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 GB

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

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.

BibTeX: Download