Optimal Incentive-Compatible Assignments with Endogenous School Priorities

Federico Echenique and Juan S. Pereyra

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Abstract: We study whether a planner can favor students at schools they rank more highly while preserving truthful reporting. The standard implementation of the deferred acceptance (DA) algorithm is typically not the solution. With interior cutoffs, DA with multiple tie-breaking (DA-MTB) solves the planner's optimization problem if and only if the planner's payoff from a school assignment is independent of the students' preferences. This is typically not the case, and strict incentive compatibility under DA-MTB leaves room for improvement via preference-dependent priority adjustments. We characterize optimal rank-dependent cutoff adjustments in a two-school model and show that, in a many-school environment, near-optimal approximately incentive-compatible assignments can be chosen with small support (so each type of student may only attend a small number of schools).

Date: 2026-10
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