IDEAS home Printed from https://ideas.repec.org/a/eee/chieco/v57y2019ics1043951x19300914.html
   My bibliography  Save this article

Does the high- and new-technology enterprise program promote innovative performance? Evidence from Chinese firms

Author

Listed:
  • Dai, Xiaoyong
  • Wang, Fang

Abstract

This study evaluates the unique high- and new-technology enterprise (HNTE) program implemented in China. The program grants a reduced corporate income tax rate to certificated HNTEs. Based on a sample of Chinese listed firms during 2006–2016, we investigate the impact of HNTE certification on firms' R&D intensity and productivity using a combination of the propensity score matching approach and difference-in-differences estimator. The results confirm the overall effectiveness of the program in promoting innovative performance among Chinese listed firms in terms of both R&D intensity and productivity. Such effects are persistent over the valid certification period. However, the overall effects mask substantial heterogeneity across different types of certification users. Positive effects are mainly driven by repeatedly certificated firms, while no significant effects are found for firms acquiring their HNTE certificate for the first time. By distinguishing one-time and highly qualified certifications, we reveal the potential existence of fraudulent HNTEs. These results imply that the effectiveness of government programs in supporting innovation could be improved through a more thorough policy design and implementation.

Suggested Citation

  • Dai, Xiaoyong & Wang, Fang, 2019. "Does the high- and new-technology enterprise program promote innovative performance? Evidence from Chinese firms," China Economic Review, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:chieco:v:57:y:2019:i:c:s1043951x19300914
    DOI: 10.1016/j.chieco.2019.101330
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1043951X19300914
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chieco.2019.101330?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mulligan, Kevin & Lenihan, Helena & Doran, Justin & Roper, Stephen, 2022. "Harnessing the science base: Results from a national programme using publicly-funded research centres to reshape firms’ R&D," Research Policy, Elsevier, vol. 51(4).
    2. Dai, Xiaoyong & Wang, Mengqi, 2024. "Unintended effects of tax incentives on firms’ strategic patenting," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 1-24.
    3. Zhang, Hongyan & Zhang, Lin, 2023. "Public support and energy innovation: Why do firms react differently?," Energy Economics, Elsevier, vol. 119(C).
    4. Fu, Minghui & Liu, Chuanjiang & Yang, Mian, 2020. "Effects of public health policies on the health status and medical service utilization of Chinese internal migrants," China Economic Review, Elsevier, vol. 62(C).
    5. Liu, Changqing & Li, Lei, 2021. "Place-based techno-industrial policy and innovation: Government responses to the information revolution in China," China Economic Review, Elsevier, vol. 66(C).
    6. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    7. Bai, Caiquan & Liu, Hangjuan & Zhang, Rongjie & Feng, Chen, 2023. "Blessing or curse? Market-driven environmental regulation and enterprises' total factor productivity: Evidence from China's carbon market pilots," Energy Economics, Elsevier, vol. 117(C).
    8. Ding, Jinxiu & Lu, Zhe & Yu, Chin-Hsien, 2022. "Environmental information disclosure and firms’ green innovation: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 147-159.
    9. Yue Zhu & Ziyuan Sun & Ling Wang & Xiaoping Wang & Lu Zhang, 2020. "Research on Innovation Catering Behavior and Its Economic Consequences—An Empirical Analysis Based on Threshold Regression Model," Sustainability, MDPI, vol. 12(19), pages 1-15, October.
    10. Yang, Baochen & Song, Xinyu, 2023. "Does oil price uncertainty matter in firm innovation? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 88(C).
    11. Dai, Xiaoyong & Chapman, Gary, 2022. "R&D tax incentives and innovation: Examining the role of programme design in China," Technovation, Elsevier, vol. 113(C).
    12. Yu, Anyu & Zhang, Qin & Yu, Rongjian & Cheng, Yu, 2023. "More is better or in waste? A resource allocation measure of government grants for facilitating firm innovations," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    13. Wen Qi & Yanyang Yan & Hongbing Yin, 2023. "Protecting Innovation Sustainability: R&D Manipulation and Effective Regulation Based on a Two-Scenario Evolutionary Game Perspective," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    14. Bai, Min & Li, Shihe & Lien, Donald & Yu, Chia-Feng (Jeffrey), 2022. "The winner's curse in high-tech enterprise certification: Evidence from stock price crash risk," International Review of Financial Analysis, Elsevier, vol. 82(C).

    More about this item

    Keywords

    HNTE certification; R&D intensity; Productivity; Chinese listed firms;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation
    • L52 - Industrial Organization - - Regulation and Industrial Policy - - - Industrial Policy; Sectoral Planning Methods
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    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:eee:chieco:v:57:y:2019:i:c:s1043951x19300914. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/chieco .

    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.