Methodology: How We Calculate University Survivability
The Collegiate Survivability Index (CSI) is a data-driven model designed to forecast which private, nonprofit universities are most at risk of closure by 2028.
It combines financial, academic, and demographic indicators to produce a percentile ranking for each institution. A higher CSI percentile score indicates a stronger likelihood of long-term sustainability.
The Three Core Components
Each institution is scored across three key categories using public data from IRS Form 990s, IPEDS, and the U.S. Census.
1. Adjusted Financial Health (40.02%)
We created an improved version of the traditional Composite Financial Index (CFI), known as the adjusted CFI (aCFI). This revision accounts for financial realities that the original CFI overlooks:
- Depreciation is removed, since it distorts short-term viability for tuition-dependent schools.
- Restricted assets are included, recognizing that institutions often access donor-restricted funds in times of crisis.
- All values are standardized using Z-scores, making comparisons fair across institutions of different sizes.
This gives a more realistic picture of an institution’s solvency over the next 3–5 years.
2. Market Saturation (39.99%)
We evaluate how crowded a school's recruitment territory is by calculating:
- The 15–19-year-old population in the state
- The number of higher ed institutions in the region
- Each university’s first-time, full-time enrollment
This creates a saturation score that reveals how fiercely a university must compete for traditional students — especially as birthrates decline.
3. Academic Efficiency (19.99%)
Academic efficiency measures whether a university is delivering strong outcomes with sustainable instructional resources. Key indicators include:
- Graduation rate
- Student-to-faculty ratio
- Degrees awarded per faculty member
- Instructional spending per student
While elite schools may intentionally maintain small classes, many low-ranked institutions show inefficiencies due to weak retention and program bloat.
Forecasting the Future
Each component is projected to 2028 using Holt-Winters exponential smoothing, a forecasting technique that accounts for trends and seasonality. To fine-tune the model:
- We apply Winsorization to control outliers
- We run a Sobol Sequence sensitivity analysis to balance the influence of each variable
- We use Bayesian optimization to adjust weights dynamically as new data becomes available
A Model That Learns and Updates
The CSI is not static. It is updated continuously as:
- New Form 990s are released
- IPEDS enrollment and graduation data are refreshed
- Colleges announce closures or mergers
Institutions that were initially excluded due to missing data will be added as information becomes available through open records requests or direct outreach.
Why CSI Matters
Unlike the federal CFI — which failed to flag at-risk schools like Limestone University and St. Andrews University — our CSI model correctly identified both as high-risk months before closure announcements.
This makes the CSI a powerful, transparent early-warning system for:
- University leadership and boards
- Donors and accreditors
- Parents and prospective students
- Journalists and policymakers