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Early college high school (for high school students)

Higher Education
Benefit-cost methods last updated December 2018.  Literature review updated February 2018.
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Early college high schools are alternative high schools designed to help under-served and underrepresented students transition to the college environment. Located on college campuses or as small stand-alone schools, they provide students with the opportunity to take high school and college courses to complete their high school graduation requirements. Unlike dual enrollment programs, where students attend a typical high school and elect to take college courses in their junior or senior year, students enroll in early college high schools in the 9th grade and participate for four years. The curriculums are specifically designed to help students transition from high school to college-level coursework. Upon graduation, students usually have finished the equivalent of two years of college course work (enough to complete a 2-year college degree or enter a 4-year college as a junior). We report on college in the high school and dual enrollment programs separately.
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 $15,507 Benefits minus costs $62,682
Participants $36,998 Benefit to cost ratio $16.54
Others $18,127 Chance the program will produce
Indirect ($3,917) benefits greater than the costs 92 %
Total benefits $66,716
Net program cost ($4,034)
Benefits minus cost $62,682
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 $44 $0 $104 $22 $170
Health care associated with educational attainment $1,298 ($355) ($1,414) $644 $173
Labor market earnings associated with higher education $19,267 $42,426 $20,766 $0 $82,458
Costs of higher education ($5,101) ($5,074) ($1,328) ($2,555) ($14,058)
Adjustment for deadweight cost of program $0 $0 $0 ($2,028) ($2,028)
Totals $15,507 $36,998 $18,127 ($3,917) $66,716
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $9,727 2015 Present value of net program costs (in 2017 dollars) ($4,034)
Comparison costs $8,695 2015 Cost range (+ or -) 25 %
WSIPP estimates the total cost of early college by taking the difference between the per-student estimate of the total expenditures per early college high school student and WSIPP’s per-student estimate of the total cost of regular K–12 education. The per-student estimate for early college is based on projected costs of early college by location, weighted by the location of the early college in the studies (Webb, 2004).
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.
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 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
Enroll in 2-year college 14 1 1044 0.511 0.231 18 0.000 0.000 0 0.511 0.027
Enroll in 4-year college 14 1 1044 0.120 0.226 18 0.000 0.000 0 0.120 0.595
Graduate with 2-year degree 14 1 1044 0.905 0.261 20 0.000 0.000 0 0.905 0.001
Graduate with 4-year degree 14 1 1044 0.277 0.195 23 0.000 0.000 0 0.277 0.156
High school graduation 14 1 1010 0.150 0.323 18 0.000 0.000 0 0.150 0.641

Citations Used in the Meta-Analysis

Berger, A., Turk-Bicakci, l., Garet, M. Song, M., Knudson, J., Haxton, C., . . . Cassidy, L. (2013). Early college, early success: Early College High School initiative impact study. Washington DC: American Institutes for Research.

Haxton, C., Song, M., Zeiser, K., Berger, A., Turk-Bicakci, L., Garet, M.S., . . . Hoshen, G. (2016). Longitudinal findings from the Early College High School initiative impact study. Educational Evaluation and Policy Analysis, 38(2), 410-430.