黄河流域九省区创新效率研究

Research on Innovation Efficiency of Nine provinces in the Yellow River Basin

摘要:

基于黄河流域9省区2008－2019年有关面板数据，运用数据包络分析（DEA）和Malmquist指数模型测算和分解其创新效率，并从静态和动态两个角度与我国31个省区市创新效率进行比较。结果表明：黄河流域创新效率总体上呈上升趋势，但仍处于较低水平，平均值落后于我国31个省区市的平均值，其中2018、2019年的创新效率分别呈“W”型和“M”型分布；各地区创新效率存在一定差异，但总体上较为均衡，其中山西和内蒙古两地保持较高的创新效率；多数地区尚处于DEA无效状态，技术进步迟缓和规模效率较低是主要原因。因应黄河流域生态保护和高质量发展国家重大战略要求，黄河流域各地区要强化多方联动，优化资源配置，加快创新人才引进，注重从规模和技术两方面综合考虑，加大创新成果产出、加速创新成果转化。

Abstract:

Based on the panel data from 2008 to 2019 in 9 provinces and autonomous regions in the Yellow River Basin, data envelopment analysis (DEA) and Malmquist index model were used to calculate and decompose their innovation efficiency. The innovation efficiency of the Yellow River Basin is compared with the innovation efficiency of 31 provinces and autonomous regions in China from static and dynamic perspectives. The results show: The innovation efficiency of the Yellow River Basin is on the rise in general, but still at a low level. The average innovation efficiency of the Yellow River Basin lags behind the average of 31 provinces and autonomous regions in China, and the innovation efficiency in 2018 and 2019 presents a "W" and "M" shape distribution respectively. There are some differences in innovation efficiency in different provinces, but they are generally balanced. Among them, Shanxi and Inner Mongolia maintain high innovation efficiency. Most regions are still in a state of ineffective DEA, mainly due to slow technological progress and low scale efficiency. In response to the major national strategic requirements for ecological protection and high-quality development in the Yellow River Basin, all regions in the Yellow River Basin should strengthen multi-party linkage, optimize resource allocation, and speed up the introduction of innovative talents. The Yellow River Basin should also comprehensively consider both scale and technology, increase the output of innovation achievements, and accelerate the transformation of innovation achievements.