IDEAS home Printed from
   My bibliography  Save this article

Non-linear effects in knowledge production


  • Purica, Ionut

    () (Institute for Economic Forecasting, Bucharest.)


The generation of technological knowledge is paramount to our present development. Economic science concentrates on representing the functions of production applied to all sectors, e.g., the well known Cobb-Douglas model, associated with parameters such as capital and labor. Based on the paradigm, demonstrated in another paper, that the production of technological knowledge is governed by the same Cobb-Douglas type model, by the means of research and the intelligence level replacing capital, respectively labor, we are exploring the basic behavior of present days economies that are producing technological knowledge, along with the 'usual' industrial production. Considering the intercorrelations of technology and industrial production we determine a basic behavior that turns out to be a 'Henon attractor', well known as one of the first analyzed systems that present chaotic behavior confined to strange attractors. The behavior inside the basin of the attractor's dynamic shows some interesting features such as the fact that too little effort in technological knowledge production is associated to low industrial production, while too much resource allocation to technological production is also reaching an area of low industrial production. This effect clearly shows that too little allocation of resources to research is equivalent to a disproportionate allocation of resources to research, namely that both hamper the industrial production. Moreover, there is an area of large industrial production that corresponds to a certain rate of technology production that, in some way, optimizes development. Measures are introduced for the gain of technological knowledge and the information of technological sequences that are based on the underlying multi-valued logic of the technological research and on nonlinear thermodynamic considerations. We have witnessed in the last decades several cases of economies, e.g., Ireland and Finland, in Europe, the Asian tigers and China in Asia, which had had a moment in their history when research (both means and intelligence) was a main priority. Luckily, the globalization acted as a stabilizer that kept them close to the optimum of 'As High As Reasonably Acceptable' technological production. By contrast to ALARA (as low as reasonably acceptable) principle, that applies in risk analysis, here we may introduce the AHARA principle resulting from the nonlinear behavior of technological production vs. industrial production.

Suggested Citation

  • Purica, Ionut, 2006. "Non-linear effects in knowledge production," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 3(4), pages 51-70, December.
  • Handle: RePEc:rjr:romjef:v:3:y:2006:i:4:p:51-70

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Iancu, Aurel, 2011. "Models of Financial System Fragility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 230-256, March.
    2. Altar, Moisa & Necula, Ciprian & Bobeica, Gabriel, 2008. "Modeling The Economic Growth In Romania. The Role Of Human Capital," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 115-128, September.

    More about this item


    knowledge management; strange attractors; experimental state of knowledge;

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty


    Access and download statistics


    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:rjr:romjef:v:3:y:2006:i:4:p:51-70. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.