The Ability of Dutch Foreclosure Auctions in Maximizing Seller Revenue
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Uncoercible E-Bidding Games
Uncoercible e-Bidding Games M. Burmester ([email protected])∗ Florida State University, Department of Computer Science, Tallahassee, Florida 32306-4530, USA E. Magkos ([email protected])∗ University of Piraeus, Department of Informatics, 80 Karaoli & Dimitriou, Piraeus 18534, Greece V. Chrissikopoulos ([email protected]) Ionian University, Department of Archiving and Library Studies, Old Palace Corfu, 49100, Greece Abstract. The notion of uncoercibility was first introduced in e-voting systems to deal with the coercion of voters. However this notion extends to many other e- systems for which the privacy of users must be protected, even if the users wish to undermine their own privacy. In this paper we consider uncoercible e-bidding games. We discuss necessary requirements for uncoercibility, and present a general uncoercible e-bidding game that distributes the bidding procedure between the bidder and a tamper-resistant token in a verifiable way. We then show how this general scheme can be used to design provably uncoercible e-auctions and e-voting systems. Finally, we discuss the practical consequences of uncoercibility in other areas of e-commerce. Keywords: uncoercibility, e-bidding games, e-auctions, e-voting, e-commerce. ∗ Research supported by the General Secretariat for Research and Technology of Greece. c 2002 Kluwer Academic Publishers. Printed in the Netherlands. Uncoercibility_JECR.tex; 6/05/2002; 13:05; p.1 2 M. Burmester et al. 1. Introduction As technology replaces human activities by electronic ones, the process of designing electronic mechanisms that will provide the same protec- tion as offered in the physical world becomes increasingly a challenge. In particular with Internet applications in which users interact remotely, concern is raised about several security issues such as privacy and anonymity. -
MICROECONOMICS and POLICY ANALYSIS - U8213 Professor Rajeev H
MICROECONOMICS AND POLICY ANALYSIS - U8213 Professor Rajeev H. Dehejia Class Notes - Spring 2001 Auctions Wednesday, February 14 Reading: Handout, Thaler, Milgram There are two basic forms of auctions: Sealed bid submissions and open bids. In a sealed bid auction individuals do not know what others are bidding. Two types of Sealed Bid Auctions: 1st Price sealed bid auction: The highest bid submitted will be the winning bid. The winner pays what he/she bid. 2nd Price sealed bid auction: Everyone submits sealed bids and the winner is the one who submits the highest bid BUT the price paid by the winner is the 2nd highest bid submitted. Two types of open auctions: English auction: The bidding starts low and incrementally rises until someone is the highest bidder and no one is willing to outbid the highest bidder. Dutch auction: The price starts very high and is keeps going down until someone bids. The first person to bid wins. Why Study Auctions? 1) Auctions can be an efficient method of valuing goods. For example: rights to air waves, signals and bandwidth. The government auctioned off parts of the spectrum in anticipation of new technology. The auctions were appealing because well- structured auctions get people to reveal the true valuation of the good. The company (private entity) actually ends up paying to the government what the good is worth to them. It turned out with these auctions that the willingness to pay for a slice of the spectrum, as revealed by the auction outcome, was much higher than expected. 2) Procurement: Governments and entities want to procure goods and services at the lowest possible price (like an auction in reverse). -
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. -
Lecture Notes
601.436/636 Algorithmic Game Theory Lecturer: Michael Dinitz Topic: Online Auctions Date: 4/28/20 Scribe: Michael Dinitz 24.1 Introduction So far all of our mechanism have been \one-shot": we run an auction by soliciting bids and then deciding on an outcome and prices. This is intuitively a pretty good model of what we think of as an \auction". But let's think of another setting: we're selling items in a store. Then players will enter our store, make us an offer, and leave the store. Clearly if we sell an item to a player then we cannot later sell the same item to someone else, and if a player leaves the store then we cannot afterwards sell them the item. So our decisions are irrevocable. This is a classical setting for online algorithms, so today we'll be considering online mechanisms which combine online algorithms with incentives. 24.2 Example Suppose that we're selling two identical items. Each bidder wants one item (they don't care which) and has a valuation for how much they value an item (the same value for both, since they're identical), but also has an arrival and departure time. Suppose that there are three bidders. Bidder 1 has a valuation of 100, arrival time of noon (12pm), and departure time of 2pm. Bidder 2 has valuation 80, arrival time of noon, and departure time of 2pm. Bidder 3 has valuation of 60, arrival time of 1pm, and departure time of 2pm. If we were in the old setting, without arrival and departure times, it's pretty easy to use VCG to figure out what to do. -
Shill Bidding in English Auctions
Shill Bidding in English Auctions Wenli Wang Zoltan´ Hidvegi´ Andrew B. Whinston Decision and Information Analysis, Goizueta Business School, Emory University, Atlanta, GA, 30322 Center for Research on Electronic Commerce, Department of MSIS, The University of Texas at Austin, Austin, TX 78712 ¡ wenli [email protected] ¡ [email protected] [email protected] First version: January, 2001 Current revision: September 6, 2001 Shill bidding in English auction is the deliberate placing bids on the seller’s behalf to artificially drive up the price of his auctioned item. Shill bidding has been known to occur in auctions of high-value items like art and antiques where bidders’ valuations differ and the seller’s payoff from fraud is high. We prove that private- value English auctions with shill bidding can result in a higher expected seller profit than first and second price sealed-bid auctions. To deter shill bidding, we introduce a mechanism which makes shill bidding unprofitable. The mechanism emphasizes the role of an auctioneer who charges the seller a commission fee based on the difference between the winning bid and the seller’s reserve. Commission rates vary from market to market and are mathematically determined to guarantee the non-profitability of shill bidding. We demonstrate through examples how this mechanism works and analyze the seller’s optimal strategy. The Internet provides auctions accessible to the general pub- erature on auction theories, which currently are insufficient to lic. Anyone can easily participate in online auctions, either as guide online practices. a seller or a buyer, and the value of items sold ranges from a One of the emerging issues is shill bidding, which has become few dollars to millions. -
How Auctions Amplify House-Price Fluctuations
How Auctions Amplify House-Price Fluctuations Alina Arefeva∗ Wisconsin School of Business, University of Wisconsin-Madison Download current version at http://www.aarefeva.com/ First draft: May 29, 2015 This draft: June 12, 2019 Abstract I develop a dynamic search model of the housing market where house prices are deter- mined in auctions rather than by Nash bargaining as in the housing search model from the literature. The model with auctions generates fluctuations between booms and busts. Dur- ing the boom multiple buyers compete for one house, while in the bust buyers are choosing among several houses. The model improves on the performance of the model with Nash bargaining by producing highly volatile house prices which helps to solve the puzzle of ex- cess volatility of house prices. Higher volatility arises because of the competition between buyers with heterogeneous values. With heterogeneous valuations, the price determination becomes important for the quantitative properties of the model. With Nash bargaining, the buyer is chosen randomly among all interested buyers. Then the average of buyers' house values determines the house price. In the auction model, the buyer is chosen by the maximum bid among all interested buyers, so the highest value determines the house prices. During the boom, the highest values increase more than the average values, making the sales price more volatile. This high volatility is constrained efficient since the equilibrium in the model decentralizes the solution of the social planner problem, constrained by the search frictions. Keywords: housing, real estate, volatility, search and matching, pricing, liquidity, Nash bargaining, auctions, bidding wars JEL codes: E30, C78, D44, R21, E44, R31, D83 ∗I am grateful for the support and guidance of my advisors Robert Hall, Monika Piazzesi, Pablo Kurlat. -
English Versus Vickrey Auctions with Loss Averse Bidders
English versus Vickrey Auctions with Loss Averse Bidders Jonas von Wangenheim School of Business & Economics Discussion Paper Economics 2019/1 English versus Vickrey Auctions with Loss Averse Bidders∗ Jonas von Wangenheimyz December 19, 2018 Abstract Evidence suggests that people evaluate outcomes relative to expecta- tions. I analyze this expectation-based loss aversion [K}oszegiand Rabin (2006, 2009)] in the context of dynamic and static auctions, where the ref- erence point is given by the (endogenous) equilibrium outcome. If agents update their reference point during the auction, the arrival of informa- tion crucially affects equilibrium behavior. Consequently, I show that| even with independent private values|the Vickrey auction yields strictly higher revenue than the English auction, violating the well known revenue equivalence. Thus, dynamic loss aversion offers a novel explanation for empirically observed differences between these auction formats. Keywords: Vickrey auction, English auction, expectation-based loss aver- sion, revenue equivalence, dynamic loss aversion, personal equilibrium JEL classification: D03, D44 ∗I thank Yves Breitmoser, Fran¸coiseForges, Matthias Hammer, Paul Heidhues, Radosveta Ivanova-Stenzel, Johannes Johnen, Thomas Mariotti, Antonio Rosato, Thomas Schacherer, Ran Spiegler, Roland Strausz, and Georg Weizs¨acker for helpful comments, as well as participants at the 11th World Congress of the Econometric Society (Montreal), the 2015 EEA conference (Mannheim), the Applied Theory Workshop at Toulouse School of Economics, the 2016 EARIE conference (Lisbon), the CRC conference in Berlin, the ZEW Research Seminar, and the 2017 Annual Conference of the Verein f¨urSocialpolitik (Vienna). I gratefully acknowledge financial support of the German Research Foundation through CRC TRR 190 and RTG 1659. -
Bimodal Bidding in Experimental All-Pay Auctions
Games 2013, 4, 608-623; doi:10.3390/g4040608 OPEN ACCESS games ISSN 2073-4336 www.mdpi.com/journal/games Article Bimodal Bidding in Experimental All-Pay Auctions Christiane Ernst 1 and Christian Thöni 2,* 1 Alumna of the London School of Economics, London WC2A 2AE, UK; E-Mail: [email protected] 2 Walras Pareto Center, University of Lausanne, Lausanne-Dorigny CH-1015, Switzerland * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +41-21-692-28-43; Fax: +41-21-692-28-45. Received: 17 July 2013; in revised form 19 September 2013 / Accepted: 19 September 2013 / Published: 11 October 2013 Abstract: We report results from experimental first-price, sealed-bid, all-pay auctions for a good with a common and known value. We observe bidding strategies in groups of two and three bidders and under two extreme information conditions. As predicted by the Nash equilibrium, subjects use mixed strategies. In contrast to the prediction under standard assumptions, bids are drawn from a bimodal distribution: very high and very low bids are much more frequent than intermediate bids. Standard risk preferences cannot account for our results. Bidding behavior is, however, consistent with the predictions of a model with reference dependent preferences as proposed by the prospect theory. Keywords: all-pay auction; prospect theory; experiment JEL Code: C91; D03; D44; D81 1. Introduction Bidding behavior in all-pay auctions has so far only received limited attention in empirical auction research. This might be due to the fact that most of the applications of auction theory do not involve the all-pay rule. -
Game Theory 2021
More Mechanism Design Game Theory 2021 Game Theory 2021 Ulle Endriss Institute for Logic, Language and Computation University of Amsterdam Ulle Endriss 1 More Mechanism Design Game Theory 2021 Plan for Today In this second lecture on mechanism design we are going to generalise beyond the basic scenario of auctions|as much as we can manage: • Revelation Principle: can focus on direct-revelation mechanisms • formal model of direct-revelation mechanisms with money • incentive compatibility of the Vickrey-Clarke-Groves mechanism • other properties of VCG for special case of combinatorial auctions • impossibility of achieving incentive compatibility more generally Much of this is also (somewhat differently) covered by Nisan (2007). N. Nisan. Introduction to Mechanism Design (for Computer Scientists). In N. Nisan et al. (eds.), Algorithmic Game Theory. Cambridge University Press, 2007. Ulle Endriss 2 More Mechanism Design Game Theory 2021 Reminder Last time we saw four auction mechanisms for selling a single item: English, Dutch, first-price sealed-bid, Vickrey. The Vickrey auction was particularly interesting: • each bidder submits a bid in a sealed envelope • the bidder with the highest bid wins, but pays the price of the second highest bid (unless it's below the reservation price) It is a direct-revelation mechanism (unlike English and Dutch auctions) and it is incentive-compatible, i.e., truth-telling is a dominant strategy (unlike for Dutch and FPSB auctions). Ulle Endriss 3 More Mechanism Design Game Theory 2021 The Revelation Principle Revelation Principle: Any outcome that is implementable in dominant strategies via some mechanism can also be implemented by means of a direct-revelation mechanism making truth-telling a dominant strategy. -
Umi-Umd-1475.Pdf (1.983Mb)
ABSTRACT Title of Dissertation / Thesis: PERFORMANCE AND ANALYSIS OF SPOT TRUCK -LOAD PROCUREMENT MARKETS USING SEQUENTIAL AUCTIONS Miguel Andres Figliozzi, Ph.D., 2004 Dissertation / Thesis Directed By: Professor Hani Mahmassani, Civil and Env ironmental Engineering Department Competition in a transportation marketplace is studied under different supply/demand conditions, auction formats, and carriers’ behavioral assumptions. Carriers compete in a spot truck -load procurement market (TLPM) using sequential auctions. Carrier participation in a TLPM requires the ongoing solution of two distinct problems: profit maximization problem (chose best bid) and fleet management problem (best fleet assignment to serve acquired shipments). Sequential aucti ons are used to model an ongoing transportation market, where carrier competition is used to study carriers’ dynamic vehicle routing technologies and decision making processes. Given the complexity of the bidding/fleet management problem, carriers can tack le it with different levels of sophistication. Carriers’ decision making processes and rationality/bounded rationality assumptions are analyzed. A framework to study carrier behavior in TL sequential auctions is presented. Carriers’ behavior is analyzed as a function of fleet management technology, auction format, carrier bounded rationality, market settings, and decision making complexity. The effects of fleet management technology asymmetries on a competitive marketplace are studied. A methodology to com pare dynamic fleet management technologies -
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. -
Introduction to Auctions Protocols Revenue and Optimal Auctions Common Value Auctions
Auctions Kate Larson Introduction Auction Protocols Common Auction Introduction to Auctions Protocols Revenue and Optimal Auctions Common Value Auctions Vulnerabilities Kate Larson in Auctions Beyond Single Cheriton School of Computer Science Item Auctions University of Waterloo Summary Outline Auctions Kate Larson 1 Introduction Introduction Auction Protocols 2 Auction Protocols Common Auction Protocols Common Auction Protocols Revenue and Optimal Auctions Common Value Revenue and Optimal Auctions Auctions Common Value Auctions Vulnerabilities in Auctions Beyond Single 3 Vulnerabilities in Auctions Item Auctions Summary 4 Beyond Single Item Auctions 5 Summary Auctions Auctions Kate Larson Methods for allocating goods, tasks, resources,... Introduction Participants Auction auctioneer Protocols Common Auction bidders Protocols Revenue and Optimal Auctions Enforced agreement between auctioneer and the Common Value Auctions winning bidder(s) Vulnerabilities in Auctions Easily implementable (e.g. over the Internet) Beyond Single Conventions Item Auctions Summary Auction: one seller and multiple buyers Reverse auction: one buyer and multiple sellers Todays lecture will discuss the theory in the context of auctions, but this applies to reverce auctions as well (at least in 1-item settings). Auction Settings Auctions Kate Larson Introduction Private value: the value of the good depends only on Auction the agent’s own preferences Protocols e.g a cake that is not resold of showed off Common Auction Protocols Revenue and Common value: an agent’s value of an item is Optimal Auctions Common Value determined entirely by others’ values (valuation of the Auctions item is identical for all agents) Vulnerabilities in Auctions e.g. treasury bills Beyond Single Item Auctions Correlated value (interdependent value): agent’s Summary value for an item dpends partly on its own preferences and partly on others’ value for it e.g.