Simulation models of technological innovation: a review

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".

[1]  Geoffrey M. Hodgson,et al.  Economics and Evolution: Bringing Life Back into Economics , 1993 .

[2]  Donald N. Michael,et al.  Learning to Plan-And Planning to Learn , 1997 .

[3]  Tony Curzon Price,et al.  Using co-evolutionary programming to simulate strategic behaviour in markets , 1997 .

[4]  Bart Verspagen,et al.  Learning, innovation and economic growth: A long-run model of industrial dynamics. , 1994 .

[5]  R. Rob,et al.  Learning, Mutation, and Long Run Equilibria in Games , 1993 .

[6]  Bart Verspagen,et al.  Collective learning, innovation and growth in a boundedly rational, evolutionary world , 1994 .

[7]  S. Winter,et al.  An evolutionary theory of economic change , 1983 .

[8]  J. Maienschein.  Growth of biological thought , 1994, Nature.

[9]  Halina Kwasnicka,et al.  Market, innovation, competition: An evolutionary model of industrial dynamics , 1992 .

[10]  E. Kalai,et al.  Rational Learning Leads to Nash Equilibrium , 1993 .

[11]  R. Solow.  TECHNICAL CHANGE AND THE AGGREGATE PRODUCTION FUNCTION , 1957 .

[12]  B. Hedberg.  How Organizations Learn and Unlearn , 1981 .

[13]  P. David.  Clio and the Economics of QWERTY , 1985 .

[14]  Kim B. Clark,et al.  The Uneasy alliance: Managing the productivity-technology dilemma , 1985 .

[15]  B. Lundvall.  National Systems of Innovation , 1992 .

[16]  Victor Polterovich,et al.  Schumpeterian dynamics as a non-linear wave theory , 1991 .

[17]  P. Romer.  Increasing Returns and Long-Run Growth , 1986, Journal of Political Economy.

[18]  David A. Lane,et al.  Artificial worlds and economics, part I , 1993 .

[19]  David M. Kreps,et al.  Learning Mixed Equilibria , 1993 .

[20]  L. Soete,et al.  Technology Diffusion and the Rate of Technical Change , 1984 .

[21]  Arnulf Grubler,et al.  The Rise and Fall of Infrastructures: Dynamics of Evolution and Technological Change in Transport , 1990 .

[22]  Luigi Orsenigo,et al.  Innovation, Diversity and Diffusion: A Self-organisation Model , 1988 .

[23]  G. Dosi.  Technological Paradigms and Technological Trajectories: A Suggested Interpretation of the Determinants and Directions of Technical Change , 1982 .

[24]  Giovanni Dosi,et al.  Norms as emergent properties of adaptive learning: The case of economic routines , 1999 .

[25]  Alan Kirman,et al.  The economy as an evolving network , 1997 .

[26]  S. Bikhchandani,et al.  You have printed the following article : A Theory of Fads , Fashion , Custom , and Cultural Change as Informational Cascades , 2007 .

[27]  Martin Posch,et al.  Cycling in a stochastic learning algorithm for normal form games , 1997 .

[28]  H. Young,et al.  Learning dynamics in games with stochastic perturbations , 1995 .

[29]  Nathan Rosenberg,et al.  Inside the black box , 1983 .

[30]  J. Duffy,et al.  Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs , 1999 .

[31]  R. Nelson.  National Innovation Systems: A Comparative Analysis , 1993 .

[32]  E. Wilson,et al.  Genes, mind, and culture : the coevolutionary process , 1982 .

[33]  G. Dosi,et al.  Technical Change and Economic Theory , 1989 .

[34]  Nicolaas J. Vriend,et al.  Self-organization of markets: An example of a computational approach , 1995 .

[35]  Katsuhito Iwai,et al.  Schumpeterian dynamics : An evolutionary model of innovation and imitation , 1984 .

[36]  W. Brian Arthur,et al.  Path-dependent processes and the emergence of macro-structure , 1987 .

[37]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[38]  E. Mansfield.  The economics of technological change , 1968 .

[39]  Kenneth G. Binmore,et al.  Essays on Foundations of Game Theory , 1982 .

[40]  Chris Birchenhall,et al.  Genetic algorithms in evolutionary modelling , 1997 .

[41]  Gavin J. Wright.  An evolutionary theory of economic change , 1982 .

[42]  Nebojsa Nakicenovic,et al.  Technological Substitution and Long Waves in the USA , 1987 .

[43]  Luigi Marengo,et al.  Speculation, Heterogeneity and Learning: A Model of Exchange Rate Dynamics , 1995 .

[44]  Katsuhito Iwai,et al.  Schumpeterian dynamics, Part II: Technological progress, firm growth and `economic selection' , 1984 .

[45]  Nebojsa Nakicenovic,et al.  “The Dynamics of Energy Systems and the Logistic Substitution Model” (1979) , 1978, The Future of Nature.

[46]  Werner Ebeling,et al.  A stochastic model of technological evolution , 1992 .

[47]  C. Birchenhall,et al.  Is product life cycle theory a special case? Dominant designs and the emergence of market niches through coevolutionary-learning , 1998 .

[48]  D. Ricardo.  On the Principles of Political Economy and Taxation , 1891 .

[49]  James M. Utterback,et al.  A dynamic model of process and product innovation , 1975 .

[50]  Rod Coombs,et al.  Technological collaboration : the dynamics of cooperation in industrial innovation , 1996 .

[51]  Ellen R. McGrattan,et al.  Money as a medium of exchange in an economy with artificially intelligent agents , 1990 .

[52]  H. Peyton Young,et al.  Stochastic Evolutionary Game Dynamics , 1990 .

[53]  D. Fudenberg,et al.  Evolutionary Dynamics with Aggregate Shocks , 1992 .

[54]  Sidney G. Winter,et al.  Schumpeterian Competition in Alternative Technological Regimes , 1983 .

[55]  K. J. Sharma.  On learning to plan—And planning to learn: Donald N. Michael, Jossey-Bass Publishers, San Francisco, 1973, 341 pp., $12.50 , 1975 .

[56]  H. Simon,et al.  Models of Thought , 1979 .

[57]  Gunnar Eliasson.  The Firm and Financial Markets in the Swedish Micro-To-Macro Model: Theory, Model, and Verification , 1985 .

[58]  Francesca Chiaromonte,et al.  Heterogeneity, competition, and macroeconomic dynamics , 1993 .

[59]  Mark Feldman,et al.  On the generic nonconvergence of Bayesian actions and beliefs , 1990 .

[60]  K. Arrow.  The Economic Implications of Learning by Doing , 1962 .

[61]  Edward O. Wilson,et al.  Genes, Mind and Culture: The Coevolutionary Process. , 1982 .

[62]  Gerald Silverberg,et al.  Long waves and 'evolutionary chaos' in a simple Schumpeterian model of embodied technical change , 1993 .

[63]  R. Punnett,et al.  The Genetical Theory of Natural Selection , 1930, Nature.

[64]  Kristian Lindgren,et al.  Evolutionary phenomena in simple dynamics , 1992 .

[65]  T. Sargent.  Bounded rationality in macroeconomics , 1993 .