Agent-Based Computational Economics (ACE)
Research Area: Technological Change and Economic Growth

Last Updated: 27 July 2007

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 Online ACE Course (Self-Study eBook) ACE Website

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

Basic Issues

• What is the process of technology creation?
• How do researchers select, imitate, and experiment with new ideas? How to model this process in a compelling useful way?
• What are the growth effects of technological change?
• How can the process of technology creation be incorporated into "endogenous growth" models?
• What causes cross-country divergencies in growth rates?
• What causes volatility in growth rates across time?

Readings

• Phillipe Aghion and Peter Howitt, Endogenous Growth Theory, The MIT Press, Cambridge, MA, 1998.

• Gerard Ballot and Erol Taymaz, "Technological Change, Learning, and Macroeconomic Coordination" (html), 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.

• 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.

• Herbert Dawid, "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, Spring 2006.
  Abstract: 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 Computational Economics.

  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,99K), Working Paper, Department of Economics, University of Washington, October 2000.

  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 EconPapers.

  Koen Frenken, 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.

  Koen Frenken, Innovation, Evolution, and Complexity Theory, Edward Elgar Publishing, 2006, 192pp.

  Abstract: "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), electronic journal.

  Elhanan Helpman, General Purpose Technologies and Economic Growth, The MIT Press, Cambridge, MA 1998.

  Huw Lloyd-Ellis, On the Role of Embodied and Investment-Specific Technological Change in the New Economy: A Survey (pdf,276K), 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 Industry" (html), 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), 1029-1045.

  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,30K), 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 Arbor, 1996.

  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 Successions" (pdf,155K), 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.

  Murat Yildizoglu, "Competing R&D Strategies in an Evolutionary Industry Model", Computational Economics, Vol. 19, 2002, 51-65.

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

Resource Sites, Groups, and Individual Researchers

• ACE/CAS Research Sites and Groups

• Individual Researchers using ACE/CAS Tools

• 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 economics.

• Thomas Brenner (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.

• Robin Cowan (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; Methodology.

• Herbert Dawid (Chair for Economic Policy, 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 optimal behavior.

• 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.

• Koen Frenken (Economic Geography, Utrecht University, the Netherlands): Complexity theory; NK models; Percolation models; Geography.

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

• 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.

• Luigi Marengo (Department of Economics, University of Trento, 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.

• Stan Metcalfe, (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.

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

• Gerald Silverberg (Maastricht Economic Research Institute on Innovation and Technology (MERIT), University of Maastricht, the Netherlands): Global economic change; Innovation clustering; Innovation in complex technology spaces; Self-organization of economic systems.

• Bart Verspagen, (Economics, Eindhoven Centre for Innovation Studies ECIS, Eindhoven University of Technology, The Netherlands): Economic growth and its relation to technological change; Evolutionary modeling (e.g., NK landscapes); European patents.

• 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.

• Paul Windrum (Business Schook, Manchester Metropolitan University, UK): Evolutionary modelling; Industry dynamics; Product life cycles; Technological lock-in; Consumer interaction and demand dynamics; Innovation and public sector services.

• 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 modelling and economic dynamics; Industry dynamics; Economics of innovation; Economic growth; Industrial organization; Decision theory and the theory of the firm.

Copyright © 2007 Leigh Tesfatsion. All Rights Reserved.