资源与产业 ›› 2022, Vol. 24 ›› Issue (3): 21-31.DOI: 10.13776/j.cnki.resourcesindustries.20220527.015

• 非主题来稿选登 • 上一篇    下一篇

基于水足迹与SBM-Malmquist模型的长江经济带工业水资源绿色效率的研究

王保乾,李昕燃   

  1. (河海大学 商学院,江苏 南京 211100)
  • 收稿日期:2021-07-21 修回日期:2021-08-11 出版日期:2021-06-20 发布日期:2022-07-18
  • 通讯作者: 李昕燃
  • 作者简介:王保乾,博士、教授,主要从事应用经济、区域经济方面的研究 E-mail: bq64@163.com
  • 基金资助:
    国家社会科学基金项目(17BJY142)

GREEN EFFICIENCY OF INDUSTRIAL WATER RESOURCE IN YANGTZE RIVER ECONOMIC ZONE BASED ON WATER FOOTPRINT AND SBM-MALMQUIST MODEL

WANG Baoqian, LI Xinran   

  1. (Business School, Hohai University, Nanjing 211100, China)
  • Received:2021-07-21 Revised:2021-08-11 Online:2021-06-20 Published:2022-07-18
  • Contact: LI Xinran

摘要: 中国是世界上水资源供需矛盾最突出的国家之一,水资源作为人类生存、社会经济发展的必备资源,一直处于被过度开发利用的状态。文章对长江经济带工业水资源绿色效率进行研究,首先基于水资源效率的内涵,引入环境污染等负面因素,对工业水资源绿色效率进行重新界定,对水资源绿色效率的内涵进行补充,其次通过理论分析与实证分析相结合的方式,了解工业水资源绿色效率的影响因素和时空特征,以此来探讨长江经济带工业水资源绿色效率的提升方法。文章在蓝水足迹与灰水足迹概念的基础上,通过运用三阶段超效率SBM模型和Malmquist-Luenberger指数分解法,选择工业从业人员(劳动)、工业固定资产投资(资本)、蓝水足迹(自然资源)作为投入变量,将工业增加值作为期望产出变量,将灰水足迹作为非期望产出变量,构建了工业水资源绿色效率的指标体系,并对长江经济带11省市2009—2019年的工业水资源绿色效率进行了测算。结果表明,长江经济带整体和区域的蓝水足迹具有波动性,灰水足迹呈下降趋势。在剔除环境因素和随机误差后,发现环境因素对纯技术效率的抑制作用较为明显,规模效率和综合技术效率还有一定的提升空间。全要素生产率指数呈现上升趋势,虽然影响全要素生产率指数变化的因素在各个省份、不同阶段有所不同,但整体上长江经济带工业水资源绿色效率的主要驱动因素源于技术进步。因此建议长江经济带的不同省份可以结合各自的产业特点,发挥各个区域的资源禀赋,通过产业上下游供应链结合等方式来提高规模效率、加强区域合作,通过投入产出要素的优化提高效益、减少水污染。

关键词: 超效率SBM模型, 工业水资源绿色效率, 蓝水足迹, 灰水足迹, 长江经济带

Abstract: China is one of countries which have a surging water supply-demand conflict. Water resource as a necessity for human's survival and economy has always been over used. This paper studies the green efficiency of industrial water resources in Yangtze River economic zone, uses environmental pollution as negative factor based on the connotation of water resource efficiency, and re-defines and replenishes the concept of green efficiency of industrial water resource. Through theoretical and experimental analysis, this paper discusses the factors and temporal-spatial features of green efficiency of industrial water resource, and presents a path to upgrading the green efficiency. By means of blue and gray water footprints, this paper uses triple-staged super-efficiency SBM model and Malmquist-Luenberger indicators decomposition to select industrial labors, industrial fixed asset investment and blue water footprint as input variables and industrial increment as expected output variable, and gray water footprint as non-expected output variable. A green efficiency of industrial water resource index system is established to estimate their 2009—2019 green efficiencies of industrial water resource of 11 provinces (cities) in Yangtze River economic zone. Blue water footprints of the whole Yangtze River economic zone and regional has volatility, while the gray water has a downward trend. With removal of environmental factor and random errors, it is found that environmental factor obviously constrains the pure technological efficiency, leaving a room to improve to size efficiency and comprehensive technological efficiency. The factors of the whole elements productivity index changes vary with provinces and stages, but technical advance is the major one, This paper suggests that provinces in Yangtze River economic zone improve size efficiencies through their actual industries and resources and upper-down stream supply chain combination, and increase outputs and decrease water pollution from optimizing input/output elements.

Key words: super-efficiency SBM model, green efficiency of industrial water resource, blue water footprint, gray water footprint, Yangtze River economic zone

中图分类号: