Optimal pricing for MHR distributions
Giannakopoulos Y, Zhu K (2018)
Publication Type: Conference contribution, Original article
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 11316 LNCS
Pages Range: 154-167
Conference Proceedings Title: Proceedings of the 14th Conference on Web and Internet Economics (WINE)
Event location: Oxford
ISBN: 9783030046118
DOI: 10.1007/978-3-030-04612-5_11
Open Access Link: https://arxiv.org/abs/1810.00800v1
Abstract
We study the performance of anonymous posted-price selling mechanisms for a standard Bayesian auction setting, where n bidders have i.i.d. valuations for a single item. We show that for the natural class of Monotone Hazard Rate (MHR) distributions, offering the same, take-it-or-leave-it price to all bidders can achieve an (asymptotically) optimal revenue. In particular, the approximation ratio is shown to be 1+O(ln ln n/ ln n), matched by a tight lower bound for the case of exponential distributions. This improves upon the previously best-known upper bound of e/(e - 1) ≈ for the slightly more general class of regular distributions. In the worst case (over n), we still show a global upper bound of 1.35. We give a simple, closed-form description of our prices which, interestingly enough, relies only on minimal knowledge of the prior distribution, namely just the expectation of its second-highest order statistic.
Authors with CRIS profile
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
Georgia Institute of Technology
United States (USA) (US)
Germany (DE)
Georgia Institute of Technology
United States (USA) (US)
How to cite
APA:
Giannakopoulos, Y., & Zhu, K. (2018). Optimal pricing for MHR distributions. In Tobias Harks, George Christodoulou (Eds.), Proceedings of the 14th Conference on Web and Internet Economics (WINE) (pp. 154-167). Oxford, GB: Springer Verlag.
MLA:
Giannakopoulos, Yiannis, and Keyu Zhu. "Optimal pricing for MHR distributions." Proceedings of the 14th International Conference on Web and Internet Economics, WINE 2018, Oxford Ed. Tobias Harks, George Christodoulou, Springer Verlag, 2018. 154-167.
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