Two-Sided Matching Markets with Correlated Random Preferences
Hugo Gimbert, Claire Mathieu, Simon Mauras

TL;DR
This paper investigates how correlations in preference lists affect the manipulability of stable matching algorithms, moving beyond worst-case analysis by modeling preferences probabilistically.
Contribution
It introduces a probabilistic model capturing preference correlations and analyzes the impact on approximate manipulability of stable matchings.
Findings
Preferences with correlated lists influence manipulability.
Approximate stability can be achieved under certain correlation structures.
The model extends understanding of stability beyond worst-case scenarios.
Abstract
Stable matching in a community consisting of men and women is a classical combinatorial problem that has been the subject of intense theoretical and empirical study since its introduction in 1962 in a seminal paper by Gale and Shapley, who designed the celebrated ``deferred acceptance'' algorithm for the problem. In the input, each participant ranks participants of the opposite type, so the input consists of a collection of permutations, representing the preference lists. A bipartite matching is unstable if some man-woman pair is blocking: both strictly prefer each other to their partner in the matching. Stability is an important economics concept in matching markets from the viewpoint of manipulability. The unicity of a stable matching implies non-manipulability, and near-unicity implies limited manipulability, thus these are mathematical properties related to the quality of stable…
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Taxonomy
TopicsGame Theory and Voting Systems · Names, Identity, and Discrimination Research · Game Theory and Applications
