IDEAS home Printed from https://ideas.repec.org/a/spr/joevec/v9y1999i1p109-133.html
   My bibliography  Save this article

Detecting self-organisational change in economic processes exhibiting logistic growth

Author

Listed:
  • John Foster

    (Department of Economics, University of Queensland, Brisbane QLD 4072, Australia)

  • Phillip Wild

    (The School of Economic Studies, University of Manchester, Manchester M13 9PL, UK)

Abstract

This paper offers an econometric methodology for the detection of self-organisational change (defined in terms of the presence of time irreversibility, structural change and fundamental uncertainty) in economic processes that follow logistic diffusion growth paths in historical time. The approach we adopted is built upon recent developments in `moving window' spectral methods which are applied to the scaled residuals generated by estimated logistic diffusion models. We illustrate the use of such methods by examining the case of a financial instrument, namely, the Australian Building Society Deposit, which experienced logistic growth in its market share until bank deregulation was enacted in the 1980s. We show that there is clear evidence that self-organisational change is present over the historical period considered.

Suggested Citation

  • John Foster & Phillip Wild, 1999. "Detecting self-organisational change in economic processes exhibiting logistic growth," Journal of Evolutionary Economics, Springer, vol. 9(1), pages 109-133.
    • Handle: RePEc:spr:joevec:v:9:y:1999:i:1:p:109-133
    as

    Download full text from publisher

    File URL: http://link.springer.de/link/service/journals/00191/papers/9009001/90090109.pdf
    Download Restriction: Access to the full text of the articles in this series is restricted
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. John Foster, 2016. "The Australian growth miracle: an evolutionary macroeconomic explanation," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 40(3), pages 871-894.
    2. Gardebroek, Cornelis, 2008. "Evaluating Different Growth Scenarios for Organic Farming Using Bayesian Techniques," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44211, European Association of Agricultural Economists.
    3. John Foster, 2015. "Energy, Knowledge and Economic Growth," Economic Complexity and Evolution, in: Andreas Pyka & John Foster (ed.), The Evolution of Economic and Innovation Systems, edition 127, pages 9-39, Springer.
    4. Oleg S. SUKHAREV, 2019. "Managing the technological development structure: Risk and “interest portfolio”," Upravlenets, Ural State University of Economics, vol. 10(1), pages 2-15, March.
    5. Foster, John & Metcalfe, J. Stan, 2012. "Economic emergence: An evolutionary economic perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 420-432.
    6. Foster, John, 2021. "In search of a suitable heuristic for evolutionary economics: from generalized Darwinism to economic self-organisation," MPRA Paper 106146, University Library of Munich, Germany.
    7. Hinich, Melvin J. & Foster, John & Wild, Phillip, 2006. "Structural change in macroeconomic time series: A complex systems perspective," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 136-150, March.
    8. John Foster & Jason Potts, 2009. "A micro-meso-macro perspective on the methodology of evolutionary economics: Integrating history, simulation and econometrics," Springer Books, in: Uwe Cantner & Jean-Luc Gaffard & Lionel Nesta (ed.), Schumpeterian Perspectives on Innovation, Competition and Growth, pages 53-68, Springer.
    9. J.S. Metcalfe, 2005. "Ed Mansfield and the Diffusion of Innovation: An Evolutionary Connection," The Journal of Technology Transfer, Springer, vol. 30(2_2), pages 171-181, January.
    10. John Foster, 2011. "Evolutionary macroeconomics: a research agenda," Journal of Evolutionary Economics, Springer, vol. 21(1), pages 5-28, February.

    More about this item

    Keywords

    Discontinuity ; Evolution ; Logistic diffusion ; Non-linearity ; Non-stationarity ; Self-organisation ; Spectral methods;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • N1 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations
    • N2 - Economic History - - Financial Markets and Institutions

    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:spr:joevec:v:9:y:1999:i:1:p:109-133. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.