Fact check: How do state-level definitions of ‘welfare’ (TANF, SNAP administrative, Medicaid, SSI) change rankings of highest and lowest per-capita spenders?

1. Why line-drawing on “welfare” changes the leaderboard — the mechanics that flip state ranks

Counting only state budget outlays versus combined state-and-federal program totals produces different leaders because programs have distinct funding flows and accounting rules: Medicaid is predominantly federal matching with sizable state administrative and waiver spending, SNAP is federally funded but can be affected by contingency reserves and emergency cost shifts, TANF mixes federal block grants with state maintenance-of-effort and flexible state spending, and SSI includes federally administered payments plus state supplements in some states. The FY2023 state welfare spending dataset shows California and Alaska at dollar extremes when measuring state spending alone, but adding federal flows or program-specific spikes — for instance, an influx of SNAP state liabilities under the 2025 OBBBA or paused federal payments — will elevate states with large safety-net caseloads or strong supplements ^{[1] [3] [4]}. Differences in whether researchers include TANF administrative costs or only cash assistance further reshuffle rankings because TANF cash benefits are uneven — some states increased benefit levels in 2022–23 while benefits still sit below 60% of the poverty line, meaning administrative-heavy states can appear higher per capita if administrative spending is included ^{[5] [6]}.

2. SNAP disruptions and policy changes: a sudden reshuffling possibility for 2025–26 lists

Policy changes in 2025 have made SNAP a pivot for rankings because the OBBBA reallocation and a government funding impasse shifted sizable costs toward states and introduced payment pauses; states with large SNAP caseloads like California and high-participation-rate states like New Mexico can see per-capita obligations spike if contingency or emergency federal funds are not counted as federal supports. Analyses show the OBBBA could increase state SNAP expenditures by anywhere from 50% to multiple-fold for affected states, and the October 2025 lapse affected roughly 42 million recipients, creating ambiguous month-to-month accounting that researchers must decide how to treat — as federal relief, state liability, or gap — and those choices change per-capita rankings materially ^{[3] [7] [8]}. The legal uncertainty over the SNAP contingency reserve — where CBPP and GAO interpretations contrast with the Administration’s public position — also matters: treating the reserve as unavailable makes the state share look larger, while recognizing it as available keeps states lower in per-capita rankings ^{[4] [8]}.

3. Medicaid billing, managed care churn, and how program integrity events alter spending profiles

Medicaid spending rankings are vulnerable to episodic events like fraud audits, managed-care plan closures, or major reimbursement reforms because such events can pause payments, accelerate state-only adjustments, or increase administrative and corrective expenditures, which temporarily raise or lower per-capita figures depending on accounting treatment. Recent audits and pauses in Minnesota and the collapse of a New York managed long-term care plan demonstrate that state-level interruptions can reduce reported outlays in one fiscal window and spike audit-related costs in another, moving states up or down comparative lists if analysts use cash-flow versus accrual accounting ^{[9] [10]}. The Medicaid financing debate — including work-requirement pushes and eligibility changes covered in Medicaid Watch — further complicates longitudinal comparisons because eligibility tightening lowers caseload-driven spending but increases per-recipient administrative cost allocations, again altering per-capita rankings depending on the definition chosen ^[11].

4. TANF and SSI: small programs with outsized effects on per-capita rankings in certain states

TANF cash assistance, while small in aggregate compared with Medicaid and SNAP, varies dramatically by state and can disproportionately affect per-capita rankings in low-population or high-benefit states; state TANF benefit ranges from roughly $204 to $1,370 monthly for a family of three, participation rates are low (fewer than 21% of eligible families accessed cash in 2021), and many states increased TANF levels in 2022–23 — all facts that change per-capita measures when counts include TANF cash or administrative spending ^{[5] [6]}. SSI’s federal-plus-state supplement structure similarly causes variance: states that add supplements such as Colorado raise per-recipient totals and therefore per-capita welfare spending if SSI is counted, while excluding state supplements or treating SSI as pure federal transfer produces different rankings; the data on top states for combined Social Security and SSI benefits show notable state variation relevant to any comprehensive ranking exercise ^{[12] [13]}.

5. Bottom line for analysts: specify inclusion rules and present alternate rankings

To produce meaningful rankings, researchers must explicitly state whether they include federal benefits as state spending, how they treat contingency or paused SNAP funding, whether TANF administrative costs are counted, and how Medicaid managed-care anomalies are handled; transparent, alternative scenarios — state-only spending, combined state+federal program totals, and program-by-program inclusion/exclusion — will reveal which states’ positions are fragile and which are robust. Existing FY2020–2023 datasets give baseline pictures (state welfare spending ranks), but 2025 policy shocks and program-specific events demonstrate that a single ranking is misleading without scenario sensitivity analysis; presenting at least three ranked tables or narrative scenarios tied to clearly stated accounting rules is required to show the true range of possible top and bottom per-capita spenders ^{[2] [14] [3]}.