Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity

Zhenbing Yang, Shuai Shao, Chengyu Li and Lili Yang

Technological Forecasting and Social Change, 2020, vol. 151, issue C

Abstract: Although China's technological strength has improved, the country's innovation inefficiency caused by research & development (R&D) resource misallocation should be addressed. Using the heterogeneous stochastic frontier approach and the panel data of China's 28 manufacturing sectors from 2001 to 2015, this paper estimates innovative technical efficiency, the output elasticity of R&D inputs, the factor-biased indicators of technological innovation, and the elasticity of substitution between R&D inputs. Ways to alleviate R&D resource misallocation are discussed based on these indicators. We find that the innovative technical efficiency of China's manufacturing sector is less than 1 and exhibits a markedly fluctuating trend, implying that R&D inputs are severely misallocated. The output elasticity of R&D capital experiences a continuously downward trend, while that of R&D personnel presents a stably upward trend. Overall, the technological innovation of China's manufacturing sector was biased to R&D personnel in the period of 2002–2013, and then presented a fluctuating change in the period of 2014–2015. R&D capital and R&D personnel exhibited a stable substitution relationship from 2008 to 2015. However, during the period of 2001–2007, the relationship between these two R&D inputs changed alternately. Finally, we provide some solutions to alleviate the misallocation of R&D resources for different sub-sectors according to the output elasticities of R&D inputs, the factor-biased level of technological innovation, and the substitution relationship between R&D inputs. Specifically, it is necessary to increase the input of R&D factor with a higher output elasticity by adjusting the factor-biased level of technological innovation.

Keywords: Misallocation of R&D inputs; Factor-biased technological innovation; Substitution elasticity; Innovation efficiency; Heterogeneous stochastic frontier approach; China (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162519310996
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:151:y:2020:i:c:s0040162519310996

DOI: 10.1016/j.techfore.2019.119878

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().