On Framework and Hybrid Auction Approach to the Spectrum
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The Evolution of U.S. Spectrum Values Over Time
The Evolution of U.S. Spectrum Values Over Time Michelle Connolly, Department of Economics, Duke University Nelson Sa, Department of Economics, Brandeis University Azeem Zaman, Department of Statistics, Harvard University Chris Roark, Department of Economics, University of Chicago Akshaya Trivedi, Trinity College, Duke University, Class of 2018 Working Paper Series 2018 | 121 Evolution of spectrum values 1 The Evolution of U.S. Spectrum Values Over Time Michelle Connolly1, Nelson Sá2, Azeem Zaman3, Chris Roark4, and Akshaya Trivedi5 February 13, 2018 Abstract We consider 1997 to 2015 data from FCC spectrum auctions related to cellular services to attempt to identify intrinsic spectrum values. Relative to previous literature, we control for license specific auction rules, and introduce measures to separate out technological progress that effectively reduces spectrum scarcity from progress that increases demand. Results confirm that technological changes have led to increases in the relative value of higher frequencies. Surprisingly, 47 percent of these licenses have been won by “small” bidders, representing 27 percent of the real value of these licenses. The use of bidding credits further appears to consistently reduce auction competition. Keywords: Spectrum, Spectrum Scarcity, Auctions, FCC, Auction Rules, Mobile Applications, Spectral Efficiency, Broadband Speeds, Closed Auctions, Small Bidders, “The Google Effect” JEL Codes: L5, O3, K2 1 Corresponding author: Michelle Connolly, [email protected], 213 Social Sciences, Box 90097, Department of Economics, Duke University, Durham, NC 27708. 2 Department of Economics, Brandeis University. 3 Department of Statistics, Harvard University. 4 Department of Economics, University of Chicago. 5 Trinity College, Duke University Class of 2018. We gratefully acknowledge the support of NSF grant 1314468. -
Robust Market Design: Information and Computation
ROBUST MARKET DESIGN: INFORMATION AND COMPUTATION A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Inbal Talgam-Cohen December 2015 Abstract A fundamental problem in economics is how to allocate precious and scarce resources, such as radio spectrum or the attention of online consumers, to the benefit of society. The vibrant research area of market design, recognized by the 2012 Nobel Prize in economics, aims to develop an engineering science of allocation mechanisms based on sound theoretical foundations. Two central assumptions are at the heart of much of the classic theory on resource allocation: the common knowledge and substitutability assumptions. Relaxing these is a prerequisite for many real-life applications, but involves significant informational and computational challenges. The starting point of this dissertation is that the computational paradigm offers an ideal toolbox for overcoming these challenges in order to achieve a robust and applicable theory of market design. We use tools and techniques from combinatorial optimization, randomized algo- rithms and computational complexity to make contributions on both the informa- tional and computational fronts: 1. We design simple mechanisms for maximizing seller revenue that do not rely on common knowledge of buyers' willingness to pay. First we show that across many different markets { including notoriously challenging ones in which the goods are heterogeneous { the optimal revenue benchmark can be surpassed or approximated by adding buyers or limiting supplies, and then applying the standard Vickrey (second-price) mechanism. We also show how, by removing the common knowledge assumption, the classic theory of revenue maximiza- tion expands to encompass the realistic but complex case in which buyers are interdependent in their willingness to pay. -
Putting Auction Theory to Work
Putting Auction Theory to Work Paul Milgrom With a Foreword by Evan Kwerel © 2003 “In Paul Milgrom's hands, auction theory has become the great culmination of game theory and economics of information. Here elegant mathematics meets practical applications and yields deep insights into the general theory of markets. Milgrom's book will be the definitive reference in auction theory for decades to come.” —Roger Myerson, W.C.Norby Professor of Economics, University of Chicago “Market design is one of the most exciting developments in contemporary economics and game theory, and who can resist a master class from one of the giants of the field?” —Alvin Roth, George Gund Professor of Economics and Business, Harvard University “Paul Milgrom has had an enormous influence on the most important recent application of auction theory for the same reason you will want to read this book – clarity of thought and expression.” —Evan Kwerel, Federal Communications Commission, from the Foreword For Robert Wilson Foreword to Putting Auction Theory to Work Paul Milgrom has had an enormous influence on the most important recent application of auction theory for the same reason you will want to read this book – clarity of thought and expression. In August 1993, President Clinton signed legislation granting the Federal Communications Commission the authority to auction spectrum licenses and requiring it to begin the first auction within a year. With no prior auction experience and a tight deadline, the normal bureaucratic behavior would have been to adopt a “tried and true” auction design. But in 1993 there was no tried and true method appropriate for the circumstances – multiple licenses with potentially highly interdependent values. -
Collusion and Equilibrium Selection in Auctions∗
Collusion and equilibrium selection in auctions∗ By Anthony M. Kwasnica† and Katerina Sherstyuk‡ Abstract We study bidder collusion and test the power of payoff dominance as an equi- librium selection principle in experimental multi-object ascending auctions. In these institutions low-price collusive equilibria exist along with competitive payoff-inferior equilibria. Achieving payoff-superior collusive outcomes requires complex strategies that, depending on the environment, may involve signaling, market splitting, and bid rotation. We provide the first systematic evidence of successful bidder collusion in such complex environments without communication. The results demonstrate that in repeated settings bidders are often able to coordinate on payoff superior outcomes, with the choice of collusive strategies varying systematically with the environment. Key words: multi-object auctions; experiments; multiple equilibria; coordination; tacit collusion 1 Introduction Auctions for timber, automobiles, oil drilling rights, and spectrum bandwidth are just a few examples of markets where multiple heterogeneous lots are offered for sale simultane- ously. In multi-object ascending auctions, the applied issue of collusion and the theoretical issue of equilibrium selection are closely linked. In these auctions, bidders can profit by splitting the markets. By acting as local monopsonists for a disjoint subset of the objects, the bidders lower the price they must pay. As opposed to the sealed bid auction, the ascending auction format provides bidders with the -
Auction Design and Tacit Collusion in FCC Spectrum Auctions
Auction Design and Tacit Collusion in FCC Spectrum Auctions Patrick Bajari and Jungwon Yeo October 19, 2008 Abstract The Federal Communications Commission (FCC) has used auctions to award spectrum since 1994. During this time period, the FCC has experimented with a variety of auctions rules including click box bidding and anonymous bidding. These rule changes make the actions of bidders less visible during the auction and also limit the set of bids which can be submitted by a bidder during a particular round. Economic theory suggests that tacit collusion may be more di¢ cult as a result. We examine this proposition using data from 4 auctions: the PCS C Block, Auction 35, the Advanced Wireless Service auction and the 700 Mhz auction. We examine the frequency of jump bids, retaliatory bids and straightforward bids across these auctions. While this simple descriptive exercise has a number of limitations, the data suggests that these rule changes did limit …rms ability to tacitly collude. Bajari: Univeristy of Minnesota and NBER, Yeo: Univeristy of Minnesota. Bajari would like to thank the National Science Foundation for generous research support. 1 1 Introduction Starting in 1994, the Federal Communications Commission (FCC) has used auctions to award spectrum. Prior to this time, the FCC used administrative hearings or lotteries to award licenses. Economic theory suggests that auctions should have a number of advantages over these earlier mechanisms. First, in many auction models, game theory predicts that the bidder which values the item most highly will win the auction. Therefore, the auction results in an e¢ cient allocation. -
Comments on the Above-Noted Consultation
Rogers Communications Inc. 333 Bloor Street East Toronto, Ontario M4W 1G9 Tel. (416) 935-7211 Fax (416) 935-7719 [email protected] Dawn Hunt Vice-President Regulatory July 15, 2009 Director, Spectrum Management Operations Radiocommunications and Broadcasting Regulatory Branch Industry Canada 300 Slater Street Ottawa ON K1A 0C8 Sent via email: [email protected] Re: Canada Gazette, Part I, April 11, 2009, Gazette Notice No. DGRB-001-09, Consultation on the Revisions to the Framework for Spectrum Auctions in Canada Rogers Communications Inc. (Rogers) appreciates the opportunity to provide reply comments on the above-noted consultation. The documents are being sent in Adobe Acrobat Professional Version 8.0. Operating System: Microsoft Windows XP. Yours very truly, Dawn Hunt Attach. WIRELESS DIGITAL CABLE INTERNET HOME PHONE VIDEO PUBLISHING BROADCASTING Reply Comments of Rogers Communications Inc. (Rogers) Canada Gazette Notice No. DGRB-001-09 Consultation on Revisions to the Framework for Spectrum Auctions in Canada Published in the Canada Gazette, Part I April 11, 2009 July 15, 2009 Rogers Communications Inc DGRB-001-09 July 15, 2009 Executive Summary Rogers Communications Inc. (“Rogers) provides the following reply to the submissions filed by other parties in response to Industry Canada’s Consultation on Revisions to the Framework for Spectrum Auctions in Canada (the “Consultation Paper”). In the Consultation Paper, the Department invited comments about spectrum management in Canada, including the use of auction types other than simultaneous multiple-round ascending (SMRA), the renewal of long-term licences, the research and development (R&D) condition of licence, and Tier areas for spectrum licensing. -
TOWARD a DIGITAL FUTURES FOUNDATION a Concept Note
April 2021 HOW TO CLOSE AMERICA'S DIGITAL EQUITY GAPS: TOWARD A DIGITAL FUTURES FOUNDATION A Concept Note Michael A. Calabrese & Lester M. Salamon A joint product of the Open Technology Institute at New America and the PtP Project PHILANTHROPICATION thru PRIVATIZATION PROJECT Calabrese and Salamon • How to Close America’s Digital Equity Gaps: Toward a Digital Futures Foundation • Page i Suggested Citation: Michael Calabrese and Lester M. Salamon, “How to Close America’s Digital Equity Gaps: Toward a Digital Futures Foundation,” A Concept Note. (Baltimore, MD: Johns Hopkins Center for Civil Society Studies and Washington, DC: New America, April 2021). Opinions expressed herein are solely the responsibility of the authors and may not necessarily be shared by New America, Johns Hopkins University, East-West Management Institute, or any other institutions with which the authors are associated, or that have supported their work. © Lester M. Salamon and Michael A. Calabrese, 2021 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Cover image adapted from rawpixel.com/Freepik Calabrese and Salamon • How to Close America’s Digital Equity Gaps: Toward a Digital Futures Foundation • Page ii TABLE OF CONTENTS INTRODUCTION 1 PART I 4 What is spectrum…and who owns it? PART II What is driving massive escalations 6 in the value of spectrum globally? PART III U.S. precedents for using proceeds from 8 the privatization of government assets PART IV The case for a private Digital Futures Foundation 11 financed by spectrum auction proceeds CONCLUSION 22 References 23 About the authors 25 bit.ly/PtP-Spectrum-Concept-Note Calabrese and Salamon • How to Close America’s Digital Equity Gaps: Toward a Digital Futures Foundation • Page 1 INTRODUCTION America’s digital ecosystem suffers from a serious set of imbalances. -
Spectrum Auctions from the Perspective of Matching
Spectrum Auctions from the Perspective of Matching Paul Milgrom and Andrew Vogt May 5, 2021 1 Introduction In July 1994, the United States Federal Communications Commission (FCC) conducted the first economist-designed auction for radio spectrum licenses. In the years since, governments worldwide have come to rely on auction mecha- nisms to allocate { and reallocate { rights to use electromagnetic frequencies. Over the same period, novel uses for spectrum have dramatically increased both the demand for licenses and auction prices, drawing continued attention to the nuances of spectrum markets and driving the development of spectrum auction design. In August 2017, the FCC completed the Broadcast Incentive Auction, a two-sided repurposing of an endogenously-determined quantity of spectrum that ranks among the most complex feats of economic engineering ever under- taken. The next generations of mobile telecommunications are poised to extend this growth, and to demand further innovation in the markets and algorithms that are used to assign spectrum licenses. What does all of this have to do with matching theory? Spectrum auctions differ from canonical matching problems in meaningful ways. Market designers often emphasize that a key element of matching markets is the presence of preferences on both sides of the market. In a marriage, for example, it is not enough that you choose your spouse; your spouse must also choose you. This two-sided choice structure applies also to matches between students and schools and between firms and workers, but not to matches between telecommunications companies and radio spectrum licenses. It is a different matching element that is often critically important in ra- dio spectrum auctions. -
Auction Theory
Auction Theory Jonathan Levin October 2004 Our next topic is auctions. Our objective will be to cover a few of the main ideas and highlights. Auction theory can be approached from different angles – from the perspective of game theory (auctions are bayesian games of incomplete information), contract or mechanism design theory (auctions are allocation mechanisms), market microstructure (auctions are models of price formation), as well as in the context of different applications (procure- ment, patent licensing, public finance, etc.). We’re going to take a relatively game-theoretic approach, but some of this richness should be evident. 1 The Independent Private Value (IPV) Model 1.1 A Model The basic auction environment consists of: Bidders i =1,...,n • Oneobjecttobesold • Bidder i observes a “signal” Si F ( ), with typical realization si • [s, s], and assume F is continuous.∼ · ∈ Bidders’ signals S1,...,Sn are independent. • Bidder i’s value vi(si)=si. • Given this basic set-up, specifying a set of auction rules will give rise to a game between the bidders. Before going on, observe two features of the model that turn out to be important. First, bidder i’s information (her signal) is independent of bidder j’s information. Second, bidder i’s value is independent of bidder j’s information – so bidder j’s information is private in the sense that it doesn’t affect anyone else’s valuation. 1 1.2 Vickrey (Second-Price) Auction In a Vickrey, or second price, auction, bidders are asked to submit sealed bids b1,...,bn. The bidder who submits the highest bid is awarded the object, and pays the amount of the second highest bid. -
Should First-Price Auctions Be Transparent?∗
Should First-Price Auctions be Transparent?∗ Dirk Bergemann† Johannes H¨orner‡ April 7, 2017 Abstract We investigate the role of market transparency in repeated first-price auctions. We consider a setting with independent private and persistent values. We analyze three distinct disclosure regimes regarding the bid and award history. In the minimal disclosure regime each bidder only learns privately whether he won or lost the auction. In equilibrium the allocation is efficient and the minimal disclosure regime does not give rise to pooling equilibria. In contrast, in disclosure settings where either all or only the winner’s bids are public, an inefficient pooling equilibrium with low revenues exists. ∗We gratefully acknowledge financial support from NSF SES 0851200 and ICES 1215808. We thank the co- editor, Phil Reny, and two anonymous referees, for helpful comments and suggestions. We are grateful to seminar participants at the NBER Market Design Meeting, University of Mannheim, University of Munich and the University of Pennsylvania for their constructive comments. Lastly, thanks to Yi Chen for excellent research assistance. †Department of Economics, Yale University, New Haven, CT 06511, [email protected] ‡Department of Economics, Yale University, New Haven, CT 06511, [email protected] 1 1 Introduction 1.1 Motivation Information revelation policies vary widely across auction formats. In the U.S. procurement context, as a consequence of the “Freedom of Information Act,” the public sector is generally subject to strict transparency requirements that require full disclosure of the identity of the bidders and the terms of each bid. In auctions of mineral rights to U.S. -
Sponsored Search Auctions: an Overview of Research with Emphasis on Game Theoretic Aspects
Sponsored Search Auctions: An Overview of Research with emphasis on Game Theoretic Aspects Patrick Maill´e∗ Evangelos Markakisy Maurizio Naldiz George D. Stamoulisy Bruno Tuffinx Abstract We provide a broad overview of the research that has been conducted until recently on the design of sponsored search auctions. We mainly focus on game theoretic and mechanism design aspects of these auctions, and we analyze the issues associated with each of the three participating entities, i.e., the search engine, the advertisers, and the users of the search engine, as well as their resulting behavior. Regarding the search engine, we overview the various mechanisms that have been proposed including the currently used GSP mechanism. The issues that are addressed include analysis of Nash equilibria and their performance, design of alternative mechanisms and aspects of competition among search engines. We then move on to the advertisers and discuss the problem of choosing a bidding strategy, given the mechanism of the search engine. Following this, we consider the end users and we examine how user behavior may create externalities and influence the performance of the advertisers. Finally, we also overview statistical methods for estimating modeling parameters that are of interest to the three entities. In each section, we point out interesting open problems and directions for future research. 1 Introduction Online advertising is a booming industry, accounting for a large percentage of the revenue generated by web services [51]. Online ads are essential to monetize valuable Internet services, offered for free to the general public, like search engines, blogs, and social networking sites; e.g. -
Lecture Note 11.Pdf
IEOR8100: Economics, AI, and Optimization Lecture Note 11: Introduction to Auctions Christian Kroer∗ March 30, 2020 1 Introduction In fair division we initially did not worry about the fact that we might not necessarily know the utility function ui of each agent. We briefly studied settings where agents may misreport their valuation in the context of dominant-resource fairness. In this lecture note we continue the study of settings where we will worry about whether agents tell the truth or not. The general study of this type of setting is called mechanism design. We will study the most classical mechanism-design setting: auctions. We will start by consid- ering single-item auctions: there is a single good for sale, and there is a set of n buyers, with each buyer having some value vi for the good. The goal will be to sell the item via a sealed-bid auction, which works as follows: 1. Each bidder i submits a bid bi ≥ 0, without seeing the bids of anyone else. 2. The seller decides who gets the good based on the submitted bids. 3. Each buyer i is charged a price pi which is a function of the bid vector b. A few things in our setup may seem strange. First, most people would not think of sealed bids when envisioning an auction. Instead, they typically envision what's called the English auction. In the English auction, bidders repeatedly call out increasing bids, until the bidding stops, at which point the highest bidder wins and pays their last bid. This auction can be conceptualized as having a price that starts at zero, and then rises continuously, with bidders dropping out as they become priced out.