基于库兹涅茨曲线的中国工业用水与经济增长关系研究

doi:10.18402/resci.2017.06.11

摘要/Abstract

摘要：

中国人均水资源量仅为世界人均水平的29%,且经济快速增长、工业用水需求也与日俱增,如何平衡经济发展与工业用水之间的关系是目前需要分析与解决的重要问题。本文将全国分为八大经济区域,建立约化模型,验证不同特征的工业用水EKC（Environmental Kuznets Curve）关系。结果显示中国工业用水发展水平符合EKC特征,人均工业用水与人均GDP存在着“倒U”型关系。拐点的出现主要由于技术创新、产业结构升级等因素导致,地区发展不平衡导致人均工业用水拐点不同。工业用水EKC曲线的研究对协同经济发展与工业用水的研究有着重要的意义,需要通过调整产业结构、提高用水效率、研发前沿技术等方法,使工业用水EKC转折点的尽早实现。

关键词: 环境库兹涅茨曲线（EKC）, 工业用水, 经济增长, 约化模型, 中国

Abstract:

Global inequity and unbalanced water resources have been critical issues for many years. Chinese water resources per capita are only 1/4 of the global average. As the Chinese economy grows rapidly,the demands for Chinese industrial water are increasing. It is therefore important to balance the relationship between economic growth and industrial water use. To make industrial water use decisions economically,we divided China into eight economic areas and based on a reduced form model verified the industrial Kuznets Curve in different areas. We used water use per capita and GDP per capita of the eight economic areas from 2002 to 2014 and applied unit root tests and co-integration tests and curve fitting. The result indicates that the trend in Chinese industrial water use fits the Kuznets Curve,and that industrial water use per capita and GDP per capita show an inverted U type relationship. The different economic areas have different turning points due to different levels of technological development and industrial structure. A study of industrial water use trends has much meaning for co-integrating economic development and industrial water use. The government should try to achieve an earlier turning point in the Kuznets Curve by optimizing industrial structure,increasing water-use efficiency and developing advanced technologies.

Key words: Environmental Kuznets Curve, industrial water use, economic growth, reduced form model, China

张月, 潘柏林, 李锦彬, 顾阿伦. 基于库兹涅茨曲线的中国工业用水与经济增长关系研究[J]. 资源科学, 2017, 39(6): 1117-1126.

Yue ZHANG, Bolin PAN, Jinbin LI, Alun GU. The relationship analysis between Chinese industrial water use and economic growth based on the Kuznets Curve[J]. Resources Science, 2017, 39(6): 1117-1126.

图/表 8

表1

2002-2014年全国人均GDP对数的ADF检验"

	显著性水平下的临界值/%			ADF检验值	$p$ 值
	1	5	10	ADF检验值	$p$ 值
原序列	-4.122	-3.145	-2.714	-2.556	0.128
一阶差分	-4.200	-3.175	-2.729	-1.083	0.681
二阶差分	-4.297	-3.213	-2.748	-3.016	0.067

表1

图1

表2

面板数据单位根检验结果"

	$lnGD P it$	$lnGD P it 2$	$lnGD P it 3$	$lnwate r it$
全国
原序列	-2.556	-1.951	-1.353	-2.534
一阶差分	-1.083	-1.327	-1.610	-1.038
二阶差分	-3.016*	-3.013*	-3.014*	-3.918**
东北地区
原序列	-4.207**	-4.707**	-6.269**	-1.013
一阶差分	-	-	-	-1.820
二阶差分	-	-	-	-3.443**
北部沿海
原序列	-3.450**	-3.853**	-4.295**	-4.064**
东部沿海
原序列	-7.046**	-5.835**	-4.652**	-3.061*
南部沿海
原序列	-4.025**	-3.942**	-3.787**	-0.570
一阶差分	-	-	-	-3.447**
黄河中游
原序列	-4.118**	-2.925	-1.789	-1.659
一阶差分	-	0.530	-1.108	-1.585
二阶差分	-	3.049*	-2.916*	-3.249**
长江中游
原序列	-2.517	-2.044	-1.560	-2.716
一阶差分	-1.070	-1.606	-2.016	-1.629
二阶差分	-3.019*	-2.917*	-2.835*	-4.409*
西南地区
原序列	-1.754	-1.438	-1.199	-0.233
一阶差分	-1.251	-1.585	-1.774	-0.653
二阶差分	-2.656	-2.516	-2.390	-3.356**
大西北地区
原序列	-0.691	0.915	1.705	-3.273**
一阶差分	-3.490**	-3.259**	-2.468
二阶差分	-	-	-2.702

表2

表3

协整检验结果"

	统计值	$p$ 值
全国	-3.391	0.036**
长江中游	-3.061	0.063*

表3

表4

2002-2014年全国及三个地区用水EKC曲线拟合参数"

	0.全国	2.北部沿海	3.东部沿海	6.长江中游
$R 2$	0.972	0.971	0.711	0.962
$F$	104.450	100.220	7.395	75.709
$p$	0.000	0.000	0.008	0.000

表4

图2

表5

全国及三个地区用水EKC曲线拟合参数及分析结果（修正后）"

	0.全国	2.北部沿海	3.东部沿海	6.长江中游
$β 0$	188.291	283.146	-301.181	230.655
$β 1$	-61.022	-80.174	82.080	-75.631
$β 2$	6.711	7.651	-7.267	8.387
$β 3$	-0.245	-0.243	0.213	-0.308
$R 2$	0.972	0.971	0.848	0.962
$F$	104.450	100.220	12.970	75.709
$p$	0.000	0.000	0.003	0.000
形状	倒U形	下降	倒U形	倒U形
拐点坐标	（9.875, 4.674）	-	（10.310, 5.478）	（9.818 , 5.062）
拐点人均GDP/元	19 436	-	30 025	18 369
拐点人均工业用水/m³	107	-	239	158

表5

图3

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