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Washington State Institute for Public Policy
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State early childhood education programs: Universal

Pre-K to 12 Education
Benefit-cost methods last updated December 2024.  Literature review updated July 2019.
To be considered a pre-kindergarten program, the program must have had an age requirement of three or four at the start of the program and an education focus. This analysis includes studies of children attending a state- or district-funded universal pre-kindergarten program, where all children in the state/district are eligible for the program, after 1975. Programs examined offered ECE services on a part-time and/or full-time basis. Comparison students may have received child care provided by family/non-family members, another preschool program, or Head Start.

We exclude programs that provided childcare subsidies, focused on the provision of general childcare, focused on parent and child development, and/or provided more extensive wraparound services.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2023).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $8,793 Benefits minus costs $21,319
Participants $15,590 Benefit to cost ratio $3.59
Others $8,217 Chance the program will produce
Indirect ($3,036) benefits greater than the costs 81%
Total benefits $29,565
Net program cost ($8,246)
Benefits minus cost $21,319

^WSIPP’s benefit-cost model does not monetize this outcome.

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 No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
K-12 grade repetition
Repeating a grade. This is sometimes called "grade retention."
 4 3 513943 -0.156 0.117 9 -0.156 0.117 9 -0.156 0.181
Grade point average^
Non-standardized measure of student performance calculated across subjects.
4 1 991 0.056 0.045 12 n/a n/a n/a 0.056 0.212
K-12 special education
Placement into special education services.
4 1 991 -0.079 0.060 12 -0.079 0.060 12 -0.079 0.186
Suspensions/expulsions^
In-school suspensions, out-of-school suspensions, or expulsions from school
 4 1 991 0.015 0.060 12 n/a n/a n/a 0.015 0.801
Executive function^
Underlying mental processes that are necessary to facilitate self-regulation, decision making, self-control, etc., typically measured with validated assessments.
 4 1 1009 0.183 0.045 4 n/a n/a n/a 0.183 0.001
Office discipline referrals^
Referrals of a student to an administrative office for disciplinary reasons.
4 1 29709 -0.010 0.011 7 n/a n/a n/a -0.010 0.348
School attendance^
Number or percentage of school days present in a given enrollment period.
 4 1 991 0.000 0.045 12 n/a n/a n/a 0.000 1.000
Test scores
Standardized, validated tests of academic achievement.
4 4 4055 0.470 0.083 5 0.146 0.092 17 0.470 0.001
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Test scores Labor market earnings associated with test scores $6,618 $15,590 $8,217 $0 $30,426
K-12 grade repetition K-12 grade repetition $200 $0 $0 $100 $300
K-12 special education K-12 special education $1,974 $0 $0 $987 $2,962
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($4,123) ($4,123)
Totals $8,793 $15,590 $8,217 ($3,036) $29,565
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $9,330 2018 Present value of net program costs (in 2023 dollars) ($8,246)
Comparison costs $2,340 2018 Cost range (+ or -) 25%
The cost of participation in universal early childhood education programs are estimated from Washington’s Early Childhood Education Assistance Program (ECEAP) for low-income preschoolers (2019-20 ECEAP Contractor Slots, Models, Overincome Allotments, and Funding https://www.dcyf.wa.gov/sites/default/files/pdf/eceap/ECEAP_Contractor_slots_models_funding.pdf). The comparison group cost consists of an estimate of all children in Washington who would have been age-eligible to participate in ECEAP/Head Start (ignoring income/ other eligibility requirements) who are participating in Head Start, receiving state-funded childcare subsidies, or receiving no state-funded care. The cost of Head Start participation was provided by T. Saenz-Thompson (personal communication, Office of Head Start Region 10, October 24, 2019). The cost of receiving state-funded childcare subsidies is based on Washington’s childcare subsidy reimbursement rates as of February 2019 (https://www.dcyf.wa.gov/node/1640). The comparison group cost is a weighted average of the costs of Head Start, state-subsidized childcare, and no state-funded care.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Bartik, T.J., Gormley, W.T., Belford, J.A., Anderson, S. (2016). A benefit-cost analysis of the Tulsa universal pre-k program (Upjohn Institute Working Paper 16-261). Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Figlio, D., & Roth, J. (2009). The behavioral consequences of pre-kindergarten participation for disadvantaged youth. In Gruber, J. (Ed.), The Problems of disadvantaged youth: An economic perspective. Chicago, IL: University of Chicago Press.

Gormley, W.T., Jr., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of universal pre-k on cognitive development. Developmental Psychology, 41(6), 872-884.

Gormley, W.T., Phillips, D., & Gayer, T. (2008). Preschool programs can boost school readiness. Science, 320(5884), 1723-4.

Gormley, W.T., Phillips, D., & Anderson, S. (2018). The effects of Tulsa's pre-k program on middle school student performance. Journal of Policy Analysis and Management, 37(1), 63-87.

Hill, C.J., Gormley, W.T., & Adelstein, S. (2015). Do the short-term effects of a high-quality preschool program persist? Early Childhood Research Quarterly, 32(3), 60-79.

Miller, L.C., & Bassok, D. (2019). The effects of universal preschool on grade retention. Education Finance and Policy, 14(2), 149-177.

Weiland, C., Yoshikawa, H. (2013). Impacts of a prekindergarten program on children' mathematics, language, literacy, executive function, and emotional skills. Child Development, 84(6), 2112-2130.

Wong, V.C., Cook, B., & Jung, K. (2008). An effectiveness-based evaluation of five state pre-kindergarten programs. Journal of Policy Analysis and Management, 27(1), 122-154.