Research · Pay Structure
Pay StructureGeography or Mission? Neither — Budget Size Moves Nonprofit Executive Pay Most, and It Is Not Close
Boards argue about cost-of-living adjustments and sector premiums. A variance decomposition across 732,319 Form 990 filings finds both arguments are about the small dials: organization budget size explains roughly five times more of the variation in officer pay than state, and roughly four times more than mission sector.
Every compensation committee eventually has the same two arguments: whether the executive deserves a cost-of-living premium for the city, and whether the mission field pays differently. Both arguments are real. Both are about the small dials. Across three-quarters of a million officer filings, the dial that dominates is the one committees debate least: how big the organization is.
The finding
Start with the role alone — the job title — which explains 20.0% of the variation in log total compensation across the corpus. Then add one dimension at a time and watch what each buys:
| Grouping | Variance explained (R²) | Added over role alone |
|---|---|---|
| role alone | 0.200 | — |
| role + budget band | 0.625 | +0.425 |
| role + sector | 0.295 | +0.095 |
| role + state | 0.241 | +0.041 |
| role + band + sector + state | 0.724 | +0.524 |
Because the three dimensions overlap (hospitals are big; big organizations cluster in some states), each factor's contribution depends on when it is added. Bounding each honestly — credited first versus credited last — the ranges do not overlap:
| Factor | Marginal R², added first | added last | categories |
|---|---|---|---|
| Budget band | +0.425 | +0.347 | 10 bands |
| NTEE sector | +0.095 | +0.065 | 25 sectors |
| State | +0.041 | +0.072 | 57 states/territories |
However the ordering is sliced, budget size explains roughly four to six times what either geography or mission does — and it does so with the fewest categories. Ten budget bands beat fifty-seven states by an order of magnitude per category, which is the opposite of what a mechanical more-bins-explain-more artifact would produce. The size effect is structure, not arithmetic.
Why committees get this backwards
Geography is visible and emotionally salient — everyone knows rent in the city — while “we are now a $12M organization, not a $4M one” arrives gradually and shows up in no one’s commute. The filings say the salient argument is the small one: moving an organization across state lines changes expected officer pay far less than the growth it experienced over the same period. A board matching comparables should match budget band first, then sector, then location — and should treat any peer set matched on location alone as decorative.
The committee-room version of this finding
Committee practice tends to weight the visible dial. Cost-of-living arguments arrive attached to rents and relocation offers; the organization’s own growth arrives silently, a budget line at a time, and rarely triggers a pay conversation at all. The structural tension shows up when the hiring market and the size-matched data disagree — a candidate arriving from a larger organization, anchored to larger-organization pay. Nothing in §4958 forbids a board from paying toward the market it is actually hiring in; what the presumption’s documentation prong requires is that a deviation from the size-matched cohort be a recorded decision with a stated reason, not an unexamined concession (Treas. Reg. §53.4958-6). The filings’ message is one of proportion: a board that adjusts a benchmark by double digits for geography while leaving budget scale unexamined has the dials reversed.
Method and scope
Scope of every figure on this page: 732,319 Form 990 filings, tax years 2021–2025 (2023 is the last complete filing year; 2024 and 2025 are still filling), covering the 107 curated officer roles CauseComp publishes, filings with a known NTEE sector only. No cohort statistic below 20 filings is reported anywhere.
- (a) R² figures are descriptive shares of variance from categorical group means on log reported total compensation — observational structure, not causal effects of moving or re-missioning an organization.
- (b) Budget band is the organization's reported revenue banded into the ten bands CauseComp uses product-wide; band boundaries are part of what is being measured.
- (c) Factors overlap; the first-added/last-added bounds are reported precisely so no single ordering is mistaken for the truth.
- (d) Metro areas are absent by design — see the FAQ; the corpus geography is the filing state.
Frequently asked questions
Does this mean location doesn't matter?
It matters — state adds a measurable 4–7 points of explained variation — it is just the smallest of the three dials. A cohort matched on budget size and mismatched on state is far closer to right than the reverse.
Why measure on a log scale?
Pay differences compound multiplicatively — a 20% difference means something similar at $80,000 and $400,000 — and the log scale keeps the largest organizations from dominating the arithmetic.
Where do metro areas fit?
They don't appear here, deliberately: this analysis groups filings by state, and CauseComp's own metro adjustment is a wage calibration applied to a state-built cohort — not a metro-built peer set. Treating it as one would overclaim.
Free to cite with attribution. The Executive product builds the cohort in exactly this order — budget band first — and names the filers behind it.
Research from CauseComp, a service of RB Consulting Services, LLC. Provides data and documentation to support board deliberations — not legal advice.