中国省际节能与环保一致性及影响因素研究

doi:10.18402/resci.2018.12.11

Abstract

Abstract:

Energy conservation and environmental protection are two basic footholds for practicing the concept of green development of China. Whether the two can be coordinated is related to the sustainable development of China's economy. Incorporated the clean structure of energy consumption into the non-radial directional distance function (NDDF) which based on environmental technology, and used it to measure the energy saving efficiency, environmental protection efficiency, energy saving and environmental protection efficiency of total factors, and judged the realization of the consistency of inter-provincial energy conservation and environmental protection in China from 2001 to 2016 according to the calculation results. Found that if the clean structure of energy consumption is not considered, it will lead to the underestimation of the above-mentioned DEA total factor efficiency value. It is also found that the phenomenon of energy saving and environmental imbalance is more common than high energy consumption and high pollution. Probit model regression results show that the direction and intensity of the impact of fiscal energy conservation and environmental protection expenditure on energy conservation and environmental protection consistency depends on the level of economic development. On the contrary, the improvement of economic development level and the enhancement of environmental regulation have a negative impact on the realization of energy conservation and environmental protection consistency. The former suggests the existence of the phenomenon that sacrificing resources and environment to exchange for economic growth, while the latter illustrates that the Potter effect of “appropriate environmental regulation can stimulate technological innovation” has not yet appeared in China. The level of openness has a negative impact on achieving energy conservation and environmental coherence. Although this negative impact is small, it is enough to warn of the existence of “pollution paradise” risk.

Key words: total factors efficiency, consistency of energy conservation and environmental protection, Non-radial Directional Distance Function(NDDF), clean structure of energy consumption, Probit Model, China

Haiying LIU, Jing SHANG, Dianwu WANG. A study on the consistency and influencing factors of China’s provincial energy saving and environmental protection[J].Resources Science, 2018, 40(12): 2438-2450.

Figures/Tables 8

Table 1

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References 48

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描述统计量/单位	最大值	最小值	均值	样本标准差
单位产值能耗/（tce/万元）	5.01	0.49	1.62	0.790
单位产值非清洁化能耗/（tce/万元）	4.09	0.26	0.98	0.550
单位产值清洁化能耗/（tce/万元）	1.16	0.10	0.21	0.040
单位产值COD排放量/（t/亿元）	554.24	9.40	61.52	0.340
单位产值氨氮排放量/（t/亿元）	33.04	1.24	6.20	0.002
单位产值SO₂排放量/（t/亿元）	1 071.66	5.60	79.04	2.180
单位产值烟（粉）尘排放量/（t/亿元）	735.90	4.08	59.74	1.430

变量属性	变量代码	变量名称	变量含义/单位
解释变量	Z₁	政府对节能环保的管理力度	财政预算支出中节能环保支出所占比重/%
	Z₂	政府对工业污染的规制强度^[25]	工业污染治理投资占GDP比重/%
	Z₃	能源消费强度	单位GDP能源消费量/（tce/万元）
控制变量	X₁	经济发展水平^{[21,22,26-28]}	不变价格的人均GDP的对数
	X₂	产业结构^[7,29,30]	第三产业增加值占地区GDP份额/%
	X₃	产权结构^[22,31]	国有控股工业总产值占工业总产值比重/%
	X₄	工业结构	高耗能高污染行业总产值占工业总产值比重/%
	X₅	城市化率^[32]	城镇人口占总人口比重/%
	X₆	科技基础条件	单位R&D人员占有研发经费/（万元/人）
	X₇	国内自主研发能力	国内发明专利申请授权量/%
	X₈	科技占有量规模	技术市场成交额占销售产值比重/%
	X₉	外资利用水平	外商直接投资与GDP之比/%
	X₁₀	出口贸易	出口总额与GDP之比/%
	X₁₁	进口贸易	进口总额与GDP之比/%

类别	考虑能源消费的清洁化结构情形下,新增的效率有效的省份（年份）
节能效率（25省次）	辽宁（2010—2012年）;吉林（2002年,2011年,2014年,2016年）;江苏（2005年）;浙江（2008年,2011年）;安徽（2003年）;江西（2002—2003年）;山东（2002—2010年,2014年）;广西（2011年）;陕西（2003年）
环保效率（45省次）	天津（2011—2015年）;吉林（2011—2016年）;黑龙江（2009—2016年）;江苏（2001年）;安徽（2004年）;福建（2005—2009年）;江西（2001年,2003年,2005—2010年）;湖南（2005年,2008—2009年,2011—2016年）;海南（2011—2012年）

年份	节能与环保一致的省份	年份	节能与环保一致的省份
2001	北京、上海、福建、广东、海南、江苏、江西	2009	北京、天津、上海、广东、海南、黑龙江、福建、江西、湖南
2002	北京、上海、福建、广东、海南	2010	北京、上海、广东、海南、黑龙江、江西
2003	北京、上海、福建、广东、海南、江西	2011	北京、上海、广东、天津、吉林、黑龙江、湖南、海南
2004	北京、上海、福建、广东、海南、安徽	2012	北京、上海、广东、天津、吉林、黑龙江、湖南、海南
2005	北京、上海、广东、海南、福建、江西、湖南	2013	北京、上海、广东、天津、吉林、黑龙江、湖南
2006	北京、上海、广东、海南、福建、江西	2014	北京、上海、广东、天津、吉林、黑龙江、湖南
2007	北京、上海、广东、海南、福建、江西	2015	北京、上海、广东、天津、吉林、黑龙江、湖南
2008	北京、上海、广东、海南、福建、江西、湖南	2016	北京、天津、上海、广东、新疆、吉林、黑龙江、湖南

变量	Z₁	Z₁²	Z₂	Z₃	C（常数项）
系数	-2.173 6*	0.374 2*	-8.457 6*	-2.145 8*	5.398 5*
McFadden R²	0.385 5	LR statistic	114.900 6	AIC	0.715 3
期望—预测表检验	82.96%	Prob(LR statistic)	0.000 0	SC	0.782 0

A study on the consistency and influencing factors of China’s provincial energy saving and environmental protection

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变量	估计系数	偏效应	变量	估计系数	偏效应
Z₁	-13.817 4*	-0.012 7	X₄	-0.056 4***	-0.003 3
Z₁²	0.370 2**	—	X₅	0.375 9*	0.022 2
Z₂	-14.979 3*	-0.885 9	X₆	-0.152 0*	-0.009 0
Z₃	-3.395 7**	-0.200 8	X₇	—	—
X₁	-57.927 1*	-0.005 9	X₈	—	—
X₁²	2.379 9*	—	X₉	-1.322 7*	-0.034 1
Z₁×X₁	1.130 8**	—	X₉²	0.067 5	—
X₂	0.091 8**	0.005 4	X₁₀	-0.087 9*	-0.005 2
X₃	-0.100 2**	-0.005 9	X₁₁	0.067 1**	0.004 0
McFadden R²	0.645 4		常数项	339.276 9*	—
期望预测表检验	90.74%		AIC	0.517 3
LR statistic	192.370 5		SC	0.743 9
Prob(LR)	0.000 0

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[3]	JI Xiaomeng, QIN Weishan, LI Shitai, LIU Xiaomei, WANG Qiuxian. Development efficiency of tourism and influencing factors in China’s prefectural-level administrative units [J]. Resources Science, 2021, 43(1): 185-196.
[4]	SUN Yixuan, CHENG Yu, LIU Na. Spatiotemporal evolution of China’s high quality economic development and its driving mechanism of scientific and technological innovation [J]. Resources Science, 2021, 43(1): 82-93.
[5]	WANG Qian, YU Jin. Effect of maize price decline on land transfer in the North China Plain [J]. Resources Science, 2020, 42(9): 1668-1679.
[6]	HAN Jing, CHEN Zexiu, LU Xinhai. Spatiotemporal change of China’s overseas investment in farmlands and influencing factors [J]. Resources Science, 2020, 42(9): 1715-1727.
[7]	WANG Pingping, HAN Yijun, ZHANG Yi. Characteristics of change and influencing factors of the technical efficiency of chemical fertilizer use for agricultural production in China [J]. Resources Science, 2020, 42(9): 1764-1776.
[8]	LUO Yi, MIAO Haimin, HUANG Dong, WU Laping, ZHU Junfeng. Household decisions on adoption of advanced storage facilities and impacts on maize storage volume and losses in China [J]. Resources Science, 2020, 42(9): 1777-1787.
[9]	ZHOU Meijing, HUANG Jianbai, SHAO Liuguo, YANG Danhui. Change and adjustment direction of China’s rare earth policy [J]. Resources Science, 2020, 42(8): 1527-1539.
[10]	DONG Juan, ZHENG Minggui, ZHONG Changbiao. Effect of government financial support on the development of China’s rare earth industry and influencing factors [J]. Resources Science, 2020, 42(8): 1551-1565.
[11]	YANG Yu, HE Ze. China’s overseas oil and gas dependence: Situation, geographical risks, and countermeasures [J]. Resources Science, 2020, 42(8): 1614-1629.
[12]	HOU Juan, ZHOU Weifeng, WANG Lumin, FAN Wei, YUAN Zuohui. Spatial analysis of the potential of deep-sea aquaculture in China [J]. Resources Science, 2020, 42(7): 1325-1337.
[13]	ZHANG Bosheng, YANG Zisheng. Coupling relationship between urban-rural coordinated development and rural poverty governance [J]. Resources Science, 2020, 42(7): 1384-1394.
[14]	ZHANG Wenxi, ZOU Jinlang, WU Qun. Effect of production factors on urban land use efficiency: Based on the provincial data of different development stages [J]. Resources Science, 2020, 42(7): 1416-1427.
[15]	YAN Qingyou, GUI Zengkan, ZHANG Wenhua, CHEN Lizhong. The heterogeneity of regional energy shadow price and energy environment efficiency in China [J]. Resources Science, 2020, 42(6): 1040-1051.