College ROI Methodology

Primary sources

Post-college earnings data is sourced from the BLS Occupational Employment and Wage Statistics (OEWS) program, which surveys 1.1 million establishments twice yearly. OEWS provides median and percentile wages by occupation and metropolitan area — the most authoritative source for expected earnings by major/career path.

Graduation rates and institutional costs are from NCES IPEDS (Integrated Postsecondary Education Data System), the federal database of postsecondary institution data. IPEDS reports 6-year graduation rates, in-state/out-of-state tuition, net price (cost minus average institutional aid), and transfer-out rates.

ROI calculation framework

College ROI = (lifetime_earnings_premium over high_school_diploma) / (total_cost_of_attendance + foregone_earnings_during_school). Lifetime earnings premium is computed as (median_degree_holder_earnings - median_high_school_earnings) × expected_work_years, discounted at 3% real discount rate. Total cost = 4-year total cost of attendance including room/board. Foregone earnings = high school diploma median × 4 years.

Net present value of a college degree: NPV = PV(earnings_premium_stream) - total_investment. Payback period: years until cumulative earnings_premium = total_investment. We compute both NPV and payback because they give different insights — a high-NPV degree with a 20-year payback may not be right for every student.

Major comparison

We use BLS wage data mapped to common college majors using the SOC (Standard Occupational Classification) codes most commonly associated with each major. Nursing maps to SOC 29-1141 (RNs). Computer science maps to SOC 15-1252 (Software Developers) and 15-1211 (Computer Systems Analysts). The mapping is approximate — actual career paths vary.

Limitations

Earnings data are medians — individual variation is substantial. Geographic wage differences matter: the same degree earns 40-60% more in San Francisco than in rural areas. Part-time work, career breaks, and graduate school are not modeled in the base case. Selectivity of institution affects earnings beyond the credential — our model uses field-of-study as the primary predictor, which is the stronger BLS signal.

Update protocol

This category is reviewed quarterly. Immediate updates are triggered by changes to the primary source documents listed in the citations above — rate table revisions, new agency guidance, or regulatory amendments.

Error reports go to info@bedrockatools.com. Corrections are published on our corrections page.