Neo-Schumpeterian Simulation Models

Windrum, Paul (2004). Neo-Schumpeterian Simulation Models. UNU-MERIT Research Memoranda. UNU-MERIT.

Document type:

  • Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials)
    Name Description MIMEType Size Downloads
    rm2004-002.pdf PDF application/pdf 205.49KB
  • Sub-type Working paper
    Author Windrum, Paul
    Title Neo-Schumpeterian Simulation Models
    Series Title UNU-MERIT Research Memoranda
    Volume/Issue No. 2
    Publication Date 2004
    Publisher UNU-MERIT
    Language eng
    Abstract The use of simulation modelling techniques by neo-Schumpeterian economists dates back to Nelson and Winter's 1982 book 'An Evolutionary Theory of Economic Change', and has rapidly expanded ever since. This paper considers the way in which successive generations of models have extended the boundaries of research (both with respect to the range of phenomena considered and the different dimensions of innovation that are considered), and while simultaneously introducing novel modelling techniques. At the same time, the paper will highlight the distinct set of features that have emerged in these neo-Schumpeterian models, and which set them apart from the models developed by other schools. In particular, they share a distinct view about the type of world in which real economic agents operate, and a invariably contain a generic set of algorithms. In addition to reviewing past models, the paper considers a number of pressing issues that remain unresolved and which modellers will need to address in future. Notable amongst these are the methodological relationship between empirical studies and simulation (e.g. 'history friendly modelling'), the development of common standards for sensitivity analysis, and the need to further extend the boundaries of research in order to consider important aspects of innovation and technical change.
    Copyright Year 2004
    Copyright type All rights reserved
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 401 Abstract Views, 255 File Downloads  -  Detailed Statistics
    Created: Fri, 13 Dec 2013, 12:40:36 JST