Adverse Selection and Auction Design for Internet Display Advertising

Author:

Arnosti Nick1,Beck Marissa2,Milgrom Paul3

Affiliation:

1. Department of Management Science and Engineering, Stanford University, 475 Via Ortega, Stanford, CA 94305 (email: )

2. Charles River Associates, 5335 College Ave., Suite 26, Oakland, CA 94618 (email: )

3. Stanford University, 579 Serra Mall, Stanford, CA 94305 (email: )

Abstract

We model an online display advertising environment in which “performance” advertisers can measure the value of individual impressions, whereas “brand” advertisers cannot. If advertiser values for ad opportunities are positively correlated, second-price auctions for impressions can be inefficient and expose brand advertisers to adverse selection. Bayesian-optimal auctions have other drawbacks: they are complex, introduce incentives for false-name bidding, and do not resolve adverse selection. We introduce “modified second bid” auctions as the unique auctions that overcome these disadvantages. When advertiser match values are drawn independently from heavy-tailed distributions, a modified second bid auction captures at least 94.8 percent of the first-best expected value. In that setting and similar ones, the benefits of switching from an ordinary second-price auction to the modified second bid auction may be large, and the cost of defending against shill bidding and adverse selection may be low. (JEL D44, D82, L86, M37)

Publisher

American Economic Association

Subject

Economics and Econometrics

Cited by 31 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Privacy and Polarization: An Inference-Based Framework;SSRN Electronic Journal;2024

2. Generative AI-Empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses;IEEE Journal of Selected Topics in Signal Processing;2023-09

3. The Early Impact of GDPR Compliance on Display Advertising: The Case of an Ad Publisher;Journal of Marketing Research;2023-06-23

4. Generative AI-empowered Effective Physical-Virtual Synchronization in the Vehicular Metaverse;2023 IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom);2023-06

5. Near-Optimal Experimental Design Under the Budget Constraint in Online Platforms;Proceedings of the ACM Web Conference 2023;2023-04-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3