IDEAS home Printed from https://ideas.repec.org/p/unm/umamer/1999005.html
   My bibliography  Save this paper

Simulation models of technological innovation: A Review

Author

Listed:
  • Windrum, Paul

    (MERIT)

Abstract

The use of simulation modelling techniques in studies of technological innovation dates back to Nelson and Winter''s 1982 book "An Evolutionary Theory of Economic Change" and is an area which has been steadily expanding ever since. Four main issues are identified in reviewing the key contributions that have been made to this burgeoning literature. Firstly, a key driver in the construction of computer simulations has been the desire to develop more complicated theoretical models capable of dealing with the complex phenomena characteristic of technological innovation. Secondly, no single model captures all of the dimensions and stylised facts of innovative learning. Indeed this paper argues that one can usefully distinguish between the various contributions according to the particular dimensions of the learning process which they explore. To this end the paper develops a taxonomy which usefully distinguishes between these dimensions and also clarifies the quite different perspectives underpinning the contributions made by mainstream economists and non-mainstream, neo-Schumpeterian economists. This brings us to a third point highlighted in the paper. The character of simulation models which are developed are heavily influenced by the generic research questions of these different schools of thought. Finally, attention is drawn to an important distinction between the process of learning and adaptation within a static environment, and dynamic environments in which the introduction of new artefacts and patterns of behaviour change the selective pressure faced by agents. We show that modellers choosing to explore one or other of these settings reveal their quite different conceptual understandings of "technological innovation".

Suggested Citation

  • Windrum, Paul, 1999. "Simulation models of technological innovation: A Review," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:umamer:1999005
    as

    Download full text from publisher

    File URL: https://www.merit.unu.edu/publications/rmpdf/1999/rm1999-005.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Giovanni Dosi & Luigi Marengo & Andrea Bassanini & Marco Valente, 2000. "Norms as Emergent Properties of Adaptive Learning: The Case of Economic Routines," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 6, pages 189-210, Edward Elgar Publishing.
    3. Henkin, Gennadi M. & Polterovich, Victor M., 1991. "Schumpeterian dynamics as a non-linear wave theory," Journal of Mathematical Economics, Elsevier, vol. 20(6), pages 551-590.
    4. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    5. Silverberg, Gerald & Lehnert, Doris, 1993. "Long waves and 'evolutionary chaos' in a simple Schumpeterian model of embodied technical change," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 9-37, June.
    6. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    7. Winter, Sidney G., 1984. "Schumpeterian competition in alternative technological regimes," Journal of Economic Behavior & Organization, Elsevier, vol. 5(3-4), pages 287-320.
    8. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
    9. Martin Posch, 1997. "Cycling in a stochastic learning algorithm for normal form games," Journal of Evolutionary Economics, Springer, vol. 7(2), pages 193-207.
    10. Bullard, James & Duffy, John, 1999. "Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 41-60, February.
    11. Chiaromonte, Francesca & Dosi, Giovanni, 1993. "Heterogeneity, competition, and macroeconomic dynamics," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 39-63, June.
    12. Tony Curson Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Levine's Working Paper Archive 588, David K. Levine.
    13. Lane, David A, 1993. "Artificial Worlds and Economics, Part I," Journal of Evolutionary Economics, Springer, vol. 3(2), pages 89-107, May.
    14. Fudenberg, D. & Harris, C., 1992. "Evolutionary dynamics with aggregate shocks," Journal of Economic Theory, Elsevier, vol. 57(2), pages 420-441, August.
    15. Kandori, Michihiro & Mailath, George J & Rob, Rafael, 1993. "Learning, Mutation, and Long Run Equilibria in Games," Econometrica, Econometric Society, vol. 61(1), pages 29-56, January.
    16. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    17. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
    18. Kwasnicki, Witold & Kwasnicka, Halina, 1992. "Market, innovation, competition: An evolutionary model of industrial dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 19(3), pages 343-368, December.
    19. Chris Birchenhall & Nikos Kastrinos & Stan Metcalfe, 1997. "Genetic algorithms in evolutionary modelling," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 375-393.
    20. Prendergast, Renee, 1992. "Increasing Returns and Competitive Equilibrium--The Content and Development of Marshall's Theory," Cambridge Journal of Economics, Oxford University Press, vol. 16(4), pages 447-462, December.
    21. Giovanni Dosi & Christopher Freeman & Richard Nelson & Gerarld Silverberg & Luc Soete (ed.), 1988. "Technical Change and Economic Theory," LEM Book Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number dosietal-1988, April.
    22. Lane, David A, 1993. "Artificial Worlds and Economics, Part II," Journal of Evolutionary Economics, Springer, vol. 3(3), pages 177-197, August.
    23. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    24. Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
    25. Tony Curzon Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 219-254.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Vanessa Oltra & Maider Saint Jean, 2005. "The dynamics of environmental innovations: three stylised trajectories of clean technology," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(3), pages 189-212.
    3. Balatsky, Ye., 2012. "Technological Diffusion and Investment Decision," Journal of the New Economic Association, New Economic Association, vol. 15(3), pages 10-34.
    4. Irina Dezhina & V. Kiseleva, 2008. "State, Science and Business in Russia's Innovation System," Research Paper Series, Gaidar Institute for Economic Policy, issue 115P.
    5. Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.
    6. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    7. Windrum, Paul, 2000. "Back from the brink: Microsoft and the strategic use of standards in the Browser Wars," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    8. d’Andria, D. & Savin, I., 2018. "A Win-Win-Win? Motivating innovation in a knowledge economy with tax incentives," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 38-56.
    9. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    10. P. Windrum, 2007. "Neo-Schumpeterian Simulation Models," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 26, Edward Elgar Publishing.
    11. Hötte, Kerstin, 2020. "How to accelerate green technology diffusion? Directed technological change in the presence of coevolving absorptive capacity," Energy Economics, Elsevier, vol. 85(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    2. G. Silverberg & B. Verspagen, 1995. "Evolutionary Theorizing on Economic Growth," Working Papers wp95078, International Institute for Applied Systems Analysis.
    3. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    4. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Beyond replicator dynamics: Innovation-selection dynamics and optimal diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 229-245, May.
    5. Sandra Silva, 2009. "On evolutionary technological change and economic growth: Lakatos as a starting point for appraisal," Journal of Evolutionary Economics, Springer, vol. 19(1), pages 111-135, February.
    6. Murat YILDIZOGLU, 2009. "Evolutionary approaches of economic dynamics (In French)," Cahiers du GREThA (2007-2019) 2009-16, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    7. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Silverberg, Gerald, 1997. "Evolutionary modeling in economics : recent history and immediate prospects," Research Memorandum 008, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    9. P. Windrum, 2007. "Neo-Schumpeterian Simulation Models," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 26, Edward Elgar Publishing.
    10. Herbert Dawid & Philipp Harting, 2012. "Capturing Firm Behavior in Agent-based Models of Industry Evolution and Macroeconomic Dynamics," Chapters, in: Guido Buenstorf (ed.), Evolution, Organization and Economic Behavior, chapter 6, Edward Elgar Publishing.
    11. Silva, Ester G. & Teixeira, Aurora A.C., 2008. "Surveying structural change: Seminal contributions and a bibliometric account," Structural Change and Economic Dynamics, Elsevier, vol. 19(4), pages 273-300, December.
    12. Fulvio Castellacci, 2007. "Evolutionary And New Growth Theories. Are They Converging?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(3), pages 585-627, July.
    13. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.
    14. Tesfatsion, Leigh, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," ISU General Staff Papers 199807010700001043, Iowa State University, Department of Economics.
    15. Dosi, Giovanni & Roventini, Andrea & Russo, Emanuele, 2019. "Endogenous growth and global divergence in a multi-country agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 101-129.
    16. repec:hal:spmain:info:hdl:2441/46k9rkvut99i7qnn4vqm25t53b is not listed on IDEAS
    17. Hyytinen, Ari & Maliranta, Mika, 2013. "Firm lifecycles and evolution of industry productivity," Research Policy, Elsevier, vol. 42(5), pages 1080-1098.
    18. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics.
    19. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    20. Vaitsos, Constantine V., 2003. "Growth Theories Revisited: Enduring Questions with Changing Answers," UNU-INTECH Discussion Paper Series 2003-09, United Nations University - INTECH.
    21. Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.

    More about this item

    Keywords

    economics of technology ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:unm:umamer:1999005. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Leonne Portz (email available below). General contact details of provider: https://edirc.repec.org/data/meritnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.