| 摘要: |
| 科学评估工业水资源效率并识别其影响因素，是提升工业用水效率，化解水资源供需矛盾，推进黄河流域生态保护和高质量发展的重要抓手之一。基于非期望产出的超效率EBM模型，以黄河流域九省（区）为研究对象，测算2010-2019年黄河流域工业水资源效率；其次，利用ML指数分析工业水资源效率动态变化；最后通过Tobit模型，对工业水资源效率影响因素进行分析。研究发现：2010-2019年黄河流域工业水资源效率整体较低，均值只有0.77，未达到有效状态，但呈现出波动上升趋势，各省（区）间差异明显，山东效率最高，宁夏最低。黄河流域工业水资源效率ML指数的提高是技术进步指数和技术效率指数共同推动的结果，但增长动力主要源自技术进步指数，规模效率指数抑制了技术效率指数对ML指数的贡献。技术水平和工业化程度对工业水资源效率攀升有促进作用；水资源禀赋、工业用水强度和政府管制程度对工业水资源效率具有显著的抑制效应。 |
| 关键词: 工业水资源效率 超效率EBM ML指数 Tobit模型 黄河流域 |
| DOI： |
| 分类号: |
| 基金项目:教育部人文社会科学重点研究基地重大项目“中国产业转型升级的轨迹和理论创新”(18JJD790002) |
|
| Spatial and Temporal Differentiation and Influencing Factors of Industrial Water Resources Efficiency in the Yellow River Basin |
|
miaojunyu
|
|
东北财经大学
|
| Abstract: |
| Scientifically assessing the efficiency of industrial water resources and identifying its influencing factors is one of the important starting points to improve the efficiency of industrial water use, resolve the contradiction between water supply and demand, and promote the ecological protection and high-quality development of the Yellow River Basin. Based on the super-efficiency EBM model of unexpected output, this paper takes nine provinces (regions) in the Yellow River Basin as the research object, and calculates the industrial water resources efficiency in the Yellow River Basin from 2010 to 2019; secondly, the ML index is used to analyze the dynamic changes of industrial water resources efficiency; Finally, the Tobit model is used to analyze the influencing factors of industrial water resources efficiency. The study found that the industrial water resources efficiency in the Yellow River Basin was generally low from 2010 to 2019, with an average value of only 0.77, which did not reach an effective state, but showed a fluctuating upward trend, with obvious differences among provinces (regions), with Shandong having the highest efficiency and Ningxia having the lowest. The improvement of the ML index of industrial water resources efficiency in the Yellow River Basin is the result of the joint promotion of the technical progress index and the technical efficiency index, but the growth momentum mainly comes from the technological progress index, and the scale efficiency index inhibits the contribution of the technical efficiency index to the ML index. Technological level and degree of industrialization can promote the rise of industrial water resources efficiency; water resources endowment, industrial water use intensity and government regulation degree have significant inhibitory effects on industrial water resources efficiency. |
| Key words: industrial water resources efficiency super-efficiency EBM ML index Tobit model Yellow River Basin |
