IDEAS home Printed from https://ideas.repec.org/p/esy/uefcwp/21684.html
   My bibliography  Save this paper

Time-Varying Parameters in Continuous and Discrete Time

Author

Listed:
  • Chambers, Marcus J
  • Taylor, AM Robert

Abstract

We consider models for both deterministic one-time and continuous stochastic parameter change in a continuous time autoregressive model around a deterministic trend function. For the latter we focus on the case where the autoregressive parameter itself follows a first-order autoregression. Exact discrete time analogue models are detailed in each case and compared to corresponding parameter change models adopted in the discrete time literature. The relationships between the parameters in the continuous time models and their discrete time analogues are also explored. For the one- time parameter change model the discrete time models used in the literature can be justified by the corresponding continuous time model, with a only a minor modification needed for the (most likely) case where the changepoint does not coincide with one of the discrete time observation points. For the stochastic parameter change model considered we show that the resulting discrete time model is characterised by an autoregressive parameter the logarithm of which follows an ARMA(1,1) process. We discuss how this relates to models which have been proposed in the discrete time stochastic unit root literature. The implications of our results for a number of extant discrete time models and testing procedures are discussed.

Suggested Citation

  • Chambers, Marcus J & Taylor, AM Robert, 2018. "Time-Varying Parameters in Continuous and Discrete Time," Essex Finance Centre Working Papers 21684, University of Essex, Essex Business School.
  • Handle: RePEc:esy:uefcwp:21684
    as

    Download full text from publisher

    File URL: http://repository.essex.ac.uk/21684/
    File Function: original version
    Download Restriction: no

    More about this item

    Keywords

    Time-varying parameters; continuous and discrete time; autoregression; trendbreak; unit root; persistence change; explosive bubbles; random coeffcient models;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:esy:uefcwp:21684. 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: (Nikolaos Vlastakis). General contact details of provider: http://edirc.repec.org/data/fcessuk.html .

    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.