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

SummaryIn 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.

[1]  Loet Leydesdorff,et al.  Are the contributions of China and Korea upsetting the world system of science? , 2005, Scientometrics.

[2]  Z. Griliches,et al.  Measuring Science: An Exploration , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986 .

[4]  P. Phillips.  Testing for a Unit Root in Time Series Regression , 1988 .

[5]  Jialian Shen.  Chinese patent applications reach six figures in 1996 , 1997 .

[6]  Werner Meske,et al.  Institutional transformation of S&T systems in the European economies in transition: Comparative analysis , 1998 .

[7]  Qiwen Lu.  Learning and innovation in a transitional economy: the rise of science and technology enterprises in the Chinese information technology industry , 2001 .

[8]  K. C. Garg.  Scientometrics of laser research in India and China , 2004, Scientometrics.

[9]  Nan Ma,et al.  A comparative study of research performance in computer science , 2004, Scientometrics.

[10]  Zvi Griliches,et al.  Research Productivity in a System of Universities , 1998 .

[11]  Ronald Zhao,et al.  Transition in R&D management control system: Case study of a biotechnology research institute in China , 2003 .

[12]  L. Xue.  A historical perspective of China's innovation system reform: a case study , 1997 .

[13]  J. Stock,et al.  Efficient Tests for an Autoregressive Unit Root , 1992 .

[14]  Slavo Radosevic,et al.  Transformation of science and technology systems into systems of innovation in central and eastern Europe: the emerging patterns and determinants , 1999 .

[15]  Borges Gouveia,et al.  Organization, Programme and Structure: An Analysis of the Chinese Innovation Policy Framework , 2004 .

[16]  P. Zhou,et al.  The Emergence of China as a Leading Nation in Science. Research Policy, 35(1), 2006, 83-104. , 2006, 0911.3421.

[17]  Eugène Zaleski.  Science policy in the USSR , 1969 .

[18]  Henk F. Moed,et al.  Measuring China"s research performance using the Science Citation Index , 2002, Scientometrics.

[19]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[20]  Xielin Liu,et al.  An exploration into regional variation in innovative activity in China , 2001, Int. J. Technol. Manag..

[21]  Slavo Radosevic.  Patterns of preservation, restructuring and survival: science and technology policy in Russia in post-Soviet era , 2003 .

[22]  Z. Griliches,et al.  Econometric Models for Count Data with an Application to the Patents-R&D Relationship , 1984 .

[23]  K. Pavitt,et al.  The Comparative Economics of Research Development and Innovation in East and West , 2002 .

[24]  Q. Wang.  China's Industrial Technology: Market Reform and Organisational Change: Shulin Gu, Routledge, London, 1999, 369 pp, [UK pound]65.00, ISBN 0415197414 , 2001 .