A pre-registered RCT in the 2025-26 NYC high school match found nudged applicants significantly more likely to rank a recommended program, with weaker evidence of increased matching

matching-marketsrecommender-systemsschool-choicenycrandomized-controlled-trialarxiv

In partnership with NYC Public Schools, Chiang, Peng, Lichtenstein, McDaniel, O'Neil, Thomas, Wright, Kleinberg, Tardos & Garg sent personalized nudge emails (two batches, Oct 30 and Nov 19, 2025) to eligible applicants from middle schools that historically sent few students to high-performing nearby programs, recommending programs within 45 minutes of home where the student held a "High" predicted offer likelihood (allocated via the paper's capacity-constrained method). Randomization was at the middle-school level (0%, 50%, or 100% treatment intensity): "We ended up with 822 control and 444 treatment students."

The pre-registered analysis found a statistically significant effect on application behavior: "Among treatment applicants, 16.4% ranked at least one program they were nudged to at least somewhere on their list; among control applicants, 10.5% ranked a program they would have been nudged to," with the regression itself reporting "treatment significantly increased the likelihood of ranking a recommended program (𝛽ˆ=0.561, SE=0.219, 𝑝=0.011)."

The paper separately reports a weaker signal on matching outcomes — applicants were more likely to actually match to a nudged program, not merely rank one: "In terms of match outcomes, 5.6% of treatment applicants matched to a nudged program, and 3.3% of control applicants matched to a program they would have been nudged to," with a point estimate the authors themselves describe as suggestive rather than conventionally significant: "There is also suggestive evidence that the treatment increased matches to recommended programs (𝛽ˆ=0.643, SE=0.356, 𝑝=0.071)." These figures were initially recorded here with a sourcing gap (numbers asserted in the capture's prose without a directly quoted sentence); the 2026-10-12 cross-model audit read §6.2 directly against a re-fetched copy matching the capture's sha and captured the verbatim sentences above, answering question-verify-nyc-school-nudge-rct-match-rate-figure-quote.