资源科学 ›› 2020, Vol. 42 ›› Issue (2): 334-345.doi: 10.18402/resci.2020.02.12

• 水资源 • 上一篇    下一篇

中国水资源投入的“拥塞效应”研究

孙才志1, 王晨2   

  1. 1. 辽宁师范大学海洋经济与可持续发展中心,大连 116029
    2. 辽宁师范大学地理科学学院,大连 116029
  • 收稿日期:2019-07-12 修回日期:2019-11-24 出版日期:2020-02-25 发布日期:2020-04-25
  • 作者简介:孙才志,男,山东烟台人,教授,博士生导师,主要从事水资源经济与海洋经济研究。E-mail: suncaizhi@lnnu.edu.cn
  • 基金资助:
    国家社会科学基金重点项目(19AJY010)

Research on the “congestion effect” in China’s water resources input

SUN Caizhi1, WANG Chen2   

  1. 1. Marine Economy and Sustainable Development Research Center, Liaoning Normal University, Dalian 116029, China
    2. School of Geography, Liaoning Normal University, Dalian 116029, China
  • Received:2019-07-12 Revised:2019-11-24 Online:2020-02-25 Published:2020-04-25

摘要:

本文在全要素生产框架下,定义水资源投入拥塞的概念,基于FGL模型对2000—2016年中国31个省份(不包括港澳台)的水资源投入进行“拥塞”识别,并将水资源投入拥塞导致的无效率从全局无效率中分离出来,为明确无效率的根源,并将全局无效率分解为拥塞无效率和纯技术无效率。。研究结果表明:①中国存在水资源投入拥塞效应,在考察期间各省份拥塞度经历由低到高、集聚到分散的演化过程,各省份水资源投入拥塞度在空间差异显著,其中北京、浙江、广东等省市拥有较低的拥塞度,整体来看,投入要素结构非均衡的中、西部地区较经济发展水平高的东部地区更易发生拥塞。②中国各省份全局水资源利用无效率呈现不同的变化态势,大部分省份由拥塞无效率与纯技术无效率共同驱动,从省际和区域来看,以纯技术无效率为主导,拥塞无效率也是影响全局无效率的一个重要原因。政府应该明确无效率的根源,因地制宜,适时调整投入要素结构,提出水资源利用改进方向,提高水资源利用效率,促进经济可持续发展。

关键词: 全要素水资源利用效率, DEA模型, FGL模型, 拥塞, 中国

Abstract:

Under the framework of total factor production, this study defined the concept of water resources input congestion. Based on the FGL (F?re, Grosskopf, and Lovell) model, this study identified the “congestion” of water resources input in 31 provinces of China’s mainland from 2000 to 2016, separated the inefficiency caused by water resources input congestion from the overall inefficiency and clarified the root causes of inefficiency. The results show that:(1) The congestion of water resources input is widespread in China. During the study period, the congestion degree of the provinces changed from low to high and agglomeration to dispersed, and the spatial differences of the congestion degree of water resources input among the provinces were significant. Among them, Beijing, Zhejiang, Guangdong and other provinces and cities had low congestion degree. On the whole, the central and western regions with unbalanced input structure was more prone to congestion than the eastern regions with high level of economic development. (2) The overall inefficiency of water resources utilization in Chinese provinces presented different trends. Most provinces were jointly driven by congestion inefficiency and pure technology inefficiency. From the inter-provincial and regional perspective, the ineffectiveness rate of pure technology was the dominant factor. Inefficiency of congestion was also an important factor affecting the overall inefficiency. The government should clarify the root causes of inefficiency, adjust the input factor structure in a timely manner based on local conditions, propose improvement directions for water resources utilization, and improve water use efficiency in order to promote sustainable economic development.

Key words: total-factor water efficiency, DEA model, FGL model, congestion, China