IDEAS home Printed from
   My bibliography  Save this paper

Factor Intensity reversal and Chaos I


  • Aditya Goenaka
  • Odile Poulsen


We derive necessary and sufficient conditions for the occurrence of ergodic oscillations and geometric sensitivity in a two-sector model of economic growth with labor augmenting externalities. We transform the Euler equation into a first order backward first order equation. Factor intensity reversal is a necessary condition for the dynamics to be chaotic, both in the sense of ergodic oscillations and geometric sensitivity when utility is linear. Under reasonable assumptions on the economic fundamentals, we show that a necessary and sufficient condition for the occurrence of ergodic oscillations and geometric sensitivity is that the representative consumer is sufficiently patient.

Suggested Citation

  • Aditya Goenaka & Odile Poulsen, 2004. "Factor Intensity reversal and Chaos I," Econometric Society 2004 Australasian Meetings 86, Econometric Society.
  • Handle: RePEc:ecm:ausm04:86

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Lawrence L. Wu, 2000. "Some Comments on “Sequence Analysis and Optimal Matching Methods in Sociology: Review and Prospectâ€," Sociological Methods & Research, , vol. 29(1), pages 41-64, August.
    2. Cramer, J. S. & Ridder, G., 1991. "Pooling states in the multinomial logit model," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 267-272, February.
    3. Duncan McVicar & Michael Anyadike-Danes, 2002. "Predicting successful and unsuccessful transitions from school to work by using sequence methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 317-334.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Labor-augmenting externalities; backward dynamics; factor intensity reversal; ergodic oscillations; geometric sensitivity;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

    NEP fields

    This paper has been announced in the following NEP Reports:


    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:ecm:ausm04:86. 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: (Christopher F. Baum). 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.