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Using simple neural networks to analyse firm activity

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  • Michael Dietrich

    (Department of Economics, The University of Sheffield)

Abstract

IntroductionCharacteristically, in economics, the analysis of firm activity is based on a production function that defines a deterministic relationship between factor inputs and firm output. The analysis of the firm as an organisation takes a somewhat different approach. For instance, behavioural economics (for example Simon, 1955; March and Simon, 1958; Cyert and March, 1963), transaction cost theory (Williamson, 1975, 1985) and capabilities approaches (for example Foss and Loasby, 1998; Foss, 2005) emphasise that economic agents have inevitably incomplete information and knowledge and are at most boundedly or limitedly rational. The implication here is that while general principles governing intra-firm interaction can be specified, detailed organisational processes inside the firm are, for practical academic purposes, effectively unobservable. Hence, the usual analytical tools designed to analyse firm behaviour, based on production functions and optimising principles with full information, are in practice an oversimplification of firm activity (Loasby, 1999).

Suggested Citation

  • Michael Dietrich, 2005. "Using simple neural networks to analyse firm activity," Working Papers 2005014, The University of Sheffield, Department of Economics, revised Jul 2005.
    • Handle: RePEc:shf:wpaper:2005014
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    File URL: http://www.shef.ac.uk/content/1/c6/03/91/72/SERP2005014.pdf
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    References listed on IDEAS

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    3. Daniel Santin & Francisco Delgado & Aurelia Valino, 2004. "The measurement of technical efficiency: a neural network approach," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 627-635.
    4. Christos Papadas & W. George Hutchinson, 2002. "Neural network forecasts of input-output technology," Applied Economics, Taylor & Francis Journals, vol. 34(13), pages 1607-1615.
    5. Michael Dietrich, 2003. "The importance of management and transaction costs for large UK firms," Applied Economics, Taylor & Francis Journals, vol. 35(11), pages 1317-1329.
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    Cited by:

    1. Michael Dietrich, 2006. "Neural networks and the evolution of firms and industries: An application to UK SIC34 and SIC72," Working Papers 2006007, The University of Sheffield, Department of Economics, revised May 2006.

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