绿色税收视角下产业结构变迁对中国碳排放的影响

doi:10.18402/resci.2021.04.05

Abstract

Abstract:

Exploring the relationship between industrial structure transformation and carbon emissions from the perspective of green tax is helpful for making public policies on controlling carbon emissions, as well as for promoting green development. This study first calculated the CO₂ emissions of 30 provinces in China’s mainland from 2003 to 2016, then examined the relationship between industrial structure transformation and carbon emissions based on the extended STRIPAT model by using the static panel model and panel threshold model, and analyzed the relationship from the dimensions of industrial structure rationalization and upgrading. The empirical results show that: (1) Industrial structure transformation significantly affects China’s carbon emissions, and the green tax has a threshold effect on the impact; (2) Before achieving the threshold value, the green tax level effectively strengthens the impact of industrial structure transformation on carbon emissions, but the impact is quite different when the threshold value has been achieved. On the one hand, green taxation still has a strong effect on the decline of carbon emissions when upgrading the industrial structure although the influence is lower than before. On the other hand, it hinders the effect of industrial structure rationalization in reducing carbon emissions; (3) The green tax levels in some provinces exceeded the threshold after 2009, probably mainly due to the tax reform.

Key words: carbon emissions, green tax, industrial structure rationalization, industrial structure upgrading, threshold effect, China

ZHOU Di, LUO Dongquan. Green taxation, industrial structure transformation, and carbon emissions reduction[J].Resources Science, 2021, 43(4): 693-709.

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变量	指标	数据来源
CO₂排放量（Cbn）	CO₂排放测算公式	国泰安数据库和《中国能源统计年鉴》
产业结构合理化（Rat）	加权后的结构偏离度	中国国家统计局与各省（市、区）统计年鉴
产业结构高级化（Upg）	产业结构层次指数	中国国家统计局
人口总数（Pop）	各地区常住人口	中国国家统计局
人均GDP（Pgdp）	以2003年为基期平减的GDP/人口规模	中国国家统计局
能源强度（Eng）	能源消费量/人均GDP	中国国家统计局和《中国能源统计年鉴》
对外贸易程度（Trade）	进出口贸易总额	中国国家统计局、世界银行数据库
城镇化水平（Urb）	城镇人口/各地区总人口	中国国家统计局
绿色税收（Gretax）	7个具有绿化功能的税收+排污费/税收收入+排污费	《中国环境年鉴》《中国税务年鉴》和地方财政统计资料

具体指标	相关文献
结构偏离度	Lu等^[37]
泰尔指数	袁航等^[38]
结构偏离度与模糊数学中的Hamming贴近度评价方法结合	邓慧慧等^[39]
Moore值	王兵等^[40]
结构偏离度加权法	韩永辉等^[36]

指标分类	具体指标	相关文献
产业结构比例法（产值或就业人数）	第三产业从业人员占从业人数比重	贾敬全等^[45]
	第三产业占第二产业比重	邓慧慧等^[39]
	第三产业占GDP比重	成金华等^[46]
	第二产业占GDP比重	张辉等^[47]
产业结构比例加权法	产业结构层次指数	唐宇娣等^[44]
	第二产业产值×0.4+第三产业×0.6	Xu等^[48]
	各产业比重×劳动生产率	刘伟等^[41]
技术复杂度法	企业各类型产品产出×技术复杂度	周茂等^[49]
夹角余弦法	Moore指数	王波等^[50]
内部结构升级法	通过对第二产业以及第三产业的细分行业或从业人员进行分类后构建相应的指标制造业升级、服务业升级指标	傅元海等^[42]
内部结构升级法	通过对第二产业以及第三产业的细分行业或从业人员进行分类后构建相应的指标制造业升级、服务业升级指标	张权^[43]

变量	均值	标准差	最小值	最大值
CO₂排放量/亿t	2.870	2.120	0.130	10.730
产业结构合理化	4.010	0.800	1.200	5.870
产业结构高级化	229.350	12.620	202.770	279.730
人口总数/万人	4415.410	2654.740	534.000	10999.000
人均GDP/亿元	3.270	2.280	0.370	11.550
能源强度/（亿t标准煤/亿元）	1178.900	686.730	271.220	4524.430
对外贸易程度/亿元	6213.680	11313.700	28.080	67678.050
城镇化水平/%	50.580	14.450	13.890	89.600
绿色税收/%	18.820	7.490	4.260	42.670

解释变量	（1）	（2）
lnRat1	0.018* （0.010）	0.031** （0.013）
lnUpg1	-2.165*** （0.456）	-2.191*** （0.444）
lnPop	-0.462*** （0.149）	-0.504*** （0.146）
lnPgdp	0.596*** （0.149）	0.592*** （0.020）
lnEng		0 .128*** （0.025）
lnTrade		0.010 （0.007）
lnUrb		0.036 （0.055）
截距项	15.728*** （2.439）	15.242*** （2.377）
F值	164.290***	160.450***
Within R²	0.838	0.849
N	420	420

Green taxation, industrial structure transformation, and carbon emissions reduction

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解释变量	（1）	（2）	（3）	（4）	（5）	（6）
L.Cbn					0.928*** （0.041）	0.915*** （0.056）
lnRat1	0.033** （0.035）		0.112*** （0.036）		0.008 （0.012）	0.005 （0.011）
lnRat2		0.031** （0.013）		0.035 （0.040）
lnUpg1	-2.269***（0.462）	-0.270*** （0.039）			-0.928*** （0.309）
lnUpg2			-1.790*** （0.461）	-0.247*** （0.048）		-0.129*** （0.041）
控制变量	是	是	是	是	是	是
常数项	11.445*** （2.583）	1.764 （1.207）	11.788*** （2.609）	1.496 （1.236）	5.253*** （1.334）	0.269 （0.451）
Within R²	0.868	0.857	0.851	0.855
F值	155.24***	124.810***	105.120***	94.560***
AR（1）					-2.347 [0.019]	-2.392 [0.017]
AR（2）					-0.078 [0.938]	0.083 [0.934]
Sargan					27.490 [0.778]	26.372 [0.822]
N	420	420	420	420	420	420

解释变量	门槛变量	门槛数量	F值	P值	BS次数	临界值
解释变量	门槛变量	门槛数量	F值	P值	BS次数	1%	5%	10%
Rat3	Gretax	单一门槛	37.970*	0.055	400	33.213	39.008	49.813
		双重门槛	3.140	0.998	400	29.382	33.303	41.903
		三重门槛	3.710	0.993	400	19.472	23.436	27.177
Rat4	Gretax	单一门槛	40.350**	0.040	400	34.549	39.129	44.991
		双重门槛	3.920	0.993	400	28.579	31.545	39.506
		三重门槛	5.400	0.958	400	24.261	27.837	34.983

解释变量	（1）	（2）	（3）	（4）
lnRat·I（lnGretax≤15.330%）	0.008** （0.004）	0.026** （0.012）
lnRat·I（lnGretax>15.330%）	0.023** （0.009）	0.058*** （0.013）
lnRat			0.015** （0.006）	0.034*** （0.012）
lnUpg·I（lnGretax≤15.330%）			-2.297*** （0.435）	-2.327*** （0.422）
lnUpg·I（lnGretax>15.330%）			-2.271*** （0.435）	-2.302*** （0.422）
lnUpg	-2.234*** （0.437）	-2.260*** （0.424）
lnPop	-0.475*** （0.142）	-0.520*** （0.139）	-0.470*** （0.141）	-0.517*** （0.139）
lnPgdp	0.565*** （0.018）	0.561*** （0.020）	0.562*** （0.018）	0.556*** （0.020）
lnEng		0.124*** （0.024）		0.121*** （0.024）
lnTrade		0.007 （0.007）		0.008 （0.007）
lnUrb		0.041 （0.053）		0.050 （0.052）
截距项	16.254*** （2.337）	15.832*** （2.272）	16.462*** （2.325）	16.055*** （2.263）
F值	180.260***	177.140***	182.420***	178.890***
Within R²	0.852	0.863	0.854	0.864
N	420	420	420	420

年份	Gretax≤15.330%	Gretax>15.330%	合计
2003	16	14	30
2004	17	13	30
2005	19	11	30
2006	18	12	30
2007	18	12	30
2008	16	14	30
2009	7	23	30
2010	6	24	30
2011	6	24	30
2012	7	23	30
2013	8	22	30
2014	8	22	30
2015	6	24	30
2016	7	23	30
合计	159	261	420

年份	Gretax≤15.330%的省（市、区）
2003	北京天津河北山西内蒙古上海江苏浙江福建山东广东广西海南青海宁夏新疆
2008	北京天津河北山西内蒙古黑龙江上海江苏浙江福建山东广东海南青海宁夏新疆
2009	北京天津山西上海江苏浙江广东
2016	北京天津上海江苏浙江福建广东

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解释变量	门槛变量	门槛数量	F值	P值	BS次数	临界值
解释变量	门槛变量	门槛数量	F值	P值	BS次数	1%	5%	10%
Upg3	Gretax	单一门槛	43.240**	0.043	400	35.162	42.409	51.879
		双重门槛	4.790	0.983	400	28.635	31.294	39.788
		三重门槛	5.480	0.885	400	17.743	19.984	37.609
Upg4	Gretax	单一门槛	44.530**	0.020	400	31.010	37.540	48.627
		双重门槛	4.260	0.995	400	28.487	32.380	45.458
		三重门槛	3.650	0.970	400	17.384	20.972	29.369