中国31个省市及重点省域科技创新效率评价研究——基于超效率SBM-Malmquist模型

Research on the Evaluation of Science and Technology Innovation Efficiency in 31 Provinces and Key Provinces in China —— Based on super SBM-Malmquist model

摘要:

科技创新已成为中国社会进步、经济发展、国家安全保障的重要路径。本文以2015~2020年我国31个省市为研究对象，利用SBM-Malmquist模型对我国科技创新效率进行了静态与动态的测算；选取《中国区域科技创新评价报告2021》中综合科技创新水平指数最高的的十大省市，对其进行重点分析。实证结果表明：我国整体科技创新效率较低，但有向好趋势，区域间呈现出西部>东部>中部地区的态势；我国科技创新效率的增长主要得益于技术进步，其对科技创新效率的拉动作用抵消了技术效率衰退的影响；综合科技创新水平指数最高的上海市和北京市分别出现了科技创新投入冗余和技术进步不足的问题。为实现我国科技创新自立自强，需从区域协同、技术进步、资源优化配置等方面发力。

Abstract:

Science and technology innovation has emerged as a critical path for China"s social advancement, economic development, and national security protection. The paper takes 31 provinces in China from 2015 to 2020 as the research objects, and uses the SBM-Malmquist model to measure the efficiency of S&T innovation in China statically and dynamically; meanwhile, Selecting the top ten provinces of the comprehensive S&T innovation level index in the China Regional Science and Technology Innovation Evaluation Report 2021, and analyzing them with emphasis. According to the empirical findings, China"s total S&T innovation efficiency is poor, but there is an improving trend, with a trend of western > eastern > central regions; the growth of China"s S&T innovation efficiency benefits from technological progress and offsets the impact of declining technical efficiency; Shanghai and Beijing, which have the most comprehensive S&T innovation level indexes, respectively, have issues with duplicate S&T innovation investment and inadequate technical growth. We must focus on regional synergy, technical progress, and optimal resource allocation to achieve China"s scientific and technology innovation self-sufficiency and self-improvement.