IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789811270277_0037.html
   My bibliography  Save this book chapter

Can Tax Cuts Promote Green Innovation? — Based on Empirical Evidence of A-Share Listed Companies in Heavy Pollution Industries

In: Economic Management and Big Data Application Proceedings of the 3rd International Conference

Author

Listed:
  • Fan Xiang

Abstract

Using the green patent data of A-share listed companies in China’s heavy pollution industry from 2011 to 2020, this paper empirically tests the effect of tax reduction on the green innovation level of enterprises. The findings are as follows: First, tax reduction can significantly improve the level of green innovation. Second, R&D investment is one of the influencing mechanisms of tax reduction to improve the level of green innovation. Third, the incentive effect of tax reduction on the green innovation level of enterprises is more significant in non-state-owned enterprises, and the green innovation level increases by about 3.013% for every 1% reduction in tax burden. Fourthly, after the robustness test, the conclusion of the paper still stands. Finally, this paper puts forward some suggestions on how tax reduction can improve enterprise green innovation.

Suggested Citation

  • Fan Xiang, 2024. "Can Tax Cuts Promote Green Innovation? — Based on Empirical Evidence of A-Share Listed Companies in Heavy Pollution Industries," World Scientific Book Chapters, in: Sikandar Ali Qalati (ed.), Economic Management and Big Data Application Proceedings of the 3rd International Conference, chapter 37, pages 406-414, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811270277_0037
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789811270277_0037
    Download Restriction: Ebook Access is available upon purchase.
    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789811270277_0037
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

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

    More about this item

    Keywords

    Big Data; Information Management; Economic; Data Applications; Blockchain; E-commerce;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology

    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:wsi:wschap:9789811270277_0037. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.