Agent-Based Computational Economics (ACE)

Learning and Coordination in
Decentralized Market Economies

Last Updated: 17 June 2009

Site Maintained By: Leigh Tesfatsion Department of Economics Iowa State University Ames, Iowa 50011-1070 http://www.econ.iastate.edu/tesfatsi/ tesfatsi AT iastate.edu Macroeconomic Coordination (Course Module) Learning and the Embodied Mind Macro and Financial Economics Resources Online ACE Course (Self-Study eBook) ACE Website

Table of Contents: Basic Issues Introductory Materials General Readings Software, Toolkits, and Demos Resource Groups and Sites Individual Researchers

Basic Issues

• The complexity of decentralized market economies
• How are goods produced in real-world markets? How are prices determined in real-world markets?
• Integration and coordination of market processes (production, pricing, and distribution)
• Modeling economic systems as circular-flow multiple-market processes
• Taking agent autonomy seriously in multiple-market modeling
• Modeling the co-evolution of market behaviors and market institutions

Introductory Materials

• Rob Axtell, "Very Large-Scale Multi-Agent Systems and Emergent Macroeconomics" (pdf,559K), Lecture Notes, The Brookings Institution, Washington, D.C., 2005.

• Shu-Heng Chen, "Agent-Based Computational Macroeconomics: A Survey" (pdf,235K), In T. Terano, H. Deguchi, and K. Takadama, Meeting the Challenge of Social Problems via Agent-Based Simulation, post-proceedings of the Second International Workshop of Agent-Based Approaches in Economic and Social Complex Systems, New York: Springer, 2003, pp. 141-170.
  Abtract: "While by all standards the macroeconomic system is qualified to be a complex adaptive system, mainstream macroeconomics is not capable of demonstrating this feature. Recent applications of agent-based modeling to macroeconomics define a new research direction, which demonstrates how the macroeconomic system can be modeled and studied as a complex adaptive system. This paper shall review the development of agent-based computational modeling in macroeconomics."

  Giorgio Fagiolo and Andrea Roventini, "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms" (pdf,354K), Working Paper 2008/03, Laboratory of Economics and Management, Sant'Anna School of Advanced Studies, Pisa, Italy.

  Abstract: In the last years, various contributions have argued that monetary - and, more generally, economic - policy is finally becoming more of a science. According to these authors, policy rules implemented by central banks are nowadays well supported by a theoretical framework (the New Neoclassical Synthesis) upon which a general consensus has emerged in the economic profession. In other words, scientific discussion on economic policy seems to be ultimately confined to either fine-tuning this "consensus" model, or assessing the extent to which "elements of art" still exist in the conduct of monetary policy. In this paper, we present a substantially opposite view, rooted in a critical discussion of the theoretical, empirical and political-economy pitfalls of the neoclassical approach to policy analysis. Our discussion indicates that we are still far from building a science of economic policy. We suggest that a more fruitful research avenue to pursue is to explore alternative theoretical paradigms, which can escape the strong theoretical requirements of neoclassical models (e.g., equilibrium, rationality, etc.). We briefly introduce one of the most successful alternative research projects - known in the literature as agent-based computational economics (ACE) - and we present the way it has been applied to policy analysis issues. We conclude by discussing the methodological status of ACE, as well as the (many) problems it raises.

  John Foster, "Why is Economics Not a Complex Systems Science" (pdf,132K), Discussion Paper No. 336, School of Economics, University of Queensland, December 2004.

  Abstract: The author notes that current economic theory "is ahistorical and outcome focused, i.e., it does not deal with economic processes." The author then argues that "all parts of the economy are inhabited by complex adaptive systems operating in complicated historical contexts and that this should be acknowledged at the core of economic analysis." The author then revisits the macroeconomics of John Maynard Keynes "to provide an example of how some economists in earlier times were able to provide powerful economic analysis that was based on intuitions that we can now classify as belonging to a complex systems perspective on the economy."

  Blake LeBaron and Leigh Tesfatsion, "Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents" (pdf,45K), American Economic Review (Papers & Proceedings), Volume 98, No. 2, 2008, pp. 246-250.

  Abstract: This study discusses the potential applicability of Agent-based Computational Economics (ACE) for macroeconomic modeling, with a particular stress on the following three issues: (1) taxonomy - what types of agents for macroeconomic models?; (2) scale robustness - how many agents for macroeconomic models?; and (3) empirical validation - connecting to data.

  Leigh Tesfatsion, "Constructive Modeling of Decentralized Market Economies: An Agent-Based Computational Economics Approach" (pdf,214K).

  Abstract: This talk presents in summary form some of the main points raised in the following handbook chapter.

  Leigh Tesfatsion, Agent-Based Computational Economics: A Constructive Approach to Economic Theory (pdf preprint,253K), pp. 831-880 in Leigh Tesfatsion and Kenneth L. Judd (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Table of Contents), Handbooks in Economics Series, North-Holland/Elsevier, the Netherlands, Spring 2006.

  Abstract: This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, behavior, and institutional arrangements.

  Leigh Tesfatsion, "Agent-Based Computational Modeling and Macroeconomics" (pdf,148K), Economic Report 05023, Iowa State University, July 2005. (Slide Presentation,pdf,234K),

  Abstract: Agent-based Computational Economics (ACE) is the computational study of economic processes modeled as dynamic systems of interacting agents. This essay discusses the potential of ACE modeling tools for the study of macroeconomic systems. Points are illustrated using an ACE model of a two-sector decentralized market economy.

  Note: This essay is an abbreviated preliminary version of the above handbook chapter with a stress on macroeconomic issues.

  Leigh Tesfatsion, Macroeconomic Theory Course Materials (Masters-Level):

  1. "Introduction to Walrasian General Equilibrium Modeling" (pdf,122K)
  2. "NonWalrasian Equilibrium: Illustrative Examples" (pdf,187K)
  3. "Universal Principles for Decentralized Market Economies?" (pdf,18K)

General Readings

• George Akerlof and Robert J. Shiller, Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism, Princeton University Press, 2009.
  Note: A short summary of the theme of this book, which provides the essence of George Ackerlof's 2009 T. W. Schultz Memorial Address at the 2009 ASSA meeting in San Francisco in January 2009, can be obtained here (pdf,21K).

  George A. Akerlof, "Behavioral Macroeconomics and Macroeconomic Behavior", The American Economic Review, Volume 92, No. 3, June 2002, pages 411-433.

  Note: This is a revised version of the Nobel Lecture Akerlof delivered in Sweden on December 8, 2001.

  Peter Albin and Duncan K. Foley, "Decentralized, Dispersed Exchange Without an Auctioneer", Journal of Economic Behavior and Organization, Volume 18, 1992, pp. 27-51. Published article available from Science Direct.

  Abstract: Albin and Foley simulate pure exchange among geographically dispersed utility-seeking agents with endowments of two distinct types of goods and with bounds to rationality and calculation. Exchange is entirely decentralized. It is initialized by individual agents who broadcast costly messages to their neighbors indicating their interest in engaging in bilateral trades. This decentralized mechanism is shown to achieve a substantial improvement in the allocation of resources and the average welfare of agents in comparison with randomized initial endowments, but persistent differences arise from Walrasian equilibrium.

  Masanao Aoki and Hiroshi Yoshikawa, Editors, Reconstructing Macroeconomics, special Issue, Economics: The Open-Access Open-Assessment E-Journal, 2009. on-line.

  Abstract: "Having sound `micro foundations for macroeconomics' has been long taken as building sophisticated optimization of an individual economic agent into a macro model. Thus, the `micro-founded' macroeconomics today begins with optimization of the representative consumer. In stark contrast to this main-stream approach in economics, it is widely recognized in natural sciences such as physics, chemistry, biology, and ecology, that a different approach is necessary when we analyze macro system consisting of a large number of micro units. The guiding principle there is that precise behavior of micro unit is irrelevant; we must resort to statistical approach to macro system as a whole. Why not in macroeconomics? The co-editors of the special issue advocated this idea in their book entitled Reconstructing Macroeconomics, Cambridge University Press, 2007. (This issue includes) papers that are intrinsically probabilistic, that is, based broadly on the principle of statistical physics. Key words such as power-law (Pareto-Zipf-Gibrat law), and econophysics may give you some idea (of the contents)."

  Jasmina Arifovic, "Evolutionary Algorithms in Macroeconomic Models,", Macroeconomic Dynamics, Vol. 4, 2000, 373-414.

  Abstract: This paper provides a survey of the applications of evolutionary algorithms in macroeconomic models. Discussion is organized around the issues related to stability of equilibria, equilibrium selection, transitional dynamics, and the long-run evolutionary dynamics different from rational expectations equilibrium outcomes. The survey also discusses criteria that can be used to evaluate the performance and usefulness of evolutionary algorithms in macroeconomic contexts.

  Jasmina Arifovic, "Genetic Algorithm Learning and the Cobweb Model", Journal of Economic Dynamics and Control 18 (1994), 3-28.

  Abstract: This paper studies a version of the famous corn-hog cycle model with agents assumed to use genetic algorithm learning.

  Truman Bewley, Why Wages Don't Fall During a Recession, Harvard University Press, Cambridge, MA 2002 (paperback edition).

  Alan Blinder, Elie Cenetti, David Lebow, and Jeremy Rudd, Asking About Prices, Russell Sage Foundation, New York, 1998.

  Samuel Bowles and Herbert Gintis, Walrasian Economics in Retrospect (pdf,205K), Quarterly Journal of Economics, November 2000, 1411-1439.

  James Bruce, Learning Algorithms in a Decentralized General Equilibrium Model (pdf,976K), Ph.D. Thesis, Department of Economics, McMaster University, Hamilton, ON, Canada, May 2003.

  Abstract: A model is developed in which economic agents learn to make price-setting, price-response, and resource allocation decisions in decentralized markets with localized information and interactions.

  Charlotte Bruun, "The Economy as an Agent-Based Whole -- Simulating Schumpeterian Dynamics" (pdf,210K), Presented at the Society for Computational Economics Conference, University of Washington, Seattle, 2003.

  Abstract: "Schumpeter's view on the dynamics of economic systems has regained topicality as an early contribution to the complexity view in economics. The aim of this paper is to test some of the ideas of Schumpeter using the agent-based computational model presented in Bruun and Luna (2001). As in the early work of Schumpeter, this model assigns a central role to entrepreneurs, and through mechanisms involving creative destruction, the model displays cyclical behavior around a growth path. Inspired by Carlsson and Eliasson's work on Schumpeterian dynamics and economic growth in their framework the experimentally organized economy (2002), focus is placed on the role of the bankruptcy mechanism in selecting winners and exiting losers."

  Bo Carlsson and Gunnar Eliasson, "Industrial Dynamics and Endogenous Growth" (pdf,90K), Industry and Innovation, December 2003, pp. 103-116.

  Abstract: "Economic growth can be described at the macro level but it can never be explained at that level. Economic growth is a matter of experimental creation of a variety of ideas, some of which result in new technologies that are confronted with potential buyers (customers) in dynamic markets and hierarchies.... Economic growth is inherently a micro phenomenon. .. The focus of this paper is on the conditions that are conducive to creation of a variety of new ideas and on those that are necessary and sufficient for effective and efficient selection and retention of winners. We refer to the former as a technological system and the latter as a competence bloc, combined with an experimentally organized economy (EOE). The confrontation between actors and between actors and ideas gives rise to what we call industrial dynamics."

  Christopher K. Chan and Ken Steiglitz, "An Agent-Based Model of a Minimal Economy" (pdf,465K), Working Paper, Department of Computer Science, Princeton University, Princeton, NJ, May 2008.

  Abstract: "We present an agent-based model of a minimal economy containing households, retail banks, and producers of consumer and capital goods. Household behavior is based on the buffer-stock savings model by Deaton (1961), while the profit-maximizing firms employ reinforcement learning to determine pricing and production. Competitive retail banks facilitate the flow of funds between households and producers through a fractional-reserve system. Stability of the simulated markets depends only on the self-adjusting, boundedly rational behavior of the agents in the completely closed economic system."

  Christopher K. Chan and Ken Steiglitz, "A Java Library Implementation of the Gold-Food Economic Model in Repast and MASON" (pdf,911K), Working Paper, Department of Computer Science, Princeton University, Princeton, NJ, January 2008.

  Abstract: "We present a robust, extensible Java library for agent-based economic simulations. The economic model is based on the two-commodity, auction-mediated computational market described in Steiglitz et al. [8]. We implement the library on top of both the Repast and MASON agent-based Java toolkits, and compare these toolkits in terms of their feature set, documentation, execution speed, and flexibility. Though these toolkits represent distinct attempts at creating general-purpose environments for agent-based simulations, we find that their design differences are insignificant with respect to their use in our specific agent-based model, and we argue that Repast is the more appropriate toolkit for our application. Finally, we validate the correctness of our implementations by utilizing the libraries to reproduce the results from work based on the original simulation program."

  Robert Clower and Peter Howitt, "Taking Markets Seriously: Groundwork for a Post Walrasian Macroeconomics", Chapter 2 (pp. 21-37) in David Colander (ed.), Beyond Microfoundations: Post Walrasian Macroeconomics, Cambridge University Press, Cambridge, UK, 1996.

  David Colander (ed.), Post Walrasian Macroeconomics: Beyond the Dynamic Stochastic General Equilibrium Model (book contents,html), Cambridge University Press, Cambridge, UK, 2006.

  Abstract: "This book provides state-of-the-art perspectives on macro theory from many of the world's leading theorists and methodologists. (It is suitable) as a course book or supplementary textbook in graduate macroeconomics. (The book also) includes a historical section that surveys the development of macroeconomics."

  Christophe Deissenberg, Sander van der Hoog, and Herbert Dawid, "EURACE: A Massively Parallel Agent-Based Model of the European Economy" (pdf,1.3M), Document de Travail no. 2008-39, Groupement de Recherche en Economie Quantitative d'Aix-Marseille (GREQAM), 24 June 2008.

  Abstract: EURACE is a major European attempt to construct an agent-based model of the European economy with a very large population of autonomous, purposive agents interacting in a complicated economic environment. To create it, major advances are needed, in particular in terms of economic modeling and software engineering. In this paper, we describe the general structure of the economic model developed for EURACE and present the Flexible Large-scale Agent Modeling Environment (FLAME) that will be used to describe the agents and run the model on massively parallel supercomputers. Illustrative simulations with a simplified model based on EURACE’s labor market module are presented.

  Domenico Delli Gatti, Edoardo Gaffeo, Mauro Gallegati, Gianfranco Giulioni, and Antonio Palestrini, Emergent Macroeconomics: An Agent-Based Approach to Business Fluctuations, Series: New Economic Windows, 2008, XII, 114 p. 30 illus., Hardcover ISBN: 978-88-470-0724-6, see also a (2006 Preprint,pdf,2.1K)

  Abstract (From the Publisher): "This book contributes substantively to the current state-of-the-art of macroeconomics by providing a method for building models in which business cycles and economic growth emerge from the interactions of a large number of heterogeneous agents. Drawing from recent advances in agent-based computational modeling, the authors show how insights from dispersed fields like the microeconomics of capital market imperfections, industrial dynamics and the theory of stochastic processes can be fruitfully combined to improve our understanding of macroeconomic dynamics."

  Giovanni Dosi, Giorgio Fagiolo, and Andrea Roventini, "An Evolutionary Model of Endogenous Business Cycles" (pdf,217K), Computational Economics 27 (2006), pp. 3-34.

  Abstract: The authors present an evolutionary model of industry dynamics comprising firms and consumer-workers that yields endogenous business cycles with "Keynesian" features. The model replicates many important stylized facts concerning microeconomic and macroeconomic dynamics, including: relative volatility properties of investment, consumption, and GDP; procyclical, coincident, and anticyclical variables; firm size distributions; and firm growth distributions.

  Giovanni Dosi, Giorgio Fagiolo, and Andrea Roventini, "Schumpeter Meeting Keynes: A Policy-Friendly Model of Endogenous Growth and Business Cycles" (pdf,402K), Laboratory of Economics and Management (LEM) Working Paper 2008/21, October 2008.

  Abstract: This paper studies an agent-based model that bridges Keynesian theories of demand-generation and Schumpeterian theories of technology-fueled economic growth. The authors employ the model to investigate the properties of macroeconomic dynamics and theimpact of public policies on supply, demand, and other fundamental aspects of the economy.

  John Duffy, Macroeconomics: A Survey of Laboratory Research (pdf,885K), 2008, Chapter prepared for the Handbook of Experimental Economics Vol. 2, J. Kagel and A.E. Roth, Eds.

  Abstract: "This chapter surveys laboratory experiments addressing macroeconomic phenomena. The first part focuses on experimental tests of the microfoundations of macroeconomic models discussing laboratory studies of intertemporal consumption/savings decisions, time (in)consistency of preferences and rational expectations. Part two explores coordination problems of interest to macroeconomists and mechanisms for resolving these problems. Part three looks at experiments in specific macroeconomic sectors including monetary economics, labor economics, international economics as well-as large scale, multi-sector models that combine several sectors simultaneously. The final section addresses experimental tests of macroeconomic policy issues."

  John Duffy, Experimental Macroeconomics (pdf,119K), August 2006, Prepared for the New Palgrave Dictionary of Economics, 2nd edition.

  Abstract: This Palgrave entry provides a brief overview of experimental macroeconomics, a subfield of experimental economics that makes use of controlled laboratory methods to understand aggregate economic phenomena and to test the specific assumptions and predictions of macroeconomic models.

  Joshua Epstein and Robert Axtell, Growing Artificial Societies: Social Science from the Bottom Up, The MIT Press, Cambridge, MA, 1996.

  A review (ps,28K) of this monograph is given by L. Tesfatsion in the Journal of Economic Literature (Vol. XXXVI, March 1998, 233-234).

  Giorgio Fagiolo, Giovanni Dosi, and Roberto Gabriele, Towards an Evolutionary Intepretation of Aggregate Labor Market Regularities (pdf,378K), Working Paper, Sant'Anna School of Advanced Studies, Pisa, Italy, January 21, 2004.

  Abstract: The authors study job matching and bargaining, wage and price setting, and output demand and supply formation in the context of an agent-based computational model of a decentralized market economy consisting of a labor and a product market. The objective of the authors is to provide possible "bottom up" micro explanations for well-known macro empirical regularities (e.g., the Beveridge curve, Okun's Law, and wage data patterns).

  Giorgio Fagiolo and Giovanni Dosi, Exploitation, Exploration, and Innovation in a Model of Endogenous Growth with Locally Interacting Agents, LEM Paper 2002-25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. Downloadable at EconPapers.

  Roman Frydman & Michael D. Goldberg (Foreword by Edmund S. Phelps), Imperfect Knowledge Economics: Exchange Rates and Risk, Princeton University Press, 2007, 368 pp.

  Abstract: "Frydman and Goldberg offer a long-overdue response to the shortcomings of conventional economic models. Drawing attention to the inherent limits of economists' knowledge, they introduce a new approach to economic analysis: Imperfect Knowledge Economics (IKE). IKE rejects exact quantitative predictions of individual decisions and market outcomes in favor of mathematical models that generate only qualitative predictions of economic change. Using the foreign exchange market as a testing ground for IKE, this book sheds new light on exchange-rate and risk-premium movements, which have confounded conventional models for decades."

  Roberto Gabriele, Labor Market Dynamics and Institutions: An Evolutionary Approach, LEM Paper 2002-07, Laboratory of Economics and Management, Sant'Anna School of Advanced Studies, Pisa, downloadable at EconPapers.

  Herbert Gintis, The Emergence of a Price System from Decentralized Bilateral Exchange (pdf,382K), The B.E. Journal of Theoretical Economics, Vol. 6, Issue 1 (Contributions), Article 13, August 18, 2005. Published article available from the Berkeley Economics Press here.

  Abstract: "This paper derives the price system in an agent-based model of decentralized bilateral exchange. When the economy is out of equilibrium, prices are individual subjective estimates of payoff-maximizing exchange ratios and hence are the private information of individual agents. The author shows, however, that a system of public prices emerges in the long run, and these public prices are equilibria of the underlying general equilibrium model. The author notes that this is the first time that a general, decentralized adjustment mechanism has been constructed that renders market equilibrium dynamically stable in a production and exchange economy (albeit highly simplified)."

  Herbert Gintis, The Dynamics of General Equilibrium (pdf,747K), The Economic Journal, Vol. 117 (October), 2007, 1280-1309.

  Abstract: "The Walrasian general equilibrium model is the centrepiece of modern economic theory, but progress in understanding its dynamical properties has been meagre. This article shows that the instability of Walras' Tâtonnement process is due to the public nature of prices, which leads to excessive correlation in the behaviour of economic agents. When prices are private information, a dynamic with a globally stable stationary state obtains in economies that are unstable in the tâtonnment process. We provide an agent-based model of a multi-sector Walrasian economy with production and exchange, in which prices are private information. This economy is dynamically well behaved."

  Peter Howitt, The Keynesian Recovery and Other Essays, The University of Michigan Press, Ann Arbor, MI, 1990.

  Charles M. Macal, "A Brief History of Economics for Optimizers: A Management Scientist's Perspective" (pdf,571K), Decision and Information Sciences Division Center for Complex Adaptive Agent Systems Simulation, Mathematics and Computer Division, Argonne National Laboratory, Chicago, IL, February 25, 2004.

  John McMillan, Reinventing the Bazaar: A Natural History of Markets, W. W. Norton & Co., 2002.

  Abstract: "New ideas in economics, and some old ones, are used in the chapters that follow to dissect exotic, innovative, and everyday marketplaces -- some in physical space, others in cyberspace. How do markets work? What can they do? What can't they do? These are the questions I will address."

  Ben Ramalingam and Harry Jones (with Toussainte Reba and John Young), Exploring the science of complexity Ideas and implications for development and humanitarian efforts (pdf,2.5M), Working Paper 285, Second Edition, Overseas Development Institute, London, October 2008.

  Abstract: "Much development and humanitarian thinking and practice is still trapped in a paradigm of predictable, linear causality and maintained by mindsets that seek accountability through top-down command and control. Recent years have seen more emphasis on the mechanistic approaches of this paradigm and the kinds of procedures which are increasingly questioned by successful private sector organisations. This has widened the gap between actual aid practices and the rhetoric of the many initiatives which aim to improve them – including aid effectiveness, institutional reform, participation, local ownership and empowerment. In the meantime and in parallel, complexity science has explored and articulated a contrasting world of understanding, helping to explain complex dynamic phenomena in a widely diverse range of settings using insights and concepts like non-linearity, edge of chaos, self-organisation, emergence and coevolution. This Working Paper is, to my knowledge, the first comprehensive and substantial work to be published that attempts, systematically and thoroughly, to bridge these two worlds, explaining and then relating the ideas of contemporary complexity theory to current development and humanitarian thinking and practice."

  David A. Robalino, Social Capital, Technology Diffusion, and Sustainable Growth in the Developing World, Ph.D. Dissertation (Linked List of Chapters, html), RAND Report RGSD-151, 2000.

  Abstract: The author develops an agent-based macro-econometric model for the developing world that endogenizes the process of technology diffusion by formalizing the role of social interactions.

  James A. Sprigg, Jr., and Mark A. Ehlen, "Comparative Dynamics in an Overlapping Generations Model: The Effects of Quasi-Rational Discrete Choice on Finding and Maintaining a Nash Equilibrium," Computational Economics 29 (2007), 69-96. The published article is available through Springer Link.

  Abstract: Many models of Nash equilibrium are complex enough that it becomes difficult to ascertain if and under what conditions the economic players can find and maintain this equilibrium. Using an analytical overlapping generations model of goods, labor, and banking markets with quasi-rational discrete-choice decision making, we find through agent-based simulations that a Nash Equilibrium in goods market prices is at least locally stable when firms are sufficiently sensitive to changes in profits. Agent simulations are then used to explore variations in: (1) the mechanisms by which firms select profit-maximizing prices; (2) the mechanisms by which consumers find a low-price firm; (3) mechanisms in the supporting labor market; and (4) the overall parameters that drive the system.

  Vernon L. Smith, Rationality in Economics: Constructivist and Ecological Forms, Cambridge University Press, New York, 2008

  Abstract (from the Publisher: "The principal findings of experimental economics are that impersonal exchange in markets converges in repeated interaction to the equilibrium states implied by economic theory, under information conditions far weaker than specified in the theory. In personal, social, and economic exchange, as studied in two-person games, cooperation exceeds the prediction of traditional game theory. This book relates these two findings to field studies and applications and integrates them with the main themes of the Scottish Enlightenment and with the thoughts of F. A. Hayek."

Software, Toolkits, and Demos

• Annotated list of pointers to ACE/CAS General Software and Toolkits

• Annotated list of pointers to ACE/CAS Computational Laboratories and Demonstration Software

Research Groups and Sites

• Participants in the EURACE Project are developing a large-scale ACE framework to facilitate the systematic experimental study of macroeconomic policy design for the European economy. Key technical issues being addressed in the project are the definition of formal languages for modeling and optimal code generation, the development of scalable computational simulation tools, and the standardization of data repositories with easy-to-use human-machine interfaces.

• The Alliance for Innovative Manufacturing (AIM) at Stanford University maintains an interesting site titled How Everyday Things Are Made. The site provides manufacturing video (virtual factory tours) covering the manufacturing processes for over forty types of common products (cars, planes, chocolate, glass bottles, etc.). These videos stress the extraordinary degree of coordination among input suppliers, producers, and distributors required to bring to market even seemingly simple products such as a jelly bean.

• Other ACE-Related Research Groups

Individual Researchers

• Jasmina Arifovic, (Economics, Simon Fraser University, Burnaby, Canada): Evolutionary algorithms in macroeconomic models; Artificial foreign exchange markets; Genetic algorithm learning; Communication in sender/receiver games.

• Samuel Bowles (Santa Fe Institute, New Mexico, and University of Siena, Italy): Co-evolution of preferences, institutions, and behavior; Causes and consequences of economic inequality.

• William A. Brock (Economics, University of Wisconsin, Madison): Interaction-based modeling; Models of complexity in economics and finance; Models of complexity in chaos theory and nonlinear science.

• Charlotte Bruun (Department of Economics, Politics, and Public Administration, Aalborg University, Denmark): Microfoundations for macroeconomics using agent-based methods (agent-based Keynesian economics); Modeling endogenous growth and learning using Swarm.

• Bo Carlsson (Economics, Case Western Reserve University, Cleveland, Ohio): Industrial dynamics; Role of entrepreneurship in economic growth; Clustering of economic activity in industries and regions (international comparison); Intellectual property management; Innovation systems.

• Myong-Hun Chang (Economics, Cleveland State University, Ohio): Industrial organization; Computational organization theory; Multi-agent adaptive systems; Applied game theory.

• Huw D. Dixon (Cardiff Business School, Cardiff University, UK): Imperfect competition and macroeconomics with heterogeneous sectors; Bounded rationality and evolutionary models of learning in industrial organization; Policy coordination; Dynamic models of firm formation; Transition economies.

• Giovanni Dosi (Economics, Sant'Anna School of Advanced Studies, Pisa, Italy): Technical change and industrial transformation; Innovation, organization, and economic dynamics; Evolutionary economics.

• Theo S. Eicher, (Department of Economics, University of Washington, Seattle): Evolutionary approach to technical change and growth; Technological innovation; R and D Microfoundations; Search algorithms.

• Giorgio Fagiolo (Sant'Anna School of Advanced Studies, Pisa, Italy): Local interaction models; Evolution of social and economic networks; Learning; Endogenous interactions; Economics of innovation and technical change.

• Herbert Gintis (Santa Fe Institute, New Mexico, and Central European University, Budapest, Hungary): Agent-based evolutionary game dynamics; Evolution of strong reciprocity; Moral economy of communities; Evolution of social norms.

• Joe Harrington (Department of Economics, Johns Hopkins University, Baltimore): Industrial organization; Political economy; Evolutionary economics; Game theory.

• Peter Howitt (Department of Economics, Brown University, Providence, Rhode Island): The emergence of economic organization; Monetary exchange; Job creation and destruction; Endogenous growth.

• Tomas Klos (Center for Mathematics and Computer Science - CWI, Amsterdam, the Netherlands): Computational economic organization; Governance and matching; Firms and markets; Repeated prisoner's dilemma.

• Paul Krugman (Economics, Princeton University, Princeton, NJ): New trade theory (consequences of increasing returns and imperfect competition); Spatial economics; The self-organizing economy; The size distribution of cities; Economic geography.

• Witold Kwasnicki (Institute of Economic Sciences, Wroclaw University, Poland): Evolutionary approach to socio-economic development; Innovation processes, entrepreneurship, and knowledge management; Technological change; History of economic thought (e.g., Austrian Economics); Computer simulation of socio-economic systems.

• Axel Leijonhufvud (Economics, Universita degli Studi di Trento, Italy, and Professor Emeritus, Department of Economics, UCLA): Computable economics; Evolution of modern macroeconomics; High inflations; Alternative monetary regimes; Transformation of socialist systems.

• Stan Metcalfe, (CRIC - Centre for Research on Innovation and Competition, University of Manchester, UK): Evolutionary economics and the modeling of evolutionary processes in relation to innovation, competition, and economic growth.

• Bart Nooteboom (Rotterdam School of Management, Erasmus University, Rotterdam, The Netherlands): Organizational dynamics; Agent-based transaction cost economics; New institutional economics.

• Richard Pryor ( Sandia National Laboratories, Albuquerque, New Mexico): The Aspen model of the US economy.

• Andreas Pyka (Economics, University of Bremen, Germany): Decay innovation theory; Evolutionary economics; Schumpeterian economics; Innovation networks; Innovation and employment.

• Leigh Tesfatsion (Economics, Iowa State University, Ames, Iowa): Macroeconomic coordination; Agent learning in multiple-market contexts; Modeling decentralized market economies as distributed local-interaction systems; Construction of computational laboratories for the systematic study of decentralized market processes.

• Gérard Weisbuch (Département de Physique, Ecole Normale Supérieure, Paris): Complex system dynamics; Bounded rationality and socio-economic institutions; Market organization; Information contagion; Sustainable development; Mutualism.

• Ian F. Wilkinson (School of Marketing, University of New South Wales, Australia): Evolution of institutional and network structures; Structural dynamics of industrial networks; the Kauffman NK model.

• Ulrich Witt (Evolutionary Economics Unit, Max Planck Institute for Research into Economic Systems, Jena, Germany): Evolutionary economics; Economic behaviour, cognition, and social learning; Institutions and public choice; Market process and industry dynamics; Long-term economic development and growth; Austrian approach to economics.

• Murat Yildizoglu (Institut Federatif de Recherche sur les Dynamiques Economiques (IFREDE), Universite Montesquieu Bordeaux IV, Pessac, France): Evolutionary modeling and economic dynamics; Industry dynamics; Economics of innovation; Economic growth; Industrial organization; Decision theory and the theory of the firm.

Copyright © 2009 Leigh Tesfatsion. All Rights Reserved.