IDEAS home Printed from https://ideas.repec.org/a/ids/ijlica/v17y2020i2p187-211.html
   My bibliography  Save this article

Is the influence of intellectual capital on firm performance homogeneous? Evidence from India employing quantile regression model

Author

Listed:
  • Santi Gopal Maji
  • Mitra Goswami

Abstract

This paper investigates the association between intellectual capital (IC) and firm performance by employing quantile regression model to derive robust and complete association that the classical mean regression fails to extricate. Secondary data on 253 listed Indian firms are collected from 'Capitaline Plus' corporate database for a period of 16 years from 1999-2000 to 2014-2015. IC and its components are computed using Pulic's value added intellectual coefficient (VAIC) model and firm performance is measured by return on asset (ROA). Both pooled OLS and quantile regression models are used to test the hypotheses. The results indicate that the pooled ordinary least square regression provides an incomplete picture about IC efficiency of firms. The results of quantile regression indicate that the positive influence of intellectual capital is higher at upper quantiles. The results also reveal that intellectual capital is a vital factor that creates a significant difference between out-performing and non-performing firms.

Suggested Citation

  • Santi Gopal Maji & Mitra Goswami, 2020. "Is the influence of intellectual capital on firm performance homogeneous? Evidence from India employing quantile regression model," International Journal of Learning and Intellectual Capital, Inderscience Enterprises Ltd, vol. 17(2), pages 187-211.
    • Handle: RePEc:ids:ijlica:v:17:y:2020:i:2:p:187-211
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=108897
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijlica:v:17:y:2020:i:2:p:187-211. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=86 .

    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.