Assignment Maximization

Mustafa O\u{g}uz Afacan, In\'acio B\'o and Bertan Turhan

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Abstract: We evaluate the goal of maximizing the number of individuals matched to acceptable outcomes. We show that it implies incentive, fairness, and implementation impossibilities. Despite that, we present two classes of mechanisms that maximize assignments. The first are Pareto efficient, and undominated -- in terms of number of assignments -- in equilibrium. The second are fair for unassigned students and assign weakly more students than stable mechanisms in equilibrium.

Date: 2020-12
New Economics Papers: this item is included in nep-des
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Journal Article: Assignment maximization (2023)
Working Paper: Assignment Maximization (2020)
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