IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-030-58131-2_12.html
   My bibliography  Save this book chapter

Uniqueness in Planar Endogenous Business Cycle Theories

In: Keynesian, Sraffian, Computable and Dynamic Economics

Author

Listed:
  • Ragupathy Venkatachalam

    (University of London)

  • Ying-Fang Kao

    (Machine Learning and AI Division, Just Eat)

Abstract

We examine some uniqueness theorems concerning the attractors (limit cycles) of dynamic planar models of non-linear, endogenous theories of the business cycle. We confine our attention to the pioneering models of Goodwin, Kaldor, Hicks and their variations. For Goodwin’s non-linear multiplier-accelerator model with a single non-linearity, we provide sufficient conditions for establishing uniqueness of the limit cycle based on a theorem by de Figueiredo. We also discuss issues concerning the algorithmic decidability of the number of attractors for these models within the framework of computable analysis.

Suggested Citation

  • Ragupathy Venkatachalam & Ying-Fang Kao, 2021. "Uniqueness in Planar Endogenous Business Cycle Theories," Springer Books, in: Kumaraswamy Velupillai (ed.), Keynesian, Sraffian, Computable and Dynamic Economics, chapter 12, pages 273-310, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-58131-2_12
    DOI: 10.1007/978-3-030-58131-2_12
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:sprchp:978-3-030-58131-2_12. 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.