College Major Selection & Shift Analysis
Longitudinal look at how U.S. college majors changed from 2009–2023, linking shifts in student interest with wage dynamics using IPUMS USA microdata and weighted aggregation.
Research Focus
Which majors gained and lost traction?
Ranked the top majors by graduate counts over time, highlighting growing domains like Computer Engineering and Psychology versus declines in General Business.
Do wage signals precede popularity shifts?
Tracked median wages and wage growth to see how compensation correlates with enrollment changes, revealing strong alignment for high-growth technical majors.
What broader socio-economic patterns emerge?
Connected trends to cultural and policy factors-e.g., psychology and biology growth alongside increased focus on healthcare and mental health services.
Data Pipeline
Filtered ACS microdata (2009–2024) for employed bachelor-degree holders with valid wages, respecting IPUMS weighting guidance and omitting anomalous 2020 data.
Applied person-level weights (`PERWT`) to compute nationally representative graduate counts and median wage benchmarks per major and year.
Built time-series and slope charts with Seaborn/Matplotlib, layering annotations to narrate how compensation, policy, and student preference intersect.
Key Insights
Wage growth and enrollment move in sync
Computer Engineering majors enjoyed ~40% wage growth while adding thousands of graduates, suggesting compensation remains a pivotal decision factor for STEM-bound students.
Accounting’s durable appeal
Despite turbulence in other business tracks, Accounting expanded its graduate share by 16.6%, pairing steady wage growth with resilient employer demand.
Cultural shifts influence STEM vs. social sciences
Psychology and Biology growth tracks broader interest in health, wellness, and public sector careers, balancing out declines in generalist business programs.
Full Analysis (PDF)
Detailed report containing methodology, visualizations, and policy takeaways. Mobile users can open or download using the buttons.
Next Steps
Causal inference opportunities
Extend the analysis with lag models or difference-in-differences to better isolate whether wage changes precede enrollment shifts or follow demand signals.
Equity deep dive
Segment by gender and race to surface representation gaps and ensure wage gains are equitably distributed across demographic cohorts.
Program planning partnerships
Package recommendations for university leaders to align curriculum investments with verified demand, especially in high-growth engineering and health tracks.