Paul Milgrom and Robert Wilson's Contributions To
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Introduction to Computational Social Choice
1 Introduction to Computational Social Choice Felix Brandta, Vincent Conitzerb, Ulle Endrissc, J´er^omeLangd, and Ariel D. Procacciae 1.1 Computational Social Choice at a Glance Social choice theory is the field of scientific inquiry that studies the aggregation of individual preferences towards a collective choice. For example, social choice theorists|who hail from a range of different disciplines, including mathematics, economics, and political science|are interested in the design and theoretical evalu- ation of voting rules. Questions of social choice have stimulated intellectual thought for centuries. Over time the topic has fascinated many a great mind, from the Mar- quis de Condorcet and Pierre-Simon de Laplace, through Charles Dodgson (better known as Lewis Carroll, the author of Alice in Wonderland), to Nobel Laureates such as Kenneth Arrow, Amartya Sen, and Lloyd Shapley. Computational social choice (COMSOC), by comparison, is a very young field that formed only in the early 2000s. There were, however, a few precursors. For instance, David Gale and Lloyd Shapley's algorithm for finding stable matchings between two groups of people with preferences over each other, dating back to 1962, truly had a computational flavor. And in the late 1980s, a series of papers by John Bartholdi, Craig Tovey, and Michael Trick showed that, on the one hand, computational complexity, as studied in theoretical computer science, can serve as a barrier against strategic manipulation in elections, but on the other hand, it can also prevent the efficient use of some voting rules altogether. Around the same time, a research group around Bernard Monjardet and Olivier Hudry also started to study the computational complexity of preference aggregation procedures. -
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. -
Stable Matching: Theory, Evidence, and Practical Design
THE PRIZE IN ECONOMIC SCIENCES 2012 INFORMATION FOR THE PUBLIC Stable matching: Theory, evidence, and practical design This year’s Prize to Lloyd Shapley and Alvin Roth extends from abstract theory developed in the 1960s, over empirical work in the 1980s, to ongoing efforts to fnd practical solutions to real-world prob- lems. Examples include the assignment of new doctors to hospitals, students to schools, and human organs for transplant to recipients. Lloyd Shapley made the early theoretical contributions, which were unexpectedly adopted two decades later when Alvin Roth investigated the market for U.S. doctors. His fndings generated further analytical developments, as well as practical design of market institutions. Traditional economic analysis studies markets where prices adjust so that supply equals demand. Both theory and practice show that markets function well in many cases. But in some situations, the standard market mechanism encounters problems, and there are cases where prices cannot be used at all to allocate resources. For example, many schools and universities are prevented from charging tuition fees and, in the case of human organs for transplants, monetary payments are ruled out on ethical grounds. Yet, in these – and many other – cases, an allocation has to be made. How do such processes actually work, and when is the outcome efcient? Matching theory The Gale-Shapley algorithm Analysis of allocation mechanisms relies on a rather abstract idea. If rational people – who know their best interests and behave accordingly – simply engage in unrestricted mutual trade, then the outcome should be efcient. If it is not, some individuals would devise new trades that made them better of. -
Regulatory Growth Theory
Regulatory Growth Theory Danxia Xie Tsinghua University December 31, 2017 Abstract This research explores and quantifies the downside of innovations, especially the negative externality of an innovation interacting with the stock of existing innovations. Using two novel datasets, I find that the number of varieties of innovation risks is quadratic in the varieties of innovations that caused them. Based on this new empirical fact, I develop a Regulatory Growth Theory: a new growth model with innovation-induced risks and with a regulator. I model both the innovation risk generating structure and the regulator’sendoge- nous response. This new theory can help to interpret several empirical puzzles beyond the explanatory power of existing models of innovations: (1) skyrocketing expected R&D cost per innovation and (2) exponentially increasing regulation over time. Greater expenditures on regulation and corporate R&D are required to assess the net benefit of an innovation because of “Risk Externality”: negative interaction effects between innovations. The rise of regulation versus litigation, and broader implications for regulatory reform are also discussed. Address: Institute of Economics, Tsinghua University, China. The author’s e-mail address is [email protected]. I am grateful to Gary Becker, Casey Mulligan, Randy Kroszner, Tom Philipson, and Eric Posner for invaluable advice. Also thank Ufuk Akcigit, Olivier Blanchard, Will Cong, Steve Davis, Jeffrey Frankel, Matt Gentzkow, Yehonatan Givati, Michael Greenstone, Lars Hansen, Zhiguo He, Chang- Tai Hsieh, Chad Jones, Greg Kaplan, John List, Bob Lucas, Joel Mokyr, Roger Myerson, Andrei Shleifer, Hugo Sonnenschein, Nancy Stokey, and Hanzhe Zhang for very helpful suggestions and discussions. An early version was presented at Econometric Society 2015 World Congress, Montreal. -
The Portfolio Optimization Performance During Malaysia's
Modern Applied Science; Vol. 14, No. 4; 2020 ISSN 1913-1844 E-ISSN 1913-1852 Published by Canadian Center of Science and Education The Portfolio Optimization Performance during Malaysia’s 2018 General Election by Using Noncooperative and Cooperative Game Theory Approach Muhammad Akram Ramadhan bin Ibrahim1, Pah Chin Hee1, Mohd Aminul Islam1 & Hafizah Bahaludin1 1Department of Computational and Theoretical Sciences Kulliyyah of Science International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia Correspondence: Pah Chin Hee, Department of Computational and Theoretical Sciences, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia. Received: February 10, 2020 Accepted: February 28, 2020 Online Published: March 4, 2020 doi:10.5539/mas.v14n4p1 URL: https://doi.org/10.5539/mas.v14n4p1 Abstract Game theory approach is used in this study that involves two types of games which are noncooperative and cooperative. Noncooperative game is used to get the equilibrium solutions from each payoff matrix. From the solutions, the values then be used as characteristic functions of Shapley value solution concept in cooperative game. In this paper, the sectors are divided into three groups where each sector will have three different stocks for the game. This study used the companies that listed in Bursa Malaysia and the prices of each stock listed in this research obtained from Datastream. The rate of return of stocks are considered as an input to get the payoff from each stock and its coalition sectors. The value of game for each sector is obtained using Shapley value solution concepts formula to find the optimal increase of the returns. The Shapley optimal portfolio, naive diversification portfolio and market portfolio performances have been calculated by using Sharpe ratio. -
Loss Aversion and Sunk Cost Sensitivity in All-Pay Auctions for Charity: Experimental Evidence∗
Loss Aversion and Sunk Cost Sensitivity in All-pay Auctions for Charity: Experimental Evidence∗ Joshua Fostery Economics Department University of Wisconsin - Oshkosh August 30, 2017 Abstract All-pay auctions have demonstrated an extraordinary ability at raising money for charity. One mechanism in particular is the war of attrition, which frequently generates revenue well beyond what is theoretically predicted with rational bidders. However, what motivates the behavioral response in bidders remains unclear. By imposing charity auction incentives in the laboratory, this paper uses controlled experiments to consider the effects of loss aversion and sunk cost sensitivity on bidders’ willingness to contribute. The results indicate that revenues in incremental bidding mechanisms, such as the war of attrition, rely heavily on bidders who are sunk cost sensitive. It is shown this behavioral response can be easily curbed with a commitment device which drastically lowers contributions below theoretical predictions. A separate behavioral response due to loss aversion is found in the sealed-bid first-price all-pay auction, which reduces bidders’ willingness to contribute. These findings help explain the inconsistencies in revenues from previous all-pay auction studies and indicate a mechanism preference based on the distribution of these behavioral characteristics. Keywords: Auctions, Market Design, Charitable Giving JEL Classification: C92, D03, D44, D64 ∗I would like to thank Cary Deck, Amy Farmer, Jeffrey Carpenter, Salar Jahedi, Li Hao, and seminar participants at the University of Arkansas, ESA World Meetings, ESA North America Meetings, and the SEA Annual Meetings for their helpful comments at various stages of the development of this project. yContact the author at [email protected]. -
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. -
Paul Milgrom Wins the BBVA Foundation Frontiers of Knowledge Award for His Contributions to Auction Theory and Industrial Organization
Economics, Finance and Management is the seventh category to be decided Paul Milgrom wins the BBVA Foundation Frontiers of Knowledge Award for his contributions to auction theory and industrial organization The jury singled out Milgrom’s work on auction design, which has been taken up with great success by governments and corporations He has also contributed novel insights in industrial organization, with applications in pricing and advertising Madrid, February 19, 2013.- The BBVA Foundation Frontiers of Knowledge Award in the Economics, Finance and Management category goes in this fifth edition to U.S. mathematician Paul Milgrom “for his seminal contributions to an unusually wide range of fields of economics including auctions, market design, contracts and incentives, industrial economics, economics of organizations, finance, and game theory,” in the words of the prize jury. This breadth of vision encompasses a business focus that has led him to apply his theories in advisory work with governments and corporations. Milgrom (Detroit, 1942), a professor of economics at Stanford University, was nominated for the award by Zvika Neeman, Head of The Eitan Berglas School of Economics at Tel Aviv University. “His work on auction theory is probably his best known,” the citation continues. “He has explored issues of design, bidding and outcomes for auctions with different rules. He designed auctions for multiple complementary items, with an eye towards practical applications such as frequency spectrum auctions.” Milgrom made the leap from games theory to the realities of the market in the mid 1990s. He was dong consultancy work for Pacific Bell in California to plan its participation in an auction called by the U.S. -
Fact-Checking Glen Weyl's and Stefano Feltri's
The Market Design Community and the Broadcast Incentive Auction: Fact-Checking Glen Weyl’s and Stefano Feltri’s False Claims By Paul Milgrom* June 3, 2020 TV Station Interference Constraints in the US and Canada In a recent Twitter rant and a pair of subsequent articles in Promarket, Glen Weyl1 and Stefano Feltri2 invent a conspiratorial narrative according to which the academic market design community is secretive and corrupt, my own actions benefitted my former business associates and the hedge funds they advised in the 2017 broadcast incentive auction, and the result was that far too little TV spectrum was reassigned for broadband at far too little value for taxpayers. The facts bear out none of these allegations. In fact, there were: • No secrets: all of Auctionomics’ communications are on the public record, • No benefits for hedge funds: the funds vigorously opposed Auctionomics’ proposals, which reduced their auction profits, • No spectrum shortfalls: the number of TV channels reassigned was unaffected by the hedge funds’ bidding, and • No taxpayer losses: the money value created for the public by the broadband spectrum auction was more than one hundred times larger than the alleged revenue shortfall. * Paul Milgrom, the co-founder and Chairman of Auctionomics, is the Shirley and Leonard Ely Professor of Economics at Stanford University. According to his 2020 Distinguished Fellow citation from the American Economic Association, Milgrom “is the world’s leading auction designer, having helped design many of the auctions for radio spectrum conducted around the world in the last thirty years.” 1 “It Is Such a Small World: The Market-Design Academic Community Evolved in a Business Network.” Stefano Feltri, Promarket, May 28, 2020. -
Introduction to Computational Social Choice Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D
Introduction to Computational Social Choice Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia To cite this version: Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia. Introduction to Computational Social Choice. Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia, Handbook of Computational Social Choice, Cambridge University Press, pp.1-29, 2016, 9781107446984. 10.1017/CBO9781107446984. hal-01493516 HAL Id: hal-01493516 https://hal.archives-ouvertes.fr/hal-01493516 Submitted on 21 Mar 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Introduction to Computational Social Choice Felix Brandta, Vincent Conitzerb, Ulle Endrissc, J´er^omeLangd, and Ariel D. Procacciae 1.1 Computational Social Choice at a Glance Social choice theory is the field of scientific inquiry that studies the aggregation of individual preferences towards a collective choice. For example, social choice theorists|who hail from a range of different disciplines, including mathematics, economics, and political science|are interested in the design and theoretical evalu- ation of voting rules. Questions of social choice have stimulated intellectual thought for centuries. Over time the topic has fascinated many a great mind, from the Mar- quis de Condorcet and Pierre-Simon de Laplace, through Charles Dodgson (better known as Lewis Carroll, the author of Alice in Wonderland), to Nobel Laureates such as Kenneth Arrow, Amartya Sen, and Lloyd Shapley. -
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. -
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.