Environmental Protection Tax Law on the synergy of pollution reduction and carbon reduction in China: Evidence from a panel data of 107 cities

还原(数学) 碳排放税 面板数据 中国 环境税 经济 环境污染 自然资源经济学 污染 公共经济学 环境科学 法学 环境保护 税制改革 温室气体 政治学 计量经济学 数学 生物 生态学 几何学
作者
Xinwei Gao,Na Liu,Yujie Hua
出处
期刊:Sustainable Production and Consumption [Elsevier]
卷期号:33: 425-437 被引量:200
标识
DOI:10.1016/j.spc.2022.07.006
摘要

Many of air pollutants and carbon dioxide (CO2) have common emission sources, determining that they should be controlled collaboratively rather than treated separately. To protect the environment, China implemented the Environmental Protection Tax (EPT) Law on January 1st, 2018. Yet CO2 is not included in the tax category, whether the EPT Law can achieve coordinated control of air pollutants and CO2 emissions remains unclear. This paper examines the role of the EPT Law in the synergy of pollution reduction (PR) and carbon reduction (CR) by employing the Difference-In-Differences (DID) model on China's 107 cities from 2015 to 2019. We find that the policy, although not including CO2 as one taxable item, has significantly increased the synergistic reduction degree of “sulfur dioxide (SO2)-CO2” by 41%, and the synergistic reduction degree of “particulate matter (PM)-CO2” by 39%. Moreover, strengthening environmental protection supervision, optimizing energy structure and improving green technology innovation are main transmission mechanisms through which EPT Law affects the synergy degree of PR and CR. Further, the heterogeneity of policy effects caused by different magnitudes of tax rate increase is unveiled, showing that the policy effects on the synergy of PR and CR are most significant in regions that raised the SO2 tax rate beyond 2.4 Yuan and raised the PM tax rate between 2.4 Yuan and 6 Yuan. This paper suggests that the EPT Law serves a critical function in enhancing the synergy of PR and CR, and thus the synergistic effect of air pollutants reduction on carbon reduction should be considered when formulating possible carbon tax rate in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
开朗皮皮虾完成签到,获得积分10
2秒前
yiyi关注了科研通微信公众号
3秒前
杨廷友发布了新的文献求助10
3秒前
乐乐应助波妞采纳,获得10
3秒前
HAHA_完成签到,获得积分10
4秒前
6秒前
敏感可冥发布了新的文献求助10
6秒前
8秒前
10秒前
又吃包子呢包包侠完成签到,获得积分10
11秒前
可爱的函函应助森水垚采纳,获得10
11秒前
12秒前
界外球完成签到,获得积分10
12秒前
Lu完成签到,获得积分10
12秒前
BINBIN发布了新的文献求助10
12秒前
波妞完成签到,获得积分10
13秒前
LG发布了新的文献求助10
13秒前
14秒前
中国大陆发布了新的文献求助10
15秒前
15秒前
16秒前
16秒前
小马甲应助张毅杰采纳,获得20
16秒前
子铭发布了新的文献求助10
17秒前
123发布了新的文献求助10
17秒前
yiyi发布了新的文献求助10
17秒前
顾矜应助znn采纳,获得10
18秒前
19秒前
华仔应助lmg采纳,获得10
20秒前
Miracle完成签到,获得积分10
20秒前
炙热幻灵发布了新的文献求助10
20秒前
境屾完成签到,获得积分10
20秒前
莫青成完成签到,获得积分10
21秒前
allen发布了新的文献求助10
21秒前
冬瓜熊发布了新的文献求助10
23秒前
25秒前
Jasper应助HRC采纳,获得10
25秒前
香蕉觅云应助allen采纳,获得10
26秒前
vv发布了新的文献求助30
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 生物化学 化学工程 物理 计算机科学 复合材料 内科学 催化作用 物理化学 光电子学 电极 冶金 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6023016
求助须知:如何正确求助?哪些是违规求助? 7645959
关于积分的说明 16171105
捐赠科研通 5171318
什么是DOI,文献DOI怎么找? 2767068
邀请新用户注册赠送积分活动 1750461
关于科研通互助平台的介绍 1637029