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Neural networks and the evolution of firms and industries: An application to UK SIC34 and SIC72

Dietrich, M. (2006) Neural networks and the evolution of firms and industries: An application to UK SIC34 and SIC72. Working Paper. Department of Economics, University of Sheffield ISSN 1749-8368

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Abstract

This paper considers whether neural networks might be used to analyse firm activity and the evolution of industries. The key findings of the simulation results used are summarised as follows. While efficiency seeking behaviour has growth advantages, compared to unchanged firms, these are small compared to the growth advantages that are displayed with firms that are able to exploit input use variability. In addition the two sectors analysed here (UK SIC34 and SIC72) show different profit implications of these growth advantages. In SIC34 an increase in firm growth caused by strategic flexibility coincides with an increase in profitability, whereas in SIC72 the increase in firm growth coincides with a profitability reduction. This difference is explained in terms of the differing market structures in the two sectors along with the differing effects of market shocks. Finally the market structure effects of differing firm types have been analysed. It is shown that factor flexibility generates relative growth advantages that benefit smaller firms. But strategic flexibility generates relative growth effects that benefit larger firms.

Item Type: Monograph (Working Paper)
Copyright, Publisher and Additional Information: The Sheffield Economics Research Paper (SERP) series offers a forum for the research output of the academic staff and research students of the Department of Economics, University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. All papers may be downloaded free on the understanding that the contents are preliminary and therefore permission from the author(s) should be sought before they are referenced.
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) > Sheffield Economics Research Papers Series
Depositing User: Repository Officer
Date Deposited: 20 Oct 2009 15:03
Last Modified: 08 Feb 2013 16:59
Published Version: http://www.shef.ac.uk/economics/research/serps/yea...
Status: Published
Publisher: Department of Economics, University of Sheffield
Identification Number: Sheffield Economic Research Paper Series 2006007
URI: http://eprints.whiterose.ac.uk/id/eprint/9945

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