摘要
本文从智能产业金融支持投入角度入手,以2015-2019年606家智能产业上市公司为研究对象,利用熵值法对各省市智能产业金融支持水平进行计算,并用DEA模型和Malmquist指数测算了各省市的智能产业金融支持效率。结果表明:总体而言,智能产业金融支持水平处于较低水平且各省市之间的差异较大,智能产业金融支持效率表现较好且省市之间的总体差距较小。从总体来看,智能产业金融支持水平整体上保持上升态势,其中,银行信贷和政府补助是智能产业金融支持水平增长的主要推动力;智能产业金融支持效率呈波动上升趋势,但每个阶段对全要素生产率起促进作用的因素不同。省际水平上看,各省市的智能产业金融支持水平和效率发展主要表现出不协调不匹配的特征。
From the perspective of financial support investment in smart industry,this paper takes 606 listed companies in smart industry from 2015 to 2019 as the research object.Entropy method is used to calculate the level of financial support for smart industry in each province and city.DEA model and Malmquist index are used to measure the efficiency of financial support for smart industry in each province and city.The results show that,in general,the level of financial support for smart industry is at a low level and the differences among provinces and cities are large.The efficiency of financial support for smart industry is good and the overall gap between provinces and cities is small.In general,the level of financial support for smart industry keeps rising on the whole,among which bank credit and government subsidies are the main driving forces for the increase of financial support for smart industry.The financial support efficiency of smart industry shows a fluctuating upward trend,but the factors that promote the total factor productivity in each stage are different.At the provincial level,the development of financial support level and efficiency of smart industry in various provinces and cities mainly shows the characteristics of incoordination and mismatch.
作者
吴晨阳
张红梅
WU Chenyang;ZHANG Hongmei(School of Big Data Application and Economics(Guiyang Institute for Big Data and Finance),Guizhou University of Finance and Economics,Guizhou Guiyang 550000;Guizhou Institute of Science and Technology Innovation and Venture Capital,Guizhou Guiyang 550000)
出处
《西部金融》
2022年第11期65-74,共10页
West China Finance
作者简介
吴晨阳(1998-),女,贵州贞丰人,硕士研究生,现就读于贵州财经大学大数据应用与经济学院(贵阳大数据金融学院);张红梅(1969-),女,贵州贵阳人,硕士,教授,现供职于贵州财经大学贵州科技创新创业投资研究院。