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Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities

Author

Listed:
  • Jose H. Blanchet
  • Martin I. Reiman
  • Viragh Shah
  • Lawrence M. Wein
  • Linjia Wu

Abstract

We consider a matching market where buyers and sellers arrive according to independent Poisson processes at the same rate and independently abandon the market if not matched after an exponential amount of time with the same mean. In this centralized market, the utility for the system manager from matching any buyer and any seller is a general random variable. We consider a sequence of systems indexed by $n$ where the arrivals in the $n^{\mathrm{th}}$ system are sped up by a factor of $n$. We analyze two families of one-parameter policies: the population threshold policy immediately matches an arriving agent to its best available mate only if the number of mates in the system is above a threshold, and the utility threshold policy matches an arriving agent to its best available mate only if the corresponding utility is above a threshold. Using a fluid analysis of the two-dimensional Markov process of buyers and sellers, we show that when the matching utility distribution is light-tailed, the population threshold policy with threshold $\frac{n}{\ln n}$ is asymptotically optimal among all policies that make matches only at agent arrival epochs. In the heavy-tailed case, we characterize the optimal threshold level for both policies. We also study the utility threshold policy in an unbalanced matching market with heavy-tailed matching utilities and find that the buyers and sellers have the same asymptotically optimal utility threshold. We derive optimal thresholds when the matching utility distribution is exponential, uniform, Pareto, and correlated Pareto. We find that as the right tail of the matching utility distribution gets heavier, the threshold level of each policy (and hence market thickness) increases, as does the magnitude by which the utility threshold policy outperforms the population threshold policy.

Suggested Citation

  • Jose H. Blanchet & Martin I. Reiman & Viragh Shah & Lawrence M. Wein & Linjia Wu, 2020. "Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities," Papers 2002.03205, arXiv.org, revised Jun 2021.
  • Handle: RePEc:arx:papers:2002.03205
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    References listed on IDEAS

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    1. Baccara, Mariagiovanna & Lee, SangMok & Yariv, Leeat, 2020. "Optimal dynamic matching," Theoretical Economics, Econometric Society, vol. 15(3), July.
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    4. Gunter J. Hitsch & Ali Hortaçsu & Dan Ariely, 2010. "Matching and Sorting in Online Dating," American Economic Review, American Economic Association, vol. 100(1), pages 130-163, March.
    5. Nikhil Agarwal, 2015. "An Empirical Model of the Medical Match," American Economic Review, American Economic Association, vol. 105(7), pages 1939-1978, July.
    6. Donald Boyd & Hamilton Lankford & Susanna Loeb & James Wyckoff, 2013. "Analyzing the Determinants of the Matching of Public School Teachers to Jobs: Disentangling the Preferences of Teachers and Employers," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 83-117.
    7. Burak Büke & Hanyi Chen, 2017. "Fluid and diffusion approximations of probabilistic matching systems," Queueing Systems: Theory and Applications, Springer, vol. 86(1), pages 1-33, June.
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