【作者】 孙爱军；

【导师】 董增川；

【作者基本信息】 河海大学 ， 水文学及水资源， 2007， 博士

【摘要】 水资源可持续利用是我国经济社会发展的战略问题，水资源保障和工业经济发展的关系表现在工业对水资源的需求和水环境的变化对工业的影响，核心是提高水资源利用效率，关键是提高用水的技术效率。借鉴技术效率定义，针对工业用水系统，提出工业用水技术效率的概念，总结运用随机生产函数、随机前沿生产函数——面板数据、随机成本函数等三种不同形式计算工业用水技术效率的方法。计算工业生产过程中的用水技术效率，分析并预测耗水量，为工业用水规划、水资源优化配置提供依据。建立随机前沿生产函数模型，对我国1953—2004年间的工业水资源利用技术效率进行测算，分析技术效率变化、技术进步指数和TFP，建立预测工业耗水量的误差修正模型模型。结果表明：工业用水技术效率变化平稳，总体来看，呈现缓慢的上升趋势；引入技术效率变量，用误差修正模型预测工业耗水量，对未来工业耗水量预测的精确度明显提高，如2005年的耗水量预测误差仅为4.96％，而没有引入技术效率时的误差超过80％。_工业化导致的废水排放，严重污染环境。考虑到工业用水技术效率，在格兰杰因果关系检验基础上，建立VAR模型，运用脉冲响应函数和方差分解进行分析，量化研究中国工业产值增长、工业用水技术效率与工业废水排放量之间的关系。结果表明：工业经济增长、用水技术效率分别与废水排放量之间存在着因果关系，废水排放量对经济增长的影响具有明显的时滞性。技术效率对废水排放量的贡献逐渐平稳。工业用水量与工业用水技术效率密切相关，从成本角度出发，建立随机前沿成本函数模型，计算工业用水技术效率。引入技术效率变量，构建向量误差修正模型，预测未来的工业用水量，对确定适当的工业供水设施建设投资总额，缓解用水危机十分重要。工业为主体的城市经济，与水环境的关系主要取决于其与用水技术效率之间的协调程度。建立随机前沿生产函数—面板数据模型，计算城市经济的用水技术效率。借鉴物理学中的耦合度函数，改进协调度测算方法，计算典型城市的城市经济和用水技术效率的协调度，并进行横向和纵向的比较，分析原因与对策。更多还原

【Abstract】 The sustainable utilization of water resource is the stratagem of social and economical development. The core problem to guarantee industrial water is to increase efficiency of industrial water usage. Technical efficiency is of great importance.The technical efficiency of industrial water usage is brought forward and calculated with the aid of stochastic frontier analysis (SFA) function model.Scientific calculation and analysis of technical efficiency and prediction of industrial water consumption is of great significance to China’s industrial water planning. By setting up a model containing variables of industrial water consumption, together with SFAP model, the paper calculates the technical efficiency (TE) of industrial water in China during the period of 1953 to 2004, and it is used to predict China’s industrial water consumption. The technical efficiency of industrial water in China has been in slow but stable growth.A case in point is the fact that the prediction error of industrial water consumption in 2005 is just 4.96%, compared with the prediction error 80% before 2005 without considering TE.The released waste water effluent, produced during China’s industrialization, has seriously polluted the environment. In my thesis, TE of water use is taken into serious consideration. Based on Granger Causal test, the VAR model is set up.The impulse response function and variance decomposition is employed to conduct a quantitative study of the relationship among China’s industrial output growth, TE of industrial water and waste water effluent. The study reveals a mechanism of interaction among China’s economic growth, waste water effluent and technical efficiency of industrial water. China’s industrial economic growth affects the quantity of waste water effluent connecting with technical efficiency. Waste water effluent has an obvious time-lagging effect on economic growth.The quantity of industrial water is increasing. To a great extent, it is up to technical efficiency. In point of cost, the stochastic frontier analysis cost function is applied to compute TE.Furthermore, the TE is taken into account to constitute econometrics model.The VECM model would be more accurate with consideration into the technical efficiency. Compared with other research, the conclusion is relatively scientific.It is important and necessary to determine the scale of industrial water supply.It not only helps to determine proper investment of industrial water establishment, but also helps to reduce the pressure of water crisis.It is well known that industry is the main part of city economy. The relation between city economy and water environment rests on the proper harmony of economy and technical efficiency.The stochastic frontier analysis production function -panel data is applied to compute technical efficiency of different cities. This paper puts forward the model with reference to the coupling degrees function in physics, and calculates the coupling degrees between city economy and technical efficiency and sets up the evaluation of coupling degrees. According to analysis, the study also suggests that various measures should be taken.更多还原