低碳试点政策对城市碳排放绩效的影响评估及机制分析

doi:10.18402/resci.2019.03.12

摘要/Abstract

摘要：

低碳试点是实现中国低碳经济发展的一项重要政策,客观评价其实施效果,不仅有利于低碳试点地区更好地推进低碳工作,而且对于低碳试点政策的进一步推广具有重要意义,但低碳试点政策能否实现碳排放绩效的提升尚未得出一致的结论。本文以第二批低碳试点政策为例,基于2012—2016年的地级市面板数据,采用倾向得分匹配—双重差分（PSM-DID）方法研究低碳试点政策对降低城市碳排放强度的影响,以有效降低样本自选择及政策内生性等问题导致的处理效应偏差。研究发现：低碳试点政策对城市的碳排放强度下降具有显著且持续的推动作用;进一步的机制识别结果显示,低碳试点城市主要是通过能源效率的提高以及产业结构升级等方式实现碳强度的下降,且产业升级的效果有逐年增强的趋势,但通过城市绿地碳汇水平的提高而降低碳排放的目标尚未实现。基于此结论,本文认为中国应进一步推广低碳试点政策,积极探索低碳城市的发展模式,特别是提升宜居绿色的城市环境。

关键词: 低碳试点, 碳强度, 倾向得分匹配, 双重差分, 低碳城市

Abstract:

Low-carbon pilot project is an important policy to realize the development of low-carbon economy in China. Objectively evaluating its implementation effect is not only conducive to better promoting low-carbon work in low-carbon pilot project areas, but also of great significance for the further promotion of low-carbon pilot policy. However, there is no consistent conclusion on whether the low-carbon pilot policy can enhance the performance of carbon emissions. Taking the second batch of low-carbon pilot projects as an example and using city panel data from 2012 to 2016, this study examined the impact of low-carbon pilot policy on the reduction of local carbon emission intensity by using the Propensity Score Matching-Difference in Difference (PSM-DID) method in order to effectively reduce the processing effect bias caused by the problem of sample selection and policy endogeneity. It was found that the low-carbon pilot policy had a significant and sustained effect on local carbon intensity reduction. Further mechanism identification results show that low-carbon pilot areas mainly achieve a decline in carbon intensity through the improvement of energy efficiency and upgrading of industrial structure, and the upgrading of industrial structure shows a trend of increase year by year. However, the goal of reducing carbon emissions by raising the level of carbon sink in urban green spaces has not yet been achieved. Based on this conclusion, we believe that China should further promote the low-carbon pilot policy and actively explore the development model of low-carbon cities, in particular by further establishing a livable and green urban environment.

Key words: low-carbon pilot, carbon intensity, propensity score matching, double difference, low- carbon cities

周迪, 周丰年, 王雪芹. 低碳试点政策对城市碳排放绩效的影响评估及机制分析[J]. 资源科学, 2019, 41(3): 546-556.

Di ZHOU, Fengnian ZHOU, Xueqin WANG. Impact of low-carbon pilot policy on the performance of urban carbon emissions and its mechanism[J]. Resources Science, 2019, 41(3): 546-556.

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变量	含义	全部样本(N=202)		实验组样本(N=20)		对照组样本(N=182)
变量	含义	均值	标准差	均值	标准差	均值	标准差
lnicar	碳排放强度,碳排放量与实际GDP之比	6.256	0.778	6.325	0.758	6.248	0.781
lnrgdp	人均GDP,实际GDP/年末总人口	10.311	0.674	10.578	0.683	10.282	0.667
lnene	能源强度,全社会用电量/实际GDP	1.522	0.804	1.585	0.786	1.515	0.806
lnsec	第二产业比重,第二产业增加值/GDP	3.880	0.221	3.856	0.150	3.883	0.227
lnthi	第三产业比重,第三产业增加值/GDP	3.617	0.228	3.722	0.202	3.605	0.228
lngre	建成区绿化覆盖率/%	3.642	0.365	3.715	0.168	3.634	0.379
lnwage	职工平均工资	10.481	0.350	10.605	0.247	10.467	0.357
lnpop	年末总人口	5.894	0.711	5.934	0.740	5.890	0.708

变量	匹配前后	实验组均值	对照组均值	t值	P值
lnrgdp	匹配前	10.396	10.094	1.950*	0.053
lnrgdp	匹配后	10.396	10.341	0.340	0.755
lnene	匹配前	1.639	1.607	0.170	0.864
lnene	匹配后	1.639	1.586	0.220	0.826
lnwage	匹配前	10.384	10.223	2.660***	0.008
lnwage	匹配后	10.387	10.367	0.260	0.794
lnpop	匹配前	5.926	5.882	0.260	0.794
lnpop	匹配后	5.926	5.881	0.200	0.841
lnsec	匹配前	3.909	3.948	-0.770	0.441
lnsec	匹配后	3.909	3.920	-0.200	0.844
lnthi	匹配前	3.646	3.497	2.540**	0.015
lnthi	匹配后	3.646	3.621	0.360	0.741

	平均处理效应		动态边际效应
	（1）	（2）	（3）	（4）
Treat×T	-0.690***(-6.019)	-0.693***(-6.483)
t	-0.0457(-0.846)	-0.0845(-0.618)
Treat×t₂₀₁₃			-0.592***(-4.134)	-0.579***(-4.361)
Treat×t₂₀₁₄			-0.425***(-2.967)	-0.430***(-3.239)
Treat×t₂₀₁₅			-0.968***(-6.760)	-0.964***(-7.265)
Treat×t₂₀₁₆			-0.774***(-5.402)	-0.820***(-6.194)
lnene		0.756***(9.041)		0.762***(9.249)
lnrgdp		-0.071(-0.195)		-0.219(-1.188)
lnsec		0.963***(2.691)		0.860***(2.838)
cons	6.421***(176.913)	9.740***(2.612)	6.421***(179.036)	10.846***(3.984)
城市固定	是	是	是	是
时间固定	是	是	是	是
N	680	680	680	680
R²	0.085	0.210	0.111	0.237
F	9.950***	17.800***	8.370***	16.590***

	2012—2013年		2012—2014年		2012—2015年
	(1)	(2)	(3)	(4)	(5)	(6)
Treat×T	-0.592***	-0.587***	-0.508***	-0.504***	-0.662***	-0.652***
	(-7.444)	(-7.685)	(-5.546)	(-5.801)	(-5.998)	(-6.292)
t	-0.015	-0.053	-0.007	0.028	-0.075	0.001
	(-0.503)	(-0.414)	(-0.180)	(0.208)	(-1.486)	(0.007)
lnene		0.605***		0.601***		0.704***
		(3.990)		(5.960)		(7.500)
lnrgdp		0.452		-0.145		-0.352
		(0.644)		(-0.202)		(-0.535)
lnsec		0.539		0.454		0.787*
		(0.568)		(0.814)		(1.835)
cons	6.421***	2.938	6.421***	8.748	6.421***	12.017*
	(322.396)	(0.466)	(242.208)	(1.260)	(189.774)	(1.840)
城市固定	是	是	是	是	地区	是
时期固定	是	是	是	是	时期	是
N	272	272	408	408	544	544
R²	0.339	0.411	0.127	0.230	0.109	0.222
F	34.310***	18.250***	13.040***	13.260***	12.290***	16.340***

	lnsec		lnthi		lnene		lngre
	（1）	（2）	（3）	（4）	（5）	（6）	（7）	（8）
Treat×T	-0.332***		0.561***		-0.331***		0.056
	(-9.318)		(9.207)		(-2.807)		(1.047)
t	-0.068***		0.091***		0.009		0.009
	(-4.071)		(3.149)		(0.163)		(0.457)
Treat×t₂₀₁₃		-0.046		0.115*		-0.489***		0.046
		(-1.265)		(1.720)		(-3.300)		(0.671)
Treat×t₂₀₁₄		-0.213***		0.440***		-0.143		0.046
		(-5.893)		(6.581)		(-0.967)		(0.680)
Treat×t₂₀₁₅		-0.434***		0.721***		-0.530***		0.128*
		(-12.047)		(10.790)		(-3.576)		(1.881)
Treat×t₂₀₁₆		-0.636***		0.970***		-0.164		0.005
		(-17.622)		(14.517)		(-1.104)		(0.076)
cons	3.922***	3.922***	3.600***	3.600***	1.635***	1.635***	3.691***	3.691***
	(347.492)	(434.285)	(186.409)	(215.163)	(43.738)	(44.087)	(217.121)	(216.882)
城市固定	是	是	是	是	是	是	是	是
时期固定	是	是	是	是	是	是	是	是
N	680	680	680	680	680	680	680	680
R²	0.232	0.511	0.207	0.408	0.023	0.043	0.004	0.013
F	32.640***	70.090***	28.160***	46.210***	2.480**	3.030***	0.980	0.850