IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v59y2025i5d10.1007_s11135-025-02136-4.html
   My bibliography  Save this article

Methodological guide to the augmented ARDL model: step-by-step application with South Korean data

Author

Listed:
  • Muhammad Raees Shaik Saffarudin

    (Sunway College Johor Bahru)

  • Soo Khoon Goh

    (Universiti Sains Malaysia)

  • Robert McNown

    (University of Colorado at Boulder)

Abstract

This paper provides a detailed, step-by-step guide for implementing the Augmented Autoregressive Distributed Lag (A-ARDL) method, focusing on the aging-income inequality nexus in South Korea. The A-ARDL method has gained popularity in fields such as energy, development, and population economics due to its enhanced robustness in testing long-run relationships. The vital contribution of the A-ARDL model is that it complements the existing two tests in the ARDL model by incorporating an extra F-test on the lagged-level of the independent variable(s), significantly reducing the risk of spurious cointegration. Despite its advantages, a common challenge in applying the A-ARDL model is the lack of easily accessible program code. Consequently, many researchers rely on automated ARDL procedures in EViews, which often omit the additional test. To that effect, this paper offers a structured, stepwise approach to applying the A-ARDL model, enabling researchers to correctly replicate, apply, and interpret their findings for more effective policy analysis.

Suggested Citation

  • Muhammad Raees Shaik Saffarudin & Soo Khoon Goh & Robert McNown, 2025. "Methodological guide to the augmented ARDL model: step-by-step application with South Korean data," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(5), pages 4631-4646, October.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:5:d:10.1007_s11135-025-02136-4
    DOI: 10.1007/s11135-025-02136-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-025-02136-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-025-02136-4?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

    Keywords

    ;
    ;
    ;
    ;

    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:spr:qualqt:v:59:y:2025:i:5:d:10.1007_s11135-025-02136-4. 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.