IDEAS home Printed from https://ideas.repec.org/a/sae/millen/v16y2025i1p102-128.html
   My bibliography  Save this article

Estimating Relative Tax Efficiency for Selected States in India: An Error Correction Approach

Author

Listed:
  • Dinesh Kumar Srivastava
  • Muralikrishna Bharadwaj
  • Tarrung Kapur
  • Ragini Trehan

Abstract

We estimate state-level tax efficiency in India using an error correction framework, making a distinction between a long-term cointegrating relationship and a short-term dynamics around it. We use a stochastic frontier approach in a panel data framework considering 17 medium and large (ML) states for the period 2004–2005 to 2019–2020. We find that the FC14’s initiative to sharply increase the states’ share in the divisible pool of central taxes had an adverse impact on states’ own tax revenues. The short-term relationship converges to the long-term relationship in 2.6 years. In terms of relative tax effort, the most efficient state was Tamil Nadu, while the least efficient was Bihar. Results from this study would be useful in averting the problem of adverse incentives, while determining the intergovernmental transfers. In the post-GST scenario, operating at their tax efficiency frontier would be critical for states especially in the light of discontinuation of the GST compensation cess.

Suggested Citation

  • Dinesh Kumar Srivastava & Muralikrishna Bharadwaj & Tarrung Kapur & Ragini Trehan, 2025. "Estimating Relative Tax Efficiency for Selected States in India: An Error Correction Approach," Millennial Asia, , vol. 16(1), pages 102-128, March.
    • Handle: RePEc:sae:millen:v:16:y:2025:i:1:p:102-128
    DOI: 10.1177/09763996231157048
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/09763996231157048
    Download Restriction: no
    File URL: https://libkey.io/10.1177/09763996231157048?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
    ---><---

    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:sae:millen:v:16:y:2025:i:1:p:102-128. 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: SAGE Publications (email available below). General contact details of provider: .

    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.