MacKenzie Scott's giving, in QALYs
How much health does $26.3 billion of philanthropy buy? Drag the
assumptions and watch a Monte Carlo cost-effectiveness model rerun in
your browser.
Drag to see the estimate move. The model reruns in your browser.
Skeptical weights each effect by how well its study identifies causation. Credulous trusts every cited effect at face value.
Central value (mode) of a 0.55–1.10 triangular draw for the share of the studied effect a marginal unrestricted grant delivers — the whole distribution is sampled, not this number alone.
Real 2026 dollars. Default inflates each year's gifts ($26.39B nominal, 2020–2025) to ~$30.3B with CPI-U.
Annual discount on future life-years.
The most important control is evidence stance: from
skeptical (~70,000 QALYs — each effect weighted by how well its study
identifies causation) to credulous (~200,000 — every cited effect at
face value). That gap, not the dollar figure, is the real uncertainty.
About this model
MacKenzie Scott's Yield Giving network has made over $26 billion
in 2,700+ gifts since 2019 — $26.3 billion through 2025 by
CNBC's year-end accounting. This page asks what that buys in
quality-adjusted life-years, the unit health economists use to
compare a death averted against years lived in better health.
[over $26 billion
in 2,700+ gifts](https://yieldgiving.com/)
It is a GiveWell-style model: 13 intervention
archetypes, each cost-per-QALY drawn where possible from a published
causal estimate
(Medicaid mortality,
community health centers,
supportive housing,
collaborative-care depression),
each effect shrunk toward zero in proportion to how well its study
identifies causation, and the whole thing rerun through thousands of
Monte Carlo draws each time you move a slider.
I built the model with Claude; every estimate here is a model output,
not a measured fact. The Python package, tests, and sources are on
GitHub; this page runs a checked TypeScript
implementation in the browser, reading the exported parameter file.
How it works
Each Monte Carlo draw takes the giving — each year's gifts
inflated to 2026 dollars
($26.39 billion nominal ≈ $30.3 billion, so the dollars and the
cost-effectiveness evidence share one price level) — allocates it
across the archetypes (a Dirichlet whose centers come from
Scott's own gift database —
dollar amounts are disclosed for about two-thirds of the money, and
each organization's dollars are split across its reported focus
areas and mapped to the 13 archetypes; the undisclosed remainder is
imputed from her announced year totals, scaled by each recipient's
pre-gift IRS 990
revenue), assigns each a
cost-per-QALY, and multiplies by two independent discounts:
[IRS 990
revenue](https://projects.propublica.org/nonprofits/)
The gift-size data yields one measured regularity along the way:
across the 1,313 disclosed gift–revenue pairs, gift size scales
with the recipient's pre-gift revenue to the power 0.41
(R² 0.37) — a 10× larger organization receives about 2.5× more
money, not 10× more. That fitted elasticity, not proportionality,
weights the imputation of the undisclosed gifts.
Causal credibility — how well the effect is
identified, drawn from the study's design tier: a
lottery RCT (income → mortality)
is trusted; an associational SNAP correlation
is shrunk hard; an assumption-only bucket (arts, civic) goes to near
zero. This is the evidence stance slider.
lottery RCT (income → mortality)
associational SNAP correlation
Realization — the fraction of the studied effect a
marginal unrestricted grant actually delivers.
The model also prices the same dollars at the global-health
frontier. GiveWell's current impact
estimates put the 2022–2024 program averages at ~$4,000 per life
saved (Malaria Consortium) to ~$5,500 (AMF nets). A child death
averted at ~age 1 is ~25 discounted QALYs under this model's
own conventions (~65 remaining years, 3% discount, utility ~0.87), so
those endpoints — inflated to 2026 dollars — become roughly $175–$241
per QALY-equivalent; I model the benchmark as loguniform $150–$260,
handicapped with the same realization and credibility as Scott's
portfolio (and rescaled at other discount rates) so the comparison
is like-for-like. At the skeptical defaults, the frontier delivers
roughly 1,500× more health per marginal dollar.
[GiveWell's current impact
estimates](https://www.givewell.org/impact-estimates)
That multiple is a marginal comparison — the next dollar,
not the whole portfolio. Frontier-priced opportunities are scarce:
GiveWell directed $397 million in all
of 2024 and moves its
cost-effectiveness bar with the money it expects to raise —
funding down to ~6× cash when flush, back up to 10× when projections
fell. Malaria control, the deepest frontier bucket, absorbed
$3.9 billion in 2024 against a $9.3
billion target, while ~610,000 people died. And the implied
frontier counterfactual — ~105 million QALYs at the default settings
— would mean averting ~4.2 million child deaths, most of
a full year of the world's under-5
deaths; no amount of money buys that at bed-net prices.
Redeploying the full $30 billion would ride up the marginal-cost
curve — to a few hundred times rather than ~1,500×, at my guess —
softer in magnitude, same in direction. The floor is direct cash,
the one option with effectively unbounded capacity, which
GiveWell now scores at 3–4× its own
historic benchmark: in health-only terms, somewhere under
50–100×.
[$397 million in all
of 2024](https://blog.givewell.org/2025/08/13/givewells-2024-metrics-and-impact/)
[moves its
cost-effectiveness bar with the money it expects to raise](https://blog.givewell.org/2022/07/05/update-on-givewells-funding-projections/)
[$3.9 billion in 2024 against a $9.3
billion target, while ~610,000 people died](https://www.who.int/news/item/04-12-2025-new-tools-saved-a-million-lives-from-malaria-last-year-but-progress-under-threat-as-drug-resistance-rises)
[a full year of the world's under-5
deaths](https://www.who.int/news/item/18-03-2026-progress-in-reducing-child-deaths-slows-as-4.9-million-children-die-before-age-five)
[GiveWell now scores at 3–4× its own
historic benchmark](https://blog.givewell.org/2024/11/12/re-evaluating-the-impact-of-unconditional-cash-transfers/)
What this doesn't capture
A QALY is a health metric. Most of Scott's giving targets
economic mobility, education, and equity, whose value is largely
non-health — income, opportunity, rights, wellbeing. The model
therefore understates her total social impact; it answers one specific
question. The largest dollar buckets (equity & justice at ~22%,
education at ~18%) contribute little health precisely because
no credible study ties those grants to QALYs, not because the giving
lacks value.
Key sources
Sommers (2017), AJHE 3(3) — Medicaid cost per life saved $327k–$867k in 2007 dollars, CPI-U inflated here to $529k–$1.40M; mortality effect corroborated by Miller, Johnson & Wherry (2021), QJE.
Miller, Johnson & Wherry (2021), QJE
Bailey & Goodman-Bacon (2015), AER — community health centers at ~$54k per life-year (2012 dollars), ~$79k in 2026 dollars, converted to $/QALY with the model's utility draw.
Bailey & Goodman-Bacon (2015), AER
~$54k per life-year (2012 dollars)
Holtgrave et al. (2013), AIDS and Behavior — Housing & Health intervention $62,493/QALY (HIV-positive unstably-housed cohort, stated in 2005 dollars; ~$107k in 2026 dollars); NASEM (2018) for the mixed-evidence assessment of supportive housing.
Holtgrave et al. (2013), AIDS and Behavior
Collaborative-care depression reviews (Community Guide, 2008 dollars: $17k–$39k; van Steenbergen-Weijenburg 2010: $21.5k–$49.5k, unnormalized) — roughly $26k–$77k in 2026 dollars.
Collaborative-care depression reviews
Cesarini et al. (2016), QJE — lottery evidence of a ~null causal income→mortality effect.
HHS ASPE (2026), Table 3 — value per QALY, $726k central at a 3% discount rate in constant 2025 dollars (~$756k in May-2026 dollars), used for the benefit/cost ratio.
GiveWell current impact estimates — 2022–2024 lives-saved program averages converted here to $150–$260 per QALY-equivalent.
GiveWell current impact estimates
Yield Giving gift database — 2,711 gifts with dollar amounts disclosed for about two-thirds of the $26.39B; org-reported focus areas drive the allocation split (area-to-archetype mapping); undisclosed amounts imputed from year totals in proportion to pre-gift IRS 990 revenue, elasticity fit on the disclosed gifts.
Full annotated bibliography, parameter file, and the tested Python
package: github.com/MaxGhenis/mackenzie-scott-qaly.