黄河流域沿线城市绿色发展效率时空演变及其影响因素

doi:10.18402/resci.2020.12.02

摘要/Abstract

摘要：

黄河流域在中国经济社会发展和生态安全方面具有十分重要的地位。本文基于2005—2017年黄河流域沿线57个城市的面板数据,通过Super-SBM模型测算流域内各城市的绿色发展效率,构建Tobit模型,实证分析黄河流域绿色发展效率的影响因素。研究发现：①全流域的绿色发展效率整体呈现波动上升趋势,上游最高,下游次之,中游最低,效率高值集中在西宁、郑州、西安、太原等省会中心城市和中卫、武威、鄂尔多斯等地区中心城市。②从Tobit回归结果来看,经济发展和产业结构升级可以显著促进黄河流域绿色发展效率的提高,城镇化对黄河流域绿色发展效率的影响呈现“U”型曲线关系,外资利用和科技水平对黄河流域的绿色发展效率有负向影响,环境规制对绿色发展效率的影响不明显。③从各影响因素作用的区域异质性来看,科技水平和外资利用对上游绿色发展效率的影响不显著,经济发展水平对中游的影响有限,而产业结构升级对中游的绿色发展效率有显著的负向作用,外资利用对下游的影响不显著。本文对提升黄河流域的绿色发展水平、助推该地区的高质量发展具有重要意义。

关键词: 黄河流域, 绿色发展效率, Super-SBM, 时空演变, 影响因素

Abstract:

The Yellow River Basin plays an important role in the economic development and ecological security in China. Based on the panel data of 57 cities in the Yellow River Basin from 2005 to 2017, this study calculated the urban green development efficiency of the basin using the super-SBM (slacks-based measure) model, and constructed a Tobit model to empirically analyze the influencing factors of the green development efficiency of the basin. The results of this paper were as follows: (1) The overall green development efficiency of the basin is fluctuating and rising, with the highest in the upper reaches, followed by the lower reaches and the lowest is found in the middle reaches. The high efficiency values are concentrated in provincial capital cities such as Xining, Zhengzhou, Xi’an, and Taiyuan, and regional central cities such as Zhongwei, Wuwei, and Ordos. (2) Economic development and industrial structure upgrading can significantly improve the green development efficiency of the basin. The impact of urbanization on the green development efficiency of the basin presents a U-shaped curve. The use of foreign capital and science and technology development level have a negative impact on the green development efficiency of the basin. The impact of environmental regulations on the green development efficiency is not obvious. (3) The science and technology level and FDI have no significant impact on the green development efficiency of the upper reaches. The level of economic development has limited impact on the middle reaches, while upgrading industrial structure has negative impact on the green development efficiency of the middle reaches, and the impact of FDI on the the green development efficiency of the lower reaches is not significant. This study is of significance for improving the green development level of the Yellow River Basin and boosting the high-quality development of the region.

Key words: Yellow River Basin, green development efficiency, Super-SBM, spatiotemporal change, influencing factors

岳立, 薛丹. 黄河流域沿线城市绿色发展效率时空演变及其影响因素[J]. 资源科学, 2020, 42(12): 2274-2284.

YUE Li, XUE Dan. Spatiotemporal change of urban green development efficiency in the Yellow River Basin and influencing factors[J]. Resources Science, 2020, 42(12): 2274-2284.

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标准层	要素层	指标层	单位	观测数	均值	标准差	最小值	最大值
投入指标	劳动力	城市就业人员数	万人	741	38.75	32.95	4.84	207.56
	资本	资本存量	亿元	741	4048.72	4497.32	104.20	33395.27
	资源	城市建设用地面积	km²	741	96.88	90.68	6.00	661.00
		供水总量	万t	741	78.55	94.24	0.81	1035.40
		全社会用电总量	万kW·h	741	0.87	0.97	0.02	5.74
期望产出	经济收益	实际GDP	亿元	741	988.67	934.47	4.26	5897.44
	社会收益	城镇居民平均工资	元	741	27421.33	9763.39	8659.14	58504.86
	环境收益	公园绿地面积	hm²	741	1055.66	1112.80	1.00	9199.00
非期望产出	对环境的负面影响	工业废水排放量	万t	741	5366.05	4856.08	99.00	22522.00
		工业SO₂排放量	万t	741	7.66	5.83	0.06	33.72
		工业烟粉尘排放量	万t	741	5.04	22.54	0.03	516.88

变量	流域整体	黄河上游	黄河中游	黄河下游
lnpgdp	0.1710***	0.1370***	0.00159	0.3430***
lnpgdp	(6.89)	(3.98)	(0.03)	(6.39)
urb	-0.0226***	-0.0320***	-0.0168**	-0.0232***
urb	(-7.63)	(-9.15)	(-2.25)	(-2.92)
urb²	0.0002***	0.0002***	0.0002***	0.0002**
urb²	(6.31)	(7.64)	(3.74)	(2.10)
is	-0.0030***	-0.0057***	0.0130***	-0.0080***
is	(-3.22)	(-4.16)	(6.41)	(-3.11)
lnfdi	-0.0186***	0.0074	-0.0349***	-0.0223
lnfdi	(-3.30)	(0.97)	(-3.62)	(-0.94)
lntec	-0.0290***	-0.0215	-0.0300*	-0.0696***
lntec	(-2.89)	(-1.44)	(-1.74)	(-3.11)
er	0.00004	0.0008	0.0003	0.0013
er	(0.09)	(1.28)	(0.41)	(0.75)
_cons	-0.0787	0.3940	0.4160	-1.6730***
_cons	(-0.37)	(1.38)	(0.92)	(-2.99)
var(e.gde)	0.0719***	0.0538***	0.0624***	0.0569***
var(e.gde)	(19.25)	(11.40)	(11.68)	(10.20)
N	741	260	273	208

变量名称	2005—2011年				2012—2017年
变量名称	流域整体	黄河上游	黄河中游	黄河下游	流域整体	黄河上游	黄河中游	黄河下游
lnpgdp	0.1520***	0.0703	0.0230	0.3690***	0.3060***	0.2250***	0.3030**	0.4460***
lnpgdp	(4.11)	(1.54)	(0.23)	(5.26)	(7.97)	(3.65)	(3.25)	(4.86)
urb	-0.0159***	-0.0301***	-0.0077	-0.0159	-0.0316***	-0.0319***	-0.0311	-0.0450**
urb	(-4.03)	(-7.32)	(-0.85)	(-1.39)	(-5.55)	(-4.11)	(-1.37)	(-2.48)
urb²	0.0001***	0.0002***	0.0002*	0.0001	0.0002***	0.0002***	0.0003*	0.0003*
urb²	(3.07)	(5.79)	(1.92)	(0.97)	(4.50)	(3.41)	(1.68)	(1.87)
is	-0.0036**	-0.0041*	0.0135***	-0.0130***	-0.0054***	-0.0066***	0.0062**	-0.0137***
is	(-2.39)	(-1.96)	(3.65)	(-3.31)	(-4.04)	(-3.14)	(2.40)	(-3.80)
lnfdi	-0.0280***	0.0097	-0.0435***	-0.0209	-0.0199**	-0.0017	-0.0353***	-0.0126
lnfdi	(-3.30)	(0.93)	(-3.05)	(-0.60)	(-2.49)	(-0.12)	(-2.93)	(-0.39)
lntec	-0.0266*	-0.0034	-0.0663**	-0.0411	-0.0117	-0.0409	0.0045	-0.0985**
lntec	(-1.91)	(-0.18)	(-2.44)	(-1.63)	(-0.79)	(-1.60)	(0.21)	(-2.18)
er	0.00005	0.0014*	0.0005	-0.0099**	0.0008	-0.00002	0.0013	0.0040*
er	(0.08)	(1.79)	(0.55)	(-2.41)	(1.34)	(-0.02)	(1.40)	(2.16)
_cons	0.0798	0.8810*	-0.0044	-0.750	-1.1550***	-0.3240	-1.9150**	-2.1680*
_cons	(0.26)	(2.41)	(-0.01)	(-1.05)	(-3.30)	(-0.62)	(-2.58)	(-1.82)
var (e.gde)	0.0767***	0.0463***	0.0644***	0.0514***	0.0601***	0.0589***	0.0447***	0.0484***
var (e.gde)	(14.12)	(8.37)	(8.57)	(7.48)	(13.08)	(7.75)	(7.94)	(6.93)
N	399	140	147	112	342	120	126	96

变量	流域整体	黄河上游	黄河中游	黄河下游
lnpgdp	0.1610***	0.1060***	-0.0117	0.2950***
lnpgdp	(6.61)	(3.31)	(-0.19)	(6.47)
urb	-0.0234***	-0.0339***	-0.0111	-0.0221***
urb	(-8.05)	(-9.67)	(-1.47)	(-2.87)
urb²	0.0002***	0.0002***	0.0002***	0.0002*
urb²	(6.40)	(7.91)	(3.40)	(1.86)
is	0.0045***	0.0062***	-0.0142***	0.0120***
is	(4.01)	(3.92)	(-5.78)	(4.28)
lnfdi	-0.0215***	0.0028	-0.0295***	-0.0339
lnfdi	(-3.81)	(0.36)	(-2.97)	(-1.44)
lntec	-0.0328***	-0.0234	-0.0333*	-0.0763***
lntec	(-3.27)	(-1.62)	(-1.94)	(-3.29)
er	0.1110	0.3260***	0.0163	0.0697
er	(1.48)	(3.18)	(0.12)	(0.28)
_cons	-0.3180	0.1100	1.5230***	-1.8300***
_cons	(-1.43)	(0.38)	(2.81)	(-3.51)
var (e.gde)	0.0712***	0.0525***	0.0638***	0.0548***
var (e.gde)	(19.25)	(11.40)	(11.68)	(10.20)
N	741	260	273	208