Witness outlines $15,000-per-student foundation model and key trade-offs for Vermont school funding

Montpelier — At an April 17 joint meeting of the Vermont Senate Education and Finance committees, education finance researcher Dr. Tim Colby told lawmakers a student-based “foundation” funding formula would set the state’s funding obligation up front and allocate dollars to districts based on enrolled students and specific cost adjustments.

The model Colby described establishes a base per‑student funding amount — the state’s defined obligation — and then adds defined dollar cost adjustments for student and school factors that drive additional spending. “The student based funding formula is a fundamental shift from what we have right now,” Colby said, adding that the approach makes spending “predictable and transparent” for districts and the state.

Colby said his team used an education cost‑function approach, paired with professional‑judgment panels for context, and updated models through recent school years to estimate a base per‑student state funding level of about $15,000. He said the analysis then produced dollar adjustments (which translate into weights relative to that base) for factors including economic disadvantage, English‑learner status, special education needs, small‑school/sparsity effects and school size.

Why it matters: A foundation formula explicitly defines the state’s per‑student obligation and then directs additional funds where students’ needs or school contexts require them. That differs from Vermont’s current system, which Colby described as equalizing districts’ budgets after they are set (tax‑capacity equalization). Under the proposed model, the state sets the base amount first and the dollars follow students.

Key findings and design choices discussed

• Base amount and method: Colby said the education cost‑function estimate of the base per‑student amount in the updated Vermont analysis is about $15,000 (presented to the committees as $15,000.03). He described the education cost function as a statistical model that estimates the efficient level of spending tied to student outcomes, and said his team paired that with professional‑judgment panels to clarify how funds would be used in practice.

• Example cost adjustments (state dollars only): Colby presented an additional state‑level cost for a student experiencing economic disadvantage of roughly $15,334 (state dollars). He also reported large variation in English‑learner costs by proficiency: about $31,657 for students at the lowest proficiency level and roughly $17,800 for students at higher proficiency levels, illustrating that a single average EL weight can obscure important differences.

• Special education and federal dollars: Colby noted the analysis separates the state obligation from federal funding; federal special‑education dollars are uneven across districts and typically account for a minority of IEP costs (he said federal funding is “on average, only about 10%” for those services). He referenced national and state special‑education cost studies used to estimate differential IEP costs by disability category.

• Transportation, capital and tuition students: Colby recommended treating transportation and school construction (capital and debt service) outside the operating base in many cases. Vermont currently operates transportation as a categorical program; Colby said the state’s geographic variability makes folding transportation into a uniform base difficult. He also noted the policy choices needed for applying the formula to tuitioned students (students sent by towns to nonoperating schools): whether towns may pay tuition amounts different from the base and whether weights apply to tuition payments.

• Weights vs. categorical grants: Colby explained trade‑offs between weights (multiplicative factors tied to the base) and categorical grants (explicit dollar amounts with programmatic guardrails). Weights produce fungible dollars tied to students; categorical grants allow more precise restrictions on how funds are used but add administrative burden.

• Indexing/inflation: The team inflated results to current dollars using the Bureau of Labor Statistics Employment Cost Index (ECI) and recommended an inflation index tied to labor/compensation rather than a product price index, since most K‑12 costs are labor‑related.

Comparisons with other approaches

Committee members raised an evidence‑based study circulated earlier (participants referenced a house/agency analysis with a lower base in the $12,000–$13,000 range). Colby cautioned that evidence‑based models use a different set of explicit assumptions (a prototypical school with specified staffing ratios), producing numbers that reflect those assumptions rather than current, observed spending patterns. “Those are really apples and oranges,” he said, adding that the education cost‑function result represents the most efficient level of spending given current governance and school structures, while evidence‑based approaches can represent a desired or aspirational service package.

Questions and concerns from senators

Several legislators asked how the formula would keep dollars close to the students who generate them in large, multi‑school districts and whether smaller or rural schools would be “rewarded” for inefficiencies. Colby said policymakers can design categorical eligibility or regulatory guardrails to ensure funds reach students or to limit levy authority above the base. He also stressed that the cost adjustments in the statistical model reflect economies of scale and sparsity; a small remote school may receive additional dollars for unavoidable fixed costs and limited contract options.

No formal votes or committee decisions were taken during the session. The hearing functioned as a briefing and Q&A on methodology, choices and implications for future statute and rulemaking.

Ending

Colby closed by reiterating design choices remain policy decisions for the Legislature — including whether to treat transportation and capital outside the base, how to apply weights to tuition students, and which inflation measure to use — and said the state should regularly update any formula (every three to four years was discussed) so weights and bases reflect changing data and practice. “The base amount is usually named in statute,” he said, and “the escalator matters.”