The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2017). 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	$7,254		Benefits minus costs	$10,688
	Participants	$9,775		Benefit to cost ratio	$2.18
	Others	$6,215		Chance the program will produce
	Indirect	($3,468)		benefits greater than the costs	70 %
	Total benefits	$19,776
	Net program cost	($9,088)
	Benefits minus cost	$10,688

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
Benefits from changes to:1	Benefits to:
	Taxpayers	Participants	Others2	Indirect3	Total
Crime	$1,440	$0	$3,195	$728	$5,362
Labor market earnings associated with high school graduation	$5,082	$11,192	$5,132	$0	$21,406
K-12 grade repetition	$99	$0	$0	$50	$150
Public assistance	$7	($3)	$0	$3	$7
Health care associated with educational attainment	$1,701	($464)	($1,847)	$859	$249
Costs of higher education	($1,059)	($899)	($295)	($533)	($2,786)
Subtotals	$7,270	$9,826	$6,185	$1,107	$24,388
From secondary participant
Labor market earnings associated with high school graduation	$24	$53	$24	$0	$102
K-12 grade repetition	$1	$0	$0	$1	$2
Health care associated with educational attainment	$8	($2)	$7	$4	$17
Costs of higher education	($5)	($4)	($1)	($3)	($13)
Mortality associated with smoking	($44)	($98)	$0	$0	($142)
Subtotals	($16)	($51)	$30	$2	($34)
Adjustment for deadweight cost of program	$0	$0	$0	($4,578)	($4,578)
Totals	$7,254	$9,775	$6,215	($3,468)	$19,776

Detailed Annual Cost Estimates Per Participant
Annual cost		Year dollars	Summary
Program costs	$9,469	2012	Present value of net program costs (in 2017 dollars)	($9,088)
Comparison costs	$903	2012	Cost range (+ or -)	10 %

Estimated Cumulative Net Benefits Over Time (Non-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 non-discounted dollars to simplify the “break-even” point from a budgeting perspective. 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.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, 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.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease 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. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. 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	Adjusted 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
Crime	4	Primary	2	517	-0.183	0.270	21	-0.183	0.270	31	-0.183	0.497
High school graduation	4	Primary	2	517	0.181	0.077	18	0.181	0.077	18	0.181	0.018
K-12 grade repetition	4	Primary	5	1738	-0.075	0.133	12	-0.075	0.133	12	-0.075	0.572
Teen births under age 18	4	Primary	1	327	-0.466	0.292	19	-0.466	0.292	19	-0.466	0.111
Test scores	4	Primary	7	4750	0.172	0.027	4	0.036	0.006	17	0.172	0.001
Teen births (second generation)	1	Secondary	1	327	-0.466	0.292	19	-0.466	0.292	19	-0.466	0.111

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Aughinbaugh, A. (2001). Does Head Start yield long-term benefits? The Journal of Human Resources, 36(4), 641-665. Currie J., & Thomas, D. (1995). Does Head Start make a difference? The American Economic Review, 85(3), 341-364. Currie, J., & Thomas, D. (1999). Does Head Start help Hispanic children? Journal of Public Economics, 74(2), 235-262.

Deming, D. (2009). Early childhood intervention and life-cycle skill development: Evidence from Head Start. American Economic Journal: Applied Economics, 1(3), 111-134.

Garces, E., Thomas, D., & Currie, J. (2002). Longer-term effects of Head Start. The American Economic Review, 92(4), 999-1012.

Lee, V.E., Brooks-Gunn, J., Schnur, E. (1988). Does Head Start work?: A 1-year follow-up comparison of disadvantaged children attending Head Start, no preschool, and other preschool programs. Developmental Psychology, 24(2), 210-222.

Lee, V.E., Brooks-Gunn, J., Schnur, E., & Liaw, F.R. (1990). Are Head Start effects sustained? A longitudinal follow-up comparison of disadvantaged children attending Head Start, no preschool, and other preschool programs. Child Development, 61(2), 495-507.

Puma, M., Bell, S., Cook, R., Heid, C., Shapiro, G., Broene, P., . . . Spier, E. (2010). Head Start impact study: Final report. Washington, DC: U.S. Department of Health and Human Services.

Roy, A. (2003). Evaluation of the Head Start Program: Additional evidence from the NLSCM79 data (Doctoral dissertation, University at Albany, State University of New York).

Zhai, F., Brooks-Gunn, J., & Waldfogel, J. (2011). Head start and urban children's school readiness: A birth cohort study in 18 cities. Developmental Psychology, 47(1), 134-152.

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