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Need-based grants (for high school students and graduates)

Higher Education
  Literature review updated December 2017.

Need-based grants provide means-tested financial assistance to low-income students. Need-based grants can come from many sources and in various forms. In this meta-analysis, we focus on need-based federal and state grants with minimal eligibility requirements. Example programs in this review include the Federal Pell Grant Program and state grant programs similar to Washington’s State Need Grant. Grants funded by private entities may also be included if their implementation is similar to that of federal and state need-based grants. We exclude institutional need-based aid, as well as other grant programs that have conditions for aid receipt other than income (such as work study programs or merit-based aid). The studies in this meta-analysis evaluate the effects of need-based grants for students who are still attending high school or have recently graduated high school and have not yet enrolled in college.
 
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META-ANALYSIS
CITATIONS

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 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
18 2 4875 0.169 0.028 24 0.169 0.001
18 1 3485 0.097 0.033 19 0.097 0.003
18 1 3776 0.003 0.029 19 0.003 0.927
18 7 33407 0.131 0.049 21 0.131 0.008
18 1 4423 0.004 0.028 21 0.004 0.881
18 2 3967 0.199 0.146 19 0.199 0.174

Citations Used in the Meta-Analysis

Carruthers, C.K., & Welch, J.G. (2015). Not whether, but where? Pell grants and college choices. Knoxville, TN: University of Tennessee.

Castleman, B.L. & Long, B.T. (2013). Looking beyond enrollment: The causal effect of need-based grants on college access, persistence, and graduation. Cambridge, Mass: National Bureau of Economic Research.

Castleman, B.L., Long, B.T., & Mabel, Z. (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.

Dynarski, S.M. (2003). Does aid matter? Measuring the effect of student aid on college attendance and completion. American Economic Review, 93(1), 279-288.

Kane, T.J. (1994). College entry by blacks since 1970: The role of college costs, family background, and the returns to education. Journal of Political Economy, 102(5), 878-911.

Seftor, N.S., & Turner, S.E. (2002). Back to school: Federal student aid policy and adult college enrollment. The Journal of Human Resources, 37(2), 336-352.