Tiered Random Matching Markets: Rank is Proportional to Popularity

We study the stable marriage problem in two-sided markets with randomly generated preferences. We consider agents on each side divided into a constant number of "soft tiers", which intuitively indicate the quality of the agent. Specifically, every agent within a tier has the same public score, and agents on each side have preferences independently generated proportionally to the public scores of the other side. We compute the expected average rank which agents in each tier have for their partners in the men-optimal stable matching, and prove concentration results for the average rank in asymptotically large markets. Furthermore, we show that despite having a significant effect on ranks, public scores do not strongly influence the probability of an agent matching to a given tier of the other side. This generalizes results of [Pittel 1989] which correspond to uniform preferences. The results quantitatively demonstrate the effect of competition due to the heterogeneous attractiveness of agents in the market, and we give the first explicit calculations of rank beyond uniform markets.

[1]  L. B. Wilson An analysis of the stable marriage assignment algorithm , 1972 .

[2]  Günter J. Hitsch,et al.  Matching and Sorting in Online Dating , 2008 .

[3]  Boris G. Pittel,et al.  On Likely Solutions of the Stable Matching Problem with Unequal Numbers of Men and Women , 2017, Math. Oper. Res..

[4]  Vassilis G. Papanicolaou,et al.  The Coupon Collector's Problem Revisited: Asymptotics of the Variance , 2012, Advances in Applied Probability.

[5]  Linda Cai,et al.  The Short-Side Advantage in Random Matching Markets , 2019, ArXiv.

[6]  B. Pittel On Likely Solutions of a Stable Marriage Problem , 1992 .

[7]  Itai Ashlagi,et al.  Stability in Large Matching Markets with Complementarities , 2014, Oper. Res..

[8]  Boris G. Pittel,et al.  The Average Number of Stable Matchings , 1989, SIAM J. Discret. Math..

[9]  M. Braverman,et al.  Communication Requirements and Informative Signaling in Matching Markets , 2017, EC.

[10]  Rajeev Motwani,et al.  Stable husbands , 1990, SODA '90.

[11]  L. B. Wilson,et al.  Stable marriage assignment for unequal sets , 1970 .

[12]  Nicole Immorlica,et al.  Incentives in Large Random Two-Sided Markets , 2015, TEAC.

[13]  Claire Mathieu,et al.  Two-sided matching markets with correlated random preferences have few stable pairs , 2019 .

[14]  Éva Tardos,et al.  Effect of selfish choices in deferred acceptance with short lists , 2017, ArXiv.

[15]  Sheldon M. Ross Introduction to Probability Models. , 1995 .

[16]  Yannai A. Gonczarowski Manipulation of stable matchings using minimal blacklists , 2013, EC.

[17]  Peter Coles,et al.  Optimal Truncation in Matching Markets , 2013, Games Econ. Behav..

[18]  Yash Kanoria,et al.  Which Random Matching Markets Exhibit a Stark Effect of Competition? , 2020, ArXiv.

[19]  Jacob D. Leshno,et al.  Unbalanced Random Matching Markets: The Stark Effect of Competition , 2017, Journal of Political Economy.

[20]  SangMok Lee,et al.  Incentive Compatibility of Large Centralized Matching Markets , 2017 .

[21]  L. S. Shapley,et al.  College Admissions and the Stability of Marriage , 2013, Am. Math. Mon..

[22]  Robert K. Brayton On the asymptotic behavior of the number of trials necessary to complete a set with random selection , 1963 .