Studies included in this meta-analysis estimate the effects of a change in the price of tuition at 4-year colleges on students’ college outcomes, including the likelihood that a student will enroll in college. Results are presented as “elasticities” and are interpreted as the percent change in an outcome we expect from a 1% increase in tuition price.

This meta-analysis includes only studies that examine tuition price without subtracting federal Pell grants from full price values. In addition, this meta-analysis includes only studies that use individual-level data in their analyses. Results of group-level analyses can differ from the results of analyses of the individuals within the same groups. The studies in this meta-analysis evaluate the effects of a tuition price increase for students who are still attending high school or have recently graduated high school and have not yet enrolled in college.

 

^**The effect size for this outcome represents an elasticity, not a standardized mean difference effect size.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured	Treatment age	Primary or secondary participant	No. of effect sizes	Treatment N	Effect sizes (ES) and standard errors (SE)			Unadjusted effect size (random effects model)
					ES	SE	Age	ES	p-value
Enroll in 4-year college** Enroll in a 4-year higher education institution.	18	Primary	4	38227	-0.280	0.086	18	-0.280	0.001
Enroll in 2-year college** Enroll in a 2-year higher education institution.	18	Primary	1	10254	0.106	0.046	18	0.106	0.022
Enroll in any college** Enroll in either a 2-year or 4-year higher education institution.	18	Primary	23	3264722	-0.117	0.024	18	-0.117	0.001
Graduate with any degree** Graduate with a degree from either a 2-year or 4-year higher education institution.	18	Primary	2	9774	-0.895	0.300	23	-0.895	0.003
Apply to 4-year college** Submit an application to a 4-year higher education institution.	18	Primary	1	1424316	-0.037	0.001	18	-0.037	0.001

Baschnagel, C.N. (2015). The price sensitivity of demand for higher education among non-traditional students. (Doctoral dissertation).

Chin, A., & Juhn, C. (2010). Does reducing college costs improve educational outcomes for undocumented immigrants?: Evidence from state laws permitting undocumented immigrants to pay in-state tuition at state colleges and universities. Cambridge, Mass: National Bureau of Economic Research.

Kane, T.J. (1995). Rising public college tuition and college entry: How well do public subsidies promote access to college?. Cambridge, MA: National Bureau of Economic Research.

Knight, B.G., & Schiff, N.M. (2016). The out-of-state tuition distortion. Working Paper Series, 22996.

Cardiff-Hicks, B. (2013). The effect of tuition subsidies on student college choices (Unpublished manuscript). Palo Alto, CA: Stanford University.

Darolia, R., & Potochnick, S. (2015). Educational "when," "where," and "how": implications of in-state resident tuition policies for Latino undocumented immigrants. The Review of Higher Education, 38(4), 507-535.

Flores, S.M. (2010). State dream acts: The effect of in-state resident tuition policies and undocumented Latino students. Review of Higher Education, 33(2), 239-283.

Flores, S.M. (2010). The first state dream act: In-state resident tuition and immigration in Texas. Educational Evaluation and Policy Analysis, 32(4), 435-455.

Hilmer, M.J. (1998). Post-secondary fees and the decision to attend a university or a community college. Journal of Public Economics, 67(3), 329-348.

Kane, T.J. (1995). Rising public college tuition and college entry: How well do public subsidies promote access to college?. Cambridge, MA: National Bureau of Economic Research.

Kaushal, N. (2008). In-state tuition for the undocumented: education effects on Mexican young adults. Journal of Policy Analysis and Management, 27(4), 771-792.

Kennan, J. (2015). Spatial variation in higher education financing and the supply of college graduates. National Bureau of Economic Research.

Kim, J.Y. (2011). An analysis of the effects of state financial aid policy on the timing of postsecondary enrollment: A focus on income and race differences (Doctoral dissertation). ProQuest LLC, Ann Arbor, MI.

Rouse, C.E. (1994). What to do after high school: The two-year versus four-year college enrollment decision. Choices and Consequences: Contemporary Policy Issues in Education, 59–88.

St. John, E. (1990). Price response in enrollment decisions: An analysis of the High School and Beyond sophomore cohort. Research in Higher Education, 31(2), 161-176.

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