IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v30y2023i18p2560-2564.html
   My bibliography  Save this article

Performance feedback and strategic R&D classification: a further study of R&D tax credit

Author

Listed:
  • Furong Guo
  • Niannian Wu
  • Lei Zhu

Abstract

Tax incentives are an important measure in most industrial countries to support firms R&D. However, R&D tax credit leads firms to engage in strategic R&D classification that classifies indirect costs as eligible R&D inputs in order to reduce tax liability. Based on the behavioural theory of the firm, we investigate the impact of performance feedback on firm’s strategic R&D classification. The results show that when performance falls below aspirations, the pressure to achieve aspirations forces firms to reduce strategic R&D classification; when performance is above aspirations, in order to reduce tax liabilities, firms are more willing to engage in strategic R&D classification due to the lack of performance pressure. Our study helps to understand horizontal differences in R&D investment in the context of tax incentives.

Suggested Citation

  • Furong Guo & Niannian Wu & Lei Zhu, 2023. "Performance feedback and strategic R&D classification: a further study of R&D tax credit," Applied Economics Letters, Taylor & Francis Journals, vol. 30(18), pages 2560-2564, October.
    • Handle: RePEc:taf:apeclt:v:30:y:2023:i:18:p:2560-2564
    DOI: 10.1080/13504851.2022.2099795
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2022.2099795
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2022.2099795?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 search 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:apeclt:v:30:y:2023:i:18:p:2560-2564. 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/RAEL20 .

    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.