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基于PMC-AE指数模型的科技金融政策定量评估——以中国“十三五”以来科技金融政策为例

Quantitative evaluation of science and technology financial policies based on the PMC-AE index model: A case study of China's science and technology financial policies since the 13th five-year plan.

作者信息

Shen Hongyuan, Xiong Panyu, Yang Linfeng, Zhou Ling

机构信息

School of Economics and Management, Southwest University of Science and Technology, Mianyang, China.

China Three Gorges Group Basin Management Center, Yibin, China.

出版信息

PLoS One. 2024 Aug 1;19(8):e0307529. doi: 10.1371/journal.pone.0307529. eCollection 2024.

Abstract

The formulation of science and technology financial policies directly influences the direction of national economic development. Quantitative evaluation of these policies is an important method to reflect the consistency and strengths and weaknesses of policy interrelations. This paper analyzes 16 science and technology financial policy documents issued by the Chinese central government from 2016 to 2022, using text analysis and content analysis to extract keyword frequencies, and constructs 9 primary variables and 34 secondary variables. For the first time, a PMC-AE index model for science and technology financial policies is established, and a quantitative evaluation is conducted on 5 significant policy documents out of the 16. The results show that, from an overall analysis, Policy 1 and Policy 4 are at a good level, while the other three policies are at an excellent level. From the analysis of individual policy PMC-AE indexes, the rankings in descending order are: P2 > P5 > P3 > P4 > P1. Overall, the policies effectively meet the needs of China's science and technology financial development, with P2, P3, and P5 being at an excellent level, P4 at a good level, and P1 at an acceptable level, mainly reflecting the need for improvement in aspects such as policy synchronization with the current stage, targeted entities, guiding fields, and policy content. It is recommended that Chinese government departments should focus on five aspects in policy formulation: building a talent system for science and technology finance, improving the quality of financial services, coordinating central and local financial policies, protecting intellectual property rights in science and technology finance, and strengthening financial supervision. This will be conducive to the effective implementation of science and technology financial policies.

摘要

科技金融政策的制定直接影响着国家经济发展的方向。对这些政策进行量化评估是反映政策相互关系的一致性及优劣程度的重要方法。本文分析了中国中央政府2016年至2022年发布的16份科技金融政策文件,运用文本分析和内容分析提取关键词频次,构建了9个一级变量和34个二级变量。首次建立了科技金融政策的PMC-AE指数模型,并对16份中的5份重要政策文件进行了量化评估。结果显示,从整体分析来看,政策1和政策4处于良好水平,而其他三项政策处于优秀水平。从单个政策的PMC-AE指数分析来看,排名由高到低依次为:P2>P5>P3>P4>P1。总体而言,这些政策有效满足了中国科技金融发展的需求,其中P2、P3和P5处于优秀水平,P4处于良好水平,P1处于可接受水平,主要体现在政策与现阶段的同步性、靶向主体、引导领域及政策内容等方面有待改进。建议中国政府部门在政策制定中应重点关注五个方面:构建科技金融人才体系、提高金融服务质量、协调中央和地方金融政策、保护科技金融领域的知识产权以及加强金融监管。这将有利于科技金融政策的有效实施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f40b/11293693/27a9d73c163c/pone.0307529.g001.jpg

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