We study decentralized college admissions with uncertain student preferences. Colleges strategically admit students likely to be overlooked by competitors. Highly ranked students may receive fewer admissions or have a higher chance of receiving no admissions than those ranked below. When students’ attributes are multidimensional, colleges avoid head-on competition by placing excessive weight on school-specific attributes such as essays. Restricting the number of applications or wait-listing alleviates enrollment uncertainty, but the outcomes are inefficient and unfair. A centralized matching via Gale and Shapley’s deferred acceptance algorithm attains efficiency and fairness but may make some colleges worse off than under decentralized matching
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