A recent meta-analysis found that $1,000 in aid increased enrollment by an average of 2 to 3 percentage points and had positive impacts on year-to-year persistence and degree completion of approximately 1 percentage point. However, not all grant-like programs produce positive effects, as the context and format of how aid is delivered and to whom will moderate their effectiveness. Research indicates that federal tax credits for college, for example, have little to no effect on college enrollment.
In the meta-analysis noted above, the authors found smaller average impacts of merit-only-based programs than of programs with a need component. The reason may be that merit-based programs offer aid to more academically prepared and resourced families, who are more likely to succeed regardless.1 However, merit-based programs can achieve different goals by incentivizing students to exert more effort in high school, or they can help states improve their economy by keeping high-achieving students closer to home.
Promise programs have most consistently been shown to have positive effects on enrollment, but there are fewer studies of their long-term effects. There is considerable variability in how these programs operate, but one consistent aspect is that they serve as an early promise that helps remove uncertainty in how much college will cost. Although Promise programs are often linked to the free community college movement, they have significantly variability in who is served or where students can attend.
Most studies focus on younger, “traditional” students, even though older, nontraditional students account for a large portion of total post-secondary enrollment. There is much less research on nontraditional students, and the results are mixed, as a large proportion of these studies find weak or no effects of aid on enrollment or completion.
In addition to generosity, aid programs vary by a number of factors, such as whether the program provides “first dollar” or “last dollar” scholarships, which colleges are eligible for enrollment, or the administrative requirements for applying for or continuing to receive aid. Each choice has implications for who is targeted or how well the additional funds translate into improved student outcomes. Cost–benefit analyses show that aid programs increase societal welfare, but this positive finding may not apply to each and every program.
This brief focuses on the role of grant aid, which is financial support for attending college that generally does not need to be returned to the provider (separate briefs will cover student loans, which typically must be returned, and work-study programs). Grant aid programs have traditionally defined eligibility based primarily on student “need” or “merit.” “Need” generally indicates that a prospective student has lower income or other measures of disadvantage that might make it more difficult for them to afford college. However, a competing concern is whether providing financial aid is an efficient subsidy for promoting college enrollment and completion; if a student is unlikely to be able to complete their degree program due to poor academic preparation, then some argue that it may not be judicious to provide money to such a student unlikely to earn a degree. Hence, some programs allocate aid via some type of “merit,” such as having achieved a GPA or having obtained standardized test scores that suggest that the student meets some minimum qualification for college success. In more recent years, there has been a rise in “Promise” programs, which typically offer aid to students who graduate from high school in a specific location, may or may not have need or merit criteria, and often require eligible students to attend a specific set of colleges. Tax credits for college are similar to grants in that they provide money for college that does not have to be repaid; however, such grants are delivered very differently.
Understudied topics: There are many types of grant aid programs that aim to change behaviors for different kinds of students on different margins. For example, aid can reduce loans, can induce students to live away from home, allow students to work fewer hours (which can increase study effort and allow students to engage in different extracurricular activities or major in different fields),or change the perceived psychological cost of attending college. While existing studies have investigated some of these phenomena, a full accounting of all these possible factors and how each contributes to different outcomes is likely infeasible. We also know much more about how grant aid impacts the decisions of high school students transitioning into college and less about how aid does or does not impact older students.
Another area for further research is the increasing role of Promise programs. Although existing research shows positive effects, most studies are of a few large and early exemplar programs. These findings might not apply to the myriad Promise programs that have arisen around the country, especially as states have recently begun to adopt the “Promise” language but run such programs more like traditional state aid programs. Although there are concerns about community college-focused programs drawing students away from the four-year sector—which has been found in some studies—the existing evidence remains mixed, thus complicating how we should view these programs and their potential long-term impacts.
Policy considerations: Perhaps in contrast to many other education policy research topics, almost all studies of the impacts of financial aid use high-quality experimental or quasi-experimental designs to estimate the true causal impacts of aid. Nonetheless, the patchwork of local, state, federal, and private aid programs is complex and may interact in ways to produce outcomes that we cannot observe or adequately understand (see the later discussion of key finding #5). When new programs are introduced, the introduction occurs within this existing and varied context, which complicates effective program design.
I first discuss the different institutional sources of grant aid and then describe the impacts of these programs, the implications of different program features, and why these implications matter.
Federal aid. The most well-known and broad-based grant aid program is the Pell Grant program, which is part of the family of federal Title IV aid programs defined under the Higher Education Act.2 The Pell Grant is essentially a voucher that students take with them to the institution in which they enroll, with the amount of aid received being larger for students with higher financial “need.”3 However, the federal government has also directly provided aid to students and families via other programs, such as the National Science and Mathematics Access to Retain Talent (SMART) grant program, which were offered to low-income students to study STEM or critical foreign languages, or TEACH grants, which provide grant aid to students who later teach in a set of high-need fields. Another way in which the federal government supports college enrollment is via tax credits, which can mirror grant aid in that families are provided additional money for enrollment that they do not need to repay.
State aid. There is extraordinary variation in the generosity and format of state aid programs, likely in part because each state may be trying to achieve different goals. In addition to the typical “need” versus “merit” classifications, states often offer idiosyncratic programs that support foster youth, tribes, or undocumented students, as just a few of hundreds of possible examples.[4,5,6] One fairly consistent difference from federal aid is that most state aid programs require students to attend an in-state institution and may often restrict eligibility to only public colleges.
Promise programs. Promise programs are distinct programs where eligibility is determined primarily by the student’s geographic location, sometimes without any corresponding need- or merit-based criteria. Early adopters were typically in areas serving lower-income communities looking to turn around declining public school and post-secondary enrollments.7 Students are typically eligible if they graduate from high school in a specific area (e.g., a district, city, or state), although enrollment may be restricted to specific institutions and may not cover full tuition.
Other programs. Although the programs above constitute some of the most common and researched types of aid, grants can be allocated from many other sources. One source is institutional grant aid that comes directly from a college or university. Private scholarships are another source, with prominent examples including scholarships from the Susan Thompson Buffett Foundation and scholarships from the Gates Millenium Scholars Program. These approaches are better able to target aid to very specific groups of students in a way that would be hard to implement for large-scale federal and state programs that must use uniform administrative processes.
One way to help families pay for college is by offering financial aid, which can reduce costs and relieve short-term credit constraints so that students can reap the long-term benefits of an education.8 Since the earliest days of financial aid, most studies have focused on whether offering aid increases college enrollment, as this measure serves as the most proximate outcome that should theoretically be affected by providing students additional resources. An early summary that averaged the impacts of many different aid programs found that an additional $1,000 in aid increased college enrollment by approximately 4 percentage points.9 A more recent meta-analysis found that $1,000 in aid increased enrollment by an average of 2 to 3 percentage points.[1,10]
The goal of aid is not only to increase enrollment but also to help students earn a degree and have better employment outcomes. Although fewer studies have examined these outcomes, there are a number of works that show that aid produces long-term benefits. A meta-analysis found that $1,000 in aid had positive impacts on year-to-year persistence and degree completion of approximately 1 percentage point.1 A comprehensive study of the Pell Grant found that in the sample restricted to students who enrolled, an additional $1,000 in aid translated into an increase of approximately 1 percentage point (2–3%) in degree completion for dependent students, with slightly larger effects for independents with dependents.11 State aid programs in California and West Virginia were also shown to increase graduation and earnings.[12,13] Receiving aid can also lower students’ loan balances or encourage them to work fewer hours, which could benefit students in the long run in terms of less debt or more opportunities to study.[14,15,16,17]
As one key insight from studies of financial aid, there is no singular “impact,” as the effectiveness of aid is likely to vary by any number of contextual details. I revisit this topic below, where I discuss some design features of aid programs that are correlated with stronger or weaker student outcomes. At a basic level, simply examining the same program in different locations can reveal different effects. For example, a study examined the impact of Pell Grant receipt in Texas for students at public, four-year institutions, and it found large increases in college completion and subsequent earnings.18 The estimated effects were much larger than those found by another study that examined the same Pell Grant program nationwide using essentially the same research design.11 Program effects can vary by where the program is studied, which students are accessing the program, or how other supports—such as state-level initiatives—do or do not complement the program under study.
Although studies of aid mostly show positive results, this tendency in the findings should not imply that offering aid will always produce successful outcomes. One example of an aid program that generally does not lead to changes in outcomes is federal government support via tax credits, which can mirror grant aid in that families are provided additional money for enrollment that they do not need to repay. Tax credits have mostly been found to have little to no impact on enrollment, likely because much of this is aid is directed to higher-income families; however, tax refunds for lower-income earned income tax credit (EITC) recipients increased enrollment.[19,20,21]
One broad way of distinguishing between aid programs is according to whether eligibility is defined based on student “need” or “merit.” A systematic meta-analysis found that, on average, need-based programs produce larger impacts on student outcomes than merit-based programs do, though both can produce positive effects.1 Although some programs, such as one in West Virginia, produced positive short- and long-term effects, an evaluation of Florida’s Bright Futures program found no effect on college enrollment or completion decisions.[13,22] Given the strong correlation between income and achievement, these programs are generally offering aid to academically stronger students from families with more resources and college knowledge, that is, students who are already more likely to earn a degree.
Variation in how aid is allocated has also been linked to how students choose their college major. Need-based grants were found to increase graduation with a STEM degree.[23, 24] One explanation is that STEM courses assign lower grades and that merit aid programs that require students to maintain some academic standard can cause these students to lose aid and drop out, and so these programs can lead students to shift out of these more time-intensive majors due to the threat of losing aid.[25, 26]
It is important to distinguish between the different goals or merit- and need-based aid. Whereas need-based aid helps families with fewer resources afford college, merit-based aid can have multiple goals, including the creation of incentives that may be indirectly related to enrollment. In regard to one goal, an early guarantee of additional money may induce high school students to exert more effort to meet academic goals, which has been shown to be true in some contexts. However, a recent randomized controlled trial in Milwaukee found that students reported more effort but that this increased effort did not translate into higher grades.[27,28, 29,30] Another justification for merit-based programs is that they reduce the cost of college for high-achieving students who might otherwise leave the state for more selective colleges, a phenomenon often described as “brain drain.” A study found that merit-based aid programs increase the likelihood that a student resides in their home state as a young adult by 3 percentage points; however, estimates vary from no effect in Georgia to 8 percentage point effects found for Missouri’s Bright Flight program.[31,32, 33]
In practice, many programs use a combination of both need and merit to allocate aid, which can theoretically improve the efficiency of aid programs by better targeting aid to those who have both high need and the academic preparation to be successful. For example, California’s Cal Grant, which imposes income limits for eligibility and a minimum GPA requirement that is lower for lower-income students, substantially increased bachelor’s and graduate degree completion, long-term earnings, and the likelihood of in-state enrollment, especially for students from lower-income families.12 Even in programs that are ostensibly need based, there may be merit components. Initial eligibility for the Pell Grant is purely need based but requires students to meet the federal requirement of Satisfactory Academic Progress (SAP) by earning at least a 2.0 college GPA to continue receiving aid. Losing aid due to lower academic performance decreases persistence, with larger effects on low-income students.34
Promise programs are distinct from prior programs, as eligibility is determined primarily by graduating from high school in a specific geographic location, which can be as small as a single high school or district. Although these programs are often linked to the free community college movement, as many of them pay full tuition and fees, it is important to note that all aid programs have the potential to make college free. For example, California’s Cal Grant has long offered full tuition and fees at four-year colleges even though it is not billed as a “Promise” program, and the maximum Pell Grant award can pay full tuition and fees at many community colleges nationwide.35 Promise program enrollment is often restricted to specific institutions that are geographically proximate to where the student graduated from high school, but rules can vary significantly. For example, Promise programs have allowed for enrollment at in-state public and private colleges (Kalamazoo Promise), only public colleges (Massachusetts’ Adams Scholarship), only community and technical colleges (Tennessee Promise), or even out-of-state colleges (El Dorado Promise).
Promise programs are generally found to have positive effects on student enrollment, particularly at colleges where students can use their scholarship dollars.36 The limited evidence to date has not consistently shown any impacts on college performance or later outcomes such as earnings or debt.36 The longest studied program is the Kalamazoo Promise program, regarding which research found that college completion rates increased, though early evidence on whether this increase changed earnings outcomes is unclear.37 Knox Achieves, another early Promise program, incentivized community college enrollment, leading to large increases in associate’s degree completion but no observable differences in bachelor’s degree attainment or earnings.38
Promise programs may be particularly effective because they provide a clear and early story that money will be available to cover tuition. This is in contrast to more opaque programs, such as the Pell Grant, that have complex application requirements and where students may not know whether they will receive aid or how much will be provided until after enrollment.[39,40,41] Although not a typical Promise program, Michigan’s High Achieving Involved Leader (HAIL) program engaged in proactive outreach to low-income, high-achieving students and informed them that if they were accepted to the University of Michigan, then they would receive full grant aid to cover their entire tuition. Although the HAIL program did not actually change the aid that students were likely to receive, given that most students would have received a full ride scholarship regardless, the clear and early messaging that attending college at the University of Michigan would be free is likely what changed enrollment decisions.42
One shift has been a movement to create state-level Promise programs, which are different from earlier programs that often existed at a smaller geographic level and relied on philanthropic and private funders for financial support. Three examples include the Tennessee Promise, the Oregon Promise, and the California Promise Grant programs, all of which provide aid only for community college tuition. The Oregon Promise program has both need-based and GPA-based eligibility criteria, and operates similarly to prior state-based programs and less like earlier Promise programs.
One question related to Promise programs that frequently arises is whether the increase in two-year enrollment comes from students who were unlikely to attend college or whether these programs shift enrollment away from four-year colleges. This question is important, as many prior studies find that attending a more resourced college—especially choosing a four-year over a two-year college—has a causal impact on an increased likelihood of graduation.43 First, it is important to remember that Promise programs are not synonymous with free community college programs, as described above. For programs that are focused on community colleges, different studies find wholly different amounts of shifting away from four-year colleges, and there is not yet a clear consensus regarding their effects.
Although college enrollment has increased significantly since the 1950s, this growth in enrollment has led to an increase in students who attended college but never earned a degree. These noncompleters struggle the most with student loan debt, and how to best to induce them to return to college an earn a degree remains an open question.44 Compared to studies of high school graduates transitioning immediately to college, there is less research examining the impacts of offering financial aid to these older, nontraditional students.
Although the number of studies on nontraditional students is limited, the studies that exist often find smaller effects than studies on high school students. A study that used the universe of Free Application for Federal Student Aid (FAFSA) applicants found mixed evidence of impacts, with Pell aid supporting independent students with dependents to earn degrees from private, “less than two-year” colleges but having no impacts on other independent students.11 Other papers have examined the impacts of reductions in lifetime Pell Grant eligibility, tax credits, changes in dependency status, early Pell Grant expansions, and an idiosyncratic California program that targeted older students.[45,46,47,48,49] Although one can find areas where these papers point to positive impacts, they mostly find null effects on college enrollment, completion, or employment and earnings outcomes. Given the paucity of research, there is less ability in this space to compare which types of programs are working and for whom, relative to studies of high school students where variation in program features can help us interpret the relative value of different aid program structures. Perhaps the one area where aid has been most strongly linked to increased enrollment and completion outcomes is with military veterans, who likely differ in a number of ways from the majority of the older, U.S. population still looking to earn their first degree.50
One strength of research on financial aid is that it almost exclusively draws from high-quality studies that use randomized controlled trials or other research designs to produce strong causal estimates of the effectiveness of aid. Given the large number of studies conducted, researchers have tried to draw some broad lessons regarding program design and how design features do or do not support positive student outcomes. Ultimately, there is no one “impact” of financial aid, given that how is aid is offered, to whom, and in what context change significantly between programs. Below, we examine some salient features of aid programs and how these features can factor into these programs’ observed impacts.
Last dollar programs may provide less resources to lower-income students: Aid programs vary based on whether they provide first dollar or last dollar scholarships. In first dollar programs, the awarded funds are applied to tuition without regard for any other assistance that the student may receive. For example, if a state implemented a first dollar program, then a low-income student could use their Pell Grant for any number of expenses such as housing costs or to reduce work hours. In last dollar programs, the awarded funds are used to backfill tuition gaps after other sources of funding are applied. In this case, a new last dollar program would provide a higher portion of money to middle- or higher-income families, who receive less Pell aid or other resources, whereas low-income students might be unaffected and receive little to no benefit from this new program. The recent Oregon Promise program is one such example where more funds went to higher-income families, relative to other programs.51
Programs that restrict enrollment to institutions with lower graduation rates can negatively impact student outcomes. Each program varies by which types of institutions are eligible to receive aid. Even the Pell Grant requires institutions to be Title IV eligible, with some colleges or programs either being not qualified or choosing not to qualify. More importantly, nonfederal aid programs often restrict students to attending a set of institutions, with the most common distinction being whether aid is intended for two-year or four-year college enrollment. Prior research consistently finds that attending a “higher-quality” college causally increases graduation rates.[52,43] Quality is often proxied by measures such as graduation rates, the academic preparation of enrolled students, or financial expenditures, and these measures suggest that four-year colleges are generally of “higher quality” than two-year colleges.
One prominent example of how institutional eligibility changes outcomes is Massachusetts’ Adams Scholarship, where aid was made available only for in-state, public college enrollment. This restriction financially induced some students to shift out of more selective private colleges, causing the offer of aid to lower degree completion rates.53 Offering aid only for specific types of enrollment, as when Tennessee focused on community colleges or California eliminated subsidies for for-profit colleges, shifts enrollment toward those designated colleges.[54,55] Although shifts from four-year to two-year college attendance have been causally linked in multiple contexts to lower degree completion rates, studies have not always had the opportunity to examine whether this relationship would change if those enrolling in two-year colleges were also receiving more aid. More work is needed to weigh how such tradeoffs (i.e., receipt of more aid alongside attendance of a less resourced college) work in conjunction.
The measured success of an aid program depends on how institutions respond to the increased resources. Scholars have long discussed the “Bennett hypothesis,” which suggests that increases in generosity to students lead colleges to raise tuition and fees to absorb these increases, which leaves students less well off than might be theoretically considered. To date, the strongest evidence for this hypothesis comes from private colleges, including for-profit colleges that are more reliant on tuition as their primary source of funding, with relatively little evidence of this phenomenon occurring in public colleges.[56,57,58,59,60] A few papers have found that students who receive federal grant aid may, in turn, receive less state or institutional aid, an effect that operates in a manner similar to the Bennett Hypothesis but not through formal tuition increases. However, these effects may be quite small in practice.[15,61]
The measured success of an aid program depends on how it interacts with other aid programs. Receiving aid from one program can affect how much aid students receive from other programs (as noted above in the discussion of first versus last dollar aid programs). As a result, researchers have drawn lessons from the accumulation of evidence across many programs, rather than relying on any one program in isolation. For example, eligibility for Pell aid can lead colleges to reduce the student’s institutional aid, which can understate the potential positive effects of the additional money.[15,61] This effect is not universal, as another study found that increases in the generosity of the Pittsburgh Promise program did not lead institutions to lower the amount of institutional aid that they offered to students.62 More broadly, we might expect that aid also interacts with other state or local programs in often unobservable ways. In some cases, such as a study of the Pell Grant in Texas, being eligible for the Pell led to increases in other sources of aid, hence amplifying the effect.18
Eligibility for financial aid can be loosely tied to actually receiving aid. The estimated impacts of aid may be attenuated because not everyone is able to maintain access to aid over the course of their academic career or even within a given aid year.63 First, many students may be eligible to apply for aid but do not do so, either due to insufficient knowledge of the process or because of other administrative burdens that prevent access.[64,65,66] Second, even those who apply may lose access to aid while in college due to requirements to resubmit the FAFSA each year or if their academic performance falls below federally or state mandated thresholds for each specific aid program.[67,34] In addition, other federal requirements, such as verification or the Return of Title IV Funds process, have been put in place to ensure that aid programs are not being taken advantage of.[68,69,70] In summary, we must always assume that not all eligible students receive and maintain aid throughout their academic career.
Cost–benefit analyses tend to find that offering financial aid positively affects societal welfare. Given that each aid program has different design features that impact who is targeted and how, it would be difficult to draw broad conclusions about the cost-effectiveness of aid. When cost–benefit principles have been applied to specific programs—mostly in research focusing on those programs that have been shown to be successful in increasing graduation rates—studies find that these expenditures “pay for themselves” by producing long-lasting positive changes in earnings and other measures.[12,29]
Nguyen, Tuan D., Jenna W. Kramer, and Brent J. Evans. 2019. The Effects of Grant Aid on Student Persistence and Degree Attainment: A Systematic Review and Meta-Analysis of the Causal Evidence. Review of Educational Research 89(6): 831–874.↩︎
Here, we are referring to direct grants to students. The federal government also provides other revenues directly to colleges via research funding, targeted grants for specific types of institutions (e.g., Hispanic Serving Institutions), or other methods, which may directly or indirectly benefit students.↩︎
Need has historically been measured by the federal government as students’ expected family contribution (EFC); however, currently, the Student Aid Index (SAI) is used for students applying for aid in the 2024–25 academic year.↩︎
Higher Education Services Corporation. Aid to Native Americans..↩︎
Texas Higher Education Coordinating Board. Texas Application for State Financial Aid.↩︎
California Student Aid Commission.↩︎
Perna, Laura W., and Elaine W. Leigh. 2018. Understanding the Promise: A Typology of State and Local College Promise Programs. Educational Researcher 47(3): 155–180.↩︎
Becker, Gary. S. 1964. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. University of Chicago Press.↩︎
Deming, David, and Susan Dynarski. 2010. College Aid. In Targeting Investments in Children: Fighting Poverty When Resources Are Limited. Edited by P. B. Levine and D. J. Zimmerman. University of Chicago Press. 283–302.↩︎
Both meta-analyses included only “high-quality” studies that could produce causal claims about the impact of aid, rather than studies that can show only correlations between aid and student outcomes.↩︎
Eng, Amanda, and Jordan Matsudaira. 2021. Pell Grants and Student Success: Evidence from the Universe of Federal Aid Recipients. Journal of Labor Economics 39(S2): S413–S454.↩︎
Bettinger, Eric, Oded Gurantz, Laura Kawano, Bruce Sacerdote, and Michael Stevens. 2019. The Long Run Impacts of Financial Aid: Evidence from California's Cal Grant. American Economic Journal: Economic Policy 11(1): 64–94.↩︎
Scott-Clayton, Judith, and Basit Zafar. 2019. “Financial Aid, Debt Management, and Socioeconomic Outcomes: Post-College Effects of Merit-Based Aid”. Journal of Public Economics 170: 68–82.↩︎
Odle, Taylor K., Jason C. Lee, and Steven P. Gentile. 2021. Do Promise Programs Reduce Student Loans? Evidence from Tennessee Promise. The Journal of Higher Education, 92(6): 847–876.↩︎
Park, Rina Seung Eun, and Judith Scott-Clayton. 2018. The Impact of Pell Grant Eligibility on Community College Students’ Financial Aid Packages, Labor Supply, and Academic Outcomes. Educational Evaluation and Policy Analysis 40(4): 557–585.↩︎
Darolia, Rajeev. 2014. Working (and Studying) Day and Night: Heterogeneous Effects of Working on the Academic Performance of Full-Time and Part-Time Students. Economics of Education Review 38: 38–50.↩︎
Evans, Brent J., and Tuan D. Nguyen. 2019. Monetary Substitution of Loans, Earnings, and Need-based Aid in Postsecondary Education: The Impact of Pell Grant Eligibility. Economics of Education Review 70: 1–19.↩︎
Denning, Jeffrey T., Benjamin M. Marx, and Lesley J. Turner. 2019. ProPelled: The Effects of Grants on Graduation, Earnings, and Welfare. American Economic Journal: Applied Economics 11(3): 193–224.↩︎
Long, Bridget T. 2004. The Impact of Federal Tax Credits for Higher Education Expenses. In College Choices: The Economics of Where to Go, When to Go, and How to Pay For It. Edited by C. M. Hoxby. University of Chicago Press. 101–168.↩︎
Bulman, George B., and Caroline M. Hoxby. 2015. The Returns to the Federal Tax Credits for Higher Education. Tax Policy and the Economy 29(1): 13–88.↩︎
Manoli, Day, and Nicholas Turner. 2018. Cash-on-Hand and College Enrollment: Evidence from Population Tax Data and the Earned Income Tax Credit. American Economic Journal: Economic Policy 10(2): 242–271.↩︎
Gurantz, Oded, and Taylor K. Odle. 2022. The Impact of Merit Aid on College Choice and Degree Attainment: Reexamining Florida’s Bright Futures Program. Educational Evaluation and Policy Analysis 44(1): 79–104.↩︎
Castleman, Benjamin L., Bridget Terry Long, and Zachary Mabel. 2018. Can Financial Aid Help to Address the Growing Need for STEM Education? The Effects of Need‐Based Grants on the Completion of Science, Technology, Engineering, and Math Courses and Degrees. Journal of Policy Analysis and Management 37(1): 136–166.↩︎
Anderson, Drew M., Katharine M. Broton, and David B. Monaghan. 2023. Seeking STEM: The Causal Impact of Need-Based Grant Aid on Undergraduates’ Field of Study. The Journal of Higher Education, 94(7): 921–944.↩︎
Sjoquist, David L., and John V. Winters. 2015. State Merit-Aid Programs and College Major: A Focus on STEM. Journal of Labor Economics 33(4): 973–1006.↩︎
Dee, Thomas S., and Linda A. Jackson. 1999. Who Loses HOPE? Attrition from Georgia's College Scholarship Program. Southern Economic Journal 66(2): 379–390..↩︎
Pallais, Amanda. 2009. Taking a Chance on College: Is the Tennessee Education Lottery Scholarship Program a Winner? Journal of Human Resources 44(1): 199–222.↩︎
Ash, Jennifer, Elise Swanson, and Gary Ritter. 2021. A Promise Kept? The Impact of the El Dorado Promise Scholarship on Student Achievement. Educational Evaluation and Policy Analysis 43(1): 83–107.↩︎
Harris, Douglas, and Jonathan Mills. Forthcoming. Should College Be "Free"? Evidence on Free College, Early Commitment, and Merit Aid from an Eight-Year Randomized Trial. American Economic Journal: Economic Policy.↩︎
Domina, Thurston. 2014. Does Merit Aid Program Design Matter? A Cross-Cohort Analysis. Research in Higher Education 55(1): 1–26.↩︎
Harrington, James R., José Muñoz, Bradley R. Curs, and Mark Ehlert. 2016. Examining the Impact of a Highly Targeted State Administered Merit Aid Program on Brain Drain: Evidence from a Regression Discontinuity Analysis of Missouri’s Bright Flight Program. Research in Higher Education 57(4): 423–447.↩︎
Sjoquist, David L., and John V. Winters. 2014. Merit Aid and Post-College Retention in the State. Journal of Urban Economics 80: 39–50.↩︎
Sjoquist, David L., and John V. Winters. 2013. The Effects of HOPE on Post-College Retention in the Georgia Workforce. Regional Science and Urban Economics 43(3): 479–490.↩︎
Scott-Clayton, Judith, and Lauren Schudde. 2020. The Consequences of Performance Standards in Need-Based Aid: Evidence from Community Colleges. Journal of Human Resources 55(4): 1105–1136.↩︎
As another example, California’s long-running, need-based fee waiver for community colleges changed its name from the Board of Governors Fee Waivers to the California Promise Grant, without any change in the underlying structure of the program, due to the increasing popularity of the “Promise” moniker.↩︎
Monaghan, David B. 2024. How Powerful Are Promises? A Systematic Review of the Causal Mechanisms and Outcomes of "Free College" Programs in the United States (EdWorkingPaper: 24-988).↩︎
Bartik, Timothy J., Brad Hershbein, and Marta Lachowska. 2021. The Effects of the Kalamazoo Promise Scholarship on College Enrollment and Completion. Journal of Human Resources 56(1): 269–310.↩︎
Carruthers, Celeste K., William F. Fox, and Christopher Jepsen. 2023. What Knox Achieved. Estimated Effects of Tuition-free Community College on Attainment and Earnings. Journal of Human Resources 1220–11359R11352.↩︎
Dynarski, Susan, and Judith Scott-Clayton. 2013. Financial Aid Policy: Lessons from Research. The Future of Children 23(1): 67–91.↩︎
Burland, Elizabeth, Susan Dynarski, Katherine Michelmore, Stephanie Owen, and Shwetha Raghuraman. 2023. The Power of Certainty: Experimental Evidence on the Effective Design of Free Tuition Programs. American Economic Review: Insights 5(3): 293–310.↩︎
Perna, Laura W., Elaine W. Leigh, and Stephanie Carroll. 2017. Free College: A New and Improved State Approach to Increasing Educational Attainment? American Behavioral Scientist 61(14): 1740–1756.↩︎
Dynarski, Susan, C. J. Libassi, Katherine Michelmore, and Stephanie Owen. 2021. Closing the Gap: The Effect of a Targeted, Tuition-Free Promise on College Choices of High-Achieving, Low-Income Students. American Economic Review 111(6): 1721–1756.↩︎
Mountjoy, Jack. 2022. Community Colleges and Upward Mobility. American Economic Review 112(8): 2580–2630.↩︎
Looney, Adam, and Constantine Yannelis. 2015. A Crisis in Student Loans? How Changes in the Characteristics of Borrowers and in the Institutions They Attended Contributed to Rising Loan Defaults (Brookings Papers on Economic Activity).↩︎
Denning, Jeffrey T. 2019. Born under a Lucky Star. Financial Aid, College Completion, Labor Supply, and Credit Constraints. Journal of Human Resources 54(3): 760–784.↩︎
Seftor, Neil, S., and Sarah E. Turner. 2002. Back to School: Federal Student Aid Policy and Adult College Enrollment. Journal of Human Resources 37(2): 336–352.↩︎
Mabel, Zachary. 2020. Aiding or Dissuading? The Effects of Reducing Lifetime Eligibility Limits for Need-Based Aid on Bachelor’s Degree Attainment and Time to Completion. Research in Higher Education 61(8): 966–1001.↩︎
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This is distinct from the concern that many students who are offered aid do not take up aid, which can usually be resolved in research designs via instrumental variable strategies.↩︎
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