电力市场一体化对地区绿色经济效率的影响机制

doi:10.18402/resci.2022.03.08

摘要/Abstract

摘要：

在碳达峰碳中和目标约束下,推进经济社会发展全面绿色转型势在必行。受限于电力资源供需的逆向分布特征,中国尚未有效建立统一电力市场,清洁电力消纳能力不足,严重制约地区绿色经济效率的提升。本文借助2013—2018年中国30个省（市、区）的面板数据,利用空间面板模型和中介模型分析了电力市场一体化对地区绿色经济效率的影响效应及影响机制。结果表明：①电力市场一体化不仅能够有效促进各省（市、区）自身绿色经济效率的提升,也能够对空间关联地区的绿色经济效率产生显著的溢出影响;②电力市场一体化对各省（市、区）绿色经济效率提升的促进作用既能够直接产生,也能通过实现规模效应、优化产业结构和提高企业技术创新能力3种途径的传导而间接产生。研究结果的政策启示包括：完善统一电力市场总体设计和治理体系,推进区域电力市场协同运行与融合发展,加强电力市场对地区绿色发展的支撑作用。

关键词: 电力体制改革, 电力市场一体化, 绿色经济效率, 空间溢出效应, 传导机制, 中国

Abstract:

Under the constraints of the carbon peak and carbon neutrality goals, it is imperative to promote a comprehensive green transformation of economic and social development. Limited by the spatial mismatch of supply and demand of electric power resources, there is no effectively established unified electric power market in China and the capacity of clean power consumption is insufficient, which seriously restricts the promotion of regional green economic efficiency. Based on the panel data of 30 provinces of China from 2013 to 2018, this study used the spatial panel model and the intermediary model to analyze the effect and mechanism of the electric power market integration on the efficiency of the regional green economy. The results show that the integration of the electric power market not only can effectively promote the improvement of the green economic efficiency of a region, but also have a significant spillover effect on the green economic efficiency of the spatially related areas. The integration of the electricity market can promote the efficiency of the regional green economy. The effect can be directly generated and be transmitted through three ways: achieving scale effects, optimizing industrial structure, and improving enterprise technological innovation capabilities. The main implications of this research include improving the overall design and governance system of the unified electric power market, promoting the coordinated operation and integrated development of the regional power market, and strengthening the supporting role of the power market in regional green development.

Key words: electric power system reform, electric power market integration, green economic efficiency, spatial spillover effect, transmission mechanism, China

李荣杰, 李娜, 阎晓. 电力市场一体化对地区绿色经济效率的影响机制[J]. 资源科学, 2022, 44(3): 523-535.

LI Rongjie, LI Na, YAN Xiao. Impact mechanism of electricity power market integration on regional green economic efficiency[J]. Resources Science, 2022, 44(3): 523-535.

图/表 8

图1

表1

表2

表3

表4

电力市场一体化影响绿色经济效率的回归结果

变量	邻接矩阵	地理经济距离矩阵	电网矩阵
变量	(1)	(2)	(3)
MI	0.899***	0.941***	0.979***
	(7.742)	(7.581)	(8.877)
UR	0.582***	0.540***	0.603***
	(10.106)	(7.908)	(5.803)
OD	0.354***	0.363***	0.414***
	(3.817)	(3.895)	(3.319)
ES	-0.072	-0.081	-0.090
	(-0.592)	(-0.697)	(-0.384)
$λ$	0.689***	0.702***	0.700***
	(21.955)	(18.480)	(11.566)
$ρ$	-0.745***	-0.747***	-0.706***
	(-28.607)	(-39.391)	(-5.650)
log L	217.183	216.802	217.454
模型	FE	FE	FE
样本量	180	180	180

表4

表5

表6

稳健性检验结果

变量	稳健性检验1			稳健性检验2
变量	(1)	(2)	(3)	(4)	(5)	(6)
MI/MII	0.493***	0.526***	0.529***	1.053***	1.108***	1.119***
	(4.323)	(5.003)	(4.863)	(3.967)	(3.888)	(4.826)
UR	0.419***	0.378***	0.424***	0.504***	0.465***	0.547***
	(5.049)	(4.874)	(4.336)	(5.182)	(4.803)	(3.036)
OD	0.184***	0.194***	0.197***	0.297***	0.303***	0.345***
	(14.595)	(14.121)	(9.502)	(3.046)	(3.066)	(2.800)
ES	-0.169	-0.170	-0.190	-0.038	-0.046	-0.027
	-1.298)	(-1.303)	(-1.569)	(-0.310)	(-0.382)	(-0.202)
$λ$	0.804***	0.818***	0.807***	0.679***	0.688***	0.671***
	(47.286)	(61.397)	(23.024)	(19.154)	(16.881)	(9.116)
$ρ$	-0.698***	-0.711***	-0.633***	-0.719***	-0.714***	-0.634***
	(-13.134)	(-14.902)	(-8.998)	(-18.402)	(-24.003)	(-3.689)
log L	283.836	283.402	284.924	216.605	216.204	216.632
模型	FE	FE	FE	FE	FE	FE
样本量	180	180	180	180	180	180

表6

表7

电力市场一体化的传导路径检验结果

变量	GTFP	ED	IS	RD	GTFP	GTFP	GTFP
变量	(1)	(2)	(3)	(4)	(5)	(6)	(7)
MI	0.899***	3.454**	0.154**	1.550***	0.746***	0.897***	0.797***
	(7.742)	(2.716)	(2.490)	(3.670)	(6.633)	(9.460)	(13.050)
ED					0.025**
					(2.197)
IS						0.428***
						(2.782)
RD							0.076**
							(2.338)
UR	0.582***	0.028	2.336***	16.663***	0.582***	-0.332	-0.657
	(10.106)	(0.018)	(30.910)	(44.479)	(8.180)	(-1.099)	(-1.263)
OD	0.354***	-0.527**	-0.117***	-1.740***	0.363***	0.402***	0.479***
	(3.817)	(-2.154)	(-3.502)	(-15.337)	(3.767)	(3.611)	(3.148)
ES	-0.072	-0.712	-0.141***	1.202***	-0.034	0.023	-0.118
	(-0.592)	(-1.194)	(-3.821)	(2.963)	(-0.214)	(0.251)	(-0.826)
$λ$	0.689***				0.689***	0.557***	0.613***
	(21.955)				(24.527)	(11.630)	(11.932)
$ρ$	-0.745***				-0.749***	-0.590***	-0.705***
	(-28.607)				(-26.118)	(-10.758)	(-40.902)
log L	217.183				217.669	221.173	220.670
实证	步骤一	步骤二			步骤三
实证	SARAR	OLS			SARAR
模型	FE	FE	FE	FE	FE	FE	FE
样本量	180	180	180	180	180	180	180

表7

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变量名称	变量符号	观测值	均值	标准差	最小值	最大值
绿色经济效率	GTFP	180	1.092	0.144	0.507	1.709
电力市场一体化指数	MI	180	0.046	0.018	0.007	0.097
经济规模	ED	180	9.044	0.881	6.691	10.589
产业结构升级	IS	180	2.873	0.140	2.629	3.278
技术进步	RD	180	9.065	1.444	5.323	12.702
城镇化水平	UR	180	0.582	0.118	0.378	0.896
对外开放程度	OD	180	0.244	0.257	0.012	1.270
能源结构	ES	180	0.122	0.114	0.003	0.492

变量	邻接矩阵		地理经济距离矩阵		电网矩阵
变量	Moran's I	z值	Moran's I	z值	Moran's I	z值
GTFP	0.242***	5.030	0.225***	4.849	0.188***	4.750
resid	0.510***	10.439	0.488***	10.285	0.400***	9.842

变量	逆卡方统计量	P值
GTFP	99.215	0.001
MI	145.205	0.000
ED	84.565	0.020
IS	104.199	0.000
RD	88.389	0.010
UR	106.794	0.000
OD	155.094	0.000
ES	82.429	0.029

空间效应	变量	邻接矩阵	地理经济距离矩阵	电网矩阵
空间效应	变量	(1)	(2)	(3)
直接效应	MI	1.074***	1.118***	1.137***
		(7.465)	(7.627)	(6.768)
	UR	0.692***	0.640***	0.685***
		(9.712)	(8.172)	(6.785)
	OD	0.431***	0.439***	0.494***
		(4.065)	(4.217)	(3.039)
	ES	-0.078	-0.088	-0.098
		(-0.531)	(-0.625)	(-0.024)
间接效应	MI	1.839***	2.059***	2.396**
		(5.036)	(5.006)	(2.264)
	UR	1.187***	1.178***	1.361***
		(5.334)	(5.117)	(4.378)
	OD	0.728***	0.793***	1.081*
		(4.177)	(4.582)	(1.645)
	ES	-0.159	-0.190	-0.211
		(-0.580)	(-0.657)	(-0.029)
总效应	MI	2.914***	3.177***	3.533***
		(5.993)	(6.157)	(2.917)
	UR	1.879***	1.817***	2.046***
		(6.683)	(6.397)	(6.345)
	OD	1.159***	1.232***	1.575*
		(4.267)	(4.691)	(1.950)
	ES	-0.237	-0.278	-0.309
		(-0.564)	(-0.649)	(-0.028)