Do climate change policies affect labour market distortions? Empirical evidence from China's low-carbon city pilots

气候变化 情感(语言学) 中国 经济 温室气体 自然资源经济学 碳市场 经验证据 气候政策 地理 生态学 语言学 生物 认识论 哲学 考古
作者
Meng Shen,Mengjia Yang,Luqi Xing
出处
期刊:Climate Policy [Taylor & Francis]
卷期号:: 1-16
标识
DOI:10.1080/14693062.2024.2428757
摘要

To mitigate climate change while ensuring that the substantial benefits of a green economic transition are widely shared, the concept of a just transition has emerged as a pivotal element in climate strategies. Although the effectiveness of climate policies has been a subject of ongoing debate, the integration of just transition principles is often overlooked as a key component. This study employs China's Low-Carbon City Pilot policy (LCCP) as a quasi-natural experiment and uses a time-varying difference-in-differences (DID) methodology to assess the impact of LCCP on wage distortions within firms. Using data from listed companies between 2006 and 2022, our analysis shows that the low-carbon policy itself may be a source of inequity, disproportionately benefiting capital at the expense of labour, thus exacerbating wage distortions and preventing labour from receiving fair compensation. This inequity undermines the principles of a just transition, as the allocation of policy resources tends to favour large firms, enhancing their pricing power and diminishing labour market flexibility. The economic outcomes of LCCP are mixed: while it accelerates the growth of capital share, it also leads to an unequal distribution between capital and labour. Furthermore, our exploration of the role of export trade in mitigating these distortions reveals that exports actually widen the disparity in wage distortions. Our study underscores the urgent need to prioritize equity in climate policies and improve labour allocation efficiency within climate action frameworks. We aim to provide decision-making support for the design and implementation of more equitable low-carbon policies in developing countries.

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
dato12423完成签到,获得积分10
1秒前
脑洞疼应助团子采纳,获得10
1秒前
111发布了新的文献求助10
1秒前
1秒前
2秒前
2秒前
小郭完成签到,获得积分10
3秒前
3秒前
轮回完成签到,获得积分10
3秒前
99完成签到,获得积分10
4秒前
4秒前
Akim应助无限的平露采纳,获得10
4秒前
4秒前
4秒前
罗Eason应助yyyccc采纳,获得30
4秒前
勤奋的若冰完成签到,获得积分10
5秒前
5秒前
laox完成签到,获得积分10
6秒前
6秒前
7秒前
白糖发布了新的文献求助10
7秒前
偷懒完成签到,获得积分10
8秒前
我爱金哥发布了新的文献求助10
8秒前
8秒前
烟波钓客完成签到,获得积分10
9秒前
xiaobai完成签到,获得积分10
9秒前
香蕉觅云应助钰拉A梦采纳,获得10
9秒前
彪壮的刺猬完成签到,获得积分10
9秒前
酷波er应助不想取名字采纳,获得10
10秒前
冷酷花生完成签到,获得积分10
10秒前
LZW发布了新的文献求助10
10秒前
qinhao发布了新的文献求助10
10秒前
董帅铭完成签到,获得积分10
10秒前
JamesPei应助王佟采纳,获得10
10秒前
Hello应助舒适的毛衣采纳,获得10
11秒前
英姑应助111采纳,获得10
11秒前
11秒前
monica发布了新的文献求助10
12秒前
科研通AI6.4应助陌上采纳,获得10
12秒前
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
Rosenblum, Global Change Biology 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7774422
求助须知:如何正确求助?哪些是违规求助? 9316527
关于积分的说明 20351168
捐赠科研通 7360525
什么是DOI,文献DOI怎么找? 3317637
关于科研通互助平台的介绍 2465940
邀请新用户注册赠送积分活动 2332797