IDEAS home Printed from
   My bibliography  Save this article

Scientific productivity paradox: The case of China's S&T system


  • Can Huang

    (Department of Economics, Management and Industrial Engineering, University of Aveiro, Campus Universitário de Santiago)

  • Celeste Amorim Varum

    (Department of Economics, Management and Industrial Engineering, University of Aveiro, Campus Universitário de Santiago)

  • Joaquim Borges Gouveia

    (Department of Economics, Management and Industrial Engineering, University of Aveiro, Campus Universitário de Santiago)


Summary In 1985 China began the reform of its Science & Technology (S&T) sector inherited from the planned economy. To disclose the impact of the drawn-out reform on the efficiency of the whole sector, we measure the scientific productivity of China's S&T institutes. The analysis is based on R&D input and output data at the country aggregate and provincial level. We utilize Polynomial Distributed Lag model to uncover the structure of the lag between R&D input and output. The findings reveal that the growth rate of scientific productivity of China's S&T institutes has been negative since the 1990s.

Suggested Citation

  • Can Huang & Celeste Amorim Varum & Joaquim Borges Gouveia, 2006. "Scientific productivity paradox: The case of China's S&T system," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 449-473, November.
  • Handle: RePEc:spr:scient:v:69:y:2006:i:2:d:10.1007_s11192-006-0153-6
    DOI: 10.1007/s11192-006-0153-6

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

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


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

    Cited by:

    1. Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
    2. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    3. Jiancheng Guan & Kaihua Chen, 2010. "Modeling macro-R&D production frontier performance: an application to Chinese province-level R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 165-173, January.
    4. Aristovnik, Aleksander, 2014. "Efficiency of the R&D Sector in the EU-27 at the Regional Level: An Application of DEA," MPRA Paper 59081, University Library of Munich, Germany.

    More about this item


    Access and download statistics


    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:spr:scient:v:69:y:2006:i:2:d:10.1007_s11192-006-0153-6. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.