The Review of Higher Education, I used a panel regression framework to explore potential institution-level and state-level factors affecting student fee levels between the 2001-02 and 2012-13 academic years.  For institution-level factors, I included tuition, the percent of nonresident students, measures of selectivity, and per-student athletics expenditures (a proxy for the magnitude of a college’s athletics program). For state-level factors, I considered appropriations and financial aid levels, economic conditions, whether a tuition or fee cap was in place, who had the ability to set tuition or fees (politicians, state or system boards, or the individual college), and partisan political control in the state.

Given that students subsidized athletics at public colleges to the tune of at least $10 billion over five years, I fully expected to find that higher per-student athletics expenditures would be associated with higher student fees. Yet after controlling for other factors, there was no significant relationship between athletics spending and fees. This could be explained by the small number of high-spending colleges in big-time conferences that come close to breaking even on athletics, or it could be due to my data ending in 2012-13 and larger increases in athletics fees occurring since then. The only significant institution-level factor was tuition—as tuition rose, fees fell. This implies that some colleges likely treat tuition and fees as interchangeable.

More of the state-level factors have statistically significant relationships with student fee levels. States that have capped fee levels do have fees about $128 lower than states without fee caps, but I also found evidence that colleges in states with tuition caps have fees $59 higher. This suggests that colleges will substitute fees for tuition where possible. If a state’s governor and/or legislature can set tuition, fees tend to be lower, but if policymakers can set fees, fees tend to be higher. Finally, partisan political control only has a small relationship with fees, as having a Republican governor is associated with slightly lower fee levels and control of the legislature was not significant.

Given the magnitude of student fees and the relatively small body of research in this area, I hope to see more studies (particularly qualitative in nature) digging into how student fees are set and how the money is supposed to be used compared to its actual uses.

Why is College So Expensive? (Nearly) Everyone is to Blame

“Why is college so expensive?” “Why does college cost so much?” If I had a dollar for every time I’ve been asked that type of question, I could probably pay the roughly $15,000 it takes to provide a year of college for the typical student at a four-year regional public university. This is the true cost of college—how much the college spends on a given student each year. The public is often more concerned with the price (what students and their families pay), but barring additional massive public spending on higher education, the cost of providing a college education must be brought under control in order for students to see lower price tags.

Any piece written by a member of the higher education community for the general public about college costs is likely to reach a large audience due to deep public concerns about college affordability. A recent piece in the Washington Post by Steven Pearlstein, former journalist and current professor at George Mason University, offers four potential solutions to bending the college cost curve. Below, I discuss each of his four ideas and whether they are feasible. (Note that because the focus is on reducing the cost of educating a student, state funding and additional financial aid aren’t relevant here—although they would reduce the price faced by students.)

Proposal #1: Cap administrative costs. This one seems like a no-brainer; if the goal is to educate students, more money should be spent on instruction compared to various “deanlets” and other administrators. But there are legitimate reasons for additional administrators. First, as Pearlstein notes, increasingly complex government regulations, such as for how financial aid is disbursed, do need specialized individuals. As the college-going population has become more diverse, at least some additional student services are required to serve a student body with different academic and social needs than decades ago.

However, the blame for rising administrative costs can also be shared among students and faculty in addition to administrators and regulators. Some students’ preferences for intercollegiate athletics and recreation facilities (such the infamous climbing walls and lazy rivers) also require a number of additional staff members and administrators to run these endeavors. Additionally, as Andrew Kelly of the American Enterprise Institute noted last week, even student protesters’ demands for additional services at places such as the University of Missouri and Yale could increase total costs. Faculty are also to blame—each time we give up a former part of our jobs (such as advising students, making admissions decisions, or even making copies), someone else does it.

Proposal #2: Use a year-round teaching schedule, five days per week. It’s really hard to argue that college facilities are being used in an efficient manner. Fridays tend to be ghost towns at many colleges, although many less-selective colleges do hold quite a few evening and weekend classes. But residential students tend not to like Friday classes, and faculty with demanding travel schedules also prefer to keep Fridays free for travel. I teach Monday and Wednesday evenings, and I’ll use about half of the Fridays in a given semester to go to meetings and conferences. Technology has the ability to help solve this problem through the use of hybrid classes. Faculty can teach online a few weeks each semester while they are traveling, something which I do on occasion as well as when the weather is bad.

Moving to a year-round teaching schedule, however, is likely to have significant budgetary implications. Most faculty with teaching obligations are on a 9-month or 10-month contract, meaning that they are not expected to work with students during the summer period—let alone teach. Asking faculty to teach in the summer would likely result in contracts needing to be 11 or 12 months per year, which would probably mean increased salaries. After all, if teaching is added to a professor’s schedule in the summer, she probably won’t work for free.

Proposal #3: Teach more and research less. Pearlstein notes that much research is never cited by any other academics, as well as noting that the incentive structure often favors research (which is far easier to quantify than teaching). The blame for the focus on research can be placed on both administrators and faculty, as both groups often prefer research over teaching and may both have input into the tenure and promotion process.

However, Pearlstein’s mention of research showing that “teaching loads at research universities have declined almost 50 percent in the past 30 years” is incorrect. That study, which used the National Study of Postsecondary Faculty, was rescinded in 2013 due to concerns about the wording of faculty workload questions changing during the length of the study. While it’s probably the case that faculty teaching loads at more selective institutions have declined somewhat, Pearlstein shouldn’t have used a study that was rescinded a month after it was released.

Proposal #4: Cheaper, better general education. In this section, Pearlstein pushes for more online and hybrid courses to better engage students in the material. This sounds good, but it is far from a certainty that online courses are actually less expensive than in-person courses. (Research on this is nascent and inconclusive.) Additionally, Pearlstein cites government data stating that “more than three-quarters of students at four-year colleges and universities have never taken an online or hybrid course.” As Russ Poulin at WCET notes, 27% of students took a distance education course in 2013 alone, meaning that the percentage of students with some online experience at some point in college is likely far larger than 25%. I’ll be the first to admit that general education is not my strong point as a member of the graduate faculty, but there are lots of good people working on issues of general education.

As the discussion above suggests, nearly everyone (except woefully underpaid adjuncts) is to blame for the rising costs—and prices—of a college education. The challenge is that any solution is likely to be fairly complex and involve negotiations among faculty, administrators, students, and taxpayers. This is why college costs tend to get lip service from the higher education community until revenue sources dry up. But the financial struggles of many small private colleges (let alone many cash-strapped public colleges) make cost-cutting measures necessary, and hopefully the rest of the higher education community can learn from their experiences.

What Will the College Opportunity Summit Mean for Higher Education?

Today, the White House is hosting a second College Opportunity Summit, following up on a summit held in January that was roundly criticized for focusing on elite institutions. Both this summit and the previous summit involved colleges and other organizations making pledges designed to improve college access and completion rates, particularly for underrepresented populations and in STEM. The first round of pledges (and progress made) and the second round of pledges can both be found on the White House’s website.

Several hundred people, including administrators, policy analysts, and researchers, are at today’s summit, which has the potential to generate useful discussions. But it could also be the case that the discussion turns into a stereotypical academic conference, where a lot of items are discussed but no action is ever taken. So what could the summit mean for higher education?

The first thing that jumps out from the list of pledges is the sheer number. The list contains over 600 actions that colleges, associations, and other organizations plan to take—which is admirable. But as a researcher, two key questions should be considered:

(1) Would colleges and organizations have adopted these policies even without a formal pledge? In research language, this is known as the counterfactual—considering what would have happened in the absence of the policy being studied. This list could represent a list of things that colleges already planned to do (but they get good PR and tickets to the White House tree lighting), or this could be a result of colleges setting new goals as a result of the White House’s call for commitments. When considering the impact of this summit, researchers should talk to some college administrators (while promising confidentiality) to see if the pledges were policies already being planned or a new development.

(2) Will these pledges improve student outcomes? This involves thinking carefully about program design and data collection, so it is possible to use experimental or quasi-experimental methods combined with in-depth interviews in order to examine program impacts and potential moderating and mediating factors. The Institute for Education Sciences announced an additional $10 million in funding for postsecondary research, but that amount won’t make much of a difference as funding an intervention and conducting an evaluation can easily cost several million dollars.

I hope the summit helps colleges and organizations develop partnerships similar to the University Innovation Alliance, the Student Achievement Measure, and other organizations that link colleges with similar goals to each other. But it’s worth keeping in mind that many of these pledges are likely things that colleges planned to do anyway.