Smart Lotteries in School Choice: Ex-ante Pareto-Improvement with Ex-post Stability

TL;DR

This paper introduces a 'smart lottery' mechanism for school choice that improves efficiency in probabilistic assignments while maintaining ex-post stability, using advanced optimization techniques to handle computational complexity.

Contribution

It proposes a novel stable lottery mechanism that enhances ex-ante efficiency in school choice, ensuring ex-post stability and Pareto improvements in expectation.

Findings

Welfare gains are significantly larger than standard methods.

The mechanism achieves ex-ante Pareto improvements without losing stability.

Advanced optimization techniques effectively solve the NP-hard problem.

Abstract

In a typical school choice application, the students have strict preferences over the schools while the schools have coarse priorities over the students based on their distance and their enrolled siblings. The outcome of a centralized admission mechanism is then usually obtained by the Deferred Acceptance (DA) algorithm with random tie-breaking. Therefore, every possible outcome of this mechanism is a stable solution for the coarse priorities that will arise with certain probability. This implies a probabilistic assignment, where the admission probability for each student-school pair is specified. In this paper, we propose a new efficiency-improving stable `smart lottery' mechanism. We aim to improve the probabilistic assignment ex-ante in a stochastic dominance sense, while ensuring that the improved random matching is still ex-post stable, meaning that it can be decomposed into stable matchings regarding the original coarse priorities. Therefore, this smart lottery mechanism can provide a clear Pareto-improvement in expectation for any cardinal utilities compared to the standard DA with lottery solution, without sacrificing the stability of the final outcome. We show that although the underlying computational problem is NP-hard, we can solve the problem by using advanced optimization techniques such as integer programming with column generation. We conduct computational experiments on generated and real instances. Our results show that the welfare gains by our mechanism are substantially larger than the expected gains by standard methods that realize efficiency improvements after ties have already been broken.