School Spending and Free Meals

What the evidence says

Universal free meal programs (UFM, and its main implementation mechanism, the Community Eligibility Provision or CEP) show a consistent, positive relationship with academic performance and program participation across the strongest-tier evidence here. Schwartz (2019) finds UFM raises math scores by as much as 0.083 standard deviations and ELA scores by 0.059 standard deviations for non-poor students, with smaller but still positive effects for poor students (0.032 SD math, 0.027 SD ELA). The same study finds a dose-response relationship at the individual level: each additional school lunch eaten every two weeks raises test scores by roughly 0.08 SD in math and 0.07 SD in ELA, tying the achievement effect directly to meal consumption rather than to UFM policy status alone. A separate systematic review (Cohen 2021) corroborates the direction, finding CEP-specific studies produced a 0.06 SD gain in math among elementary students. Participation effects are large and consistent: UFM raises lunch participation by 11.0 percentage points for non-poor students and 5.4 points for poor students (Schwartz), and CEP adoption raises district-wide lunch participation by 6.58 points and breakfast participation by 7.72 points (Rothbart 2022).

On diet and weight outcomes, the evidence again points one direction. Schwartz finds no evidence that UFM increases obesity, overweight probability, or average BMI, and reports some evidence of improved weight outcomes for non-poor students specifically. Cohen's review reports the same absence of adverse BMI effects and notes several reviewed studies detected a protective effect on BMI. On diet quality, Brazendale (2017) finds school lunch participants have higher Healthy Eating Index scores for milk and vegetables and lower scores for saturated fat and sodium on school days than on weekends, and that eating lunch at school produces higher overall diet quality than eating lunch brought from home. Cohen's review adds magnitude to this: universal free meals that include lunch are associated with 16% higher vegetable intake, 48% higher fish intake, and 30% lower saturated fat intake. Cohen also reports a modeling estimate that universal free meals increase household food security, with simulation modeling projecting a 3.73% increase in students becoming food secure, and notes an association between universal free meals and improved household income, attributed to families no longer paying for meals — though this is flagged as low confidence in both direction and magnitude.

On the funding side, the evidence traces where meal-program money actually goes. CEP adoption decreases local school food service revenue by $23.90 per pupil but increases federal food reimbursement revenue by $72.96 per pupil — more than offsetting the local loss — with no measured effect on state food revenue (Rothbart). Total food service expenditure rises by $38.23 per pupil, less than the revenue increase, and average food service deficits shrink by about $14 per pupil from a 2012 baseline deficit of $60 per pupil. Rothbart finds no measured effect of CEP on instructional expenditures, meaning the meal-program funding shift does not appear to draw from or add to classroom budgets. Title I funding shows a related but distinct pattern over time: a one-dollar increase in Title I per pupil raises total district revenue by $0.98 in the first year, but by the third year that same dollar produces only a statistically insignificant $0.12 increase in instructional spending per pupil — the funding effect on classroom-level spending fades rather than compounding.

Broader school finance reforms (SFRs), a different and larger lever than either meal-program or Title I funding, produce sharp, immediate, and sustained spending increases in low-income districts: absolute per-pupil funding rises by about $1,200 annually, with districts directing "substantial" amounts toward instructional spending, reducing class size (measured via increased teachers per pupil), and directing a large share — roughly half of the relative funding increase — toward capital outlays (Lafortune 2018). These spending increases translate into achievement gains of 0.12 to 0.24 standard deviations per $1,000 in additional annual per-pupil spending, but the same study finds no discernible effect of SFRs on statewide achievement gaps between high- and low-income or minority and white students — the spending narrows within-district outcomes without measurably narrowing state-level gaps.

One study in this set examines school choice rather than school spending policy: Muralidharan (2015) finds that a voucher program covering private school fees, books, and uniforms did not provide any allowance in place of the free midday meals that public schools provide, and that voucher-winning households showed no significant change in household education spending or student homework time — suggesting whatever test-score effects a voucher program produces (if any) come from the school itself rather than compensating household behavior.

Where the evidence splits

CEP's effect on school food deficits reverses by district type. On average, CEP adoption reduces food service deficits by about $14 per pupil from a $60 per pupil baseline, because federal revenue gains exceed expenditure increases in most districts. But in rural districts specifically, the deficit grows by roughly $30 per pupil instead of shrinking. Rothbart (2022) explains the reversal: rural districts had a larger share of students paying for meals before CEP, so they lose more local revenue when CEP eliminates that revenue stream, and CEP also increases rural personnel food-service expenditures in a way not seen in metro or town districts.

Cohen (2021) reports a split by meal type within the same review: studies of universal free meal programs that included free lunch found positive associations with diet quality, food security, and academic performance, while studies examining universal free breakfast alone found mixed results on those same outcomes. The stated explanatory factor is which meal the program covers — lunch inclusion versus breakfast-only.

Cohen (2021) also reports that findings on school attendance were "similarly mixed" across the reviewed studies, citing both a 0.24 percentage point increase among low-income students and a 3.5 percentage point reduction in low attendance in some studies, without consistent results across the literature. The source does not state what distinguishes the studies that found an effect from those that did not — the split is unexplained by the sources on this page.

Thresholds and dose-response

An additional school lunch eaten every two weeks increases test scores by roughly 0.08 standard deviations in math and 0.07 standard deviations in ELA (Schwartz 2019) — an individual-level dose-response rate distinct from the aggregate UFM policy effect.

Each additional $1,000 per pupil in annual school spending is associated with an achievement gain of between 0.12 and 0.24 standard deviations (Lafortune 2018).

Title I funding shows a size change over time: a one-dollar per-pupil increase raises total district revenue by $0.98 in the first year following census updating, but the same one-dollar increase produces only a statistically insignignificant $0.12 increase in instructional spending per pupil by the third year (Gordon 2003) — the effect on classroom spending shrinks and loses significance as the funding ages.

Open empirical questions

• No source here measures long-run outcomes (adult earnings, health, educational attainment) from universal free meal programs or school finance reforms — all effect sizes are short- or medium-run test scores, participation rates, or spending shares.
• No source establishes why breakfast-only universal meal programs produce mixed diet-quality, food-security, and academic results while lunch-inclusive programs produce consistently positive ones — only that the split exists.
• No source quantifies the total taxpayer cost of CEP or UFM adoption relative to the measured academic or health benefits, so no cost-per-SD-gained or cost-per-participation-point figure can be drawn from these claims.
• No source explains what drives the mixed attendance findings under universal free meals — which student or district characteristics predict an attendance gain versus no effect.