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Productivity in China's high technology industry: Regional heterogeneity and R&D

Author

Listed:
  • Zhang, Rui
  • Sun, Kai
  • Delgado, Michael S.
  • Kumbhakar, Subal C.

Abstract

This paper analyzes the impact of Research and Development (R&D) on the productivity of China's high technology industry. In order to capture important differences in the effect of R&D on output that arise from geographic and socioeconomic differences across three major regions in China, we use a novel semiparametric approach that allows us to model heterogeneities across provinces and time. Using a unique provincial level panel dataset spanning the period 2000–2007, we find that the impact of R&D on output varies substantially in terms of magnitude and significance across different regions. Results show that the eastern region benefits the most from R&D investments, however it benefits the least from technical progress, while the western region benefits the least from R&D investments, but enjoys the highest benefits from technical progress. The central region benefits from R&D investments more than the western region and benefits from technical progress more than the eastern region. Our results suggest that R&D investments would significantly increase output in both the eastern and central regions, however technical progress in the central region may further compound the effects of R&D on output within the region.

Suggested Citation

  • Zhang, Rui & Sun, Kai & Delgado, Michael S. & Kumbhakar, Subal C., 2012. "Productivity in China's high technology industry: Regional heterogeneity and R&D," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 127-141.
  • Handle: RePEc:eee:tefoso:v:79:y:2012:i:1:p:127-141
    DOI: 10.1016/j.techfore.2011.08.005
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    Cited by:

    1. Delgado, Michael S. & McCloud, Nadine & Kumbhakar, Subal C., 2014. "A generalized empirical model of corruption, foreign direct investment, and growth," Journal of Macroeconomics, Elsevier, vol. 42(C), pages 298-316.
    2. Xie, Hualin & Wang, Wei & Yang, Zihui & Choi, Yongrok, 2016. "Measuring the sustainable performance of industrial land utilization in major industrial zones of China," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 207-219.
    3. Marian Rizov & Xufei Zhang, 2014. "Regional disparities and productivity in China: Evidence from manufacturing micro data," Papers in Regional Science, Wiley Blackwell, vol. 93(2), pages 321-339, June.
    4. Subal C. Kumbhakar & Kai Sun & Rui Zhang, 2016. "Semiparametric Smooth Coefficient Estimation of a Production System," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 464-482, October.
    5. repec:eee:deveco:v:132:y:2018:i:c:p:18-31 is not listed on IDEAS
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    9. repec:eee:tefoso:v:135:y:2018:i:c:p:83-90 is not listed on IDEAS

    More about this item

    Keywords

    China; Research and Development (R&D); Productivity; Semiparametric smooth coefficient model (SPSCM);

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • L00 - Industrial Organization - - General - - - General

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