A Primer on Auction Design, Management, and Strategy∗
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FERC Scarf-Nov-11-2003-Latest
Efficient Market-Clearing Prices in Markets with Nonconvexities Richard P. O’Neill a Paul M. Sotkiewicz b Benjamin F. Hobbs c Michael H. Rothkopf d William R. Stewart, Jr. e December, 2000; Revised November, 2003 Abstract This paper addresses the existence of market clearing prices and the economic interpretation of strong duality for integer programs in the economic analysis of markets with nonconvexities (indivisibilities). Electric power markets in which nonconvexities arise from the operating characteristics of generators motivate our analysis; however, the results presented here are general and can be applied to other markets in which nonconvexities are important. We show that the optimal solution to a linear program that solves the mixed integer program has dual variables that: (1) have the traditional economic interpretation as prices; (2) explicitly price integral activities; and (3) clear the market in the presence of nonconvexities. We then show how this methodology can be used to interpret the solutions to nonconvex problems such as the problem discussed by Scarf (1994). Economics, Equilibrium Pricing; MIP models of markets, MIP Applications a Chief Economic Advisor, Federal Energy Regulatory Commission. b Public Utility Research Center, University of Florida. c Department of Geography and Environmental Engineering, The Johns Hopkins University. d Department of Management Science and Information Systems and RUTCOR, Rutgers University. e School of Business, College of William and Mary. 1 I. Introduction Scarf (1990, 1994) describes most markets in today's advanced economies as having considerable indivisibilities (nonconvexities). For example, firms must make discrete decisions on whether to invest in a new project or when to start-up a production process. -
Obviousness Around the Clock
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Breitmoser, Yves; Schweighofer-Kodritsch, Sebastian Working Paper Obviousness around the clock WZB Discussion Paper, No. SP II 2019-203 Provided in Cooperation with: WZB Berlin Social Science Center Suggested Citation: Breitmoser, Yves; Schweighofer-Kodritsch, Sebastian (2019) : Obviousness around the clock, WZB Discussion Paper, No. SP II 2019-203, Wissenschaftszentrum Berlin für Sozialforschung (WZB), Berlin This Version is available at: http://hdl.handle.net/10419/195919 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu Yves Breitmoser Sebastian Schweighofer-Kodritsch Obviousness around the clock Put your Research Area and Unit Discussion Paper SP II 2019–203 March 2019 WZB Berlin Social Science Center Research Area Markets and Choice Research Unit Market Behavior Wissenschaftszentrum Berlin für Sozialforschung gGmbH Reichpietschufer 50 10785 Berlin Germany www.wzb.eu Copyright remains with the author(s). -
The Market As a Learning Algorithm: Consequences for Regulation and Antitrust
THE MARKET AS A LEARNING ALGORITHM: CONSEQUENCES FOR REGULATION AND ANTITRUST Ramsi A. Woodcock* ABSTRACT The heart of the Chicago School’s attack on the antitrust laws was a skepticism about the ability of government to improve upon unregulated market outcomes. Although the attack failed to eliminate regulation or antitrust entirely, it has proven so enduringly devastating as an intellectual matter that virtually no proposal for government regulation or increased antitrust enforcement is put forward today without an attempt either to justify the proposed departure from an assumed-legitimate free market baseline or to dismiss Chicago School skepticism as an intellectual plot bankrolled by business elites. Chicago School skepticism has been so devastating because it draws sustenance from an inapt metaphor for the economy: that of evolution through natural selection. The free market is, for the Chicago School, nature itself, and all the glories of life suggest that evolution does just fine when left to its own devices, creating a powerful basis for skepticism regarding the need for government intervention in the economy. Except that evolution never did do anything to promote economic growth, so much as theft, a fact that human beings know well given their status as predators of unparalleled success. Humanity did not escape from the subsistence economics that characterizes all of evolved life until humanity started to exert control over the forces of evolution, which is to say: to regulate. A better metaphor for the economy than natural selection is that of a computer running a machine learning algorithm engineered to channel evolutionary forces away from theft and toward growth. -
Common-Value Auctions with Liquidity Needs: an Experimental
CommonValue Auctions with Liquidity Needs: An Experimental Test of a Troubled Assets Reverse Auction Lawrence M. Ausubel, Peter Cramton, Emel Filiz‐Ozbay, Nathaniel Higgins, Erkut Ozbay, and Andrew Stocking* 21 May 2009 Abstract We experimentally test alternative auction designs suitable for pricing and removing troubled assets from banks’ balance sheets as part of the financial rescue. Many individual securities or pools of securities are auctioned simultaneously. Securities that are widely held are purchased in auctions for individual securities. Securities with concentrated ownership are purchased as pools of related securities. Each bank has private information about its liquidity need and the true common value of each security. We study bidding behavior and performance of sealed‐ bid uniform‐price auctions and dynamic clock auctions. The clock and sealed‐bid auctions resulted in similar prices. However, the clock auctions resulted in substantially higher bank payoffs, since the dynamic auction enabled the banks to better manage their liquidity needs. The clock auctions also reduced bidder error. The experiments demonstrated the feasibility of quickly implementing simple and effective auction designs to help resolve the crisis. (JEL D44, C92, G01, G21. Keywords: financial crisis, uniform‐price auction, clock auction, market design, experiments, troubled assets, TARP.) 1 Introduction On 3 October 2008, the US Congress passed and the President signed the Emergency Economic Stabilization Act of 2008 (Public Law 110‐343). The Act established the $700 billion Troubled Asset Relief Program (TARP). It authorized the US Treasury to purchase troubled assets in order to restore liquidity to financial markets, favoring. the use of market mechanisms such as reverse auctions for asset purchases. -
Handout 21: “You Can't Handle the Truth!”
CSCE 475/875 Multiagent Systems Handout 21: “You Can’t Handle the Truth!” October 24, 2017 (Based on Shoham and Leyton-Brown 2011) Independent Private Value (IPV) To analyze properties of the various auction protocols, let’s first consider agents’ valuations of goods: their utilities for different allocations of the goods. Auction theory distinguishes between a number of different settings here. One of the best-known and most extensively studied is the independent private value (IPV) setting. In this setting all agents’ valuations are drawn independently from the same (commonly known) distribution, and an agent’s type (or “signal”) consists only of its own valuation, giving itself no information about the valuations of the others. An example where the IPV setting is appropriate is in auctions consisting of bidders with personal tastes who aim to buy a piece of art purely for their own enjoyment. (Note: Also think about the common-value assumption. Resale value!) Second-price, Japanese, and English auctions Theorem 11.1.1 In a second-price auction where bidders have independent private values, truth telling is a dominant strategy. Proof. Assume that all bidders other than i bid in some arbitrary way, and consider i’s best response. First, consider the case where i’s valuation is larger than the highest of the other bidders’ bids. In this case i would win and would pay the next-highest bid amount. Could i be better off by bidding dishonestly in this case? • If i bid higher, i would still win and would still pay the same amount. • If i bid lower, i would either still win and still pay the same amount or lose and pay zero. -
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. -
CS395T Agent-Based Electronic Commerce Fall 2003
CS395T Agent-Based Electronic Commerce Fall 2003 Peter Stone Department or Computer Sciences The University of Texas at Austin Week 2a, 9/2/03 Logistics • Mailing list and archives Peter Stone Logistics • Mailing list and archives • Submitting responses to readings Peter Stone Logistics • Mailing list and archives • Submitting responses to readings − no attachments, strange formats − use specific subject line (see web page) Peter Stone Logistics • Mailing list and archives • Submitting responses to readings − no attachments, strange formats − use specific subject line (see web page) − by midnight; earlier raises probability of response Peter Stone Logistics • Mailing list and archives • Submitting responses to readings − no attachments, strange formats − use specific subject line (see web page) − by midnight; earlier raises probability of response • Presentation dates to be assigned soon Peter Stone Logistics • Mailing list and archives • Submitting responses to readings − no attachments, strange formats − use specific subject line (see web page) − by midnight; earlier raises probability of response • Presentation dates to be assigned soon • Any questions? Peter Stone Klemperer • A survey • Purpose: a broad overview of terms, concepts and the types of things that are known Peter Stone Klemperer • A survey • Purpose: a broad overview of terms, concepts and the types of things that are known − Geared more at economists; assumes some terminology − Results stated with not enough information to verify − Apolgies if that was frustrating Peter Stone -
Forward Auction Bidding System User Guide Disclaimer
FCC Incentive Auction Forward Auction Clock Phase Bidding System USER GUIDE Last updated: July 22, 2016 Forward Auction Bidding System User Guide Disclaimer DISCLAIMER The Federal Communications Commission (the “Commission”) will make available a web-based Auction System for incentive auction bidding purposes. The Commission makes no warranty whatsoever with respect to the Auction System. In no event shall the Commission, or any of its officers, employees or agents, be liable for any damages whatsoever (including, but not limited to, loss of business profits, business interruption, loss of business information, or any other loss) arising out of, or relating to the existence, furnishing, functioning or use of the Auction System that is accessible to bidders in connection with this auction. Moreover, no obligation or liability will arise out of the Commission’s technical, programming or other advice or service provided in connection with the Auction System. The examples that appear in this document are based on fictitious data and do not represent the actual data for this auction. Additionally, they do not reflect any predictions or assumptions about the actual bidding in the auction, the number of rounds, or the outcome of the auction. Any similarity to actual company names, PINs, FCC Registration Numbers (FRNs), or other personal information is coincidental. COPYRIGHT NOTICE Copyright © 2005–2016 by Power Auctions LLC. The software service makes use of proprietary technology protected by US Patent Numbers 7,062,461; 7,165,046; 7,343,342; 7,467,111; 7,870,050; 7,899,734; 7,966,247; 8,447,662; and 8,762,222. -
Is the Market a Test of Truth and Beauty Essays in Political
Is the Market a Test of Truth and Beauty? Is the Market a Test of TRUTH BEAUTY? Essays in Political Economy by L B. Y Ludwig von Mises Institute © 2011 by the Ludwig von Mises Institute and published under the Creative Commons Attribution License 3.0. http://creativecommons.org/licenses/by/3.0/ Ludwig von Mises Institute 518 West Magnolia Avenue Auburn, Alabama 36832 mises.org ISBN: 978-1-61016-188-6 Contents Introduction . vii : Should Austrians Scorn General Equilibrium eory? . Why Subjectivism? ..................... Henry George and Austrian Economics ........... e Debate about the Efficiency of a Socialist Economy . e Debate over Calculation and Knowledge ......... Austrian Economics, Neoclassicism, and the Market Test . Is the Market a Test of Truth and Beauty? . Macroeconomics and Coordination . e Keynesian Heritage in Economics . Hutt and Keynes ....................... e Image of the Gold Standard . Land, Money, and Capital Formation . Tacit Preachments are the Worst Kind . Tautologies in Economics and the Natural Sciences . : Free Will and Ethics . Elementos del Economia Politic . Is ere a Bias Toward Overregulation? . Economics and Principles .................. American Democracy Diagnosed . Civic Religion Reasserted . A Libertarian Case for Monarchy . v vi Contents Uchronia, or Alternative History . Hayek on the Psychology of Socialism and Freedom . Kirzner on the Morality of Capitalist Profit . Mises and His Critics on Ethics, Rights, and Law . e Moral Element in Mises’s Human Action . Can a Liberal Be an Egalitarian? ............... Rights, Contract, and Utility in Policy Espousal . Index ............................... Introduction Tis book’s title is the same as the newly chosen title of chapter , “Is the Market a Test of Truth and Beauty?” Tat chapter, along with the one before it, questions a dangerously false argument for the free-market economy sometimes made by its supposed friends. -
Hiding Information in Open Auctions with Jump Bids David Ettinger, Fabio Michelucci
Hiding Information in Open Auctions with Jump Bids David Ettinger, Fabio Michelucci To cite this version: David Ettinger, Fabio Michelucci. Hiding Information in Open Auctions with Jump Bids. Economic Journal, Wiley, 2016, 126 (594), pp.1484 - 1502. 10.1111/ecoj.12243. hal-01432853 HAL Id: hal-01432853 https://hal.archives-ouvertes.fr/hal-01432853 Submitted on 12 Jan 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. Hiding Information in Open Auctions with Jump Bids∗ David Ettinger and Fabio Michelucci We analyse a rationale for hiding information in open ascending auction formats. We focus on the incentives for a bidder to call a price higher than the highest standing one in order to prevent the remaining active bidders from aggregating more accurate information by observing the exact drop out values of the opponents who exit the auction. We show that the decision whether to allow jump bids or not can have a drastic impact on revenue and efficiency. Economists have focused extensive attention on market environments where the aggregation of new information is important.1 The possibility of aggregating new information is also the key feature of open auction formats, which often leads auction theorists and designers to advocate the use of open auction formats as opposed to sealed bid auction formats. -
Mechanism Design for Multiagent Systems
Mechanism Design for Multiagent Systems Vincent Conitzer Assistant Professor of Computer Science and Economics Duke University [email protected] Introduction • Often, decisions must be taken based on the preferences of multiple, self-interested agents – Allocations of resources/tasks – Joint plans – … • Would like to make decisions that are “good” with respect to the agents’ preferences • But, agents may lie about their preferences if this is to their benefit • Mechanism design = creating rules for choosing the outcome that get good results nevertheless Part I: “Classical” mechanism design • Preference aggregation settings • Mechanisms • Solution concepts • Revelation principle • Vickrey-Clarke-Groves mechanisms • Impossibility results Preference aggregation settings • Multiple agents… – humans, computer programs, institutions, … • … must decide on one of multiple outcomes… – joint plan, allocation of tasks, allocation of resources, president, … • … based on agents’ preferences over the outcomes – Each agent knows only its own preferences – “Preferences” can be an ordering ≥i over the outcomes, or a real-valued utility function u i – Often preferences are drawn from a commonly known distribution Elections Outcome space = { , , } > > > > Resource allocation Outcome space = { , , } v( ) = $55 v( ) = $0 v( ) = $0 v( ) = $32 v( ) = $0 v( ) = $0 So, what is a mechanism? • A mechanism prescribes: – actions that the agents can take (based on their preferences) – a mapping that takes all agents’ actions as input, and outputs the chosen outcome -
Research Paper
The Importance of Being Intelligent: Understanding Market Institutions Shyam Sunder Yale University ABSTRACT Those using artificial intelligence (AI) in finance and other fields seek to meet or beat human intelligence by a chosen index of performance appropriate to each context. Efforts are focused on finding ways of increasing the intelligence of artificial agents through analysis, machine learning or other methods to achieve this goal. This paper reports on an effort in which the goal of gaining understanding of the properties of social institutions — markets in particular — is sought by populating them with minimally- intelligent agents (called zero-intelligence agents), and examining institutional performance. Computer simulations with Zero Intelligence (ZI) agents reveal robust outcomes in certain markets and sensitivity of others, to trader intelligence. Data analyses from simulations help to address some important questions about why certain markets, even when they are populated by cognitively-bounded human traders, yield outcomes predicted by models predicated on utility maximization, while other markets exhibit systematic deviations from such predictions. A certain kind of intelligence — extraction of social surplus—appears to be embedded in the rules and structure of markets and social institutions. Keywords: Intelligence of markets, zero-intelligence traders, computer simulations, predicting market behavior Revised May 11, 2021 I am grateful for participant comments on an earlier version of this paper prepared as one of three Annual Distinguished Lectures at the Centre for Computational Finance and Economic Agents (CCEFA), University of Essex, U.K. I thank my research collaborators Dan K. Gode, Karim Jamal, Antoni Bosch, and Shabnam Mousavi for helpful comments and suggestions and Elizabeth Viloudaki for editing.