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

Abstract

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

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.

Figures/Tables 8

Table 1

ADF test on the logarithms of GDP per capita of China from 2002 to 2014"

	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

Table 1

Figure 1

Table 2

Unit root test results of panel data"

	$lnGD P it$	$lnGD P it 2$	$lnGD P it 3$	$lnwate r it$
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

Table 2

Table 3

Co-integration test results"

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

Table 3

Table 4

EKC fitting parameters of China,Northern Coast,Eastern Coast and Middle Yangtzi River regions from 2002 to 2014"

	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

Table 4

Figure 2

Table 5

Estimated parameters and analysis results with EKC Curve method of China,Northern Coast,Eastern Coast,and Middle Yangtzi River regions （corrected）"

	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

Table 5

Figure 3

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The relationship analysis between Chinese industrial water use and economic growth based on the Kuznets Curve

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