职务科技成果赋权改革政策效果研究——基于双重机器学习的因果推断

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Abstract The empowerment reform of job-related scientific and technological achievements is an important measure to promote the deep integration of science and technology with the economy and cultivate new quality productive forces.This paper constructs a dataset based on the patent data of 76 universities and research institutions from 2014 to 2023,and designs a quasi-natural experiment based on the“the Pilot Implementation Plan for Empowering Scientific and Technological Achievements Ownership or Long-term Use Right to Scientific Researchers”jointly issued by the Ministry of Science and Technology and another nine ministries in 2020.A double machine learning model is built to verify the promoting effect of the empowerment reform policy on the transformation of scientific and technological achievements,its promoting mechanism,and the heterogeneity of the promoting effect.The research finds that the empowerment reform can promote the transformation of scientific and technological achievements,mainly through promoting the collaboration of multiple innovation subjects.However,the three mechanisms of property rights structure change,increase in the quantity and quality of scientific and technological achievements have not shown significant effects yet.In addition,the promoting effect on the transformation of scientific and technological achievements varies due to the differences in the affiliation level and the nature of the units,with more obvious effects in central units and universities.Based on these findings,policy suggestions are proposed to improve the management mechanism of achievements,optimize the implementation mechanism of transformation,and build a complete transformation service system.

Key words： Job-related scientific and technological achievement Empowerment reform Transformation of scientific and technological achievement Double machine learning

Received: 10 September 2024

PACS:	D922.17
	G644

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	Articles by authors
	Tang Yichao
	Pan Chengli
	Li Jing
	Xiao Guohua
	Ma Shiying
	Ma Yucong

Cite this article:

Tang Yichao,Pan Chengli,Li Jing, et al. Research on the Effect of Policy on the Empowerment Reform of Job-Related Scientific and Technological Achievements: Causal Inference Based on Double Machine Learning[J]. , 2025, 6(7): 27-35.

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http://www.zgkjlt.org.cn/EN/ OR http://www.zgkjlt.org.cn/EN/Y2025/V6/I7/27

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