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Return on Investment Report
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This report displays Return on Investment (ROI) estimates for Bachelor's level academic programs. Estimates are based on 1819 graduating cohort consisting of 201,423 student records with 90,200 wage records available in 2023.
Total Program Count
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Programs generating $1 Million or more in ROI per student
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Programs with 50% of more students in negative ROI
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Programs with average negative ROI
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Methodology and Limitations
Methodology
SCHEV's Return on Investment (ROI) model starts with constructing a lifetime wage projection model using person-level wage data spanning 25 years, following these four steps:
Wage data of graduates from 1995-96 to 2019-20 are adjusted to 2023 values, by each year post-completion for which wages are available, for at least three quarters of the calendar year.
To minimize the impact of random and short-term fluctuations, seven-year moving averages are calculated using median wages per program level and "program area" of instructional program (i.e., two-digit CIP code).
A linear regression model is constructed for each program area at each program level based on historic performance of wages from 1995-96 to 2019-20. For each program level, we limit records to only students whose highest degree earned is at the same level.
Students who have earned both Bachelor’s and Master’s degrees are not included in the construction of the model for Bachelor’s level wage projection.
We assume wage changes follow the same pattern beyond 2019-20 in each program area and at each program level and then project a lifetime wage income for students individually using their 4th year postgraduation wages as an anchor.
Using the 2018-19 Bachelor’s graduating cohort as the study population: Students with valid wage data in 2023, and no higher level of degree, are included in the analysis. Assuming they continue to work until age 67 when they reach full retirement under Social Security, we apply the regression model by student and calculate their lifetime wage income from 2020, until the year they turn 67. In other words, students have varying numbers of working years based on their age at graduation, which in turn is based on age at entry and the time spent completing their degree. The longer a student stays in school, typically the lower their lifetime earnings.
In parallel, we construct a counterfactual lifetime wage projection for the same population where the students never never entered college, following these three steps:
Census Bureau’s ACS 5-year estimates of wages for high school (HS) graduates in Virginia from 2010 to 2023 are adjusted to 2023 values.
Linear regression coefficients are calculated based on the above ACS estimates. HS level wages beyond 2023 are projected based on the historic pattern of change in the past 14 years.
Assuming each student included in the analysis would enter the workforce upon HS graduation, earning HS level wage each year up to age 67, we calculate their HS lifetime wage income. This eliminates the opportunity cost of time in college.
The total cost of a Bachelor’s degree is calculated for each student as the sum of total student loans and net price charged to each student (i.e., institutional budget minus all gift aid in each semester enrolled in a Bachelor’s program). Net prices are adjusted to 2023 equivalents.
The projected Bachelor’s lifetime wage represents the total gain from earning a Bachelor’s degree.
The sum of projected high school graduate-level lifetime wages represents the counterfactual comparison.
The total cost of earning a Bachelor’s degree and years delayed entering the workforce full-time combined represent the real and opportunity costs of earning a Bachelor’s degree.
We then contrast the total gain and total loss. The ROI estimates are represented in two different calculations:
Net Lifetime Difference
=[Projected Bachelor’s Lifetime Wages]-[Projected HS Lifetime Wages]-[ Student Debt]-[Net Price]
ROI ratio
=[Projected Bachelor’s Lifetime Wages]/([Projected HS Lifetime Wage]+[Student Debt]+[Net Price])
A positive Net Lifetime Difference shows a net gain from earning a Bachelor’s degree, the same as an ROI ratio greater than one.
Limitations
SCHEV's Return on Investment model has these limitations:
Data are limited too individuals employed in Virginia and in jobs covered by the Commonwealth's Unemployment Insurance program. Certain populations are excluded:
Independent Contractors & Gig Workers:
Individuals classified as independent contractors rather than employees.
Agricultural Laborers:
Specific types of farm labor, except where specifically covered.
Domestic Service Workers:
Individuals working in private homes, local college clubs, or local chapters of fraternities/sororities, unless meeting specific criteria.
Religious & Non-Profit Employees:
Employees of certain non-profit organizations or religious organizations.
Real Estate/Insurance Agents:
Agents working solely on commission.
Government Officials:
Elected officials.
Federal Employees:
Generally, federal workers are covered under a separate federal system (UCFE), not state UI, including military personnel.
Railroad Employees:
Covered under the Railroad Unemployment Insurance Act.
The four-year Bachelor's degree serves a variety of purposes. A degree at this level is designed to demonstrate that the graduate has a broad and general education, combined with a focus on a subject of interest. In the liberal arts and sciences, the area of focus serves to engage the student's interest while sharpening their skills of analysis, inquiry, and communication (among others) while providing a background for further study. In many programs, graduate or professional study beyond the Bachelor's degree is the primary goal. Leaders in business, industry, and politics have earned degrees in a wide range of majors. An individual's outcome and earnings may be affected as much by characteristics of the individual or where they live and work as much or more than the degree earned.
Other programs are specifically preparation for a non-academic career following graduation. Business, engineering, nursing, Allied Health professions, and teacher preparation programs are traditional examples of these.
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