The Normative Gap: Mechanism Design and Ideal Theories of Justice
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Welfare Economy
Welfare Economy Chapter 1 Welfare, an individual and collective concept We present what is welfare for economists, we elaborate the bedrock of normative economics Winter 2019 Université de Tours - A. Chassagnon Welfare Economics Welfare economics aims to define and to measure social welfare, and to provide evaluations of public policies. A typical question : between different economic situations, more precisely, between different resource allocations, which is the best ? It follows that a deep critical analysis of the instruments is required in that field. Individual and collective welfare First, the welfare should be defined at the individual level. There are many measures It could be a declarative measure : how do you feel your welfare is ? It could be the utility of consumption : What bundle do you prefer ? Second, the welfare should be defined at the collective level There are many measures From a qualitative point of vue, definition of the Pareto optimal allocations From a quantitative point of vue, consider weighted average of the utilities Vocabulary All of those words should be reviewed (in textbooks or in wikipedia) • declarative measure • Bundle (of goods) • weighted average • qualitative measure • quantitative measure • Welfare • Utility function • Allocation (of resources) Map of the talk 1) Individual welfare Declarative welfare, Happiness, Utility functions Time and Inter-country comparisons 2) Collective welfare Pareto optimal (or efficient) allocations Social Welfare Functions and utilities 1a. Individual welfare Declarative welfare, Happiness, Happiness Given its very nature, reported happiness is subjective. It is difficult to compare one person’s happiness with another’s It can be especially difficult to compare happiness across cultures One concern has always been the accuracy and reliability of people’s responses to happiness surveys. -
How Far Is Vienna from Chicago? an Essay on the Methodology of Two Schools of Dogmatic Liberalism
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Paqué, Karl-Heinz Working Paper — Digitized Version How far is Vienna from Chicago? An essay on the methodology of two schools of dogmatic liberalism Kiel Working Paper, No. 209 Provided in Cooperation with: Kiel Institute for the World Economy (IfW) Suggested Citation: Paqué, Karl-Heinz (1984) : How far is Vienna from Chicago? An essay on the methodology of two schools of dogmatic liberalism, Kiel Working Paper, No. 209, Kiel Institute of World Economics (IfW), Kiel This Version is available at: http://hdl.handle.net/10419/46781 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 Kieler Arbeitspapiere Kiel Working Papers Working Paper No. -
A New Normative Economics for the Formation of Shared Social Values
1 1 A new normative economics for the formation of shared social values 2 Neil Ravenscroft 3 School of Environment & Technology, University of Brighton, Lewes Road, Brighton BN2 4 4GJ, UK 5 6 [email protected] 7 Introduction 8 9 It is widely accepted that transition towards a more sustainable society is in part dependent 10 upon an ability to link scientific knowledges - generated in fields such as sustainability 11 science - with socio-political actions that foster sustainable outcomes. For Miller, et al (2014: 12 p.239), this is about strengthening ‘… the role of values in science and decision-making for 13 sustainability,’ while for Rodriguez-Morales and Rawluk (this issue), it is primarily about the 14 deployment of political power in sustainability decision-making processes. In their work, 15 Westberg and Polk (2016) argue that this is about catalysing knowledge exchange between 16 sustainability science and society in such a way that new composite, socially constructed, 17 knowledges are generated that can inform the development of sustainability policy. As 18 Rawluk, et al (this issue) argue, this revolves around complex social-ecological 19 conceptualisations of values that inform the resource trade-offs that society is prepared to 20 accept in pursuit of sustainability, with the fundamental question being one of how choices 21 are made about these trade-offs (see also Anderson, et al, 2015, 2016). 22 23 Conventionally, in neoclassical economics, the social welfare questions raised by the pursuit 24 of sustainability have been addressed by reference to the aggregation of individual 25 preferences – often expressed and captured through market mechanisms (Bartkowski and 26 Lienhoop, 2018). -
Values in Welfare Economics Antoinette Baujard
Values in Welfare economics Antoinette Baujard To cite this version: Antoinette Baujard. Values in Welfare economics. 2021. halshs-03244909 HAL Id: halshs-03244909 https://halshs.archives-ouvertes.fr/halshs-03244909 Preprint submitted on 1 Jun 2021 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. WP 2112 – June 2021 Values in Welfare economics Antoinette Baujard Abstract: This chapter focuses on the inner rationale and consequences of four different archetypal positions regarding how ethical and political values are tackled in welfare economics. Welfare economics is standardly associated with the welfarist framework, for which social welfare is based on individual utility only. Beyond this, we distinguish the value-neutrality claim – for which ethical values should be and are out of the scope of welfare economics –, the value confinement ideal – for which ethical values are acceptable if they are minimal and consensual–, the transparency requirement – for which any ethical values may be acceptable in the welfare economics framework if explicit and formalized –, and the entanglement claim – which challenges the very possibility of demarcation between facts and values. Keywords: Welfare economics, facts and values, value judgement, welfarism, transparency, demarcation, normative and positive, neutrality JEL codes: B41, D60, D63 Values in Welfare economics1 By Antoinette Baujard2 Abstract. -
Multi-Pose Interactive Linkage Design Teaser
EUROGRAPHICS 2019 / P. Alliez and F. Pellacini Volume 38 (2019), Number 2 (Guest Editors) Multi-Pose Interactive Linkage Design Teaser G. Nishida1 , A. Bousseau2 , D. G. Aliaga1 1Purdue University, USA 2Inria, France a) b) e) f) Fixed bodies Moving bodies c) d) Figure 1: Interactive design of a multi-pose and multi-body linkage. Our system relies on a simple 2D drawing interface to let the user design a multi-body object including (a) fixed bodies, (b) moving bodies (green and purple shapes), (c) multiple poses for each moving body to specify the desired motion, and (d) a desired region for the linkage mechanism. Then, our system automatically generates a 2.5D linkage mechanism that makes the moving bodies traverse all input poses in a desired order without any collision (e). The system also automatically generates linkage parts ready for 3D printing and assembly (f). Please refer to the accompanying video for a demonstration of the sketching interface and animations of the resulting mechanisms. Abstract We introduce an interactive tool for novice users to design mechanical objects made of 2.5D linkages. Users simply draw the shape of the object and a few key poses of its multiple moving parts. Our approach automatically generates a one-degree-of- freedom linkage that connects the fixed and moving parts, such that the moving parts traverse all input poses in order without any collision with the fixed and other moving parts. In addition, our approach avoids common linkage defects and favors compact linkages and smooth motion trajectories. Finally, our system automatically generates the 3D geometry of the object and its links, allowing the rapid creation of a physical mockup of the designed object. -
Computing in Mechanism Design∗
Computing in Mechanism Design¤ Tuomas Sandholm Computer Science Department Carnegie Mellon University Pittsburgh, PA 15213 1. Introduction Computational issues in mechanism design are important, but have received insufficient research interest until recently. Limited computing hinders mechanism design in several ways, and presents deep strategic interactions between com- puting and incentives. On the bright side, the vast increase in computing power has enabled better mechanisms. Perhaps most interestingly, limited computing of the agents can be used as a tool to implement mechanisms that would not be implementable among computationally unlimited agents. This chapter briefly reviews some of the key ideas, with the goal of alerting the reader to the importance of these issues and hopefully spurring future research. I will discuss computing by the center, such as an auction server or vote aggregator, in Section 2. Then, in Section 3, I will address the agents’ computing, be they human or software. 2. Computing by the center Computing by the center plays significant roles in mechanism design. In the following three subsections I will review three prominent directions. 2.1. Executing expressive mechanisms As algorithms have advanced drastically and computing power has increased, it has become feasible to field mecha- nisms that were previously impractical. The most famous example is a combinatorial auction (CA). In a CA, there are multiple distinguishable items for sale, and the bidders can submit bids on self-selected packages of the items. (Sometimes each bidder is also allowed to submit exclusivity constraints of different forms among his bids.) This increase in the expressiveness of the bids drastically reduces the strategic complexity that bidders face. -
Supermodular Mechanism Design
Theoretical Economics 5(2010),403–443 1555-7561/20100403 Supermodular mechanism design L M Department of Economics, University of Texas This paper introduces a mechanism design approach that allows dealing with the multiple equilibrium problem, using mechanisms that are robust to bounded ra- tionality. This approach is a tool for constructing supermodular mechanisms, i.e., mechanisms that induce games with strategic complementarities. In quasilinear environments, I prove that if a social choice function can be implemented by a mechanism that generates bounded strategic substitutes—as opposed to strate- gic complementarities—then this mechanism can be converted into a supermod- ular mechanism that implements the social choice function. If the social choice function also satisfies some efficiency criterion, then it admits a supermodular mechanism that balances the budget. Building on these results, I address the multiple equilibrium problem. I provide sufficient conditions for a social choice function to be implementable with a supermodular mechanism whose equilibria are contained in the smallest interval among all supermodular mechanisms. This is followed by conditions for supermodular implementability in unique equilib- rium. Finally, I provide a revelation principle for supermodular implementation in environments with general preferences. K.Implementation,mechanisms,multipleequilibriumproblem,learn- ing, strategic complementarities, supermodular games. JEL .C72,D78,D83. 1. I For the economist designing contracts, taxes, or other institutions, there is a dilemma between the simplicity of a mechanism and the multiple equilibrium problem. On the one hand, simple mechanisms often restrict attention to the “right” equilibria. In public good contexts, for example, most tax schemes overlook inefficient equilibrium situa- tions, provided that one equilibrium outcome is a social optimum. -
Formation of Coalition Structures As a Non-Cooperative Game
Formation of coalition structures as a non-cooperative game Dmitry Levando, ∗ Abstract We study coalition structure formation with intra and inter-coalition externalities in the introduced family of nested non-cooperative si- multaneous finite games. A non-cooperative game embeds a coalition structure formation mechanism, and has two outcomes: an alloca- tion of players over coalitions and a payoff for every player. Coalition structures of a game are described by Young diagrams. They serve to enumerate coalition structures and allocations of players over them. For every coalition structure a player has a set of finite strategies. A player chooses a coalition structure and a strategy. A (social) mechanism eliminates conflicts in individual choices and produces final coalition structures. Every final coalition structure is a non-cooperative game. Mixed equilibrium always exists and consists arXiv:2107.00711v1 [cs.GT] 1 Jul 2021 of a mixed strategy profile, payoffs and equilibrium coalition struc- tures. We use a maximum coalition size to parametrize the family ∗Moscow, Russian Federation, independent. No funds, grants, or other support was received. Acknowledge: Nick Baigent, Phillip Bich, Giulio Codognato, Ludovic Julien, Izhak Gilboa, Olga Gorelkina, Mark Kelbert, Anton Komarov, Roger Myerson, Ariel Rubinstein, Shmuel Zamir. Many thanks for advices and for discussion to participants of SIGE-2015, 2016 (an earlier version of the title was “A generalized Nash equilibrium”), CORE 50 Conference, Workshop of the Central European Program in Economic Theory, Udine (2016), Games 2016 Congress, Games and Applications, (2016) Lisbon, Games and Optimization at St Etienne (2016). All possible mistakes are only mine. E-mail for correspondence: dlevando (at) hotmail.ru. -
Chapter on Automated Mechanism Design
Chapter 6 Automated Mechanism Design Mechanism design has traditionally been a manual endeavor. The designer uses experience and intuition to hypothesize that a certain rule set is desirable in some ways, and then tries to prove that this is the case. Alternatively, the designer formulates the mechanism design problem mathemat- ically and characterizes desirable mechanisms analytically in that framework. These approaches have yielded a small number of canonical mechanisms over the last 40 years, the most significant of which we discussed in Chapter 4. Each of these mechanisms is designed for a class of settings and a specific objective. The upside of these mechanisms is that they do not rely on (even probabilistic) information about the agents' preferences (e.g. Vickrey-Clarke-Groves mechanisms), or they can be easily applied to any probability distribution over the preferences (e.g. the dAGVA mechanism, the Myerson auction, and the Maskin-Riley multi-unit auction). However, these general mechanisms also have significant downsides: ² The most famous and most broadly applicable general mechanisms, VCG and dAGVA, only maximize social welfare. If the designer is self-interested, as is the case in many electronic commerce settings, these mechanisms do not maximize the designer's objective. ² The general mechanisms that do focus on a self-interested designer are only applicable in very restricted settings. For example, Myerson's expected revenue maximizing auction is for selling a single item, and Maskin and Riley's expected revenue maximizing auction is for selling multiple identical units of an item. ² Even in the restricted settings in which these mechanisms apply, the mechanisms only allow for payment maximization. -
Lectures in Contract Theory1
Lectures in Contract Theory1 Steve Tadelis and Ilya Segal2 UC Berkeley and Stanford University Preliminary and Incomplete December 2005 1These notes were prepared for a second year graduate course in Contract theory at Stanford University (Econ 282/291) and UC Berkeley (Econ 206). They are preliminary and incomplete. Thanks also to Debbie Johnston for typing the first version and to Scott Hemphill for excellent research assistance. 2Copyright c 1998-2005 by Steven Tadelis and Ilya Segal. All rights reserved. No part of these° notes may be reproduced in any form by any electronuic or mechanical means without writen permission from the author. Contents IIntroduction 5 0.1Tradewithsmallnumbersofagents............... 6 0.2 Incentives ............................. 7 0.3BoundedRationality....................... 8 0.4Contracts,Mechanisms,Institutions............... 8 II Hidden Information 10 1 The Principal-Agent Model 12 1.1Setup................................ 12 1.1.1 Preferences........................ 12 1.1.2 Contracting........................ 13 1.2Single-CrossingandtheMonotonicityofChoice........ 13 1.3TheFullInformationBenchmark................ 16 1.4TheRevelationPrinciple..................... 18 1.5SolutionwithTwoTypes..................... 20 1.5.1 ManyDiscreteTypes................... 24 1.6SolutionwithaContinuumofTypes.............. 25 1.6.1 TheRelaxedProblem................... 28 1.6.2 Whattodoifmonotonicitybinds(technical)...... 31 1.7ApplicationsoftheModel.................... 32 1.7.1 SecondDegreePriceDiscrimination.......... -
Robust Mechanism Design∗
Robust Mechanism Design∗ Dirk Bergemann† Stephen Morris‡ First Version: December 2000 This Version: November 2001 Preliminary and incomplete Abstract The implementation literature is often criticized because the mechanisms do not seem to be robust to assumed features of the underlying environment. This paper explores one way of formalizing robustness: fixing the set of pay- off relevant types of each player, we ask whether it is possible to implement a given object on large type spaces (reflecting a lack of common knowledge the environment). We show how equilibrium implementation conditions on the universal type space translates into strong solution concepts on the original types space of payoff relevant types. Keywords: Mechanism Design, Common Knowledge, Universal Type Space, Interim Equilibrium, Ex-Post Equilibrium. Jel Classification: ∗This research is support by NSF Grant #SES-0095321. We are grateful for comments from seminar participants at the Institute for Advanced Study, the Stony Brook Game Theory Conference: Seminar on Contract Theory, and the University of Pennsylvania who heard very preliminary versions of this work. We thank Matt Jackson, Jon Levin, Zvika Neeman, Andrew Postlewaite and especially Bart Lipman for valuable discussions about the universal type space. †Department of Economics, Yale University, 28, Hillhouse Avenue, New Haven, CT 06511, [email protected]. ‡Department of Economics, Yale University, 30, Hillhouse Avenue, New Haven, CT 06511, [email protected]. “Game theory has a great advantage in explicitly analyzing the con- sequences of trading rules that presumably are really common knowl- edge; it is deficient to the extent it assumes other features to be com- mon knowledge, such as one agent’s probability assessment about an- other’s preferences or information. -
Mechanism Design: a Linear Programming Approach Rakesh V
Cambridge University Press 978-1-107-00436-8 - Mechanism Design: A Linear Programming Approach Rakesh V. Vohra Frontmatter More information Mechanism Design Mechanism design is an analytical framework for thinking clearly and carefully about exactly what a given institution can achieve when the information necessary to make decisions is dispersed and privately held. This book provides an account of the underlying mathematics of mechanism design based on linear programming. Three advantages characterize the approach. The first is simplicity: arguments based on linear programming are both elementary and transparent. The second is unity: the machinery of linear programming provides a way to unify results from disparate areas of mechanism design. The third is reach: the technique offers the ability to solve problems that appear to be beyond the reach of traditional methods. No claim is made that the approach advocated should supplant traditional mathematical machinery. Rather, the approach represents an addition to the tools of the eco- nomic theorist who proposes to understand economic phenomena through the lens of mechanism design. Rakesh V. Vohra is the John L. and Helen Kellogg Professor of Managerial Eco- nomics and Decision Sciences at the Kellogg School of Management, Northwest- ern University, where he is also Director of the Center for Mathematical Studies in Economics and Management Science. He previously taught at the Fisher School of Business, Ohio State University, and is the author of Advanced Mathematical Eco- nomics (2005). Professor Vohra has also completed a manuscript on the principles of pricing with Lakshman Krishnamurthi, Professor of Marketing at the Kellogg School. Professor Vohra received his doctorate in mathematics from the University of Maryland.