陈清 林珊珊

摘 要：基于2009—2018年我国省际面板数据，运用Super-SBM模型同时测度了考虑非期望产出的绿色创新效率和不考虑非期望产出的传统创新效率，并运用Malmquist-Luenberger指数方法对绿色创新效率进行了动态分析。研究表明：我国绿色创新效率整体呈增长态势但水平偏低，呈无效率状态，进步空间较大;我国三大地区绿色创新效率呈现出由东向西递减的格局，且各省市绿色创新效率根据变动情况可以分为平稳型、增长型和波动型三类;考虑非期望产出的绿色创新效率比不考虑非期望产出的传统创新效率低，且中西部差异更显著;技术效率和技术进步共同导致我国绿色创新水平的提高，且技术进步的影响程度大于技术效率，其与ML指数变动的趋同性也更高;我国绿色创新的动态效率呈现中部>西部>东部的格局，且多数省市的ML指数均大于1，存在不同程度的进步。

关键词：绿色创新;效率评价;Super-SBM模型;Malmquist-Luenberger指数;非期望产出

中图分类号：F 205

文献标识码：A   文章编号：1672-7312（2021）05-0510-09

Evaluation of Green Innovation Efficiency at

Provincial Level in China

——Based on Super-SBM model and ML index

CHEN Qing，LIN Shanshan

（School of Economics and Management，Nantong University，Nantong 226000，China）

Abstract：Based on Chinas provincial panel data from 2009 to 2018，this paper used Super-SBM model to measure both green innovation efficiency with non-expected outputs and traditional innovation efficiency without non-expected outputs，and used Malmquist-Luenberger index method to conduct dynamic analysis on green innovation efficiency.The results show that the overall green innovation efficiency in China is growing，but the level is low，showing inefficiency，and there is much room for progress.The efficiency of green innovation in the three regions of China is decreasing from east to west，and the efficiency of green innovation in each province can be divided into three types：stable，increasing and fluctuating.The efficiency of green innovation considering non-expected output is lower than that of traditional innovation without considering non-expected output，and the difference between the central and western regions is more significant.Technological efficiency and technological progress lead to the improvement of green innovation level in China，and the influence of technological progress is greater than that of technical efficiency，and the convergence between technological progress and ML index changes is higher.The dynamic efficiency of green innovation in my China presents a pattern of central>western>eastern，and most provinces and cities have ML indexes greater than 1，showing different degrees of progress.

Key words：green innovation;efficiency evaluation;super-SBM model;Malmquist-Luenberger index;undesired output

0 引言近年来，我国经济高速发展伴随而来的资源环境问题亟待解决，2020年中国的全球环境绩效指数（EPI）排名在180个国家和地区中排第120位，而据《2020年全国生态环境质量简况》显示，2020年全国337个地级以上城市中有135个城市的空气质量超标。针对这一现象，《2035远景目标》中提出至2035年要基本实现美丽中国的建设目标;“十四五”规划更是提出要完善生态领域的统筹协调机制以促进经济社会发展实现全面绿色转型。因此，在高质量发展过程中如何实現绿色转型成为当务之急，而绿色创新正是实现绿色转型的必由之路。通过客观……