Myong-Hun Chang, A Computational Model of Industry Dynamics, Advances in Experimental and Computable Economics Book Series, Routledge, 2015.
Abstract: "This book endeavours to explain many well-documented aspects of the evolution of industries over time. It uses an agent-baed computational model in which artificial industries are created and grown to maturity in silico. ... (The model) is able to replicate many of the stylized facts from the empirical industrial organization literature, particularly as the facts pertain to the dynamics of firm entry and exit."
Myong-Hun Chang, "Agent-Based Modeling and Computational Experiments in Industrial Organization: Growing Firms and Industries in silico"(pdf,88KB),
Eastern Economic Journal 37 (2011), 28-34.
Abstract: This paper discusses the need for, the mechanics of, and some potential application of agent-based modeling and computational analysis in industrial organization.
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.
"Agent-Based Models of Innovation and Technological Change",
in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam,
This chapter discusses the potential of the agent-based
computational economics approach for the analysis of processes of
innovation and technological change. It is argued that, on the one
hand, several genuine properties of innovation processes make the
possibilities offered by agent-based modelling particularly
appealing in this field, and that, on the other hand, agent-based
models have been quite successful in explaining sets of empirical
stylized facts, which are not well accounted for by existing
representative-agent equilibrium models. An extensive survey of
agent-based computational research dealing with issues of innovation
and technological change is given and the contribution of these
studies is discussed. Furthermore a few pointers towards potential
directions of future research are given.
Guido Fioretti, "Agent-Based Models of Industrial Clusters and
in Albert Tavidze (ed.), Progress in Economics Research, Vol. IX
Chapter VIII, 2006, pp. 125-142.
Abstract: "Agent-based models, an instance of a wider
class of connectionist models, allow bottom-up simulations of organizations
constituted by a large number of interacting parts. Thus, geographical
clusters of competing or complementary firms constitute an obvious field of
application. This contribution explains what agent-based models are, reviews
applications in the field of industrial clusters, and focuses on a simulator
of infra- and inter-firm communication."
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."
John Sutton, Market Structure: Theory and Evidence(pdf,856KB),
Latest Revision (2/09 download): February 2006.
Abstract: Topics covered in this survey include: Introduction; Cross-Industry Literature; Size Distribution Literature; Dynamics of Market Structure; Caveats and Controversies; and Unanswered Questions and Current Research.
Leigh Tesfatsion, "Testing Institutional Designs via Agent-Based Modeling: A U.S. Electricity Market Example"(pdf,2.5MB),
Colloquium Talk, WICI, University of Waterloo, March 22, 2010.
Paul Twomey and Richard Cadman, "Agent-Based Modelling of Customer
Behavior in the Telecoms and Media Markets"(pdf,141KB),
Info, Vol. 4(1), 2002, pp. 56-63.
Abstract: The aim of this paper is to introduce the reader
to some of the basic concepts and methods behind agent-based modelling and to
present some recent business applications of these tools, including work in
the telecoms and media markets.
Gary H. Anthes,
"Agents of Change: Software Agents Tame Supply Chain
Complexity and Optimize Performance"(html,Use Quicklink 35605 Search)ComputerWorld, January 27, 2003.
Abstract: This news item relates how Proctor and
Gamble's use of agent-based modeling helped them fundamentally (and
profitably) transform their supply chain system connecting over 5 billion
consumers in 140 countries into a "supply network."
Robert Axtell, "Team Dynamics and the Empirical Structure of U.S. Firms"(pdf,3.7MB),
Working Paper, Department of Computational Social Science, George Mason University, Fairfax, VA, 2013.
A model in which purposive agents self-organize into teams is demonstrated to closely reproduce empirical data on the population of U.S. firms. There are increasing returns within teams and agents move between teams or start new teams when it is in their self-interest. Nash equilibria of the team formation game exist but are unstable. Dynamics are studied using
agent-based computing at full-scale with the U.S. private sector (120 million agents).
Robert Axtell, "Zipf Distribution of U.S. Firm Sizes"(pdf,143KB),
Science, 293, 2001, 1818-1820.
Abstract: "Firm sizes have typically been described by lognormal distributions, with Pareto, Yule and
related distributions accurately capturing the upper (large size) tail. Utilizing data on the entire population of U.S. firms, including small businesses, we find that the Pareto distribution well describes the entire firm size distribution. Furthermore, the exponent of this distribution is essentially unity, thus we have the special case of the Zipf distribution.
Data on self-employment, not normally included in small firm data, are consistent with the Zipf characterization. These results are shown to be robust to alternative definitions of firm size."
Jason Barr and Francesco Saraceno, "A Computational Theory of the Firm"(pdf,315KB),
Journal of Economic Behavior and Organization 49 (2002), 345-361.
"This paper proposes using computational learning theory (CLT) as a framework for analyzing the information processing behavior of firms; we argue that firms can be viewed as learning algorithms.
The costs and benefits of processing information are linked to the structure of the firm and its relationship with the environment. We model the firm as a type of artificial neural network (ANN). By a simulation experiment, we show which types of networks maximize the net return to computation given different environments."
Jason Barr and Francesco Saraceno, "Cournot Competition, Organization,
Journal of Economic Dynamics and Control 29 (2005), 277-295.
Abstract: "We model firms' output decisions in a
repeated duopoly framework focusing on three related issues: (1) the role of
learning in the adjustment process toward equilibrium; (2) the role of
organization structure in organizational decision making; and (3) the role of
changing environmental conditions on learning and output decisions."
Jason Barr and Francesco Saraceno, "Organization, Learning, and
Newark Working Paper No. 2004-001, Rutgers University,
March 2004, to appear in the Journal of Economic Behavior and Organization.
Abstract: "We model the organization of the firm as a
type of artificial neural network in a duopoly framework. The firms plays a
repeated Prisoner's Dilemma type game, but also must learn to map
environmental signals to demand parameters. We study the prospects for
cooperation given the need for the firm to learn the environment and its
rival's output. We show how a firm's profit and cooperation rates are
affected by its size, its rival's size and willingness to cooperate, and
Lucio Biggiero and Enrico Sevi, "Opportunism by Cheating and its Effects on Industry Profitability: The CIOPS Model"(pdf,1.1MB),
Comput. Math. Organization Theory 15 (2009), 191-236.
The CIOPS (Cognitive Inter-organizational Production SysteMB) model is an agent-based model that integrates industry structural aspects and agents’ cognitive characteristics.
A demand-driven industry, whose profitability depends on the quality of
suppliers’ products, is represented by a three-stage vertically integrated industry. Four
types of decision-making methods are analyzed and compared ranging from random choice to a complex method involving direct and indirect experience and reputation aspects.
Myong-Hun Chang, "Industry Dynamics with Knowledge-Based Competition: A Computational Study of Entry and Exit Patterns"(pdf,1.4MB),
Journal of Economic Interaction and Coordination, 4 (2009), 73-114.
Abstract: This study develops a computational model of industry evolution capable of matching many stylized
facts. It views the firm as a myopic but adaptive entity whose survival depends on its ability to perform various activities with greater efficiency than its rivals. In this model,
the shakeout pattern arises naturally in the early stage of industrial development. The author provides
a full comparative dynamics analysis of how various industry-specific factors determine the
numbers and the rates of entries and exits over time as well as the ages of the exiting firms.
Myong-Hun Chang, "Entry, Exit, and the Endogenous Market Structure in Technologically Turbulent Industries"(pdf,538KB),
Eastern Economic Journal 37 (2011), 51-84
Abstract: "Empirical studies have found high correlation between entry and exit across industries,
indicating that industries differ substantially in their degree of firm turnover. I propose a computational model of dynamic oligopoly with entry and exit in a turbulent technological environment. I examine how industry-specific factors give rise to across industries
differences in turnover. An analysis of the endogenous relationships between firm turnover,industry concentration, and the performance variables shows: 1) the rate of turnover and industry concentration are positively related; 2) industry concentration and market price
are positively related; 3) no general relationship exists between industry concentration and
and Bin-Tzong Chie, "Agent-Based Simulation of Product Innovation: Modularity, Complexity, and Diversity"(pdf,446KB),
Proceedings, Agent 2007 Conference on Complex Interaction and Social Emergence (Agent 2007), Northwestern University, Evanston, Illinois, Nov. 15-17, 2007, pp. 295-305.
Abstract: This work is a continuation of earlier work by the authors in which they develop an agent-based model to simulate the evolution of product innovation. The earlier work introduced a new representation of commodities, production processes, and preferences via the use of genetic programming (GP). However, in this earlier work the authors only considered a simple version of genetic programming that could not suitably express functional modularities. The result was that their simulated economy only rarely advanced to a mature state where consumers’ desires could be met to a sophisticated degree. In this paper the authors remedy this problem by replacing simple GP with automatically defined terminals (ADTs), which are very similar in spirit to the automatically defined functions (ADFs) invented by John Koza. The authors then demonstrate how their approach permits them to model product innovation as the incremental development of products "from the bottom up".
Evan J. D. Gee, Agent-Based Modeling of Non-Walrasian Markets with
Entrance and Exit of Agents(pdf,597KB),
Work Submitted in Fulfillment of Requirements for a Degree with Honor,
Williams College, Spring 2004.
Abstract: The author uses agent-based modeling to
explore not only the effects of bounded rationality but also the effects of
asymmetric information on markets with entry and exit of agents. An example
of such a market would be the housing market in a college town filled with
students looking for housing and landlords willing to provide it. The author
finds that even small departures from perfect information cause large changes
in both the total surplus and the distribution of that surplus. Given the
magnitudes of these effects, he conjectures that very few actual markets are
likely to have outcomes anywhere near the competitive equilibrium.
Peter Howitt and Robert Clower, "The Emergence of Economic Organization"(pdf,947KB),
Journal of Economic Behavior and Organization, Vol. 41, No. 1, January 2000, 55-84.
"This paper studies the mechanism by which exchange activities are coordinated in a decentralized market economy. Our topic is not amenable to conventional equilibrium theory, which assumes that exchanges plans are coordinated perfectly by an external
agent (usually unspecified but sometimes referred to as `the auctioneer') with no identifiable real-world counterpart. In contrast, we depict transactors as acting on the basis of trial and error rather than pre-reconciled calculation, and we start by noting that in reality most transactions are coordinated by an easily identified set of agents; namely, specialist trading enterprises."
Erich Kutschinski, Thomas Uthmann, and Daniel Polani, "Learning
Competitive Pricing Strategies by Multi-Agent Reinforcement Learning",
Journal of Economic Dynamics and Control 27(11-12), September 2003,
pp. 2207-2218, available from
Abstract: The authors study several adaptive pricing
strategies and learning behaviors in a co-learning market scenario with
different levels of competition."
Jean Pierre Nadal, Denis Phan, Mirta B. Gordan, and Jean Vannimenus,
"Monopoly Market with Externality: An Analysis with Statistical Physics and
Economics Working Paper Archive, Washington University at St. Louis, 2002.
Abstract: "In this paper we explore the effects of
localised externalities introduced through interaction structures upon the
properties of the simplest market model: the discrete choice model with a
single homogeneous product and a single seller (the monopoly case)."
Junjie Sun and Leigh Tesfatsion, "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework"
Computational Economics, Volume 30, Number 3, 2007, pp. 291-327. This article is an abridged version of ISU Economics Working Paper No. 06025
Abstract: In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) - for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, and the Southwest, and adopted for implementation in California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration.
Katarzyna Sznajd-Weron and Rafal Weron, "How Effective is Advertising
in Duopoly Markets?"(html),
Economics Working Paper Archive at Washington University, St. Louis, 2003.
(Also published in Physica A 324 (2003), 437-444.)
Abstract: "A simple Ising spin model which can
describe the mechanism of advertising in a duopoly model is proposed. In
contrast to other agent-based models, the influence does not flow inward from
the surrounding neighbors to the center site, but spreads outward from the
center to the neighbors. The model thus describes the spread of opinions
among customers. It is shown via standard Monte Carlo simulations that very
simple rules and inclusion of an external field -- an advertising campaign --
lead to phase transitions, i.e., extreme and fast changes in market share."
Xavier Vila and Francesc Rocher, "A Note on Agent-Based Imperfect
Presented at the First World Congress of the Game Theory Society (Games
2000), July 24-28, 2000.
Abstract: "The model we discuss in this note is a
re-examination of the classical Bertrand model of imperfect competition. The
main difference is that consumers are allowed to have some strategic behavior
when deciding which one of the two sellers they will buy from."
Junfu Zhang, "Growing Silicon Valley on a Landscape", Journal of
Evolutionary Economics 13 (2003), 529-548.
Abstract: "We propose a Nelson-Winter model with an
explicitly defined landscape to study the formation of high-tech industrial
clusters such as those in Silicon Valley. ... We argue that the emergence of
clusters can be explained by the social effect through which the appearance
of one or a few entrepreneurs inspires many followers locally. Agent-based
simulation is employed to show the dynamics of the model. Data from the
simulation and the properties of the model are discussed in light of
Peter Haddawy, Khaimook Dhananaiyapergse, Yongyos Kaewpitakkun, and Thai
Bui, "Data-Driven Agent-Based Simulation of Commercial Barter Trade"(pdf,271KB),
Report, CSIM Program, Asian Institute of Technology, downloaded 5/12/05.
Abstract: This paper presents TRADES, a data-driven
agent-based simulator for barter trade exchanges. This simulator is built by
learning proabilistic models of company purchase behavior using transaction
history data from an operating trade exchange. The authors evaluate the
accuracy of their simulator by comparing simulated trade to the transaction
data, showing a high degree of agreement between the two. They also use the
simulator to evaluate the effectiveness of a particular trade brokering
The Alliance for Innovative Manufacturing (AIMB) at Stanford University
maintains an interesting site titled How Everyday Things Are Made(html).
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.
Resource Sites, Groups, and Some Early Individual Researchers
(Economics, Cleveland State University, Ohio): Industrial organization;
Computational organization theory; Multi-agent adaptive systems; Applied game
(Economics, University of Bielefeld, Germany): Economics of innovation;
Industry Dynamics, Market Design, Agent-based Computational Economics ,
Evolutionary Game Theory.
(University of Groningen, the Netherlands): Social simulation of consumer behaviour and market dynamics;
Sustainable consumption and diffusion of sustainable technology; Network effects on market dynamics.
Marco A. Janssen
(School of Human Evolution and Social Change, Arizona State University, Tempe, AZ):
The consumat approach (multi-agent modeling of consumer behavior).
(Economics and Business, Tilburg University, the Netherlands): Organizational
dynamics; Agent-based transaction cost economics; New institutional
(Economics, University of Augsburg, Germany): Decay innovation theory;
Evolutionary economics; Schumpeterian economics; Innovation networks;
Innovation and employment.
(Economics, Iowa State University, Ames, Iowa): Electricity restructuring; Multi-market coordination
with learning traders; Modeling decentralized market economies as distributed local-interaction systems;
Construction of computational laboratories for the systematic study of decentralized market
(Département de Physique, Ecole Normale Supérieure, Paris):
Complex system dynamics; Bounded rationality and socio-economic institutions;
Market organization; Information contagion; Sustainable development;
Ian F. Wilkinson
(Discipline of Marketing, The University of Sydney
Business School, University of Sydney, NSW, Australia):
Evolution of institutional and network structures; Structural dynamics of industrial networks; the Kauffman NK model.
(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.
(Université Montesquieu Bordeaux IV, Pessac, France): Evolutionary modelling
and economic dynamics; Industry dynamics; Economics of innovation; Economic
growth; Industrial organization; Decision theory and the theory of the firm.