A<scp>uctioning the</scp> A<scp>irwave</scp>s: T<scp>he</scp> C<scp>ontest</scp> f<scp>or</scp> B<scp>roadband pcs</scp> S<scp>pectru</scp>m

Chakravorti, Bhaskar; Sharkey, William W.; Spiegel, Yossi; Wilkie, Simon

doi:10.1111/j.1430-9134.1995.00345.x

Cited by 30 publications

(11 citation statements)

References 24 publications

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“…Below I summarize several of the important issues. Although spectrum auction design is discussed elsewhere (McMillan 1994, Milgrom 1995, and Chakravorti et al, 1995, I review the issues here, since understanding the issues will be helpful in assessing the spectrum auctions.…”

Section: Auction Designmentioning

confidence: 99%

The FCC Spectrum Auctions: An Early Assessment

Cramton¹

1997

Journal of Economics &Amp; Management Strategy

203

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This paper analyzes six spectrum auctions conducted by the Federal Communications Commission (FCC) from July 1994 to May 1996. These auctions were simultaneous multipleround auctions in which collections of licenses were auctioned simultaneously. This auction form proved remarkably successful. Similar items sold for similar prices and bidders successfully formed efficient aggregations of licenses. Bidding behavior differed substantially in the auctions. The extent of bidder competition and price uncertainty played an important role in determining behavior. Bidding credits and installment payments also played a major role in several of the auctions. JEL No.: D44 (Auctions), L96 (Telecommunications)

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Section: Auction Designmentioning

confidence: 99%

The FCC Spectrum Auctions: An Early Assessment

Cramton¹

1997

Journal of Economics &Amp; Management Strategy

203

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“…At the heart of a smart market is a constrained optimization, in which bids are selected while a range of constraints are satisfied. Smart markets are operating for radio spectrum rights (Chakravorti et al 1995), natural gas (McCabe et al 1991, electricity (Hogan et al 1996), course registration (Graves et al 1993), and even school catering (Epstein et al 2002). Murphy et al (2000) proposed a smart market for water, giving a highly simplified (indeed, trivial) example with a pipe network, used in lab experiments.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

A Smart Market for Impervious Cover

Raffensperger

Cochrane

2010

Water Resour Manage

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When farmland or undeveloped ground is covered over, runoff can cause environmental damage and flood risk. Policymakers want to compare the economic improvement of new development to the costs produced by the associated environmental impacts. In this paper, we propose a smart market in impervious cover. A smart market is a periodic auction which is cleared by an optimization model, a linear program (LP) in this case. The LP constraint coefficients come from a hydrological model. The LP objective coefficients come from users' bids. To operate the auction, local government would appoint an auction manager, who would be responsible for maintaining the hydrological model and the LP, for operating the auction, and for maintaining the desired environmental standards. At regular intervals, the auction manager would accept bids over the internet, solve the corresponding LP, and announce the results. By LP duality, the smart market prices impervious cover at the opportunity cost to society, adjusted for location, the sensitivity of environmental features, and the incremental value of the development as indicated by bids. This design uses relevant hydrological information, and accepts community input on the desired environmental standards (avoiding the tragedy of the commons). The auction creates incentives to remove impervious cover, especially near environmentally sensitive areas. The proposed system nearly eliminates transaction costs associated with trading development rights.

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“…This process is known as bid shading. Bid shading is relatively new to online advertising, but it has been used in auctions from other industries [7,8,11,20].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions

Zhou

Pan

et al. 2021

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &Amp; Data Mining

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Since 2019, most ad exchanges and sell-side platforms (SSPs), in the online advertising industry, shifted from second to first price auctions. Due to the fundamental difference between these auctions, demand-side platforms (DSPs) have had to update their bidding strategies to avoid bidding unnecessarily high and hence overpaying. Bid shading was proposed to adjust the bid price intended for second-price auctions, in order to balance cost and winning probability in a first-price auction setup. In this study, we introduce a novel deep distribution network for optimal bidding in both open (non-censored) and closed (censored) online first-price auctions. Offline and online A/B testing results show that our algorithm outperforms previous state-of-art algorithms in terms of both surplus and effective cost per action (eCPX ) metrics. Furthermore, the algorithm is optimized in run-time and has been deployed into VerizonMedia DSP as production algorithm, serving hundreds of billions of bid requests per day. Online A/B test shows that advertiser's ROI are improved by +2.4%, +2.4%, and +8.6% for impression based (CPM), click based (CPC), and conversion based (CPA) campaigns respectively. CCS CONCEPTS• Applied computing → Online auctions; • Information systems → Display advertising; • Computing methodologies → Machine learning algorithms.

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Auctioning the Airwaves: The Contest for Broadband pcs Spectrum

Cited by 30 publications

References 24 publications

The FCC Spectrum Auctions: An Early Assessment

The FCC Spectrum Auctions: An Early Assessment

A Smart Market for Impervious Cover

An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions

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