Heterogeneous environmental regulations and carbon emission efficiency in China: A perspective of resource endowment

捐赠 中国 资源(消歧) 自然资源经济学 可持续发展 波特假说 面板数据 经济 环境法规 环境经济学 环境资源管理 业务 地理 生态学 政治学 计算机网络 计算机科学 法学 考古 计量经济学 生物
作者
Jiazhan Gao,Guihong Hua,AbidAli Randhawa,Baofeng Huo
出处
期刊:Energy & Environment [SAGE Publishing]
被引量:2
标识
DOI:10.1177/0958305x241270274
摘要

China, as the world's largest carbon emitter, is striving for green transformation through the implementation of various environmental policies. This study employs panel data from 30 Chinese provinces between 2000 and 2022 to analyze in-depth the heterogeneous effects of three types of environmental regulations. The findings reveal a U-shaped relationship between both general public environmental regulation (GER) and mandatory environmental regulation (MER) and carbon emission efficiency (CEE). Conversely, stimulating environmental regulations (SERs) exhibit an inverted U-shaped relationship with CEE. Mechanism analysis further reveals that environmental regulations enhance CEE by promoting industrial structural upgrades and technological innovation. Notably, SERs are particularly effective in improving the CEE in resource-rich and moderately resourced provinces. However, GER exhibits a masking effect on the pathway of technological innovation, indicating potential inefficiencies in its implementation. Moreover, heterogeneity analysis demonstrates that mandatory environmental regulation has a more pronounced impact on improving the CEE in resource-rich and moderately resourced provinces, whereas this impact is relatively weaker in resource-poor provinces. This finding underscores the importance of tailoring environmental policies to the specific resource characteristics of different regions. The insights from this study offer critical guidance for policymakers in designing and implementing differentiated environmental regulation policies, particularly in advancing China’s transition toward a sustainable, green, and low-carbon 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
刚刚
刚刚
刚刚
泥娃娃苘发布了新的文献求助10
1秒前
印第安老斑鸠应助mmm采纳,获得10
1秒前
2秒前
山河远完成签到,获得积分10
2秒前
2秒前
3秒前
隐形曼青应助哲999采纳,获得10
3秒前
3秒前
李健的小迷弟应助YNA采纳,获得10
3秒前
11完成签到,获得积分10
4秒前
4秒前
4秒前
4秒前
5秒前
6秒前
烟花应助虚心念桃采纳,获得10
6秒前
Cordero发布了新的文献求助10
6秒前
6秒前
ly3948完成签到,获得积分10
6秒前
新嗨发布了新的文献求助10
7秒前
LILLIAN发布了新的文献求助10
7秒前
7秒前
科研通AI6.4应助顺心醉柳采纳,获得10
7秒前
韦德德发布了新的文献求助10
7秒前
8秒前
8秒前
大模型应助大军门诊采纳,获得10
9秒前
泥娃娃苘发布了新的文献求助10
9秒前
9秒前
羽化发布了新的文献求助10
9秒前
lnx发布了新的文献求助10
10秒前
无辜稀完成签到,获得积分10
11秒前
张张zhang发布了新的文献求助10
11秒前
桐桐应助ADmsder采纳,获得10
11秒前
yu发布了新的文献求助10
11秒前
倩倩子发布了新的文献求助10
12秒前
ning发布了新的文献求助10
12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
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6501983
求助须知:如何正确求助?哪些是违规求助? 8296751
关于积分的说明 17707147
捐赠科研通 5599535
什么是DOI,文献DOI怎么找? 2918871
邀请新用户注册赠送积分活动 1896078
关于科研通互助平台的介绍 1757347