资源科学 ›› 2018, Vol. 40 ›› Issue (4): 784-796.doi: 10.18402/resci.2018.04.12

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城镇化进程中人口结构变动对用水量的影响

金巍1,2(), 章恒全1, 张洪波2, 孔伟2(), 毛广雄2, 张陈俊3, 严翔1,4   

  1. 1. 河海大学商学院,南京 211100
    2. 淮阴师范学院城市与环境学院,淮安 223300
    3. 河海大学企业管理学院,常州 213022
    4. 盐城师范学院商学院,盐城 224007
  • 收稿日期:2017-08-10 修回日期:2018-01-10 出版日期:2018-05-02 发布日期:2018-05-02
  • 作者简介:

    作者简介:金巍,男,河南项城人,博士生,讲师,主要研究方向为水资源经济与管理。E-mail: kingwei1985@foxmail.com

  • 基金资助:
    国家自然科学基金项目(41271135);江苏高校哲学社会科学研究和重点项目(2017ZDIXM028)

The influence of population structural change on water consumption in urbanization

Wei JIN1,2(), Hengquan ZHANG1, Hongbo ZHANG2, Wei KONG2(), Guangxiong MAO2, Chenjun ZHANG3, Xiang YAN1,4   

  1. 1. School of Business, Hohai University, Nanjing 211100, China
    2. School of Urban and Environmental Sciences, Huaiyin Normal University, Huai’an 223300, China;
    3. School of Business Administration, Hohai University, Changzhou 213022, China
    4. Business School of Yancheng Teachers University, Yancheng 224007, China
  • Received:2017-08-10 Revised:2018-01-10 Online:2018-05-02 Published:2018-05-02

摘要:

本文在城镇化背景下,利用系统GMM模型和面板门槛模型分析评价中国31个省份及东中西部地区2000—2016年人口结构变动与用水量之间的关系,结果表明:①中国人口结构中人口老龄化对用水量的弹性系数最大(0.042);非人口结构因素中上期用水量对本期的弹性系数最大(0.978),其次是万元GDP用水量(0.020)和人口规模(0.018),产业结构调整显著抑制用水量增加(-0.041),其他变量回归结果不显著;②东部用水量受人口结构变动影响大于其他因素,高端消费、人口城镇化和农业劳动人口每提高1个百分点分别导致用水量分别提高12.1、6.5和3.6个百分点;中西部人口结构变动暂时不能显著影响用水量;③人口年龄结构和产业结构在各自作用下对用水量存在双重门槛效应,弹性系数分别是0.174、0.150、0.139和-0.012、-0.008、-0.020;2016年仅西藏未跨越人口年龄结构的第一门槛值,其他省份均跨越第二门槛值;北京和上海2016年已跨越产业结构的第二门槛值,天津、山西等11个省份处于门槛的第二个阶段,其他18个省份未跨越第一门槛值。因此,需要缓解人口结构变动对用水量的促进作用,适当延长退休年龄,合理控制城镇流动人口,引导居民形成节水消费和理念,推广节水型公共设施及家庭设备,合理配置各产业间人力资源,提高第三产业比重,加快技术创新及技术溢出,实现经济高质量发展和区域协调发展。

关键词: 人口结构变动, 用水量, 城镇化进程, 系统GMM, 门槛效应, 中国

Abstract:

We used the dynamical system GMM and panel threshold model to analyze the relationship between population structure change and water consumption in 31 provinces of China from 2000 to 2016. We found that the elasticity coefficient of aging population to water consumption is the largest (0.042). Among non-population structure factors, the elasticity coefficient of the water consumption of previous period to this period is the largest (0.978), followed by the water consumption by million CNY of GDP (0.020) and population scale (0.018). Industrial restructuring significantly inhibits water increases (-0.041); other regression results were not significant. Water use in the east is more affected by changes in population structure than other factors. With one percentage point increase in high-end consumption, population urbanization and rural labor force, water consumption respectively increased by 12.1, 6.5 and 3.6 percentage points respectively. Population structure changes in central and western regions did not significantly affect water consumption. The age and industrial structures have a threshold effect on water consumption, and the elastic coefficients are 0.174, 0.150, 0.139 and -0.012, -0.008 and -0.020, respectively. In 2016, only Tibet did not cross the first threshold of the population age structure, while other provinces crossed the second threshold. Beijing and Shanghai have crossed the second threshold of industrial structure in 2016, with 11 provinces in the second phase of the threshold, while the other 18 provinces have not crossed the first threshold. It is necessary to reduce the promoting effect of population structural change on water consumption, appropriately extend the retirement age and rationally control urban floating population. Other measures such as guiding residents to form water-saving ideas and achieving coordinated regional development are also needed.

Key words: population structure change, water consumption, urbanization, system GMM, threshold effect, China