Not-so-Free College and the Disappointment Effect

One of the most appealing aspects of tuition-free higher education proposals is that they convey a simple message about higher education affordability. Although students will need to come up with a substantial amount of money to cover textbooks, fees, and living expenses, one key expense will be covered if students hold up their end of the bargain. That is why the results of existing private-sector college promise programs are generally promising, as shown in this policy brief that I wrote for my friends at the Midwestern Higher Education Compact.

But free college programs in the public sector often come with a key limitation—the amount of money that the state has to fund the program in a given year. Tennessee largely avoided this concern by endowing the Tennessee Promise program through lottery funds, and the program appears to be in good financial shape at this point. However, two other states are finding that available funds are insufficient to meet program demand.

  • Oregon will provide only $40 million of the $48 million needed to fund its nearly tuition-free community college program (which requires a $50 student copay). As a result, the state will eliminate grants to the 15% to 20% of students with the highest expected family contributions (a very rough proxy for ability to pay).
  • New York received 75,000 completed applications for its tuition-free public college program, yet still only expects to give out 23,000 scholarships. Some of this dropoff may be due to students attending other colleges, but other students are probably still counting on the money.

In both states, a number of students who expected to get state grant aid will not receive any money. While rationing of state aid dollars is nothing new (many states’ aid programs are first-come, first-served), advertising tuition-free college and then telling students they won’t receive grant aid close to the beginning of the academic year may have negative effects such as choosing not to attend college at all or diminished academic performance if they do attend. There is a sizable body of literature documenting the “disappointment effect” in other areas, but relatively little in financial aid. There is evidence that losing grant aid can hurt continuing students, yet this does not separate out the potential effect of not having money from the potential disappointment effect.

The Oregon and New York experiences provide for a great opportunity to test the disappointment effect. Both states could compare students who applied for but did not receive the grant in 2017-18 to similar students in years prior to the free college programs. This would allow for a reasonably clean test of whether the disappointment effect had any implications for college choice and eventual persistence.

Examining Variations in Marriage Rates across Colleges

This piece originally appeared at the Brookings Institution’s Brown Center Chalkboard blog.

Young adulthood is not only the time when most people attend college, but also a time when many marry. In fact, college attendance and marriage are linked and have social and economic consequences for individuals and their families.

When (and if) people get married is an important topic due to the presence of what is known as assortative mating. This phenomenon, in which a person is likely to marry someone with similar characteristics such as education, is a contributing factor to increasing levels of income inequality. In some circles, there is pressure to marry someone with a similar pedigree, as evidenced by the high-profile Princeton alumna who urged women at the university to find a spouse while in college. For people attending less-selective colleges, having the possibility of a second household income represents a key buffer against economic shocks.

In this blog post, I use a tremendous dataset compiled by The Equality of Opportunity Project that is based on deidentified tax records for 48 million Americans who were born between 1980 and 1991. This dataset has gotten a great deal of attention on account of its social mobility index, which examines the percentage of students who move well up in the income distribution by young adulthood.

I use the publicly available dataset to examine marriage rates of traditional-age college students through age 34 based on their primary institution of attendance. In particular, I am curious about the extent to which institutional marriage rates seem to be affected by the institution itself versus the types of students who happen to enroll there. My analyses are based on 820 public and private nonprofit four-year colleges that had marriage rates and other characteristics available at the institutional level. This excludes a number of public universities that reported tax data as a system (such as all four-year institutions in Arizona and Wisconsin).

The first two figures below show the distribution of marriage rates for the 1980-82 and 1989-91 birth cohorts as of 2014 for students who attended public, private religious, and private nonsectarian institutions. Marriage rates for the younger cohorts (who were between ages 23 and 25) were low, with median rates of 12% at public colleges, 14% at religiously-affiliated colleges, and just 5% at private nonsectarian colleges. For the older cohort (who were between ages 32 and 34), marriage rates were 59% at public colleges, 65% at religiously-affiliated colleges, and 56% at private nonsectarian colleges.

There is an incredible amount of variation in marriage rates within each of these three types of colleges. In the two figures below, I show the colleges with the five lowest and five highest marriage rates for both cohorts. In the younger cohort (Figure 3), the five colleges with the lowest marriage rates (between 0.9% and 1.5%) are all highly selective liberal arts colleges that send large percentages of their students to graduate school—a factor that tends to delay marriage. At the high end, there are two Brigham Young University campuses (which are affiliated with the Church of Jesus Christ of Latter-day Saints, widely known as the Mormon church), two public universities in Utah (where students are also predominately Mormon), and Dordt College in Iowa (affiliated with the Christian Reformed Church). Each of these colleges has at least 43% of students married by the time they reach age 23 to 25.

A similar pattern among the high-marriage-rate colleges emerges in the older cohorts, with four of the five colleges with the highest rates in students’ mid-20s had marriage rates over 80% in students’ early-30s.

A more fascinating story plays out among colleges with the lowest marriage rates. The selective liberal arts colleges with the lowest marriage rates in the early cohort had marriage rates approaching 60% in the later cohort, while the 13 colleges with the lowest marriage rates in the later cohort were all either historically black colleges or institutions with high percentages of African-American students. This aligns with the large gender gap in bachelor’s degree attainment among African-Americans, with women representing nearly 60% of African-American degree completions.

Finally, I examined the extent to which marriage rates were associated with the location of the college and the types of students who attended as well as whether the college was public, private nonsectarian, or religious. I ran regressions controlling for the factors mentioned below as well as the majors of graduates (not shown for brevity). These characteristics explain about 55% of the variation in marriage rates for the younger cohorts and 77% of the variation in older cohorts. Although students at religiously-affiliated institutions had higher marriage rates across both cohorts, this explains less than five percent of the overall variation after controlling for other factors. In other words, most of the marriage outcomes observed across institutions appear to be related mostly to students, and less to institutions.

Colleges in the Northeast had significantly lower marriage rates in both cohorts than the reference group of the Midwest, while colleges in the South had somewhat higher marriage rates. The effects of institutional type and region both got smaller between the two cohorts, which likely reflects cultural differences in when people get married rather than if they ever get married.

Race and ethnicity were significant predictors of marriage. Colleges with higher percentages of black or Hispanic students had much lower marriage rates than colleges with more white or Asian students. The negative relationship between the percentage of black students and marriage rates was much stronger in the older cohort. Colleges with more low-income students had much higher marriage rates in the earlier cohort but much lower marriage rates in the later cohort. Less-selective colleges had higher marriage rates for the younger cohort, while colleges with higher student debt burdens had lower marriage rates; neither was significant for the older cohort.

There has been a lot of discussion in recent years as to whether marriage is being increasingly limited to Americans in the economic elite, both due to the presence of assortative mating and the perception that marriage is something that must wait until the couple is financially secure. The Equality of Opportunity project’s dataset shows large gaps in marriage rates by race/ethnicity and family income by the time former students reach their early 30s, with some colleges serving large percentages of minority and low-income students having fewer than one in three students married by this time.

Yet, this exploratory look suggests that the role of individual colleges in encouraging or discouraging marriage is generally limited, since the location of the institution and the types of students it serves explain most of the difference in marriage rates across colleges.

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:

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:

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:

The College of New Jersey’s FY 2016 audited financial statements:

Moody’s credit rating report for The College of New Jersey:

Information on The College of New Jersey’s budgeting cycle:


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. (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:

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:


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)

Examining Trends in the Pell Grant Program

The U.S. Department of Education recently released its annual report on the federal Pell Grant program, which provides detailed information about the program’s finances and who is receiving grants. The most recent report includes data from the 2015-16 academic year, and I summarize the data and trends over the last two decades in this annual post on the status of the Pell program. (Very preliminary data on Pell receipt for the first two quarters of the 2016-17 academic year can be found in the Title IV program volume reports on the Office of Federal Student Aid’s website.)

The number of Pell recipients fell for the fourth year in a row in 2015-16 to 7.66 million. This represents a 7.9% decline in the last year and an 18.9% drop since the peak in 2011-12. The decline is steepest in the for-profit sector (down 13.9% in one year and 36.7% since 2011-12) and among community colleges (down 13.3% and 28.3%, respectively), while private nonprofit and public four-year colleges stayed relatively constant. For the first time since at least 1993, more students at public four-year colleges received Pell Grants than community college students. While most of this change is likely due to a drop in community college enrollment, some could be due to community colleges offering a small number of bachelor’s degrees being counted as four-year colleges. (Thanks for Ben Miller of the Center for American Progress for pointing that out!)

Pell Grant expenditures fell to $28.6 billion in 2015-16, down from $35.7 billion in 2010-11. After adjusting for inflation, program expenditures are down 26% since the peak. This has allowed the Pell program to develop a surplus of $10.6 billion, $1.3 billion of which was taken to use for other programs in the 2017 budget deal. This surplus also allowed for the Pell Grant to be available for more than two semesters per year as of July 1, which was allowed between 2008 and 2011 before being cut due to budgetary concerns.

Most of the decline in Pell enrollment and expenditures can be attributed to a drop in the number of students who are considered independent for financial aid purposes (typically students who are at least 24 years of age, are married, or have a child). The number of independent Pell recipients fell by 28% in the last four years (to 4.05 million), while the number of dependent Pell recipients fell by just 6.4% (to 3.61 million), as shown in the chart below. However, independent students still make up the majority of Pell recipients, as they have every year since 1993.

There has been an even larger drop in the number of students with an automatic zero expected family contribution, who automatically qualify for the maximum Pell Grant based on family income and receiving means-tested benefits. (For more on these students, check out this article I wrote in the Journal of Student Financial Aid in 2015.) The number of independent students with dependents who received an automatic zero EFC fell by 50% since 2011-12, while the number of dependent students in this category fell by 29%. (Independent students without any dependents are not eligible to receive an automatic zero EFC.) Part of this decline was due to a decrease in the maximum income limit that automatically qualified students for an automatic zero EFC, while the rest can be attributed to an improving economy that has both induced adult students to return to the labor market and raised some incomes beyond the threshold for qualifying for an automatic zero EFC.