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Prisoners of Reason Game Theory and Neoliberal Political Economy
C:/ITOOLS/WMS/CUP-NEW/6549131/WORKINGFOLDER/AMADAE/9781107064034PRE.3D iii [1–28] 11.8.2015 9:57PM Prisoners of Reason Game Theory and Neoliberal Political Economy S. M. AMADAE Massachusetts Institute of Technology C:/ITOOLS/WMS/CUP-NEW/6549131/WORKINGFOLDER/AMADAE/9781107064034PRE.3D iv [1–28] 11.8.2015 9:57PM 32 Avenue of the Americas, New York, ny 10013-2473, usa Cambridge University Press is part of the University of Cambridge. It furthers the University’s mission by disseminating knowledge in the pursuit of education, learning, and research at the highest international levels of excellence. www.cambridge.org Information on this title: www.cambridge.org/9781107671195 © S. M. Amadae 2015 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2015 Printed in the United States of America A catalog record for this publication is available from the British Library. Library of Congress Cataloging in Publication Data Amadae, S. M., author. Prisoners of reason : game theory and neoliberal political economy / S.M. Amadae. pages cm Includes bibliographical references and index. isbn 978-1-107-06403-4 (hbk. : alk. paper) – isbn 978-1-107-67119-5 (pbk. : alk. paper) 1. Game theory – Political aspects. 2. International relations. 3. Neoliberalism. 4. Social choice – Political aspects. 5. Political science – Philosophy. I. Title. hb144.a43 2015 320.01′5193 – dc23 2015020954 isbn 978-1-107-06403-4 Hardback isbn 978-1-107-67119-5 Paperback Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party Internet Web sites referred to in this publication and does not guarantee that any content on such Web sites is, or will remain, accurate or appropriate. -
Statistical Decision Theory: Concepts, Methods and Applications
Statistical Decision Theory: Concepts, Methods and Applications (Special topics in Probabilistic Graphical Models) FIRST COMPLETE DRAFT November 30, 2003 Supervisor: Professor J. Rosenthal STA4000Y Anjali Mazumder 950116380 Part I: Decision Theory – Concepts and Methods Part I: DECISION THEORY - Concepts and Methods Decision theory as the name would imply is concerned with the process of making decisions. The extension to statistical decision theory includes decision making in the presence of statistical knowledge which provides some information where there is uncertainty. The elements of decision theory are quite logical and even perhaps intuitive. The classical approach to decision theory facilitates the use of sample information in making inferences about the unknown quantities. Other relevant information includes that of the possible consequences which is quantified by loss and the prior information which arises from statistical investigation. The use of Bayesian analysis in statistical decision theory is natural. Their unification provides a foundational framework for building and solving decision problems. The basic ideas of decision theory and of decision theoretic methods lend themselves to a variety of applications and computational and analytic advances. This initial part of the report introduces the basic elements in (statistical) decision theory and reviews some of the basic concepts of both frequentist statistics and Bayesian analysis. This provides a foundational framework for developing the structure of decision problems. The second section presents the main concepts and key methods involved in decision theory. The last section of Part I extends this to statistical decision theory – that is, decision problems with some statistical knowledge about the unknown quantities. This provides a comprehensive overview of the decision theoretic framework. -
Journal of Mathematical Economics Implementation of Pareto Efficient Allocations
Journal of Mathematical Economics 45 (2009) 113–123 Contents lists available at ScienceDirect Journal of Mathematical Economics journal homepage: www.elsevier.com/locate/jmateco Implementation of Pareto efficient allocations Guoqiang Tian a,b,∗ a Department of Economics, Texas A&M University, College Station, TX 77843, USA b School of Economics and Institute for Advanced Research, Shanghai University of Finance and Economics, Shanghai 200433, China. article info abstract Article history: This paper considers Nash implementation and double implementation of Pareto effi- Received 10 October 2005 cient allocations for production economies. We allow production sets and preferences Received in revised form 17 July 2008 are unknown to the planner. We present a well-behaved mechanism that fully imple- Accepted 22 July 2008 ments Pareto efficient allocations in Nash equilibrium. The mechanism then is modified Available online 5 August 2008 to fully doubly implement Pareto efficient allocations in Nash and strong Nash equilibria. The mechanisms constructed in the paper have many nice properties such as feasibility JEL classification: C72 and continuity. In addition, they use finite-dimensional message spaces. Furthermore, the D61 mechanism works not only for three or more agents, but also for two-agent economies. D71 © 2008 Elsevier B.V. All rights reserved. D82 Keywords: Incentive mechanism design Implementation Pareto efficiency Price equilibrium with transfer 1. Introduction 1.1. Motivation This paper considers implementation of Pareto efficient allocations for production economies by presenting well-behaved and simple mechanisms that are continuous, feasible, and use finite-dimensional spaces. Pareto optimality is a highly desir- able property in designing incentive compatible mechanisms. The importance of this property is attributed to what may be regarded as minimal welfare property. -
Richard Bradley, Decision Theory with a Human Face
Œconomia History, Methodology, Philosophy 9-1 | 2019 Varia Richard Bradley, Decision Theory with a Human Face Nicolas Gravel Electronic version URL: http://journals.openedition.org/oeconomia/5273 DOI: 10.4000/oeconomia.5273 ISSN: 2269-8450 Publisher Association Œconomia Printed version Date of publication: 1 March 2019 Number of pages: 149-160 ISSN: 2113-5207 Electronic reference Nicolas Gravel, « Richard Bradley, Decision Theory with a Human Face », Œconomia [Online], 9-1 | 2019, Online since 01 March 2019, connection on 29 December 2020. URL : http://journals.openedition.org/ oeconomia/5273 ; DOI : https://doi.org/10.4000/oeconomia.5273 Les contenus d’Œconomia sont mis à disposition selon les termes de la Licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Pas de Modification 4.0 International. | Revue des livres/Book review 149 Comptes rendus / Reviews Richard Bradley, Decision Theory with a Human Face Cambridge: Cambridge University Press, 2017, 335 pages, ISBN 978-110700321-7 Nicolas Gravel∗ The very title of this book, borrowed from Richard Jeffrey’s “Bayesianism with a human face” (Jeffrey, 1983a) is a clear in- dication of its content. Just like its spiritual cousin The Foun- dations of Causal Decision Theory by James M. Joyce(2000), De- cision Theory with a Human Face provides a thoughtful descrip- tion of the current state of development of the Bolker-Jeffrey (BJ) approach to decision-making. While a full-fledged presen- tation of the BJ approach is beyond the scope of this review, it is difficult to appraise the content of Decision Theory with a Hu- man Face without some acquaintance with both the basics of the BJ approach to decision-making and its fitting in the large cor- pus of “conventional” decision theories that have developed in economics, mathematics and psychology since at least the publication of Von von Neumann and Morgenstern(1947). -
Arxiv:0803.2996V1 [Q-Fin.GN] 20 Mar 2008 JEL Classification: A10, A12, B0, B40, B50, C69, C9, D5, D1, G1, G10-G14
The virtues and vices of equilibrium and the future of financial economics J. Doyne Farmer∗ and John Geanakoplosy December 2, 2008 Abstract The use of equilibrium models in economics springs from the desire for parsimonious models of economic phenomena that take human rea- soning into account. This approach has been the cornerstone of modern economic theory. We explain why this is so, extolling the virtues of equilibrium theory; then we present a critique and describe why this approach is inherently limited, and why economics needs to move in new directions if it is to continue to make progress. We stress that this shouldn't be a question of dogma, but should be resolved empir- ically. There are situations where equilibrium models provide useful predictions and there are situations where they can never provide use- ful predictions. There are also many situations where the jury is still out, i.e., where so far they fail to provide a good description of the world, but where proper extensions might change this. Our goal is to convince the skeptics that equilibrium models can be useful, but also to make traditional economists more aware of the limitations of equilib- rium models. We sketch some alternative approaches and discuss why they should play an important role in future research in economics. Key words: equilibrium, rational expectations, efficiency, arbitrage, bounded rationality, power laws, disequilibrium, zero intelligence, mar- ket ecology, agent based modeling arXiv:0803.2996v1 [q-fin.GN] 20 Mar 2008 JEL Classification: A10, A12, B0, B40, B50, C69, C9, D5, D1, G1, G10-G14. ∗Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe NM 87501 and LUISS Guido Carli, Viale Pola 12, 00198, Roma, Italy yJames Tobin Professor of Economics, Yale University, New Haven CT, and Santa Fe Institute 1 Contents 1 Introduction 4 2 What is an equilibrium theory? 5 2.1 Existence of equilibrium and fixed points . -
An Equilibrium-Conserving Taxation Scheme for Income from Capital
Eur. Phys. J. B (2018) 91: 38 https://doi.org/10.1140/epjb/e2018-80497-x THE EUROPEAN PHYSICAL JOURNAL B Regular Article An equilibrium-conserving taxation scheme for income from capital Jacques Temperea Theory of Quantum and Complex Systems, Universiteit Antwerpen, Universiteitsplein 1, 2610 Antwerpen, Belgium Received 28 August 2017 / Received in final form 23 November 2017 Published online 14 February 2018 c The Author(s) 2018. This article is published with open access at Springerlink.com Abstract. Under conditions of market equilibrium, the distribution of capital income follows a Pareto power law, with an exponent that characterizes the given equilibrium. Here, a simple taxation scheme is proposed such that the post-tax capital income distribution remains an equilibrium distribution, albeit with a different exponent. This taxation scheme is shown to be progressive, and its parameters can be simply derived from (i) the total amount of tax that will be levied, (ii) the threshold selected above which capital income will be taxed and (iii) the total amount of capital income. The latter can be obtained either by using Piketty's estimates of the capital/labor income ratio or by fitting the initial Pareto exponent. Both ways moreover provide a check on the amount of declared income from capital. 1 Introduction distribution of money over the agents involved in additive transactions follows a Boltzmann{Gibbs exponential dis- The distribution of income has been studied for a long tribution. Note that this is a strongly simplified model of time in the economic literature, and has more recently economic activity: it is clear that in reality global money become a topic of investigation for statistical physicists conservation is violated. -
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springer.com/booksellers Springer News 11/12/2007 Statistics 49 D. R. Anderson, Colorado State University, Fort J. Franke, W. Härdle, C. M. Hafner U. B. Kjaerulff, Aalborg University, Aalborg, Denmark; Collins, CO, USA A. L. Madsen, HUGIN Expert A/S, Aalborg, Denmark Statistics of Financial Markets Model Based Inference in the An Introduction Bayesian Networks and Life Sciences Influence Diagrams: A Guide A Primer on Evidence to Construction and Analysis Statistics of Financial Markets offers a vivid yet concise introduction to the growing field of statis- The abstract concept of “information” can be tical applications in finance. The reader will learn Probabilistic networks, also known as Bayesian quantified and this has led to many important the basic methods to evaluate option contracts, to networks and influence diagrams, have become advances in the analysis of data in the empirical analyse financial time series, to select portfolios one of the most promising technologies in the area sciences. This text focuses on a science philosophy and manage risks making realistic assumptions of of applied artificial intelligence, offering intui- based on “multiple working hypotheses” and statis- the market behaviour. tive, efficient, and reliable methods for diagnosis, tical models to represent them. The fundamental The focus is both on fundamentals of math- prediction, decision making, classification, trou- science question relates to the empirical evidence ematical finance and financial time series analysis bleshooting, and data mining under uncertainty. for hypotheses in this set - a formal strength of and on applications to given problems of financial Bayesian Networks and Influence Diagrams: A evidence. Kullback-Leibler information is the markets, making the book the ideal basis for Guide to Construction and Analysis provides a information lost when a model is used to approxi- lectures, seminars and crash courses on the topic. -
Theories of International Relations* Ole R. Holsti
Theories of International Relations* Ole R. Holsti Universities and professional associations usually are organized in ways that tend to separate scholars in adjoining disciplines and perhaps even to promote stereotypes of each other and their scholarly endeavors. The seemingly natural areas of scholarly convergence between diplomatic historians and political scientists who focus on international relations have been underexploited, but there are also some signs that this may be changing. These include recent essays suggesting ways in which the two disciplines can contribute to each other; a number of prizewinning dissertations, later turned into books, by political scientists that effectively combine political science theories and historical materials; collaborative efforts among scholars in the two disciplines; interdisciplinary journals such as International Security that provide an outlet for historians and political scientists with common interests; and creation of a new section, “International History and Politics,” within the American Political Science Association.1 *The author has greatly benefited from helpful comments on earlier versions of this essay by Peter Feaver, Alexander George, Joseph Grieco, Michael Hogan, Kal Holsti, Bob Keohane, Timothy Lomperis, Roy Melbourne, James Rosenau, and Andrew Scott, and also from reading 1 K. J. Holsti, The Dividing Discipline: Hegemony and Diversity in International Theory (London, 1985). This essay is an effort to contribute further to an exchange of ideas between the two disciplines by describing some of the theories, approaches, and "models" political scientists have used in their research on international relations during recent decades. A brief essay cannot do justice to the entire range of theoretical approaches that may be found in the current literature, but perhaps those described here, when combined with citations of some representative works, will provide diplomatic historians with a useful, if sketchy, map showing some of the more prominent landmarks in a neighboring discipline. -
Improving Monetary Policy Models by Christopher A. Sims, Princeton
Improving Monetary Policy Models by Christopher A. Sims, Princeton University and NBER CEPS Working Paper No. 128 May 2006 IMPROVING MONETARY POLICY MODELS CHRISTOPHER A. SIMS ABSTRACT. If macroeconomic models are to be useful in policy-making, where un- certainty is pervasive, the models must be treated as probability models, whether formally or informally. Use of explicit probability models allows us to learn sys- tematically from past mistakes, to integrate model-based uncertainty with uncertain subjective judgment, and to bind data-bassed forecasting together with theory-based projection of policy effects. Yet in the last few decades policy models at central banks have steadily shed any claims to being believable probability models of the data to which they are fit. Here we describe the current state of policy modeling, suggest some reasons why we have reached this state, and assess some promising directions for future progress. I. WHY DO WE NEED PROBABILITY MODELS? Fifty years ago most economists thought that Tinbergen’s original approach to macro-modeling, which consisted of fitting many equations by single-equation OLS Date: May 26, 2006. °c 2006 by Christopher A. Sims. This material may be reproduced for educational and research purposes so long as the copies are not sold, even to recover costs, the document is not altered, and this copyright notice is included in the copies. Research for this paper was supported by NSF grant SES 0350686 and by Princeton’s Center for Economic Policy Studies. This paper was presented at a December 2-3, 2005 conference at the Board of Governors of the Federal Reserve and may appear in a conference volume or journal special issue. -
Introduction to Decision Theory: Econ 260 Spring, 2016
Introduction to Decision Theory: Econ 260 Spring, 2016 1/7. Instructor Details: Sumantra Sen Email: [email protected] OH: TBA TA: Ross Askanazi OH of TA: TBA 2/7. Website: courseweb.library.upenn.edu (Canvas Course site) 3/7. Overview: This course will provide an introduction to Decision Theory. The goal of the course is to make the student think rigorously about decision-making in contexts of objective and subjective uncertainty. The heart of the class is delving deeply into the axiomatic tradition of Decision Theory in Economics, and covering the classic theorems of De Finetti, Von Neumann & Morgenstern, and Savage and reevaluating them in light of recent research in behavioral economics and Neuro-economics. Time permitting; we will study other extensions (dynamic models and variants of other static models) as well, with the discussion anchored by comparison and reference to these classic models. There is no required text for the class, as there is no suitable one for undergraduates that covers the material we plan to do. We will reply on lecture notes and references (see below). 4/7. Policies of the Economics Department, including course pre-requisites and academic integrity Issues may be found at: http://economics.sas.upenn.edu/undergraduate-program/course- information/guidelines/policies 5/7. Grades: There will be two non-cumulative in-class midterms (20% each) during the course and one cumulative final (40%). The midterms will be on Feb 11 (will be graded and returned by Feb 18) and April 5th. The final is on May 6th. If exams are missed, documentable reasons of the validity of such actions must be provided within a reasonable period of time and the instructor will have the choice of pro-rating your grade over the missed exam rather than deliver a make-up. -
Strong Nash Equilibria and Mixed Strategies
Strong Nash equilibria and mixed strategies Eleonora Braggiona, Nicola Gattib, Roberto Lucchettia, Tuomas Sandholmc aDipartimento di Matematica, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy bDipartimento di Elettronica, Informazione e Bioningegneria, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy cComputer Science Department, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA Abstract In this paper we consider strong Nash equilibria, in mixed strategies, for finite games. Any strong Nash equilibrium outcome is Pareto efficient for each coalition. First, we analyze the two–player setting. Our main result, in its simplest form, states that if a game has a strong Nash equilibrium with full support (that is, both players randomize among all pure strategies), then the game is strictly competitive. This means that all the outcomes of the game are Pareto efficient and lie on a straight line with negative slope. In order to get our result we use the indifference principle fulfilled by any Nash equilibrium, and the classical KKT conditions (in the vector setting), that are necessary conditions for Pareto efficiency. Our characterization enables us to design a strong–Nash– equilibrium–finding algorithm with complexity in Smoothed–P. So, this problem—that Conitzer and Sandholm [Conitzer, V., Sandholm, T., 2008. New complexity results about Nash equilibria. Games Econ. Behav. 63, 621–641] proved to be computationally hard in the worst case—is generically easy. Hence, although the worst case complexity of finding a strong Nash equilibrium is harder than that of finding a Nash equilibrium, once small perturbations are applied, finding a strong Nash is easier than finding a Nash equilibrium. -
Egalitarianism in Mechanism Design∗
Egalitarianism in Mechanism Design∗ Geoffroy de Clippely This Version: January 2012 Abstract This paper examines ways to extend egalitarian notions of fairness to mechanism design. It is shown that the classic properties of con- strained efficiency and monotonicity with respect to feasible options become incompatible, even in quasi-linear settings. An interim egali- tarian criterion is defined and axiomatically characterized. It is applied to find \fair outcomes" in classical examples of mechanism design, such as cost sharing and bilateral trade. Combined with ex-ante utilitari- anism, the criterion characterizes Harsanyi and Selten's (1972) interim Nash product. Two alternative egalitarian criteria are proposed to il- lustrate how incomplete information creates room for debate as to what is socially desirable. ∗The paper beneficiated from insightful comments from Kfir Eliaz, Klaus Nehring, David Perez-Castrillo, Kareen Rozen, and David Wettstein. Financial support from the National Science Foundation (grant SES-0851210) is gratefully acknowledged. yDepartment of Economics, Brown University. Email: [email protected] 1. INTRODUCTION Developments in the theory of mechanism design, since its origin in the sev- enties, have greatly improved our understanding of what is feasible in envi- ronments involving agents that hold private information. Yet little effort has been devoted to the discussion of socially desirable selection criteria, and the computation of incentive compatible mechanisms meeting those criteria in ap- plications. In other words, extending the theory of social choice so as to make it applicable in mechanism design remains a challenging topic to be studied. The present paper makes some progress in that direction, with a focus on the egalitarian principle.