Phillipe Aghion and Peter Howitt, Endogenous Growth Theory, The
MIT Press, Cambridge, MA, 1998.
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."
W. Brian Arthur, The Nature of Technology: What it is and How it Evolves, Free Press (Simon & Schuster) in US, Penguin Books in UK, 2009.
Preview (from the author): "In the last few years I have become deeply fascinated with technology and how it evolves. Technology creates our modern world and our modern economy and its evolution—innovation—drives all our hopes for the future. Yet we do not understand technology or innovation at all well—there is no "-ology of technology." These challenges intrigue me. I am currently writing a book, The Nature of Technology, that will look deeply into technology and its innovation. It will argue that all technologies share certain principles; these determine the character of technology and how novel technologies come into being—and hence how innovation works."
Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, Edward Elgar Publishing, Cheltenham, 2011.
Review (Manfred Paier, Jan 2012)
Gerard Ballot and Erol Taymaz, "Technological Change, Learning, and
Journal of Artificial Societies and Social Simulation, Vol. 2 (1999),
1999 (electronic journal).
Chris Birchenhall, "Modular Technical Change and Genetic
Algorithms", Computational Economics, Vol. 8 (1995), 233-253.
U. Cantner and A. Pyka, "Absorbing Technological Spillovers:
Simulations in an Evolutionary Framework", Industrial and Corporate
Change, Vol. 7 (1998), 369-397.
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".
F. Chiaromonte, G. Dosi, and L. Orsenigo, "Heterogeneity, Competition
and Macroeconomic Dynamics in the Process of Development: On the Foundations
of Growth Regimes", in R. Thompson (ed.), Learning and Technological
Change, MacMillan Press, 1993, 117-149.
"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.
Herbert Dawid, Marc Reimann, and Bernd Bullnheimer, "To Innovate or
Not to Innovate?", IEEE Transactions on Evolutionary Computation,
Vol. 5(5), October 2001, 471-481.
Herbert Dawid and Marc Reiman, "Evaluating Market Attractiveness:
Individual Incentives v. Industrial Profitability", 2004, to appear in
Giovanni Dosi and Massimo Egidi, "Substantive and Procedural Uncertainty: An Exploration of Economic Behaviors in Changing Environments"(pdf,6.9MB),
Journal of Evolutionary Economics 1(1991), 145-168.
Abstract: Different sources of uncertainty are analyzed and a representation of decision-making in principle consistent with behavioural evidence is proposed. The endogenous emergence of "innovations", in the form of unexpected events and novel behaviours, is also examined.
Giovanni Dosi and Franco Malerba (eds.), Organization and Strategy
in the Evolution of Enterprise, MacMillan Press, London, 1996.
Theo Eicher and Klaas van't Veld,
Search in Research: An Evolutionary Approach to
Technical Change and Growth(pdf,99KB),
Working Paper, Department of Economics, University of Washington, October
Giorgio Fagiolo and Giovanni Dosi, Exploitation, Exploration, and
Innovation in a Model of Endogenous Growth with Locally Interacting
Agents, Structural Change and Economic Dynamics, Vol. 14 (2003),
237-273. Pre-Print downloadable at
Martin Ford, Rise of the Robots: Technology and the Threat of a Jobless Future, Basic Books, NY, 2015.
Abstract: As noted by a commentator from the Financial Times, this study is "well-researched and disturbingly persuasive."
History, State, and Prospects of Evolutionary Models of
Technical Change: A Review with Special Emphasis on Complexity Theory(pdf,28pp.),
Working Paper, Utrecht University, The Netherlands, November 2004.
Abstract: The goal of this paper is to provide an
introductory review of recent complexity models of technical change in an
evolutionary economics framework. The author first discusses some of the
early evolutionary models developed in the 1980s and 1990s. He then focuses
on three recent strands of modeling using complexity theory: fitness
landscape models; percolation models; and network models. He concludes with
a discussion of some of the methodological challenges entailed by this
approach as well as promising research avenues for the future.
Innovation, Evolution, and Complexity Theory, Edward Elgar Publishing, 2006, 192pp.
"The motivation behind this book is the desire to integrate complexity theory into economic models of technological evolution. By means of developing an evolutionary model of complex technological systems, the book contributes to the neo-Schumpeterian literature on innovation, diffusion, and technological paradigms."
Nigel Gilbert, Andreas Pyka, and Petra Ahrweiler, "Innovation
Networks: A Simulation Approach"(html),
Journal of Artificial Societies and Social Simulation, Vol. 4 (2001),
Elhanan Helpman, General Purpose Technologies and Economic
Growth, The MIT Press, Cambridge, MA 1998.
Florian Wendelspiess Chávez Juárez,
Agent-based modeling techniques for development economics(pdf,227KB),
Working Paper, Department of Economics, University of Geneva, February, 2014.
Abstract: This articles discusses the potential role of agent-based modeling (ABM) techniques in development economics. The author maintains that ABM techniques are a promising alternative to traditional modeling techniques for development economics, as they can easily incorporate the non-standard findings of the experimental development economics literature. More generally, the author discusses the opportunities for a mutually beneficial interplay between experiment-based empirical research and agent-based models.
Huw Lloyd-Ellis, On the Role of Embodied and Investment-Specific
Technological Change in the New Economy: A Survey(pdf,276KB),
Working Paper, Department of Economics, Queen's University, November, 2001.
Franco Malerba, Richard Nelson, Luigi Orsenigo, and Sidney Winter,
"History-Friendly Models: An Overview of the Case of the Computer
Journal of Artificial Societies and Social Simulation, Vol. 4 (2001), electronic journal.
M. Natter, A. Mild, M. Feuerstein, G. Dorffner, and A. Taudes, "The
Effect of Incentive Schemes and Organizational Arrangements on the New
Product Development Process", Management Science, Vol. 47 (2001),
Richard Nelson, Recent Evolutionary Theorizing About Economic
Change, Journal of Economic Literature 33 (1995), 48-90.
Douglas C. North, The New Institutional Economics and Development(pdf,30KB),
Working Paper, Washington University, St. Louis, 1993.
Richard Nelson and Gavin Wright, The Rise and Fall of American
Technological Leadership: The Postware Era in Historical Perspective,
Journal of Economic Literature 30(4), 1992, 1931-1964.
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.
Gerry Silverberg and Bart Verspagen, "From the Artificial to the
Endogenous: Modeling Evolutionary Adaptation and Economic Growth",
in E. Helmstadter and M. Perlman (eds.), Behavioral Norms, Technological
Progress, and Economic Dynamics, The University of Michigan Press, Ann
Gerry Silverberg and Bart Verspagen, "Evolutionary Theorizing on
Economic Growth", in K. Dopfer (ed.), The Evolutionary Foundations of
Economics, Harvard University Press, Cambridge, MA, 2005, to appear.
Paul Windrum and Chris Birchenhall, "Is Product Life Cycle Theory a
Special Case?: Dominant Designs and the Emergence of Market Niches Through
Co-Evolutionary Learning", Structural Change and Economic
Dynamics, Vol. 9 (1998), 109-134.
Paul Windrum and Chris Birchenhall, "Structural Change in the Presence
of Network Externalities: A Co-Evolutionary Model of Technological
Journal of Evolutionary Economics, Vol. 15 (2004), 123-148.
Abstract: This paper uses a two-stage multi-agent
simulation model to examine the conditions under which technological
successions can occur in the presence of network externalities. Data are
used to identify a robust econometric model of the probability of succession.
Four key factors affecting this probability of succession are identified.
Thomas Vallée and Murat Yildizoglu, "Social and Technological Efficiency of Patent Systems"(pdf,178KB),
Journal of Evolutionary Economics, Vol. 16, 2006, 189-206.
"This article develops an evolutionary model of industry dynamics in order to carry out a richer theoretical analysis of the consequences of a stronger patent system. The first results obtained in our article are rather consistent with
the anti-patent arguments and do not favor the case for a stronger patent system: higher social welfare and technical progress are observed in our model in industries with milder patent systems (lower patent height and patent life)."
Murat Yildizoglu, "Competing R&D Strategies in an Evolutionary Industry
Model", Computational Economics, Vol. 19, 2002, 51-65.
Esben S. Andersen,
(Business Studies, Aalborg University, Denmark): Economic organization
(knowledge creation, specialisation, and networks); Evolutionary modelling
and simulation; History of economic analysis, with a focus on Schumpeterian
(Innovation and Technology Management, UCD Business School, University College Dublin, Ireland): Artificial social systems; Innovation networks; Computer simulation; Policy research; Science and technology studies; Economic sociology; Innovation and technology management.
(Max-Planck-Institute for Research into Economic Systems, Jena, Germany):
Evolution of industrial clusters and milieux; Transfer of knowledge;
Modelling of learning in economics; Evolutionary game theory; Consumer
interaction and fashions; Diffusion of innovations.
(Maastricht Economic Research Institute on Innovation and Technology (MERIT),
University of Maastricht, the Netherlands, and Economics Department,
University of Waterloo, Canada): Economics of technology adoption; Dynamics
of networks and network structures; Economics of knowledge generation;
Technological competition and standardization; Consumption dynamics;
(Chair for Economic Theory and Computational Economics, University of Bielefeld, Germany): Simulation
studies of imitation and innovation in markets; Genetic algorithms as a model
of social learning; Adaptive learning in games; Comparison of adaptive and
(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.
(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.
(Economic Geography, Utrecht University, the Netherlands): Complexity theory; NK models;
Percolation models; Geography.
(Department of Economics, Brown University, Providence, Rhode Island): The
emergence of economic organization; Monetary exchange; Job creation and
destruction; Endogenous growth.
(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
(Department of Economics, Laboratory of Economics and Management, Sant'Anna, Pisa, Italy): Application of
artificial intelligence methodologies to the study of decision making and
organizations; Learning and decision-making in non-Bayesian worlds;
Economics of information firms and organizations; Economics of innovation and
technological change; Game theory.
Roger A. McCain
(Economics, Drexel University, Philadelphia, Pennsylvania):
Agent-based computer simulation of dichotomous economic growth; A
framework for cognitive economics; Endogenous growth modelling using
cellular automata frameworks.
(CRIC - Centre for Research on Innovation and Competition, University of
Manchester, UK): Evolutionary economics and the modelling of evolutionary
processes in relation to innovation, competition, and economic growth.
Margaret M. Polski
(Institute for Development Strategies, Indiana University, Bloomington, and
A. T. Kearney, New York): Agent-based modelling; Economic development and
institutional change; Innovation and growth in the new economy; Institutional
evolution and change in U.S. commercial banking; Legislative games.
(Chair for Economics of Innovation, University of Hohenheim, Germany): Decay innovation theory;
Evolutionary economics; Schumpeterian economics; Innovation networks;
Innovation and employment.
(UNU Maastricht Economic and Social Research Institute on Innovation and Technology, University of Maastricht, the Netherlands): Global economic change; Innovation clustering; Innovation in complex technology spaces;
Self-organization of economic systems.
(UNU Maastricht Economic and Social Research Institute on Onnovation and Technology, University of Maastricht, the Netherlands ): Economic growth and its relation to technological change; Evolutionary modeling (e.g., NK landscapes); European patents.
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.
(Business School, Nottingham University Business School, UK): Evolutionary
modelling; Industry dynamics; Product life cycles; Technological lock-in;
Consumer interaction and demand dynamics; Innovation and public sector
(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.
(Economics, Montesquieu Bordeaux IV University, Pessac, France): Evolutionary modelling
and economic dynamics; Industry dynamics; Economics of innovation; Economic
growth; Industrial organization; Decision theory and the theory of the firm.