IDEAS home Printed from https://ideas.repec.org/a/taf/jnlbes/v43y2025i3p696-709.html
   My bibliography  Save this article

An Adaptive Kernel-Based Structural Change Test for Copulas

Author

Listed:
  • Xiaohui Lu
  • Yahong Zhou

Abstract

This article proposes a structural change test for copula models based on the kernel smoothing method. The proposed approach enables adaptable estimation of the dynamic marginal distributions, either parametrically or semi-parametrically. The test statistic is formulated via the weighted quadratic distance between the local smoothing copula and the empirical copula function, using pseudo-observations of marginal distributions. The test statistic is pivotal with an asymptotic standard Normal distribution, irrespective of the marginal distributions, parameters, and estimations, and is consistent against a wide range of smoothly transitioning structural changes as well as abrupt structural breaks for copula models. Monte Carlo simulations show that the test performs well in finite samples and outperforms existing tests in the case of periodic changes.

Suggested Citation

  • Xiaohui Lu & Yahong Zhou, 2025. "An Adaptive Kernel-Based Structural Change Test for Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(3), pages 696-709, July.
    • Handle: RePEc:taf:jnlbes:v:43:y:2025:i:3:p:696-709
    DOI: 10.1080/07350015.2024.2422980
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07350015.2024.2422980
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07350015.2024.2422980?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    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:taf:jnlbes:v:43:y:2025:i:3:p:696-709. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UBES20 .

    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.