Dynamic Mechanism Design in the Field

14 Pages Posted: 24 Apr 2017 Last revised: 21 Feb 2018

See all articles by Vahab Mirrokni

Vahab Mirrokni

Google Inc.

Renato Paes Leme

Google Inc.

Rita Ren

Google Inc., New York

Song Zuo

Google Inc., New York

Date Written: February 21, 2017

Abstract

Dynamic mechanisms are a powerful technique in designing revenue-maximizing repeated auctions. Despite their strength, these types of mechanisms have not been widely adopted in practice for several reasons, e.g., for their complexity, and for their sensitivity to the accuracy of predicting buyers' value distributions. In this paper, we aim to address these shortcomings and develop simple dynamic mechanisms that can be implemented efficiently, and provide theoretical guidelines for decreasing the sensitivity of dynamic mechanisms on prediction accuracy of buyers' value distributions. We prove that the dynamic mechanism we propose is provably dynamic incentive compatible, and introduce a notion of buyers' regret in dynamic mechanisms, and show that our mechanism achieves bounded regret while improving revenue and social welfare compared to a static reserve pricing policy. Finally, we confirm our theoretical analysis via an extensive empirical study of our dynamic auction on real data sets from online adverting. For example, we show our dynamic mechanisms can provide a 17% revenue lift with relative regret less than 0.2%.

Keywords: Dynamic Mechanism Design, Dynamic Auctions, Dynamic Second Price Auction, Bank Account Mechanisms, Internet Advertising

JEL Classification: D44, C73, D82

Suggested Citation

Mirrokni, Vahab and Paes Leme, Renato and Ren, Rita and Zuo, Song, Dynamic Mechanism Design in the Field (February 21, 2017). Available at SSRN: https://ssrn.com/abstract=2956713 or http://dx.doi.org/10.2139/ssrn.2956713

Vahab Mirrokni

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Renato Paes Leme

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Rita Ren

Google Inc., New York ( email )

111 8th Ave
New York, NY 10011
United States

Song Zuo (Contact Author)

Google Inc., New York ( email )

111 8th Ave
New York, NY 10011
United States

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