Assignment Maximization

Mustafa Oguz Afacan, Inacio Bo and Bertan Turhan

ISU General Staff Papers from Iowa State University, Department of Economics

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. We provide comparisons with well-known mechanisms through computer simulations. Those show that the difference in number of matched agents between the proposed mechanisms and others in the literature is large and significant.

Date: 2020-01-09
New Economics Papers: this item is included in nep-des and nep-mic
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Related works:
Journal Article: Assignment maximization (2023)
Working Paper: Assignment Maximization (2020)
Working Paper: Assignment maximization (2018)
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