I am comfortable recommending a rule that is internally valid with all our presented assumptions. Our analysis operates in the 25th percentile of outcomes; that implies a cost per student of $1,855. (This lines up with the ~95% cost coverage in your row 39, though that is a happy coincidence!)
However, if you choose to weight across the distribution, here is how the cost per student evolves based on recycling performance and leverage assumptions:
p10: $3,472 (Zero leverage)
p25: $1,855 (Zero leverage)
p50: $353 (Assuming 2:1 leverage)
p75: $377 (Assunming 2:1 leverage; note: more Master’s students in this scenario compensates for lower dropout rates, leading to the flatness here)
p90: $141 (5:1 leverage)
Note: These figures are derived from the distribution in the top comment: $1m / (num_students * leverage).
If you want my personal “best guess”: I believe management will react to the data. If we are able to iterate for a decade, we will push toward p90. The team will find cost reductions using partners and tech, optimize contract specifications to ensure we achieve the target leverage, and refine the underwriting model to find the students most likely to succeed.
So, for your BOTEC, I would put $141 per student (implying ~99.5% effective cost coverage via recycling + leverage). But bear in mind, you are speaking to the person who already made that wager!
At the risk of being pedantic, the answer depends heavily on your decision rule regarding uncertainty (relevant: Noah Haber’s work on GiveWell’s uncertainty problem).
I am comfortable recommending a rule that is internally valid with all our presented assumptions. Our analysis operates in the 25th percentile of outcomes; that implies a cost per student of $1,855. (This lines up with the ~95% cost coverage in your row 39, though that is a happy coincidence!)
However, if you choose to weight across the distribution, here is how the cost per student evolves based on recycling performance and leverage assumptions:
p10: $3,472 (Zero leverage)
p25: $1,855 (Zero leverage)
p50: $353 (Assuming 2:1 leverage)
p75: $377 (Assunming 2:1 leverage; note: more Master’s students in this scenario compensates for lower dropout rates, leading to the flatness here)
p90: $141 (5:1 leverage)
Note: These figures are derived from the distribution in the top comment: $1m / (num_students * leverage).
If you want my personal “best guess”: I believe management will react to the data. If we are able to iterate for a decade, we will push toward p90. The team will find cost reductions using partners and tech, optimize contract specifications to ensure we achieve the target leverage, and refine the underwriting model to find the students most likely to succeed.
So, for your BOTEC, I would put $141 per student (implying ~99.5% effective cost coverage via recycling + leverage). But bear in mind, you are speaking to the person who already made that wager!
I appreciate the caveat and you sharing your best guess!