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Random Matching Markets with Correlated Preferences

Bill Wang

Abstract

In the Gale-Shapley model of two-sided matching, it is well known that for generic preferences, the outcomes for each side can vary dramatically in the male-optimal vs. female-optimal stable matchings. In this paper, we show that under a widely used characterization of similarity in rankings, even a weak correlation in preferences guarantees assortative matching with high probability as the market size tends to infinity. It follows that the men's average ranking of women and the women's average ranking of men are asymptotically equivalent in all stable matchings with high probability, as long as the market imbalance is not too extreme.

Random Matching Markets with Correlated Preferences

Abstract

In the Gale-Shapley model of two-sided matching, it is well known that for generic preferences, the outcomes for each side can vary dramatically in the male-optimal vs. female-optimal stable matchings. In this paper, we show that under a widely used characterization of similarity in rankings, even a weak correlation in preferences guarantees assortative matching with high probability as the market size tends to infinity. It follows that the men's average ranking of women and the women's average ranking of men are asymptotically equivalent in all stable matchings with high probability, as long as the market imbalance is not too extreme.

Paper Structure

This paper contains 6 sections, 6 theorems, 26 equations.

Key Result

Lemma 3.1

For every $j\in\{1,\ldots,s\}$, let $\pi_{j}\sim F_{\phi,t}$ independently. If $s\leq O(t^{z})$ for some $z\in\mathbb{R}_{+}$ and $d=c\log{t}$, where $c>-(z+1)/\log{\phi}$, then

Theorems & Definitions (11)

  • Lemma 3.1
  • proof
  • Lemma 3.2
  • Proposition 3.3
  • proof
  • Theorem 3.4
  • proof
  • Corollary 3.5
  • proof
  • Corollary 3.6
  • ...and 1 more